Latest news with #machineLearning
South China Morning Post
10-07-2025
- Science
- South China Morning Post
Award-winning data scientist She Yiyuan takes job in China after decades in US
Award-winning data scientist She Yiyuan has left the United States to take up a full-time position at Westlake University in eastern China's Zhejiang province. Advertisement She, who taught at Florida State University for almost two decades, will conduct research at his new institution as a chair professor at the school of science and the Institute for Theoretical Sciences, according to a July 1 social media post by the Chinese university. She has won the Career Award, the most prestigious award from the US National Science Foundation to support early career scholars. He is a fellow of some of the world's most prominent communities of statisticians, including the American Statistical Association and the Institute of Mathematical Statistics. He is also an elected member of the International Statistical Institute. The statistician's move is set to boost China's position in emerging hi-tech sectors, such as artificial intelligence (AI) and medical sciences, amid fierce competition with the West. Statistics, as the foundation of data science, is 'an indispensable supporting discipline in fields such as machine learning and artificial intelligence', according to Westlake University. The discipline underpins a wide range of fields, including the natural sciences, engineering, technology and social sciences. Advertisement According to the university's website, She's research focuses on high-dimensional statistics, machine learning, optimisation techniques, big data analysis and robust statistics, among other areas. His research takes a cross-disciplinary approach, integrating the theories, methods, and applications of statistics, mathematics and computer science. Westlake University said that She's research not only provided new methods for machine learning to discover patterns in complex data, but also offered effective tools and innovative approaches for data analysis in disciplines such as biomedicine and economics.
Yahoo
09-07-2025
- Business
- Yahoo
IP Infusion Advances AI Data Center Networking with Ethernet-based Disaggregated Solution
Partners with HYPER SCALERS to Deploy Agile, Cost-Efficient Networks for GPU-intensive AI Workloads SANTA CLARA, Calif., July 09, 2025--(BUSINESS WIRE)--IP Infusion, a global leader in open networking solutions, today announced the release of OcNOS® Data Center (OcNOS-DC) 6.6.1, the industry's most widely deployed disaggregated networking software specifically designed to support the demanding requirements of artificial intelligence (AI) and machine learning (ML) workloads. Built to run on Broadcom's Tomahawk 5 chipset, OcNOS-DC 6.6.1 powers high-performance, low-latency Ethernet-based AI/ML data center fabrics on ONIE-enabled Edgecore AS9817-64D and UfiSpace S9321-64E white-box switches with 51.2Tbps switching capacity. As AI/ML training clusters scale exponentially, traditional networking solutions struggle to handle the intensive east-west traffic patterns and stringent latency and packet loss requirements of distributed GPU workloads. OcNOS-DC 6.6.1 addresses these challenges with advanced features, including Priority-based Flow Control (PFC) over Layer 3, Enhanced Transmission Selection (ETS), Data Center Bridging Capabilities Exchange Protocol (DCBX), and Dynamic Load Balancing (DLB). These capabilities work cohesively to deliver high-throughput, lossless connectivity, which is critical for AI-driven networks. OcNOS-DC 6.6.1 enhances AI workload orchestration by exporting real-time gNMI telemetry to orchestrators like Kubernetes, enabling dynamic job allocation and reallocation when network paths are overloaded. Integration with Ansible further automates the reservation of lossless queues, priority-to-traffic-class mapping, and activation of dynamic load balancing on job-specific links, optimizing GPU server rack performance. By leveraging disaggregated open networking, OcNOS-DC 6.6.1 offers cost-effective scaling, flexibility in optics selection, and agile data center buildouts through competitive bidding and component-level price tracking. "OcNOS Data Center sets a new standard for AI/ML networking, delivering unparalleled performance and scalability for next-generation data centers," said Kiyo Oishi, CEO of IP Infusion. "By combining Broadcom's Tomahawk 5 chipset with our advanced software features, we're enabling customers like HYPER SCALERS to build agile, cost-efficient networks that meet the rigorous demands of GPU-intensive AI workloads." "Partnering with IP Infusion to deploy OcNOS-DC 6.6.1 has revolutionized our ability to deliver high-performance GPU-based services," said George Cvetanovski, Founder and CEO of HYPER SCALERS. "The AI-optimized features, seamless orchestration integration, and disaggregated architecture allow us to scale efficiently while maintaining the low-latency, lossless connectivity our customers require for their AI/ML workloads." Availability For more information, visit IP Infusion's website or contact ipisales@ About IP Infusion IP Infusion develops open network software solutions for carriers, service providers, and data centers. With hundreds of customers and thousands of deployments, IP Infusion leads the market in Network Operating Systems. Its flagship platform, OcNOS®, empowers network operators to disaggregate their networks, streamline operations, and reduce total cost of ownership (TCO). Headquartered in Santa Clara, Calif., IP Infusion is a wholly owned subsidiary of ACCESS CO., LTD. For more information, visit View source version on Contacts Media Contact Katherine Verducci, 1903 PRkverducci@ 408.429.5779 Effettua l'accesso per consultare il tuo portafoglio
Medical News Today
09-07-2025
- Health
- Medical News Today
Clinical test may predict best rheumatoid arthritis biologic for each individual
Rheumatoid arthritis is a painful, progressive joint disease characterized by particularly acute used to treat autoimmune diseases such as rheumatoid arthritis, target symptom mechanisms without compromising the entire immune system.A new test may take the guesswork out of finding the right biological therapy for people with rheumatoid at Queen Mary, University of London, have announced a new machine-learning-based method for predicting the biological therapy, or biologic, most likely to successfully relieve symptoms for an individual with rheumatoid scientists say that their system successfully predicted the optimal biologic for 79–85% of patients on its first try in validation the last 20 years, biologics have revolutionized the treatment of rheumatoid arthritis (RA) due to their potential to focus on the underlying cellular cause of a patient's RA is an immune disorder, conventional treatments suppress the function of the entire immune system to reduce symptoms of the condition. Absent a robust immune system, the patient is left vulnerable to idea behind biologics is that a more precise approach can be effective at reducing RA symptoms without significantly compromising the immune to its inventors, prior to the newly announced technique, identifying the correct biologic for each patient was somewhat of a hit-or-miss procedure — 40% of biological therapies fail due to inaccurate new prediction technique pinpoints which of the three main types of biologics shows the most promise for a patient.'This innovation could have major benefits for patients and healthcare providers alike. Prescribing the right treatment the first time would reduce patient suffering,' Professor Constantino Pitzalis, study author, tells Medical News scientists announced their new method of identifying the best biologic for an individual RA patient in Nature rheumatoid arthritis is treatedRheumatoid arthritis is an autoimmune disease that causes pain and inflammation in and around the joints.'The persistent inflammation can impair mobility and dexterity, making daily tasks difficult or impossible,' explained Syeda S. Nasrin, MSc, graduate of the Center for Regenerative Sciences in Dresden, Germany, who was not involved in the Bowen, PhD, bioethicist at SUNY Upstate Medical University, who was also not involved in the study, is someone who has personal experience with RA. 'When I developed RA, the pain was shocking. I'd wake up in tears in the middle of the night and no amount of NSAIDs, ice, heat, movement, rest — any of the usual things you'd try for joint pain — even began to offer relief. It spreads all over the body and makes basic life tasks, like putting on a shirt or opening a car door, agonizing,' she is a chronic and progressive condition, and may also involve other parts of the from biologics, people with RA may be treated with immune suppressors such as methotrexate and Janus kinase (JAK) inhibitors, which target the overactive immune system. For pain, doctors prescribe NSAIDs, which are notoriously hard on the stomach and GI tract with long-term use, and corticosteroids to control do biological therapies work?'Biologics,' said Nasrin, 'target specific cellular pathways in the immune system that play key roles in the inflammatory process of RA.'The idea is to address the mechanism causing an individual patient's RA-related joint inflammation without attacking the immune system itself.'For instance,' she explained, 'Interleukin-6 (IL-6) is a cytokine that is involved in immune cell modulation and inflammation. Tocilizumab (Actemra), a monoclonal antibody, can inhibit this IL-6 cytokine and reduce inflammation.'Nasrin made clear, however, that 'as far as I know, these molecular targeted therapies are able to reduce inflammation, slow joint damage, and improve physical function, but they do not cure the disease.'Why getting the right biologic is importantSince it currently takes time to identify a biologic that can address a specific patient's RA, there is an extended period during which no symptom relief are also risks associated with this period of experimentation, pointed out Nasrin. 'As these approaches often include altering the immune system at a molecular level, that means there is a suppression of the immune system in the body. This could increase infection susceptibility.'Bowen pointed out as well that even the right biologic takes time to have a positive effect on symptoms. Extended periods of trial and error may be accompanied by uncertainty in addition to the ongoing physical Bowen described it, 'What works for one person may not work for another. So it can be really demoralizing and isolating if, say, you're looking around and seeing all these people who are doing great on [one biologic], but it's doing nothing for you.''It's grueling,' she said, 'not just on a physical level but also a psychological one, where you might be dealing with huge amounts of fear, hopelessness, and doubt that you will ever find something that works.'Predicting the best drug for each individualThe new method identifies which of three biologics — etanercept, tocilizumab, or rituximab — is most likely to work for a a recent clinical trial that involved deep molecular phenotyping, the scientists developed a database of gene differences in RA patients who had responded well to biologics, compared to others who did were also able to ascertain the response of specific groups of RA-related cells to each of the drugs. From there, they built three predictive models for the three biologics to test how well a patient would do with a given predict the correct biologic for a specific patient, they extract a tissue sample from a joint affected by RA, and score the levels of activity in 524 genes they have identified as relevant. They can then match those scores to the most promising Mary, University of London, is seeking commercial partners to help develop the predictive system for real-world use. No timetable for when this may occur has yet been the validation results are promising, Nasrin, struck a note of caution:'Personalized medicine is still at a very early stage of development. So the approach should be taken with caution and only proceed with having solid clinical trial data.'Clinical trials are reportedly underway.
Yahoo
07-07-2025
- Health
- Yahoo
AI-Assisted Technique Can Measure and Track Aging Cells
NEW YORK, July 7, 2025 /PRNewswire/ -- A combination of high-resolution imaging and machine learning, also known as artificial intelligence (AI), can track cells damaged from injury, aging, or disease, and that no longer grow and reproduce normally, a new study shows. These senescent cells are known to play a key role in wound repair and aging-related diseases, such as cancer and heart disease, so tracking their progress, researchers say, could lead to a better understanding of how tissues gradually lose their ability to regenerate over time or how they fuel disease. The tool could also provide insight into therapies for reversing the damage. Led by NYU Langone Health Department of Orthopedic Surgery researchers, the study included training a computer system to help analyze animal cells damaged by increasing concentrations of chemicals over time to replicate human aging. Cells continuously confronted with environmental or biological stress are known to senesce, meaning they stop reproducing and start to release telltale molecules indicating that they have suffered injury. Publishing in the journal Nature Communications online July 7, the researchers' AI analysis revealed several measurable features connected to the cell's control center (nucleus), that, when taken together, closely tracked with the degree of senescence in the tissue or group of cells. This included signs that the nucleus had expanded, had denser centers or foci, and had become less circular and more irregular in shape. Its genetic material also stained lighter than normal with standard chemical dyes. Further testing confirmed that cells with these characteristics were indeed senescent, showing signs that they had stopped reproducing, had damaged DNA, and had densely packed enzyme-storing lysosomes. The cells also demonstrated a response to existing senolytic drugs. From their analysis, researchers created what they term a nuclear morphometric pipeline (NMP) that uses the nucleus's changed physical characteristics to produce a single senescent score to describe a range of cells. For example, groups of fully senescent cells could be compared to a cluster of healthy cells on a scale from minus 20 to plus 20. To validate the NMP score, the researchers then showed that it could accurately distinguish between healthy and diseased mouse cells from young to older mice, age 3 months to more than 2 years. Older cell clusters had significantly lower NMP scores than younger cell clusters. The researchers also tested the NMP tool on five kinds of cells in mice of different ages with injured muscle tissue as it underwent repair. The NMP was found to track closely with changing levels of senescent and nonsenescent mesenchymal stem cells, muscle stem cells, endothelial cells, and immune cells in young, adult, and geriatric mice. For example, use of the NMP was able to confirm that senescent muscle stem cells were absent in control mice that were not injured, but present in large numbers in injured mice immediately after muscle injury (when they help initiate repair), with gradual loss as the tissue regenerated. Final testing showed that the NMP could successfully distinguish between healthy and senescent cartilage cells, which were 10 times more prevalent in geriatric mice with osteoarthritis than in younger, healthy mice. Osteoarthritis is known to progressively worsen with age. "Our study demonstrates that specific nuclear morphometrics can serve as a reliable tool for identifying and tracking senescent cells, which we believe is key to future research and understanding of tissue regeneration, aging, and progressive disease," said study senior investigator Michael Wosczyna, PhD. Wosczyna is an assistant professor in the Department of Orthopedic Surgery at the NYU Grossman School of Medicine. Wosczyna says his team's study confirms the NMP's broad application for study of senescent cells across all ages and differing tissue types, and in a variety of diseases. He says the team plans further experiments to examine use of the NMP in human tissues, as well as combining the NMP with other biomarker tools for examining senescence and its various roles in wound repair, aging, and disease. The researchers say their ultimate goal for the NMP, for which NYU has filed a patent application, is to use it to develop treatments that prevent or reverse negative effects of senescence on human health. "Our testing platform offers a rigorous method to more easily than before study senescent cells and to test the efficacy of therapeutics, such as senolytics, in targeting these cells in different tissues and pathologies," said Wosczyna, who plans to make the NMP freely available to other researchers. "Existing methods to identify senescent cells are difficult to use, making them less reliable than the nuclear morphometric pipeline, or NMP, which relies on a more commonly used stain for the nucleus," said study co-lead investigator Sahil Mapkar, BS, Mapkar is a doctoral candidate at the NYU Tandon School of Engineering. Funding for the study was provided by National Institutes of Health grant R01AG053438 and the Department of Orthopedic Surgery at NYU Langone. Besides Wosczyna and Makpar, NYU Langone researchers involved in this study are co-lead investigators Sarah Bliss, and Edgar Perez Carbajal, and study co-investigators Sean Murray, Zhiru Li, Anna Wilson, Vikrant Piprode, Youjin Lee, Thorsten Kirsch, Katerina Petroff, and Fengyuan Liu. About NYU Langone HealthNYU Langone Health is a fully integrated health system that consistently achieves the best patient outcomes through a rigorous focus on quality that has resulted in some of the lowest mortality rates in the nation. Vizient Inc. has ranked NYU Langone No. 1 out of 115 comprehensive academic medical centers across the nation for three years in a row, and U.S. News & World Report recently placed nine of its clinical specialties among the top five in the nation. NYU Langone offers a comprehensive range of medical services with one high standard of care across seven inpatient locations, its Perlmutter Cancer Center, and more than 320 outpatient locations in the New York area and Florida. With $14.2 billion in revenue this year, the system also includes two tuition-free medical schools, in Manhattan and on Long Island, and a vast research enterprise. Media ContactDavid STUDY LINKhttps:// STUDY DOI10.1038/s41467-025-60975-z View original content to download multimedia: SOURCE NYU Langone Health System
Associated Press
07-07-2025
- Health
- Associated Press
AI-Assisted Technique Can Measure and Track Aging Cells
NEW YORK, July 7, 2025 /PRNewswire/ -- A combination of high-resolution imaging and machine learning, also known as artificial intelligence (AI), can track cells damaged from injury, aging, or disease, and that no longer grow and reproduce normally, a new study shows. These senescent cells are known to play a key role in wound repair and aging-related diseases, such as cancer and heart disease, so tracking their progress, researchers say, could lead to a better understanding of how tissues gradually lose their ability to regenerate over time or how they fuel disease. The tool could also provide insight into therapies for reversing the damage. Led by NYU Langone Health Department of Orthopedic Surgery researchers, the study included training a computer system to help analyze animal cells damaged by increasing concentrations of chemicals over time to replicate human aging. Cells continuously confronted with environmental or biological stress are known to senesce, meaning they stop reproducing and start to release telltale molecules indicating that they have suffered injury. Publishing in the journal Nature Communications online July 7, the researchers' AI analysis revealed several measurable features connected to the cell's control center (nucleus), that, when taken together, closely tracked with the degree of senescence in the tissue or group of cells. This included signs that the nucleus had expanded, had denser centers or foci, and had become less circular and more irregular in shape. Its genetic material also stained lighter than normal with standard chemical dyes. Further testing confirmed that cells with these characteristics were indeed senescent, showing signs that they had stopped reproducing, had damaged DNA, and had densely packed enzyme-storing lysosomes. The cells also demonstrated a response to existing senolytic drugs. From their analysis, researchers created what they term a nuclear morphometric pipeline (NMP) that uses the nucleus's changed physical characteristics to produce a single senescent score to describe a range of cells. For example, groups of fully senescent cells could be compared to a cluster of healthy cells on a scale from minus 20 to plus 20. To validate the NMP score, the researchers then showed that it could accurately distinguish between healthy and diseased mouse cells from young to older mice, age 3 months to more than 2 years. Older cell clusters had significantly lower NMP scores than younger cell clusters. The researchers also tested the NMP tool on five kinds of cells in mice of different ages with injured muscle tissue as it underwent repair. The NMP was found to track closely with changing levels of senescent and nonsenescent mesenchymal stem cells, muscle stem cells, endothelial cells, and immune cells in young, adult, and geriatric mice. For example, use of the NMP was able to confirm that senescent muscle stem cells were absent in control mice that were not injured, but present in large numbers in injured mice immediately after muscle injury (when they help initiate repair), with gradual loss as the tissue regenerated. Final testing showed that the NMP could successfully distinguish between healthy and senescent cartilage cells, which were 10 times more prevalent in geriatric mice with osteoarthritis than in younger, healthy mice. Osteoarthritis is known to progressively worsen with age. 'Our study demonstrates that specific nuclear morphometrics can serve as a reliable tool for identifying and tracking senescent cells, which we believe is key to future research and understanding of tissue regeneration, aging, and progressive disease,' said study senior investigator Michael Wosczyna, PhD. Wosczyna is an assistant professor in the Department of Orthopedic Surgery at the NYU Grossman School of Medicine. Wosczyna says his team's study confirms the NMP's broad application for study of senescent cells across all ages and differing tissue types, and in a variety of diseases. He says the team plans further experiments to examine use of the NMP in human tissues, as well as combining the NMP with other biomarker tools for examining senescence and its various roles in wound repair, aging, and disease. The researchers say their ultimate goal for the NMP, for which NYU has filed a patent application, is to use it to develop treatments that prevent or reverse negative effects of senescence on human health. 'Our testing platform offers a rigorous method to more easily than before study senescent cells and to test the efficacy of therapeutics, such as senolytics, in targeting these cells in different tissues and pathologies,' said Wosczyna, who plans to make the NMP freely available to other researchers. 'Existing methods to identify senescent cells are difficult to use, making them less reliable than the nuclear morphometric pipeline, or NMP, which relies on a more commonly used stain for the nucleus,' said study co-lead investigator Sahil Mapkar, BS, Mapkar is a doctoral candidate at the NYU Tandon School of Engineering. Funding for the study was provided by National Institutes of Health grant R01AG053438 and the Department of Orthopedic Surgery at NYU Langone. Besides Wosczyna and Makpar, NYU Langone researchers involved in this study are co-lead investigators Sarah Bliss, and Edgar Perez Carbajal, and study co-investigators Sean Murray, Zhiru Li, Anna Wilson, Vikrant Piprode, Youjin Lee, Thorsten Kirsch, Katerina Petroff, and Fengyuan Liu. About NYU Langone Health NYU Langone Health is a fully integrated health system that consistently achieves the best patient outcomes through a rigorous focus on quality that has resulted in some of the lowest mortality rates in the nation. Vizient Inc. has ranked NYU Langone No. 1 out of 115 comprehensive academic medical centers across the nation for three years in a row, and U.S. News & World Report recently placed nine of its clinical specialties among the top five in the nation. NYU Langone offers a comprehensive range of medical services with one high standard of care across seven inpatient locations, its Perlmutter Cancer Center, and more than 320 outpatient locations in the New York area and Florida. With $14.2 billion in revenue this year, the system also includes two tuition-free medical schools, in Manhattan and on Long Island, and a vast research enterprise. Media Contact David March 212-404-3528 [email protected] STUDY LINK STUDY DOI 10.1038/s41467-025-60975-z View original content to download multimedia: SOURCE NYU Langone Health System
