Allantoin

A team of researchers has developed an innovative patient triage platform powered by artificial intelligence (AI) that the researchers say is capable of predicting patient disease severity and length of hospitalization during a viral outbreak. A team of researchers from Yale University and other institutions globally has developed an innovative patient triage platform powered by artificial intelligence (AI) that the researchers say is capable of predicting patient disease severity and length of hospitalization during a viral outbreak. The platform, which leverages machine learning and metabolomics data, is intended to improve patient management and help health care providers allocate resources more efficiently during severe viral outbreaks that can quickly overwhelm local health care systems. Metabolomics is the study of small molecules related to cell metabolism. "Being able to predict which patients can be sent home and those possibly needing intensive care unit admission is critical for health officials seeking to optimize patient health outcomes and use hospital resources most efficiently during an outbreak," said senior author Vasilis Vasiliou, a professor of epidemiology at Yale School of Public Health (YSPH).The researchers developed the platform using COVID-19 as a disease model. The findings were published online in the journal Human Genomics. The platform integrates routine clinical data, patient comorbidity information, and untargeted plasma metabolomics data to drive its predictions. "Our AI-powered patient triage platform is distinct from typical COVID-19 AI prediction models," said Georgia Charkoftaki, a lead author of the study and an associate research scientist in the Department of Environmental Health Sciences at YSPH. "It serves as the cornerstone for a proactive and methodical approach to addressing upcoming viral outbreaks." Using machine learning, the researchers built a model of COVID-19 severity and prediction of hospitalization based on clinical data and metabolic profiles collected from patients hospitalized with the disease. "The model led us to identify a panel of unique clinical and metabolic biomarkers that were highly indicative of disease progression and allows the prediction of patient management needs very soon after hospitalization," the researchers wrote in the study. For the study, the research team collected comprehensive data from 111 COVID-19 patients admitted to Yale New Haven Hospital during a two-month period in 2020 and 342 healthy individuals (health care workers) who served as controls. The patients were categorized into different classes based on their treatment needs, ranging from not requiring external oxygen to requiring positive airway pressure or intubation. The study identified a number of elevated metabolites in plasma that had a distinct correlation with COVID-19 severity. They included allantoin, 5-hydroxy tryptophan, and glucuronic acid. Notably, patients with elevated blood eosinophil levels were found to have a worse disease prognosis, exposing a potential new biomarker for COVID-19 severity. The researchers also noted that patients who required positive airway pressure or intubation exhibited decreased plasma serotonin levels, an unexpected finding that they said warrants further research. The AI-assisted patient triage platform has three essential components: As part of the study, the research team developed user-friendly software -- the COVID Severity by Metabolomic and Clinical Study (CSMC) software -- that integrates machine learning and clinical data to provide pre-hospital patient management and classify patients' conditions when they arrive at the emergency department. "Our model platform provides a personalized approach for managing COVID-19 patients, but it also lays the groundwork for future viral outbreaks," said Vasiliou, chair of the YSPH Department of Environmental Health Sciences and the Susan Dwight Bliss Professor of Epidemiology (Environmental Health Sciences). "As the world continues to grapple with COVID-19 and we remain vigilant against potential future outbreaks, our AI-powered platform represents a promising step towards a more effective and data-driven public health response." Limitations of the study include the fact that all samples were collected between March and May 2020, a time period before the emergence of COVID-19 vaccines and before many treatments for the SARS-CoV-2 virus, such as remdesivir, were available. Such treatments could reduce the changes observed in metabolite biomarkers. Secondly, the population of healthy controls was mainly white, while the COVID-19 patients comprised a higher proportion of Black individuals. As such, the possibility of race /ethnicity being a factor contributing to differences in subjects cannot be excluded. Researchers with the Laboratory of Analytical Chemistry at the National and Kapodistrian University of Athens, Greece; Imperial College of London; and the São Carlos Institute of Chemistry at the University of São Palo, Brazil contributed to the study.

精彩内容6月29日晚，2023中国医药·品牌榜盛大发布。珍视明产品连获殊荣，珍视明®四味珍层冰硼滴眼液蝉联2023“中国医药·品牌榜”零售终端榜单，珍视明®|珍视润®复方尿维氨滴眼液作为眼科领域的知名产品，荣获2023“中国连锁药店最具合作价值单品”。珍视明®四味珍层冰硼滴眼液，蝉联2023中国医药·品牌榜零售终端榜单产品在三大终端近三年（2020-2022年）的销售金额及成长性，是“2023中国医药·品牌榜”主要参考标准之一。据米内数据显示，珍视明®四味珍层冰硼滴眼液在中国城市实体药店终端眼科中药滴眼液品牌TOP20居于首位。四味珍层冰硼滴眼液为中药滴眼液，该药主要成分为珍珠层粉和天然冰片，两者均为珍贵药材。该产品具有清热解痉，去翳明目之功效，用于青少年远视力下降、假性近视，可以有效缓解眼疲劳以及用眼过度引起的眼部不适。上市30多年以来，久经市场考验，是广大消费者家庭首选用药。珍视明®|珍视润®复方尿维氨滴眼液，荣获2023中国连锁药店最具合作价值单品2023“中国连锁药店最具合作价值单品”榜单是依托米内网在中国独家开发运行多年的“三大终端六大市场”终端竞争格局数据系统，根据产品在过去一年表现出的高成长性及在零售终端的销售规模，经综合评选得出的入选名单。米内网数据显示，珍视明®|珍视润®复方尿维氨滴眼液在中国城市实体药店终端的销售规模逐年上涨，在眼科用药中的市场份额呈递增态势。珍视明®|珍视润®复方尿维氨滴眼液由硫酸软骨素、尿囊素、牛磺酸、维生素E、维生素B6等组成的复方制剂。具有修复角膜、补充营养、抗炎的作用，临床上主要用于治疗慢性结膜炎、角膜损伤、结膜充血、预防眼病（游泳后、尘埃吹进或汗水流入眼睛），紫外线或受其它光线影响之眼炎，眼睑炎；缓解因配戴隐形眼镜引起的不适，眼睛疲劳，眼痒、眼朦胧等症状；还可用于眼部调节功能下降、屈光不正的辅助治疗。此次也蝉联了此榜单，代表着其疗效获得了消费者的认可与青睐，是各大药店当之无愧的“黄金单品”。护眼领导品牌，深耕眼科领域50余年珍视明药业作为拥有50余年历史的眼科企业，公司以生产中西药制剂产品为主，拥有滴眼剂为主的80+产品，其中30个国家医保品种，6个国家基本药物；拥有专利70+，其中发明专利10项，实用新型专利33项。始终秉承着与时俱进的时代创新精神，持续推出眼健康行业创新产品。此次在评选中脱颖而出，正是产品得到零售行业高度肯定与赞扬的明证，这份荣誉也是公司未来持续前进的动力。投稿及报料请发邮件到872470254@qq.com稿件要求详询米内微信首页菜单栏商务及内容合作可联系QQ：412539092【分享、点赞、在看】点一点不失联哦