Dealing with metastases is one of the major challenges of cancer therapy More than 90 percent of deaths caused by cancer are linked to metastases Understanding the conditions that cause cancer metastases and how these move through the body is key to developing new approaches to cancer treatment as cancer is also subject to the laws of physics In honour of their groundbreaking insights into the movement of tumour cells and the biophysicists Professor Dr Jochen Guck and Professor Dr Josef Käs are receiving the 2024 Greve Prize from the German National Academy of Sciences Leopoldina is donated by the Helmut and Hannelore Greve Foundation for Science “Studying the behaviour of tumour cells from the perspective of physics and linking it to direct insights gained from medical institutions has the potential to develop completely new means of treating cancer.” The potential for cancer treatment is already apparent with respect to breast cancer Whether the cancer has metastasised or not is key in determining the success of therapies it has not been possible to accurately predict when a tumour forms metastases working together with Professor Dr Axel Niendorf (Hamburg/Germany) are significantly better at indicating a tumour’s potential to metastasise They have done so using biophysical concepts the central idea of which – that metastasising cancer cells must be softer – Jochen Guck played an important role in developing In order to release themselves from the original tumour and move through the human body allowing the cancer cell aggregate to become fluid In the study carried out by Käs and Aktas together with Axel Niendorf the scientists identified the histological characteristics of the cancer cells that become fluid: they were longer and had deformed cell nuclei allowing them to “squeeze” through neighbouring tissue Their study of more than 1,000 breast cancer patients offers a strong indication that these deformed cell and nuclei forms can be used as a reliable marker for a cancer’s aggressiveness and to predict a tumour’s potential to metastasise This could permit breast cancer treatments to be more individually tailored to patients Guck developed a high-throughput method to measure the deformability of cells (real-time deformability cytometry This method is particularly suited to finding substances that can change cancer cell mechanics to prevent metastases physician Professor Dr Bahriye Aktas (photo: Stefan Straube | UKL) biophysicists Professor Dr Jochen Guck (photo: private) biophysicists Professor Dr Josef Käs (photo: Swen Reichhold | University of Leipzig) Bahriye Aktas (born in 1975) is Professor of Gynaecology at the University of Leipzig and Director of the Department of Gynaecology at the Leipzig Medical Center Aktas studied medicine at the Justus Liebig University Gießen/Germany She completed her medical training as a gynaecologist and obstetrician at the University Hospital Essen/Germany and was appointed Associate Professor in 2017 That year she switched to the University of Leipzig her focus is on minimally invasive and robot-assisted surgery which is used for gentler and precise operations with improved chances of healing and she also has a particular interest in surgery for cancer treatment She and her predecessor have helped to globally establish new operation methods that take into account how a tumour spreads Jochen Guck (born in 1973) studied physics in Würzburg/Germany and obtained his doctorate at the University of Texas in Austin/USA under Josef Käs They jointly developed tools to investigate cell mechanics (optical cell stretcher) Following research stays at the University of Leipzig and the University of Cambridge/UK in 2012 Guck was awarded the Alexander von Humboldt Professorship of Cellular Machines at the Biotechnology Centre of the Technical University of Dresden/Germany and was Senior Director there Since 2018 he has been Director at the Max Planck Institute for the Physics of Light and Professor of Biological Optomechanics at the Friedrich-Alexander-Universität Erlangen-Nürnberg He has developed further photonic and biophysical instruments including real-time deformability cytometry These form the basis for many partnerships with medical institutions in Erlangen and at the new Max Planck Centre for Physics and Medicine (MPZPM) Josef Käs (born in 1961) is Head of the Soft Matter Physics Division at the University of Leipzig’s Peter Debye Institute for Soft Matter Physics He studied physics at Columbia University in New York/USA and at the Technical University of Munich/Germany After holding a professorship at the University of Texas in Austin One of his key research areas concerns the physical properties of cancer cells He discovered how cancer cells can vary their degree of solidity and fluidity and thus achieved a paradigmatic shift in the understanding of tumour mechanics The German National Academy of Science Leopoldina’s Greve Prize is awarded to scientists or research teams that work at German universities The prize is awarded every two years and honours outstanding research achievements in the natural sciences/medicine and engineering sciences the topic is the foundations of new cancer therapies The President of the Free and Hanseatic City of Hamburg invites participants and guests to attend the event at the Hamburg City Hall All News Back Link zur Bildergalerie der Preisverleihung 2024 Greve Prize YouTube channel of the Leopoldina (livestream on 6 December) Deutsche Akademie der Naturforscher Leopoldina e – German National Academy of Sciences – Jägerberg 1 | 06108 Halle (Saale) Phone: +49 (0)345 47 239 - 600 | Telefax: +49 (0)345 47 239 - 919 E-Mail: leopoldina@leopoldina.org © 2025 Deutsche Akademie der Naturforscher Leopoldina – Nationale Akademie der Wissenschaften We use cookies to provide, personalize, and improve our website. 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Please refer to our data protection statement for more information about the use of cookies and processing of your data « Back University of Rochester Medical Center scientists received $27 million to lead a large national study expected to change heart failure care for millions This is the second $27 million award for the cardiac research team in just four months underscoring the Medical Center’s impact on heart care “A cornerstone of treatment for heart failure is the use of beta blockers,” said Mehmet Aktas, MD and principal investigator (PI) of the study “Carvedilol and metoprolol succinate are the main types of beta-blockers that are prescribed for 90 percent of people with this condition to improve survival no one has ever studied the differences in outcomes for these two drugs in patients with heart failure who receive implantable cardioverter defibrillators (ICDs).” This study is the first large-scale, head-to-head comparison of two heart failure drugs aimed at improving physicians’ ability to provide optimal heart failure management for the six million people living with this disease URMC is simultaneously conducting another major initiative that is comparing outcomes for individuals with heart failure treated with and without ICDs.   Ilan Goldenberg, MD director of URMC’s Clinical Cardiovascular Research Center (CCRC) and co-PI with Aktas said “heart failure is not only widespread in the US The results of the two major heart failure trials we are conducting will be exponentially larger than the population we're studying it in we’re not just happy with the status quo We’re constantly working to improve outcomes and we need data-driven decision making to do that.” “These two large awards build upon the foundation of innovative research that has changed heart care countless times,” said David C. Linehan, MD CEO of URMC and dean of the School of Medicine & Dentistry “As a research university with a rich history of pivotal discoveries our scientists answer some of the most difficult questions and have global impact by elevating the standard of care.” The funding comes from the Patient-Centered Outcomes Research Institute (PCORI) nonprofit organization supporting evidence-based research needed to make better-informed healthcare decisions “This study was selected for PCORI funding based on its scientific merit and commitment to engaging patients in conducting a major research effort on heart failure,” said PCORI Executive Director Nakela L “The study has the potential to fill an important evidence gap relevant to a range of health care decision makers and help them better assess their care options We look forward to following the study’s progress and working with URMC to share its results.” the ongoing efforts at URMC to refine implantable device therapies will continue to shape modern cardiac care practices “Securing these prestigious research funding awards positions URMC not only as a leader in advancing cardiac care for the communities we serve,” said Spencer Z. Rosero, MD “but also serves as a catalyst for institutional growth These trials complement our existing nationally and internationally recognized clinical research program to answer important questions This funding will help us attract new talent provide unparalleled training opportunities and expand our research capabilities to create a stronger more vibrant environment for innovation in cardiac care.” whereas carvedilol blocks two beta and one alpha receptor The five-year study will enroll 2,000 patients at 100 sites across the country to determine if carvedilol provides additional benefits “Whether we find that both drugs are equally effective it is a win for patients and providers,” said Aktas “We’ll come away with knowledge that will inform and improve how we treat patients.” and available at pharmacies in generic form Aktas said that a person’s ability to switch from one to another would be effortless from Cedars-Sinai Medical Center and Sam Sears The initiative is supported by notable institutions and the Association of Black Cardiologists “I am thrilled that University of Rochester Medical Center has earned a second well-deserved $27 million competitive award Not only will this award bolster Rochester’s status as a leader in the healthcare research field but it will advance the Clinical Cardiovascular Research Center’s mission of saving lives and improving patient outcomes specifically for those burdened by heart failure.” "This award will support the highest level of cardiovascular care in our community and around the world," said Congressman Joe Morelle. "URMC's dedication to quality healthcare and leadership in medical research saves lives and supports patients and families when they need it most I am grateful for all URMC does and I look forward to our continued work together." *This award has been approved pending completion of a business and programmatic review by PCORI staff and issuance of a formal award contract a young man who has dreamed of becoming a car painter since childhood An employment project under the EU co-funded NEET PRO Grant Programme is helping him achieve this dream I also watched car painting videos on the internet They would use spray guns to paint the cars before polishing them with machines The cars would end up looking so beautiful,” says Erdem Erdem Aktaş paints machines with clear enthusiasm He graduated from the Department of Machine Technology at a vocational high school and subsequently worked as a CNC (computer-controlled machine) technician at two different workplaces he did not like these jobs due to the poor working conditions at both locations He noticed the EU-funded ‘NEET Carries the Machinery Sector to the Future’ project of the Aegean Regional Chamber of Industry (EBSO) online and applied hoping to earn certificates that would help him acquire a better job Erdem describes the 5 weeks of classes: “The lessons differed from those I experienced in high school I learned about machine parts and materials plus I underwent a personal development course.” Erdem has moved closer to achieving his childhood dream with the EU project  After observing the paint shop at the freezer factory where he had applied for a CNC internship he knocked on the door of the general manager The paint shop resembled car paint shops and employed the same technique Kurtalan recounts that day: ”He said he wanted to undergo a dyeing internship with us I asked EBSO if this was possible under the project We gave him a chance; we were absolutely delighted with his work.” “I told him I was very pleased with him and suggested he continue working here He is a boy who follows instructions diligently Having been interested in cars since childhood he has a natural talent for this type of work He may even become a foreman here in the future,” says Yavaş Erdem Aktaş is currently working at the factory where he completed his internship and hopes to one day move on to his dream job of painting cars “I think the pinnacle of this business is car painting I would have ended up working as a CNC technician His goal after learning the trade is to open his own car paint shop talks about the project conducted under the EU-co-funded Labour Market Support Programme for Young People Not in Employment “The most significant need in our industry is for qualified staff we will continue to develop similarly effective projects to meet the human resource needs of our industry and train qualified personnel who will increase the prosperity of our country The Head of the Delegation of the European Union to Türkiye stresses the importance of youth participation in the labour market: “Young people not only represent the future of countries The EU supports the empowerment of young people in Türkiye and their participation in the labour market in all areas We are pleased to see the success of this project.” The EU-funded project with a budget of € 325,000 aims to contribute to the employment of people aged 18 to 29 in the machinery technologies sector Students have been selected through a cooperative effort of the Izmir Metropolitan Municipality Vocational Factory and the Turkish Employment Agency (ISKUR) 15 teachers were trained in Germany over 17 days Training has been provided at Konak Çınarlı Vocational and Technical Anatolian High School which renovated its laboratory as part of the project students each receive a vocational qualification certificate 3 female and 23 male trainees were employed in EBSO member companies Get the best experience and stay connected to your community with our Spectrum News app. Learn More — According to The World Health Organization an estimated 619 million people live with chronic lower back pain about one in six are suffering from vertebrogenic pain — a lesser-known back pain caused by damage to the vertebral endplates New technology is on top of it so busy moms like Chelsey Town can get back to their everyday lives “We have to do laundry every day,” she laughed Two baskets of laundry used to be a challenge she’s lived with chronic lower back pain since 2016 sharp all the time with a burning infestation in it And it felt like somebody was taking a screw and twisting it inside my back to where everything was feeling like it was being pulled out at the end And that I couldn’t get back up and I was stuck there until somebody came home to help me up.” “I deal with and manage nonoperative spine pain from the neck all the way down to the lower back and I treat them from things as simple as acute injuries to some more chronic problems Aktas is an interventional spine physician in the Physical Medicine and Rehabilitation Department at the University of Rochester Medical Center He’s currently the only doctor West of Syracuse who performs the Intracept Procedure or vertebral nerve radio frequency ablation is a minimal invasive procedure Takes about an hour to do hour or two to do it's We're not changing or affecting your spine We are using heat to destroy a sensory nerve in a vertebra that is pain generator for people with chronic low back pain So it's a it's a great additional tool that we have to try and help patients for a very common problem,” he explained.  There are roughly three to four of the procedures done every month Candidates for the non-invasive procedure have lived with chronic lower back pain for quite some time “The requirements are chronic low back pain You've tried and failed greater than six months of conservative efforts of And then a very characteristic MRI finding that would lead you to being a candidate for this procedure,” Dr Aktas said Usually after sitting in the car for 10 minutes wouldn't have to be in bed all the time with the heating pad Patients usually see a difference in their pain levels between two and three months after the procedure “It’s unbelievable to be able to bend down stay down there in that position for a while and not faint or feel like I had it because you’re in so much pain from trying to tie your son’s shoe I’m able to go up and down the stairs without even stopping I don't feel like I feel lightheaded or dizzy from the pain anymore.” A lot of people who are plagued with low back pain can really affect their activities of daily living pretty “There's nothing better than when you you find something And patients are getting better and returning to what they want to do.” among other much more entertaining activities “I didn’t feel lightheaded going down like that And usually when I’m doing standing up for this song “I've been standing for more than 10 minutes I'm ready to just keep going again.' I have the energy I originally couldn't keep up with the energy All I wanted to do was to sit there and do nothing or I was confined to my room and my back because I could do is lay down with a heating pad.” She gets to enjoy raising her children again Access to trusted news and information is urgently needed right now - and when you support WXXI’s public media mission today WXXI offers Rochester and the Finger Lakes solid trusted reporting built on a mission that uses the resources and independence of public media to serve the public good Become a monthly sustainer or increase your current sustaining gift now and your gift will be matched every month for a full year Support the facts and the truth right at the source by making a commitment to public media today your generous support for the essential coverage of WXXI is critical The University of Rochester Medical Center has been awarded funding to lead a large nationwide heart study The cardiac research team received $27 million to jump-start a head-to-head comparison of two popular drugs used to treat heart failure Carvedilol and metoprolol succinate are the two main drugs prescribed to patients with heart failure to improve chances of survival But researchers said no study has been done to determine which is the better option is leading in sudden cardiac death prevention and this study is going to continue to pursue a legacy.” Goldenberg is the director of URMC’s cardiovascular research center He said the study will enroll 2,000 patients across 100 medical centers nationwide a cardiac electrophysiologist for URMC and the lead investigator on the study said the drugs will be evaluated on various metrics to determine which is more effective He said those factors include time spent in the hospital “Patients don't want to be in the hospital,” Aktas said “So if we can demonstrate that one drug keeps patients out of the hospital avoids the chance that they may need a shock from the defibrillator Aktas said it could take several years before enough data is collected to make a decision More New York State News “If you’re looking for a little jolt to wake up a cup of coffee provides caffeine without all the additives found in energy drinks,” says Aktas Another great option for a natural energy boost is a smoothie with fruits and vegetables The added proteins provide sustained energy throughout the day and they won’t affect your sleep the way caffeine will Some of the potential issues caused by the ingredients in energy drinks include: UR Medicine’s Electrophysiology program offers some of the most advanced treatments available for heart rhythm disorders Learn more Volume 3 - 2020 | https://doi.org/10.3389/fdata.2020.608043 This article is part of the Research TopicRepresentation Learning for Graph Mining and GenerationView all 4 articles Network embedding that encodes structural information of graphs into a low-dimensional vector space has been proven to be essential for network analysis applications including node classification and community detection Although recent methods show promising performance for various applications graph embedding still has some challenges; either the huge size of graphs may hinder a direct application of the existing network embedding method to them or they suffer compromises in accuracy from locality and noise we propose a novel Network Embedding method to generate embedding more efficiently or effectively Our goal is to answer the following two questions: 1) Does the network Compression significantly boost Learning 2) Does network compression improve the quality of the representation we propose a novel graph compression method based on the neighborhood similarity that compresses the input graph to a smaller graph with incorporating local proximity of its vertices into super-nodes; second we employ the compressed graph for network embedding instead of the original large graph to bring down the embedding cost and also to capture the global structure of the original graph; third we refine the embeddings from the compressed graph to the original graph NECL is a general meta-strategy that improves the efficiency and effectiveness of many state-of-the-art graph embedding algorithms based on node proximity Extensive experiments validate the efficiency and effectiveness of our method which decreases embedding time and improves classification accuracy as evaluated on single and multi-label classification tasks with large real-world graphs network embedding is converted to word embedding with considers random walk as a sequence of words it is expected that vertices in a similar neighborhood get similar paths and hence similar representations many of these methods are still computationally expensive and need a large amount of memory so they are not scalable to large graphs (scalability problem) these approaches attempt to address the non-convex optimization goal using stochastic gradient descent hence optimization on the co-occurrence probability of the vertices can easily get stuck at a bad local minima as the result of poor initialization (initialization problem) This may cause generating dissimilar representations for vertices within the same or similar neighborhood set many of these methods use local information with short random walks during the embedding by ignoring the global structure in the graph embedding on the coarsest graph is more efficient and needs far less memory that makes existing embedding methods applicable to large graphs grouping vertices with similar characteristics in a compressed graph solves the problem of getting different representations for them HARP (Chen et al., 2018b) addresses the initialization problem by hierarchically compressing the graph by combining nodes into super-nodes randomly low-level representation of nodes though multi-level learning random edge compressing may put dissimilar nodes into the same super-node making their representation similar multi-level compressing and learning result in significant compression and embedding cost hence HARP fails to address the scalability problem we use graph compression to address these two problems and also the limitations of HARP we study graph compression for the Network Embedding problem to answer these two questions: Does the Network Compression Significantly Boost Learning Does the Network Compression Improve the Quality of the Representation Our main goal is to obtain more efficient and more effective network embedding models as answers to these questions we present an extension of our first method that is a general meta-strategy for network embedding We propose a proximity-based graph compression method that compresses the input graph to a smaller graph with incorporating the neighborhood similarity of its vertices into super-nodes NECL compresses the graph by merging vertices with similar neighbors into super-nodes instead of random edge merging NECL employs the embedding of the compressed graph to obtain the embedding of the original graph This brings down the embedding cost and captures the global structure of the original graph without losing locality kept in the super-nodes In addition to reducing the graph’s size for embedding we get less pairwise relationships from random walks on a smaller set of super-nodes which generates less diverse training data for the embedding part All these facts improve efficiency while maintaining similar or better effectiveness comparing to the baseline methods We then project the embedding of super-nodes to the original nodes we primarily focus on improving the efficiency of embedding methods we may lose some local information of the nodes because of merging we go beyond our original NECL by introducing an embedding refinement method NECL-RF uses the compressed graph’s projected embedding to initialize the representation for the original graph embedding Refining these initial representations aids in learning the original graph’s embedding This provides global information of the graph into learning and also solves the different initialization problem of similar vertices Since the compressed graph is quite small compared to the original graph the learning time will not increase significantly Hence similar efficiency is maintained compared to the baseline methods we provide a richer set of experiments to evaluate NECL and NECL-RF we only use DeepWalk and Node2vec as baseline methods for representation learning and combine them with NECL as a general meta-strategy and present the results of all with NECL and NECL-RF as the embedding of nodes with the original graph (C) and compressed graph (D) node proximity is preserved in the compressed graph nodes close in original graph embedding are also close in compressed graph embedding Example of graph compressing on Les Miserables network (Original Network (A) Embedding of Original Network (C) and Embedding of Compressed Network (D)) • New proximity-based graph compressing method: Based on the observation that vertices with similar neighborhood sets get similar random walks and eventually similar representation we merge these vertices into super-nodes to get a smaller compressed graph that preserves the proximity of nodes in the original large graph • Efficient embedding without losing effectiveness: We do random walks and embedding on the compressed graph which is much smaller than the original graph This method has similar effectiveness with baseline methods by preserving the global and local structure of the graph in the compressed graph • Effective embedding without decreasing efficiency: We use the embedding obtained from the compressed graph as initial vectors for the original graph embedding This combines the global and local structure of the graph and improves the effectiveness Embedding of a small compressed graph does not take much time with respect to original graph embedding so it will not increase the embedding time significantly • Generalizable: NECL is a general meta-strategy that can be used to improve the efficiency and effectiveness of many state-of-the-art graph embedding methods We report the results for DeepWalk Node2vec and LINE • The paper is structured as follows we give the necessary background for our method we introduce our neighborhood similarity-based graph compression model by explaining our similarity measure and two different embedding methods that use the compressed graph we present our experimental results and compare them with the baseline methods Our final remarks are reported in Section 5 we discuss related works in the area of network embedding We give some details of pioneer works in network embedding focusing on DeepWalk We also explain random walk based sampling methods and multi-level network embedding approaches here We give the formal definition of network embedding as follows Network embedding is a mappingϕ:V→ℝd,d≪|V|which represents each vertexv∈Vas a point in a low dimensional spaceℝd Here d is a parameter specifying the number of dimensions of our node representation we define NS(u)⊂V as a network neighborhood of node u generated through a neighborhood sampling strategy S We seek to optimize the following objective function which maximizes the log-probability of observing a network neighborhood NS(u) for a node u conditioned on its representation There is an assumption that the conditional independence of vertices will ignore the vertex ordering in the neighborhood sampling to make the optimization problem tractable the likelihood is factorized by assuming that the likelihood of observing a neighborhood node is independent of observing any other neighborhood node given the representation of the source The conditional likelihood of every source-neighborhood node pair is modeled as a softmax unit parametrized by a dot product of their features It is too expensive to compute the summation over all vertices for large networks, so we approximate it using negative sampling (Mikolov et al., 2013b). We optimize Equation 1 using stochastic gradient ascent over the model parameters defining the embedding ϕ The neighborhoods NS(u) are not restricted to just immediate neighbors but can have vastly different structures depending on the sampling strategy S There are many possible neighborhood sampling strategies for vertices as a form of local search Different neighborhoods coming from different strategies result in different learned feature representations random walk based methods are used to capture the structural relationships of vertices They maximize the co-occurrence probability of subsequent vertices within a fixed-length window of random walks to preserve higher-order proximity between vertices networks are represented as a collection of vertex sequence we take a deeper look at the network neighborhood sampling strategy based on random walks and the proximity captured by random walks The co-occurrence probability of node pairs depends on the transition probabilities of vertices we define adjacency matrix A that is symmetric for undirected graphs we have Aij=1 if and only if there exists an edge from vi to vj as Dij=∑kAik if i=j transition probability from one node to another depends on the degree of the vertices The probability of leaving a node from one of its edges is split uniformly among the edges We define this one step transition probability as T: T=D−1A where Tij is the probability of a transition from vertex vi to vertex vj within one step related vertices in the network are hierarchically combined into super-nodes at varying levels of coarseness After learning the embedding of the coarsened network with a state-of-the-art graph embedding method the learned embedding is used as an initial value for the next level The initialization with the embedding of the coarsened network improves the performance of the state-of-the-art methods One of the limitations of this method is that multi-level compressing and learning results in significant compression and embedding cost Random edge compressing may put dissimilar nodes into the same super-node that makes their representation similar Then they generate different meta-graph from the tree and apply the baseline method i.e. After getting the embedding from different meta-graph they combine these embeddings to find the final embedding They use a parameter to regulate the weights of different embedding for combining Our approach differs from these by applying similarity-based compressing to preserve the local information all of these approaches apply hierarchical compressing that may take more time but we apply single level compressing and use it to get the original graph embedding NECL uses the graph coarsening to capture the local structure of the network without a hierarchical manner to improve the efficiency of the random walk based state-of-the-art methods While a desirable network embedding method for real-world networks should preserve the local proximity between vertices and the global structure of the graph it should also be scalable for large networks This section presents our novel network embedding models We extend the idea of the graph compressing layout to network representation learning methods we explain our proximity-based compression method and how we combine compression with network embedding simple graph G=(VG;EG) where VG is the set of vertices and EG⊆{VG×VG} is the set of edges The set of neighbors for a given vertex v∈VG is denoted as NG(v) where NG(v)={u|u∈VG:(u,v)∈EG} A compressed graph of a given graphG=(VG;EG)is represented asCG=(S;M)whereS=(VS;ES)is the graph summary with super-nodesVSand super-edgesESand M is a mapping from each node v in $V_G$ to its super-node inVS A super-edgeE=(Vi;Vj)inESrepresents the set of all edges between vertices in the super-nodesViandVj The critical problem for graph compressing with preserving local structures of the graph is to identify vertices that have similar neighborhoods accurately so they are more likely to have similar representation we discuss how to select vertices to merge into super-nodes The motivation of our method is that if two vertices have many common neighbors many embedding algorithms that preserve local neighborhood information will give similar representations to them This comes from our following observation that if two vertices they also have similar transition probabilities to other vertices Ti=Ai*Dii1 and Tj=Aj*Djj1 Hence they have similar neighborhoods and get similar neighborhood sets from random walks they get similar representations from the learning process For example, in the toy graph in Figure 2 the neighbor sets of the nodes a and b are the same their transition probabilities to the other neighbor vertices are also the same p(ni|a)=p(ni|b)=1/4 for all i∈{1,2,3,4} Starting on either a or b yields the same or very similar walks so they have the same or similar representation instead of walking and learning representations for both a and b it is enough to learn one for both of them we can merge this node pair (a,b) into one super-node ab Transition probabilities of this super-node to neighbors of a and b are still the same with a and b p(ni|ab)=1/4 for all i∈{1,2,3,4} When we obtain the representation of the super-node ab we can project it as the representation of each node in this pair Merging these vertices keeps the preservation of the first and second-order proximity this does not affect the results of walking and learning (a,b) are merged into super-node ab connected to the neighbors of both (a,b) Furthermore, compressing may change the transition probability of neighbors of compressed vertices since the number of their neighbor decrease. As a result, the transition probability of each neighbor changes. For example, in the toy graph in Figure 2A while the transition probability from n1 to its neighbors is 1|N(n1)| it becomes 1|N(n1)|−1 since the number of neighbors decrease by one we assign weights to edges of super-nodes based on the number of merged edges within the compression the super-edge between super-node ab and n1 includes two edges which are (a,n1) and (b,n1) the weight of the super-edge (ab,n1) should be 2 it is not expected to have too many vertices sharing exactly same neighborhood such as node classification and graph clustering if two vertices share many common neighbors they are expected to be in the same class or cluster although their neighbor sets are not completely the same we expect to have similar feature vectors for the vertices in the same class/cluster after embedding we can also apply the same merge operation on these vertices Following the same idea in the example above if neighbors of two vertices are similar (but not exactly the same) we can merge them into a super-node and learn one representation for all While we can project this super-node embedding to original vertices and use the same representation for both we can also update them in the refinement phase to embed the difference of them into their representation we define our graph compressing algorithm formally if a set of vertices n1,n2,…,nr in VG have similar neighbors we merge these vertices into one super-node n12...r to get a smaller compressed graph G′(VG′,EG′) we define the neighborhood similarity based on the transition probability Before defining the neighborhood similarity we first show that cosine similarity between transition probabilities of two vertices u and v are determined by the number of their common neighbors Let T be the 1-step transition probability matrix of vertices V in a graph G and let u,v∈V Let N(u) and N(v) be the neighborhood sets of u and v and Tu and Tv be the transition probability vectors from u and v to other vertices Then the similarity between Tu and Tv is proportional to the number of common neighbors The cosine similarity between Tu and Tv is defined by we have Tu=Au|N(u)| and Tv=Av|N(v)| Hence, if we plug in these into Equation 1 we see that the similarity of transition probabilities from two vertices to other vertices depends on the similarity of their neighbors we define the neighborhood similarity between two vertices as follows Definition 3 (Neighborhood similarity) Given a graph G the neighborhood similarity between two vertices u,v is given by In order to normalize the effect of high degree vertices we divide the number of common neighbors by degree of vertices The neighborhood similarity is between 0 and 1 where it is 0 when two vertices have no common neighbor and one when both have the same neighbors we merge vertices whose similarity value is higher than a given threshold value The neighborhood similarity-based graph compressing algorithm is given in Algorithm 1 It is clear that the vertices with a nonzero neighborhood similarity are 2-step neighbors we do not need to compute the similarity between all pairs of vertices we just need to compute the similarity between vertices and their neighbors’ neighbors we compute the similarity between v and each k as neighbors of neighbors (line 3–10) we check the similarity value of all pairs (u k) in the list and if it is higher than the given threshold λ (line 12) we merge u and k into a super-node su,k (line 13) Then we delete edges of u and k and add edges between neighbors of u and k and the new super-node su,k (line 17–24) We assign weights to the edges of super-nodes based on the number of merged edges within the compression Threshold λ decides the trade-off between efficiency and effectiveness we may merge some dissimilar vertices as well which may result in an increase in efficiency but cause a decrease in accuracy Note that since we use original neighborhood similarity the order of merging does not affect the result so we randomly select a node and check neighbors for compression one super-node may include more than two vertices of the original graph if the similarity between the vertices x and y we merge x and y in sx,y and then we merge sx,y and z into sx,y,z we check whether the node y is merged with another node and if so we get the super-node of the original node x Our NECL framework is adaptive with any embedding method which preserves the neighborhood proximity of nodes We get the embedding for the original graph in two ways Our main goal in this section is to improve the efficiency of the embedding problem while maintaining similar effectiveness with the baseline methods we embed the compressed graph and employ this embedding for the original graph embedding NECL: Network Embedding on Compressed Graph after getting the weighted compressed graph S (line 1) we obtain the representation of super-nodes VS as ϕs in the compressed graph with the provided network embedding algorithm (line 2) We apply any random walk based representation learning algorithm on the compressed graph We just need to apply weighted random walks to consider the edge weights As the size of the compressed graph is smaller than the original graph it is more efficient to get embeddings of super-nodes than single vertices we assign the embedding of super-nodes to vertices according to the mapping M obtained from the compression (line 3–7) While we may lose some local information with assigning the same representation to multiple vertices we may not need to get small differences between nodes for many applications Our main goal in this section is to improve the effectiveness of the embedding problem while still maintaining similar efficiency with the baseline methods we employ the embedding of the compressed graph as initialization to the original graph embedding and refine it the original graph embedding is obtained in line eight by refining the compressed graph embedding given as the initial representation We do our experimental studies to compare our methods with different models in terms of efficiency and effectiveness We evaluate the quality of embeddings through challenging multi-class and multi-label classification tasks on four popular real-world graph datasets we present our model’s performance based on different parameters we compare the results of our models with the results of HARP Datasets: We consider four real-world graphs1 which have been widely adopted in the network embedding studies each node in the datasets has a single-label from multi-class values Baseline methods: To demonstrate that our methods can work with different graph embedding methods we use three popular graph embedding methods We combine each baseline method with our methods and compare their performance We give a brief explanation of the baseline methods in Section 2 which uses a compressed graph embedding as the original graph embedding which uses the compressed graph embedding as the initial vector for original graph embedding and refine it with the original graph we set the following parameters: the number of random walks γ window size w for the Skip-gram model and representation size d The parameter setting for all models is γ=40 The initial learning rate and final learning rate are set to 0.025 and 0.001 respectively in all models Representation size for LINE is d=64 for all model after getting embeddings for nodes in the graph we use these embeddings as the features of the nodes we train a classifier using these features we randomly sample a certain portion of labeled vertices from the graph and use the rest of the vertices as the test data we vary our training ratio from 1% to 50% on the Citeseer and DBLP datasets and from 10% to 80% for BlogCatalog We use larger portion training data for the BlogCatalog dataset because the number of class labels of BlogCatalog is about ten times other graphs Performance comparisons of NECL with baseline methods (BL) Compression ratio with the similarity threshold λ=0.5 Detailed classification results on Citeseer Detailed classification results on BlogCatalog Run time analyses for different similarity threshold values λ (Citeseer (A) The ratio of vertices/edges of the compressed graphs to that of the original graphs Gain on baseline methods: For all datasets, we present macro F1 and micro F1 scores for single and multi-label classification tasks and embedding time in Table 1 and compression ratio for edge and vertices in Table 2. We use 5% training ratio of labeled vertices for Citeseer, Wiki, and DBLP and 40% training ratio for BlogCatalog. As we see from Table 1 there is a significant gain on macro and micro F1 in addition to gain on efficiency on Citeseer while there is a significant gain on total embedding time as efficiency there is no (significant) difference between NECL and baseline methods on macro F1 and micro F1 For LINE we have a higher gain on time for all datasets For DBLP, gains of embedding time are much higher than other datasets. On the other hand, for BlogCatalog, gains of embedding times are less with respect to other datasets. As we see from the Tables 1, 2 the gain of embedding time depends on the compression ratio of the number of edges and vertices the number of vertices and edges for DBLP decrease from 27,199 to 8,824 (70%) and from 13,3664 to 32,984 (75%) embedding becomes more efficient with better or same accuracy the compression ratio is lower than the others so the neighborhood similarity is higher and this results in more compression vertices have less common neighbors and so a lower similarity We can conclude that while the gain in the effectiveness of our method depends on the baseline method the gain in efficiency of our method depends on the characteristics of the dataset Detailed Analyses: We compare the performance of NECL framework for different similarity threshold values λ that results in different compression ratios with the performance of the baseline methods. Macro F1 and micro F1 scores on different datasets are given on Figures 3–6 for Citeseer We observe that for λ>0.45 and micro F1 scores for NECL are similar with or higher than baseline methods across all datasets except Citeseer the quality of embedding decreases dramatically and so does the accuracy of classification The results for Citeseer depend on the baseline methods While λ=0.45 gives better accuracy for DeepWalk and Node2vec In addition to the macro F1 and micro F1 scores, we also report the embedding time and compression ratio for different similarity threshold values λ in Figures 7, 8 we see that NECL takes significantly less time compared to the baseline method and we get a smaller compressed graph and so the embedding time decreases As BlogCatalog has a lower compassion ratio the embedding time is less for all three baseline methods We observe that there is a linear relation between λ and the number of vertices and edges until λ=0.5 graph sizes change dramatically for smaller λ for Citeseer but the decrease is slow for BlogCatalog until λ=0.7 One of the reasons for this situation in BlogCatalog is that the sizes of the neighbor sets for some vertices are very large and it is not easy to get higher similarity for a larger set 10 common neighbors can be considered to have a higher similarity two vertices with 150 edges should have 100 common neighbors to get the same similarity value we observe that smaller λ results in smaller compressed graph we start to lose critical information about the graph we refine our results with our second method Detailed comparisons of classification results on Citeseer Detailed comparisons of classification results on Wiki Detailed comparisons of classification results on DBLP Detailed comparisons of classification results on BlogCatalog we see that NECL or NECL-RF gives the highest macro F1 and micro F1 scores for datasets with all baseline methods except for LINE on Wiki NECL or NECL-RF gives the highest accuracy for all the three baseline models NECL-RF significantly improves the quality of the embedding for all datasets except Citeseer with Node2vec and Wiki with LINE While HARP has higher accuracy than baseline methods it does multiple levels of iteration of graph coarsening and representation learning Embedding time for NECL-RF is the total of embedding time for the original graph and compressed graph the compressed graph is much smaller than an original graph so the learning time for the compressed graph is significantly less compare to the baseline method complexity does not increase significantly as in HARP we get similar or better effectiveness than HARP with less time complexity Detailed comparisons between all methods using different portions of labeled vertices as training data are presented in Figures 9–12 NECL and NECL-RF give the highest accuracy compared to other models or give better results than the baseline models The reason for this decrease might be that learning a global structure with compressed data which also includes a local structure in the super-nodes So when we relearn and update the embedding of the compressed graph it deteriorates the accuracy of the classification task our method has a better improvement on DeepWalk The reason is that while Node2vec and LINE may learn higher-order proximity regular random walk in DeepWalk may not capture higher-order proximity We present a novel method for network embedding that preserves the local and global structure of the network To capture the global structure and accelerate the efficiency of state-of-the-art methods we introduce a neighborhood similarity-based graph compression method We combine the vertices with common neighbors into super-node Then we apply network representation learning on the compressed graph so that we can reduce the run time and also capture the global structure we project the embedding of super-nodes to original nodes without refinement we relearn the representation of the network with assigning the super-nodes embedding to its’ original vertices as initial features and update this using the baseline method we combine the local structure with the global structure of the network While the first method provides efficiency with learning on the small compressed graph the second method provides effectiveness with incorporating global information into embedding with the compressed graph NECL and NECL-RF are a general meta-strategies that can be used to improve the efficiency and effectiveness of many state-of-the-art graph embedding method We use three popular state-of-the-art network embedding methods DeepWalk Experimental results on various real-world graph show the effectiveness and efficiency of our methods on challenging multi-label and multi-class classification tasks for all these three baseline methods The future work of our NECL and NECL-RF could be using different refinement methods of graph embedding We can apply different neural network models without relearning the whole network to refine the embedding which we get from the compressed graph Another extension could be done by using different clustering methods or similarity measurements to compressed the graph and use other baseline methods The original contributions presented in the study are included in the article/Supplementary Material further inquiries can be directed to the corresponding authors Conceived and designed the experiments: MI and EA Performed the experiments: MI This work was partially done by the author Ginger Johnson while she attended the Big Data Analytics REU program at Oklahoma State University supported by the National Science Foundation under Grant No The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest The content of this manuscript has been presented in part at the Big Data conference (Akbas and Aktas, 2019a). 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) distribution or reproduction in other forums is permitted provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited in accordance with accepted academic practice distribution or reproduction is permitted which does not comply with these terms *Correspondence: Muhammad Ifte Islam, aWZ0ZS5pc2xhbUBva3N0YXRlLmVkdQ==; Esra Akbas, ZWFrYmFzQG9rc3RhdGUuZWR1 Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish Connecting talented and ambitious people in the world's greatest cities our mission is to be a top quality institution Join our more than 40,000 students studying in hundreds of programs on six continents all around the globe and scholars expect high achievement in pursuit of engaging the world's diverse challenges we draw spirit from our cities and their famous cultural institutions and professional opportunities Being at the forefront of their disciplines our faculty shape the understanding of an enormous range of academic fields As an intern, Michael, who transitioned from Liberal Studies to the College of Arts and Science this semester, facilitated consumer fragrance tests and organized resulting data for presentations to retail clients.  “I think that it would be cool to take my passion for connecting with other people who are passionate about certain things and apply that to fragrance because it is similar to music,” Michael says. “It's just people coming together about something that they're passionate about, which is a lot like music.” has been selected as an American Society of Cytopathology (ASC) Partners/BIO Ventures for Global Health (BVGH) 2023 Global Health Ambassador Assistant Professor of Pathology at Yale School of Medicine and an Affiliated Faculty of the Yale Institute for Global Health BVGH has partnered with experts and key opinion leaders from industry and NGOs to target the growing cancer crisis in Africa The crisis can be attributed to many complex and connected factors including but not limited to delayed and/or incomplete diagnoses Much of sub-Saharan Africa lacks the diagnostic pathology capacity to needed accurately diagnose and stage cancers to ensure appropriate treatments are prescribed Patients suffer delays due to the lack of efficient and reliable pathology services a cytopathologist and a general surgical pathologist whose interests include quality in healthcare and digital pathology “I have always been interested in doing meaningful and impactful work and serving the big picture,” she said “That interest and purpose led me into getting a master’s in public health and becoming a cytopathologist and getting trained on performing ultrasound guided fine needle aspirations I am thrilled to have found an opportunity to realize these goals Mr Matulic and Mr Aktas have honed their craft in the region starting their career together 24 years ago and running a leading business since 2008 They have partnered with Ms Jarvis of Ray White North Ryde | Macquarie Park have combined to create Ray White The Ryde Group “As we were growing we realised that we needed to make a change to take our business to the next level,” Mr Aktas said “Ray White is the highest performing agency in the country and their systems cannot be competed with.” Mr Matulic said Ryde was a hub of activity and connectivity to the rest of Sydney “We are situated in a prime location for all the infrastructure and development happening around the city and in Western Sydney,” he said “We have connectivity to all motorways and the construction of the new light rail which will pass straight through us connecting Parramatta and Olympic Park “It is a rapidly changing and growing area; we have lots of young families setting up here who can’t afford the Inner West and plenty of first home buyers and investors chasing the apartments.” Ms Jarvis said the two established offices joining forces would lead to outstanding customer service for the region “If you look at the group partnerships that have been established all around Sydney and the success they have achieved it is clear why we have joined forces with another fantastic business,” she said The team has strong rent rolls and property management departments Mr Aktas said that by taking on a larger area there is huge potential to grow the team even further “We want to sustain and exceed the level of service we have offered the community for 24 years; the relationships we have built here are very dear to us,” he said We opened our office right in the middle of the GFC; we knew that we had the skills and connections to sustain ourselves sustainable agency for the Ryde area for years to come.” Ray White NSW Chief Executive Officer, Tim Snell said he was thrilled to watch another excellent partnership thrive within the Ray White family “It is a testament to our group when seasoned and well-respected businesses choose to join forces with our fantastic operators like Kerry Jarvis,” Mr Snell said “Operators like David Aktas and Nick Matulic are the dynamic and ambitious leaders that we strive to produce in the Ray White New South Wales network “I see a bright future ahead for the super-team that is Ray White The Ryde Group.” News Sitemap Day one of the Tallinn European Open 2024 showed promise for the young hopefuls of Estonia Judo The Italian athlete simply couldn’t keep up with the onslaught of attacks and instead ceded three shidos It will be the third time Weling and Heyder have met in competition this year Germany were guaranteed a place in the -63kg final as Hanna SEDLMAIR (GER) and Viktoria FOLGER (GER) went head to head in the first semi final. It was a tough one for the women, but in the end, Sedlmair was the winner based on the accumulation of shidos for Folger. Sedlmair will now meet Kamile NALBAT (NED) in the final. Nalbat baited Carlotta AVANZATO (ITA) in their semi final and executed a waza ari-scoring ura nage to clinch her win but Chernov was met with the stone wall of Bouda who used his opponents momentum to throw him The German theme continued in to the -73kg category with an all-German semi final between Jano RUEBO (GER) Lennard SLAMBERGER (GER) it was hard fought it was a shido conclusion with Ruebo taking the place in the final Chusniddin KARIMOV (CZE) had been explosive throughout the preliminaries and he wasn’t about to give up his place in the final but succumbed to a huge o soto gari attack from Karimov that earned him a contest-winning waza ari Not only have Germany secured some final spots, but regardless of the final result in the -78kg category, we will be hearing the German national anthem. First up, Migle Julija DUDENAITE (LTU) suffered defeat at the hands of Julie HOELTERHOFF (GER) Hoelterhoff managed to take the win with a switch she changed direction to score ippon with o uchi gari it didn’t go so swiftly for Mathilde Sophie NIEMEYER (GER) however she persevered against Paulina DZIOPA (POL) and caught her with a stunning de ashi barai candidate Buse Aktas draws on her artistic background and craftsmanship experience as she researches soft robotic structures that vary in stiffness painstakingly stitched and woven together from stiff strands of grass seems to be the polar opposite of a sophisticated But Buse Aktas sees a number of similarities between the age-old tool and ultra-modern device And she would know; Aktas, a mechanical engineering Ph.D. candidate at the Harvard John A. Paulson School of Engineering and Applied Sciences, spent several years as a broom maker’s apprentice in her native Turkey before beginning soft robotics research in the lab of Rob Howe Abbot and James Lawrence Professor of Engineering is like an extended apprenticeship,” Aktas said “I like learning things and putting that knowledge into a bigger perspective Aktas works on a handcrafted broom in the workshop of master broom maker Niyazi Usta Aktas didn’t intend to become a broom maker she enjoyed drawing and making sculptures from found materials “I became an engineer because my dad is a really big guy,” she said “He never fit behind the TV or into tight spaces like that While she found it difficult to leave Turkey Aktas enrolled at Princeton University and majored in mechanical engineering but became so disillusioned while studying engineering theory that she planned on being a full-time artist Aktas got her first taste of research in a microfluidics lab but chose a more “people-oriented” project for her thesis She developed a device to help individuals with physical and mental disabilities build objects on an assembly line at an Easter Seals workshop She also drew on her sculpture background by hosting hands-on art workshops aimed at redesigning the workplace to give employees more agency and ownership within their work experience Aktas works with high school students during a workshop where they completed a design challenge using jamming I learned that people have very different ways of expressing themselves,” she said it is important to understand what the issue is and give agency to members of that community rather than just trying to do something for them.” She enjoyed seeing how her artistic skills could make an impact and returned to Turkey with plans to be an Istanbul-based sculptor she had the opportunity to complete mini-apprenticeships with a Turkish saddle maker she launched an artistic collaboration with the broom maker while completing a master’s degree in design and cultural heritage at Istanbul’s Kadir Has University Aktas worked closely with the master broom maker absorbing each detail of the craft and then creating an exhibition of 40 sculptures that used only broom making materials and techniques “I felt this real sense of urgency to protect these dying crafts,” she said “These are types of knowledge that you can’t write down You can only transfer it over time through experiential learning Knowledge can’t just be limited to journal articles only the person who has the knowledge has the power Working 12 hours a day in a broom maker’s studio taught Aktas much more than stretching and weaving techniques “It takes a lot of time to learn something,” she said “It is very important to respect the people who are giving you that knowledge but you also need to find the right way to challenge them to be able to internalize it and make it your own.” Aktas sets up for her broom art exhibition Aktas’ passion for knowledge inspired her to pursue a Ph.D She chose Howe’s lab so she could keep working with her hands while pursuing a wide array of projects she is utilizing jamming techniques to develop soft robotic structures that vary in stiffness Jamming enables a researcher to change the mechanical properties of a material drastically by squeezing it tightly Aktas and her colleagues are modeling how jamming structures could be used to bridge the gap between soft and rigid robots Her work has applications in everything from medical devices such as wrist braces that help rehab patients to manipulators that can grasp items in a warehouse “The biggest challenge comes from the innumerable facets involved in jamming I can get lost in my own work and forget that there is this whole world of robotics applications we are trying to reach,” she said She especially enjoys how well the field lends itself to outreach Jamming is an ideal method to teach children mechanics because they can see and touch devices that clearly exhibit theoretical principles In addition to mentoring robotics teams and LEGO leagues Aktas has overseen design challenges for high school students and offered STEM workshops at science fairs She plans to make the development and scientific study of STEM workshops Aktas still considers herself as much an artist as an engineer She thinks of research as a sort of performance art and constantly explores new ways to share her work her lab presentations incorporate storytelling “I’m starting to ask my own research questions and I was feeling a bit apprehensive about it,” she said I just hadn’t done that in a scientific context My background in art helps me to be braver.” Aktas draws on her artistic background when developing research questions Aktas hopes to continue working at the intersection of art and science after completing her Ph.D She intends to become an engineering professor and wants to bring engineering and art students into her lab to work on projects together all goes back to the countless hours she spent in that broom maker’s dusty workshop “I don’t want to be a great researcher with lots of cited papers for my own sake; I want that because it would grant me the capacity to give freedom to my students because he is such an established researcher and he can also expose me to communities in which I can share my work and get useful feedback And that is because of how hard he has been working over the years,” she said so I can give my students a safe place to explore Yasemin Aktas is an IP litigator and Turkish trademark and patent attorney who has 12 years’ experience practising IP law in Turkey She advises on a wide range of IP issues and transactions regarding trademarks working with foreign and multinational clients from various industries in implementing IP protection litigation and enforcement strategies and portfolio management Ms Aktas has wide experience in building anticounterfeiting strategies She is a member of the INTA Anticounterfeiting Committee Marques Dispute Resolution Team and ECTA Publication Committee and has been selected as a member of the IP Experts Group to assist the International Anti-counterfeiting Coalition IP Advisory Board Ms Aktas has been ranked among the top tier IP professionals in Turkey by the WTR 1000 and the IAM Patent 1000 and has been listed as Recommended Lawyer by The Legal 500 Unlock unlimited access to all WTR content Tolga Aktas is a UK-based conservation biologist who participated in Black Birders Week there weren’t many outlets showing diversity so I was only able to be inspired by white conservationists and naturalists,” Aktas said “The Black Birders Week movement allowed me to see that there are many Black wildlife heroes out there It reassures me that everybody can make a difference towards our planet.” Aktas’s interest in becoming a conservation biologist storyteller and explorer was not born overnight a village in Northern Cyprus where his extended family lives Aktas spent the season exploring the natural wonder of the region always studying the animals that call the island home Aktas touched on the outdoor experiences that led him on his journey to become a conservation biologist and how he would like to empower others to go after their dreams Tolga Aktas exploring the natural landscapes in the Cotswolds Q: What experiences sparked your passion for the natural world  Tolga Aktas (TA): It all started with following my uncle at dawn and dusk as he took his sheep and goats out to graze near the mountains in Northern Cyprus I had the opportunity to travel between Northern Cyprus and Jamaica a lot because my parents were from these countries This allowed me to discover different habitats ecosystems and fundamentally the wildlife that were native to these countries My favorite memories were created in Northern Cyprus during my upbringing as I spent a lot of time away from my cousins in the fields near our homes Living in a village there were loads of animals running around I was always in awe with what I saw around me It really gave me a true appreciation of the natural world even to a point that I traded the use of my Gameboy Advance to my cousin so I could get my hands on a chicken egg I think I was around five or six when I first had a sense of the animals and environment around me and this later led to being exposed to wildlife documentaries where the late Steve Irwin and Sir David Attenborough changed everything for me My journey was a bit scrambled at first as I had to go through a career change from electrical engineering to be where I am today but when I was younger I didn’t have the resources to push me to do what I am doing today I never saw a Black person presenting wildlife programs or doing other kinds of wildlife work I thought it was a lost cause back then and after I left secondary school with bad grades I settled with anything that would get me by and this is where I got into electrical engineering Q: So how did you make it in the wildlife conservation world It has been a wacky rollercoaster ride with how I got into the conservation world to be honest it seemed like it lasted forever when I was first started out But it has been totally worth it and wouldn’t trade all of my experiences for anything in the world I owe a lot to watching wildlife documentaries when I was younger because if it wasn’t for those then I probably wouldn’t have embarked on all of the experiences which led me to the position where I am today Once I broke into the wildlife conservation field I knew that I had achieved some form of success in my life It has always been a dream to explore the natural world to witness all of the wildlife it has and the wild spaces that we all share It still hasn’t hit me that I am finally living my dream but I am grateful for everything that has been presented to me Tolga Aktas attaching a new radio tracking collar to a lion in South Africa Q: What impact has Black Birders Week had on you  TA: Black Birders Week was absolutely fantastic to watch develop I knew it was a topic that was here to stay and make an impact Before I knew it there were brothers and sisters from all races standing up for each other and what is right It was so nice to be put in touch with the many amazing people that work in STEM fields I am very excited and thrilled to know that people of all races are using their voices to educate and contribute to making a positive change towards our planet I look forward to seeing what the Black AF in STEM group will achieve next I think it would’ve meant everything to have been exposed to a scenario like this when I was a kid It would’ve brought things closer to home and I would’ve had more diversity in the people I call my heroes things will be different for the generations that are coming forth now who have the exposure to a much diverse community of nature enthusiasts and people that work in STEM fields We need to show them that jobs in these fields are achievable for them too no matter what color their skin is or where they’re from a species native to Africa and small parts of Arabia I was really moved to see all these different groups forming a community and all supporting each other Even though we are all scattered geographically around the world and the discussion about racism was circulating everywhere When I saw that video of Christian Cooper and Amy Cooper in Central Park it was really a disturbing experience and I think everybody that watched it must have felt as threatened as Christian Cooper I recall watching the video clip with my jaw open thinking if such an experience happened to me I don’t know what I would have done or if I would have handled it as well as Christian did It’s very worrying that there are people out there that feel the need to see beautiful and innocent people as a threat Tolga Aktas feeding wolves at a sanctuary in Berkshire Q: During Black Birders Week there were a lot of discussions about racism and interactions with the police have you ever experienced any challenges or dangers when conducting fieldwork  TA: I have been very fortunate to not have experienced any racism during my times conducting fieldwork that doesn’t necessarily mean that the issue isn’t present as I was probably just at the right place at the right time I do pray that I don’t have to experience something like this or that anybody else does as it could really ruin an experience that means the world to them or took a very long time to achieve the world witnessed many advocates standing up for those that had fallen due to racism whether it was modern tragedies or tragedies in the distant past I just hope that these same people stand with us for years to come Rest in peace to every angel and solider that has fallen and lost their lives to racism It has been going on for too long and it is a shame that it still occurs today Tolga Aktas adjusting a radio tracking collar onto an African wild dog Q: As a conservation biologist who focuses on canids how would you like to use your skills to further the initiative TA: A lot of people in STEM fields were inspired by a white person and hopefully through Black Birders Week people are able to be inspired by STEM professionals from all other races too If you have a dream and believe that your story and voice can make a difference towards the natural world The biggest struggle is overcoming the doubt in ourselves and finding the courage to accomplish our goals They’re doing amazing work over in South Africa protecting endangered animals like the wild dogs After spending a month with the team at Wildlife ACT tracking wild dogs and lions from dawn and dusk I knew in my heart that I would be coming the following year to study these species for my university thesis Tolga Aktas tracking and monitoring for African wild dogs in South Africa and everybody that knows me knows this very well I think anybody that hasn’t seen the species before in the wild or in captivity and eventually sees them for the first time almost certainly becomes an advocate in protecting them my attitude was to focus on a particular species and build my career around it This was when I didn’t know much about ecology and biodiversity and its importance in ecosystems you then begin to appreciate every species and the habitats that support them and realize that you have to focus on the bigger picture As our species continue to populate the world and space becomes limited alongside the natural world my biggest mission now is to build my career around a world where we can co-exist with every species Tolga Aktas exploring the ancient woodland of Epping Forest Kara Jamie Norton (@whereskara) is an independent science journalist based in New York City © 2025 WNET PBS is a 501(c)(3) not-for-profit organization An Anadolu photojournalist faced police violence Friday while covering pro-Palestinian protests in Brooklyn Fatih Aktas experienced police brutality as he was trying to capture images of the New York Police Department’s violent response to the protesters Footage taken by another journalist shows Aktas being forcefully shoved by a police officer while attempting to photograph the protests "While I was trying to capture the police intervention in the protests a police officer strongly pushed me backward," Aktas said Aktas said that with the help of another police officer and his colleagues he got back on his feet and continued his work not noticing his injuries due to the heat of the moment After the protests he saw bruising on his elbow and felt pain "I could have hit my head on the ground at that moment which could have had more severe consequences I also experienced the violent police intervention against the peaceful protesters," he said Türkiye's Communications Director Fahrettin Altun condemned the attack saying: “Press freedom is the backbone of democracy.” “We will continue to stand by all truthful journalists who fight against injustice and unfairness.” spokesman for Türkiye's Justice and Development (AK) Party “We once again express our pride in Anadolu Agency for conveying international sensitivity towards the oppressed Palestinian people,” he said police violently intervened in protests held in support of Palestine in front of New York’s Brooklyn Museum The protesters occupied parts of the museum to protest Israel's attacks on the Gaza Strip particularly the recent Israeli attack on Rafah New York Police detained dozens of pro-Palestinian supporters and journalists captured moments of a police officer throwing a female protester to the ground and punching her More than 36,000 Palestinians have been killed in Gaza in a deadly Israeli offensive on the Gaza Strip since last Oct Most of those killed have been women and children Vast tracts of Gaza lay in ruins amid Israel's crippling blockade of food Israel is accused of genocide at the International Court of Justice (ICJ) whose latest ruling ordered Tel Aviv to immediately halt its operation in Rafah where more than 1 million Palestinians had sought refuge from the war.​​​​​​​​​​​​​​ Lipoxygenases (LOXs) have essential roles in stroke, atherosclerosis, diabetes, and hypertension. 12/15-LOX inhibition was shown to reduce infarct size and brain edema in the acute phase of experimental stroke. However, the significance of 12/15-LOX on neuroinflammation, which has an essential role in the pathophysiology of stroke, has not been clarified yet. These results suggest that 12/15-LOX inhibition suppresses ischemia-induced inflammation in the acute and subacute phases of stroke via suppressing inflammasome activation. Understanding the mechanisms underlying lipid peroxidation and its associated pathways, like inflammasome activation, may have broader implications for the treatment of stroke and other neurological diseases characterized by neuroinflammation. Volume 17 - 2023 | https://doi.org/10.3389/fncel.2023.1277268 This article is part of the Research TopicThe Role of Inflammation in Neurodegenerative and Psychiatric DisordersView all 5 articles Introduction: Lipoxygenases (LOXs) have essential roles in stroke 12/15-LOX inhibition was shown to reduce infarct size and brain edema in the acute phase of experimental stroke the significance of 12/15-LOX on neuroinflammation which has an essential role in the pathophysiology of stroke ischemia/recanalization (I/R) was performed by occluding the proximal middle cerebral artery (pMCAo) in mice 50 mg/kg) or its solvent (DMSO) was injected i.p at recanalization after 1 h of occlusion Infarct volumes were calculated on Nissl-stained sections Neurological deficit scoring was used for functional analysis Lipid peroxidation was determined by the MDA assay and caspase-1 were detected with immunofluorescence staining and lipid peroxidation were significantly attenuated in ML351-treated groups at 6 ELISA results revealed that the pro-inflammatory cytokines IL-1beta and TNF-alpha were significantly decreased at 6-h and/or 24-h of I/R while the anti-inflammatory cytokines IL-10 and TNF-alpha were increased at 24-h or 72-h of ML351 treatment NLRP1 and NLRP3 immunosignaling were enhanced at three time points after I/R which were significantly diminished by the ML351 application NLRP3 immunoreactivity was more pronounced than NLRP1 we proceeded to study the co-localization of NLRP3 immunoreactivity with 12/15-LOX and caspase-1 which indicated that NLRP3 was co-localized with 12/15-LOX and caspase-1 signaling NLRP3 was found in neurons at all time points but in non-neuronal cells 72 h after I/R Discussion: These results suggest that 12/15-LOX inhibition suppresses ischemia-induced inflammation in the acute and subacute phases of stroke via suppressing inflammasome activation Understanding the mechanisms underlying lipid peroxidation and its associated pathways may have broader implications for the treatment of stroke and other neurological diseases characterized by neuroinflammation Effects of 12/15-LOX inhibition by ML351 on the acute and subacute phases of neuroinflammation following I/R ROS-induced oxidative stress exacerbates the production of oxidized lipids by the 12/15-lipooxygenase enzyme in the ischemic brain These oxidized lipids stimulate neuroinflammation and contribute to the pathophysiology of I/R Neuroinflammation is especially driven by NLRP1 and NLRP3 inflammasome protein complexes The inflammasomes convert procaspase-1 into its active form caspase-1 Caspase-1 facilitates the cleavage of the pro-inflammatory cytokine into its active form and leads to the release of IL-1beta from especially neurons at the acute phase of neuroinflammation Production of other pro-inflammatory cytokines (TNF-alpha IL-6) is significantly increased at 24 h of stroke which also initiates the synthesis of anti-inflammatory cytokines to protect the tissue itself (TGF-beta suppresses inflammasome activation by reducing lipid peroxidation and eventually decreases infarct volume and neurological deficit score (NDS) while providing an inhibitory effect on pro-inflammatory cytokines it also increases anti-inflammatory cytokines (A graphical abstract was created by Canan Cakir-Aktas and Hulya Karatas) The role of 12/15-LOX in neuroinflammation is complex and multifaceted involving the production of pro-inflammatory mediators such as leukotrienes and reactive oxygen species further research is needed to fully elucidate the role of 12/15-LOX in stroke pathophysiology and determine whether it represents a viable therapeutic target for stroke treatment this study aimed to investigate the role of 12/15-LOX inhibition by a novel and potent 12/15-LOX inhibitor on the inflammasome-related neuroinflammation induced by ischemia in acute and subacute phases of the MCAo stroke model in mice Mice were sacrificed under high-dose chloral hydrate anesthesia at 6 The following scoring system was employed for baseline and postoperative neurological examinations (Bederson et al., 1986) 0: no visible neurological damage (normal); 1: inability to extend the right paw (mild); 2: turn to the opposite side (middle); 3: loss of walking or righting reflex (severe) Lipid peroxidation was measured by TBARS Assay Kit (OxiSelect TBARS Assay Kit The principle of this method is based on the formation of a 1:2 conjugate of Malondialdehyde (MDA) with thiobarbituric acid (TBA) the tissue samples were diluted with 5% butyl hydroxytoluene and 100 μL of sodium dodecyl sulfate (SDS) lysis solution was added to 100 μL of the sample and incubated at room temperature for 5 min 250 μL TBA solution was added to samples and the mixtures were incubated at 95°C for 45 min the mixtures were cooled on ice for 5 min and centrifuged at 10.000 x g for 15 min 200 μL of the supernatant was taken and transferred to a new tube and 300 μL butanol was added The mixture was vortexed at 3000 rpm for 3 min and centrifuged at 10.000 x g for 5 min The absorbances of the supernatants were read at a wavelength of 532 nm in a microplate reader (SpectraMax M2 A standard graph was employed to calculate the results The results were standardized by dividing the wet tissue weight the mice were sacrificed with high-dose anesthesia After the removal of the infarcted brain region A buffer (25 mM Tris buffer (pH 7.4; 2 mM EDTA 0.1% Triton X-100)) suitable for the biochemical analyses was used for tissue homogenization After adding buffer and protease inhibitor (1X) to the tissues they were homogenized at 10% (w/v) by Ultra-Turrax® (S8N-5 g IKA-Werke GmbH) on ice for 3 × 10 s All these procedures were performed on ice to prevent protein degradation 100 μL samples were aliquoted from each homogenate and stored in a − 80°C freezer The remaining homogenates were centrifuged at 13.000 g for 15 min at +4°C the supernatant was separated from the pellet and used for ELISA Quantitative expression of inflammatory cytokines (IL-6 and TGF-beta) in the ischemic brain regions was detected by the sandwich ELISA method United States) were quantified with ELISA kits according to the manufacturer’s protocols I/R-DMSO and I/R-ML351-treated brain samples were compared Three mice in each group were analyzed for ELISA The absorbances of the samples were read at a wavelength of 532 nm on a microplate reader (SpectraMax M2 The curve of the standard graph was employed to calculate the results The results were normalized by the amount of total protein which was determined by BCA assay in the samples (ng/mg protein) mice were transcardially perfused with heparinized saline along with 4% PFA at 6 and 72-h after ischemia (n = 6 mice/group) The brain tissues were carefully removed and fixed in PFA at 4°C overnight the brains were sectioned in the coronal plane at a thickness of 12 μm following overnight incubation in a 30% sucrose solution The tissue sections were incubated in sodium citrate buffer (pH 6) at 80°C for 15 min for antigen retrieval they were incubated with normal serum of the associated secondary antibody host (10%) and BSA 1% in TBS for 1 h RT the sections were incubated with primary antibodies targeting specific proteins 12/15-LOX (kindly provided by Klaus van Leyen) and caspase-1 (Abcam; 1:200) the sections were washed three times with TBS containing 0.025% Triton X-100 (Merck Millipore the sections were incubated with appropriate Cy-3 or Alexa Fluor 488 conjugated anti-mouse or anti-rabbit IgG secondary antibodies (Jackson ImmunoResearch 115–165-146 or 115–545-146; 111–165-144 or 111–545-144) To employ double immunostaining of NLRP1/NeuN the blocking step was repeated using a 10% normal serum of the associated secondary antibody host the sections were incubated with appropriate Cy-3 or Alexa Fluor 488 conjugated secondary antibodies (Jackson ImmunoResearch) the stained tissues were carefully mounted with a PBS/glycerol medium containing Hoechst 33258 (InvitrogenTM) to visualize the cellular nuclei three images were captured from the peri-infarct area using a Leica TCS SP8 confocal laser scanning microscope (Leica To quantify the immunofluorescence labeling results the number of NLRP1 and NLRP3 positive cells was counted by researchers who were blinded to the DMSO and LOX inhibitor treatment groups in the I/R model The captured images were then analyzed using Image J software (NIH the results were standardized by calculating the proportion relative to the counts obtained from naive brain tissue Data were presented as mean ± standard error of the mean (S.E.M.) Differences among experimental groups were analyzed by student’s t-test or ANOVA followed by Tukey’s post hoc test Non-normally distributed data of groups were compared using the Kruskal-Wallis test and the Mann–Whitney U test was used for two-group comparisons as a post hoc test A p-value ≤0.05 was considered statistically significant Statistical analyses were carried out using GraphPad Prism software version 6 and pro- and anti-inflammatory cytokine levels in the brain tissues of I/R-DMSO and I/R-ML351 mice (A) The experimental design of the study is summarized in the schema ischemia/recanalization (I/R) was performed by proximal middle cerebral artery occlusion in mice (B) Infarct volume analysis was performed on Nissl-stained sections Infarct volumes were significantly decreased in ML351-treated groups at 6 (C) Functional outcome was determined with neurological deficit scoring following I/R Neurological deficit score results showed that 12/15-LOX inhibition significantly improved neurological deficit at all time points (n = 9 mice/group *p = 0.0420 for 6-h; *p = 0.0170 for 24-h; ***p = 0.0008 for 72-h) (D) MDA analysis results showed that increased lipid peroxidation after I/R was attenuated with ML351-treatment at all time points (n = 3 mice/group ***p = 0.0004 for 6-h *p = 0.0196 for 24-h *p = 0.0414 for 72-h) (E–G) Quantitative analysis of IL-6 and IL-1beta pro-inflammatory cytokines was done with ELISA (n = 3 mice/group) data is given as proportioned to the total protein levels of the brain tissue samples (ng/mg protein) Pro-inflammatory cytokines were induced especially at 24-h following I/R IL-6 (****p < 0.0001) and TNF-alpha (***p < 0.0004) were suppressed by administration of ML351 at 24-h of ischemia IL-1beta was increased at 6-h (***p = 0.0002) and 24-h (****p < 0.0001) of I/R and decreased with ML351 treatment at 6-h (**p = 0.003) and 24-h (****p < 0.0001) (H,I) Quantitative analysis of anti-inflammatory cytokines with ELISA (n = 3 mice/group) ML351 induced the IL-10 anti-inflammatory cytokine at 24-h and 72-h of I/R (**p = 0.0069 while TGF-beta was increased at 72-h of I/R by ML351 treatment (***p = 0.0002) These findings suggest that ML351 treatment plays a crucial role in maintaining the balance between pro- and anti-inflammatory cytokines which may contribute to its protective effects in reducing tissue damage and neuroinflammation The prominent increases in IL-10 and TGF-beta levels at 24-h or 72-h respectively and the significant increase in TGF-beta levels at 72-h provide suggestive evidence that ML351 may have a delayed but potent effect on promoting anti-inflammatory responses To further explore I/R-induced neuroinflammation we investigated the involvement of inflammasomes in ischemia-induced tissue damage This suggested that neuronal NLRP1 inflammasome activation contributes to the inflammatory response following cerebral ischemia the decrease in NLRP1 immunoreactivity with ML351 treatment indicated that 12/15-LOX inhibition may have a protective effect against inflammasome-mediated inflammation in this model Immunofluorescence analysis of NLRP1 inflammasome at 6-h (A) NLRP1 inflammasome protein was detected with immunofluorescence staining (n = 5 mice/group) Images of Hoechst-33258-labeled cell nuclei (blue) were overlapped with the images of NLRP1 (40X scale bar = 25 μm) whose expression was increased in the cell cytoplasm 6 was decreased by 12/15-LOX inhibition (ML351) In the ML351 treated group at 24-h after I/R NLRP1 appears to be expressed in both the soma and its axonal extension which may indicate that it is neuronal (White arrow) (B) Quantitative analysis showed that NLRP1 increased in DMSO groups at 6-h (**p = 0.002) 24-h (****p < 0.0001) and 72-h (**p = 0.0013) (n = 3 mice/group) and decreased with ML351 treatment (C) Double labeling of NLRP1 (red) and neurons (NeuN; neuronal marker) (green) showed that NLRP1 is colocalized with the NeuN signal Some of the overlapping markings are shown with arrows This change in cellular source suggests that NLRP3 may play a role in both neuronal and non-neuronal cells during the progression of I/R Further investigation is needed to determine the specific functions of NLRP3 in these different cell types and its implications for stroke pathology Immunofluorescence analysis of NLRP3 inflammasome at 6-h Representative images of NLRP3 (red) and Hoechst-33258 (blue) were overlapped (40X Cytoplasmic NLRP3 labeling was increased in the DMSO groups of the acute and subacute phases of I/R labeling and signal intensity of NLRP3 were dramatically decreased at all time points following I/R (B) Graphical representation of the changes in cell numbers with positive NLRP3 immunoreactivity at 6 NLRP3 positive cell numbers were increased in both the acute (6 and 24-h) and subacute (72-h) phases of I/R The decreases in NLRP3 immunoreactivity at 6-h (***p = 0.0003) 24-h (**p = 0.0027) and 72-h (****p < 0.0001) with ML351 treatment were statistically significant (n = 3 mice/group) (C) Double immunolabeling of NLRP3 (red) and neurons (NeuN; neuronal marker) (green) showed that NLRP3 is colocalized with NeuN (white arrows) signal especially at 6-h and 24-h after I/R At 72-h of I/R NLRP3 immunoreactivity was present both in neurons (white arrows) and non-neuronal cells (black arrows) (D) Comparison of NLRP3 and NLRP1 staining in I/R-DMSO groups normalized to naive brain tissue NLRP3 immunostaining was significantly increased compared to NLRP1 immunoreactivity (****p < 0.0001) suppressed neuroinflammation by inhibiting the NLRP3 inflammasome at 6-h and NLRP3/Caspase-1 immunolabelling at 6-h Nuclei were stained with Hoechst-33258 (blue) (40X (A) Representative images of NLRP3 (green) and Hoechst-33258 (blue) were overlapped in the third panel (n = 3) Double labeling of NLRP3 and 12/15-LOX showed that there was a strong colocalization that acted in parallel and decreased in ML351-treated brains at all time points of I/R a downstream effector of inflammasome activation staining indicated that caspase-1 is increased mainly at 24-h and 72-h of I/R (C) NLRP3 and caspase-1 double labeling was performed at 24-h of I/R brains as prominent caspase-1 activation was observed at this time point which revealed that caspase-1 positive cells were also positive for NLRP3 These results suggested that the increased expression of caspase-1 in the I/R groups was closely associated with the activation of the NLRP3 inflammasome which was effectively inhibited by the administration of the 12/15-LOX inhibitor these findings highlight the potential therapeutic benefits of targeting the 12/15-LOX pathway to reduce neuroinflammation via the inflammasome pathway and improve outcomes in ischemic stroke which were summarized in the graphical abstract figure the findings of this study suggest that ML351 exerts protective effects in an I/R mouse model by reducing tissue damage and modulating the production of pro- and anti-inflammatory cytokines mediated by the inhibition of NLRP1 and NLRP3 inflammasome activation which may play a crucial role in the inflammatory response following cerebral ischemia Targeting the 12/15-LOX pathway and inflammasome activation could be a potential therapeutic strategy for reducing neuroinflammation and improving outcomes in ischemic stroke anti-inflammatory cytokine (TGF-beta and IL-10) results displayed that TGF-beta was decreased after the stroke at all time points and only recovered at 72-h with 12/15-LOX inhibitor IL-10 levels were increased prominently at 24-h of stroke with 12/15-LOX inhibition These results suggest that the anti-inflammatory reaction of 12/15-LOX inhibition is mediated by IL-10 response at the acute phase while TGF-beta responds at the subacute phase of ischemia This highlights the potential therapeutic benefits of ML351 in reducing neuroinflammation following I/R and the timing of targeted inflammatory reaction has utmost importance That is why our study highlights the importance of considering multiple pathways and their interactions in the development of stroke treatment This research also provides valuable insights into the complex nature of inflammatory responses and offers potential avenues for future research and treatment options Further studies focusing on the crosstalk between lipid peroxidation and other cell death pathways may shed light on the pathophysiological mechanism of each process and might provide novel therapeutic targets for relevant diseases our findings suggest that targeting NLRP1 or NLRP3 inflammasome activation by 12/15-LOX inhibition may be a promising approach for reducing inflammation and improving outcomes in I/R injury this study emphasizes the significance of understanding the cellular sources and expression patterns of key inflammatory molecules at different stages of stroke progression we may have a better understanding of the underlying mechanisms driving stroke pathophysiology Opposite studies may be related to the complex and dynamic nature of the inflammatory response in stroke which involves multiple cell types and signaling pathways Further research is needed to elucidate the precise mechanism underlying the effects of 12/15-LOX inhibition on post-stroke inflammation and to explore its potential as a therapeutic target for stroke a comprehensive understanding of its role in stroke pathogenesis is crucial for developing effective interventions Limitations of our study include the low number of mice used in some experiments we tried to increase the accuracy of the results by obtaining at least 3 images from consecutive periinfarct areas and repeating ELISA studies 2–3 times Yet we obtained statistically significant results Another one is studying only brain tissue for ELISA analysis; serum samples would be valuable to compare brain tissue results with circulating cytokines serum levels of inflammatory cytokines may not represent brain inflammation accurately as there may be other systemic confounding factors Our results provide new insights into the role of 12/15-LOX in inflammasome signaling and neuronal damage The activation of the NLRP3 inflammasome in 12/15-LOX-positive cells may contribute to the inflammatory response and neural damage observed in stroke Targeting this pathway may represent a novel therapeutic strategy for stroke prevention and treatment our findings highlight the need for further investigation into the mechanisms underlying inflammasome activation in neurons and their contribution to neurological disorders our study sheds light on the complex interplay between inflammation and neuronal damage in stroke pathophysiology further research is needed to fully understand the role of 12/15-LOX in stroke-induced neuroinflammation the development of specific inhibitors targeting 12/15-LOX may provide a potential therapeutic strategy for stroke patients It is also important to note that neuroinflammation and lipid peroxidation are not only involved in stroke but also in other neurological disorders such as Alzheimer’s disease and Parkinson’s disease understanding the mechanisms underlying lipid peroxidation and its associated pathways may have broader implications for the treatment of various neurological diseases continued research on lipid peroxidation and its effects on neuroinflammation will contribute to a better understanding of the pathophysiology of stroke and other neurological disorders ultimately leading to improved treatments and outcomes for patients these results indicate that one of the possible mechanisms of 12/15-LOX inhibition involves the suppression of neuroinflammation in both the acute and subacute phases of cerebral ischemia/recanalization by suppressing inflammasomes and inflammasome-related proteins These findings also suggest that 12/15-LOX inhibitors may be a treatment option for stroke therapy or other diseases characterized by neuroinflammation The original contributions presented in the study are included in the article/supplementary material further inquiries can be directed to the corresponding author The animal study was approved by Hacettepe University Animal Experiments Ethics Committee (Approval No: 2016/27–04) The study was conducted in accordance with the local legislation and institutional requirements The author(s) declare financial support was received for the research This study was supported by Hacettepe University Scientific Research Projects Coordination Unit (Project number: THD-2016-11381) and The Scientific and Technological Research Council of Türkiye (TÜBİTAK) (Project number: 118S131) and Esra Buber for their helpful insights into the project We also cordially thank technician Mesut Firat who helped with the experiments The reviewer EE declared a shared affiliation with the author KL to the handling editor at the time of review The handling editor EK declared a past co-authorship with the author MY All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher Inhibition of the inflammasome complex reduces the inflammatory response after thromboembolic stroke in mice NLRP3 inflammasome in ischemic stroke: as possible therapeutic target NLRP3 inflammasome activity is negatively controlled by miR-223 Rat middle cerebral artery occlusion: evaluation of the model and development of a neurologic examination NLPR3 inflammasome inhibition alleviates hypoxic endothelial cell death in vitro and protects blood-brain barrier integrity in murine stroke The interaction between ferroptosis and inflammatory signaling pathways Neuronal NLRP3 inflammasome mediates spreading depolarization-evoked trigeminovascular activation A small-molecule inhibitor of the NLRP3 inflammasome for the treatment of inflammatory diseases 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) *Correspondence: Hulya Karatas, aHVseWFrQGhhY2V0dGVwZS5lZHUudHI= Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish. Volume 9 - 2022 | https://doi.org/10.3389/fmats.2022.845700 This article is part of the Research TopicPolymer Blends for Drug Release SystemsView all 10 articles tremendous devices and materials such as stents and vessels have been developed for medical purposes When such devices are utilized in the body the side effects or biocompatibility of the materials have to be studied extensively Interdisciplinary studies have reviled numerous strategies to overcome adverse body reactions against implanted devices Besides naturally occurring materials such as collagen various synthetic and modified materials such as poly(lactic acid) and poly(acrylamide) have been accomplished progress in polymer science makes hydrogels a valuable candidate for those utilizations hydrogels received enormous attention as drug delivery devices because of their unique properties such as soft structure and responsive capabilities based on the functional group attached the developments in synthetic materials have brought out numerous materials for medical and pharmaceutical applications have drawn considerable attention over hydrogels because of superior properties such as the coexistence of organic and aqueous phases and viscoelastic bi-phasic natures They were prepared in bulk forms and nano-scale dimensions which allow them to be utilized more extensively These incredible structures provide them with extensive features to be utilized from head to toe in every aspect of health care application we will focus on some of the pioneering perspectives of organo-hydrogels particularly accomplished in clinical therapy and the use of their biodegradable target-responsive properties as sensing components in novel microscale apertures This short review focuses on recent advances of engineered organogels for medical and drug delivery platforms and their utilization it will not cover important studies relevant to significant drug delivery materials and methods that have been tremendously studied recently Bernard et al. 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gum hydrogel and sorbitan monostearate-sesame oil-based organogel and evaluated as a controlled drug release system (Singh et al. and viscoelastic structure of bigels were investigated it was observed that the amount of ciprofloxacin drug release increased with the decrease in organogel content it has been found that drug release from all bigels conforms to the desired zero-order diffusion kinetics for a controlled release system When drug-loaded bigels were examined in terms of antimicrobial activity they had a good effect against Bacillus subtilis and it was predicted that they could be considered a drug release system (A) Schematic representation of organogels preparation (B) Schematic representation of drug loading to organogels (C) Application of drug-loaded organogels in a film form (D) Application of drug-loaded organogels in an injectable form (in nano-scale) we have focused on some recent developments of drug delivery platforms particularly organogels based applications We tried to give a point of view of state of the art It is expected that organogels will be utilized at a gradually increasing level in the coming years because of their unique characteristics such as biocompatibility These properties enable organogels to be applied with enormous potential applications in drug delivery All authors listed have made a substantial and intellectual contribution to the work and approved it for publication The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer AT declared a shared affiliation with the authors to the handling editor at the time of the review All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations or those of the publisher Which Is More Effective for Protein Adsorption: Surface Roughness Case Study of Polyurethane Films Prepared from 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use *Correspondence: Nahit Aktas, bmFoaXQuYWt0YXNAbWFuYXMuZWR1Lmtn View upcoming auction estimates and receive personalized email alerts for the artists you follow “No Man’s Land” is Deniz Aktaş’s first solo show at artSümer The exhibition features Aktaş’s rigorous drawings that are daring depictions of unsound structures still-life myths with questionable existence remnants of an archaic image that made it to today.  Aktaş examines traumas in urban memory through human and environment relations The images carefully depicted by the artist bear the marks of urban transformation demolishment and even the traces of conflict observable on the buildings of a complicated leave the viewers feeling caught in a whirlpool or lost in a labyrinth Pine Bush Central School District Dan Aktas has an excitement about him when he starts talking 3D printing an art and technology teacher at Pine Bush High School was named the High School Art Teacher of the Year for 2019-2020 from the New York State Art Teachers Association “I am so honored to receive the Region 7 New York State High School Art Teacher of the Year recognition I received this recognition in large part for the 3D printing art class I developed here at the high school called Art & Fabrication,” said Aktas “I am very excited to continue working with all of the teachers and administrators who feel so strongly about supporting students through our art and manufacturing programs.” An art teacher heard Aktas speak at a conference and was so impressed by him his passion about art and technology and his skill that she nominated him for the distinction noting that he developed and implemented “the first fine art 3D printing course at Pine Bush called Art & Fabrication to support students’ creativity with digital manufacturing equipment.” Aktas received his bachelor of fine arts in Ceramics at SUNY New Paltz while exploring digital printing technologies and his Masters at NYU Steinhardt for Art Education with an emphasis on social justice “Dan is an amazing teacher who is always looking to create authentic projects to keep his students engaged,” said Aaron Hopmayer “Annually he works with the elementary and middle school students to expose them to the exciting opportunities that await them in high school.”