Core Viewpoint - The latest research published in the journal Cell reveals that skipping breakfast can trigger a "metabolic memory" effect in the small intestine, leading to increased nutrient absorption efficiency and potentially contributing to obesity and atherosclerosis [6][7][9]. Group 1: Mechanisms of Nutrient Absorption - The small intestine operates through two independent nutrient supply pathways: luminal supply (food intake) and blood supply (internal reserves) [8]. - When breakfast is skipped, the small intestine shifts to an internal energy supply mode, activating a "metabolic compensation mechanism" that enhances nutrient absorption efficiency, particularly for cholesterol and fats [8][9]. - In mouse models simulating breakfast skipping, significant metabolic reprogramming occurs, including a nearly 40% increase in cholesterol absorption efficiency due to upregulation of key transport proteins [9][18]. Group 2: Consequences of Skipping Breakfast - Long-term skipping of breakfast leads to a "rebound absorption" effect, resulting in increased weight gain and metabolic disorders [13][15]. - Mice that regularly skip breakfast show elevated low-density lipoprotein cholesterol (LDL-C) levels, exacerbating lipid metabolism disorders and doubling the risk of atherosclerosis [18]. Group 3: Recommendations for Metabolic Health - Attempting to lose weight through hunger may backfire, as the small intestine's "super compensation absorption" can lead to greater fat accumulation [15]. - Regular breakfast consumption, particularly with a combination of protein and dietary fiber, can effectively reset absorption rhythms and stabilize metabolism [15].

Core Viewpoint - Shenzhen Medical Academy of Research and Translation (SMART) has announced procurement intentions for 47 items of laboratory equipment, with a total budget of 235 million yuan, aimed at enhancing its research capabilities in various biomedical fields [1][2][3]. Procurement Overview - The procurement includes high-performance flow cytometers, multi-parameter flow cytometers, spectral high-speed cell sorters, and other advanced laboratory instruments, with expected purchase dates between March and October 2025 [1][2][3]. - The total budget for the procurement is 235 million yuan, indicating a significant investment in research infrastructure [1]. Specific Equipment Details - High-performance flow cytometer: Designed for high-throughput detection and analysis of physical and fluorescent properties of single cells, applicable in immunology, oncology, and stem cell research [1][2]. - Spectral high-speed cell sorter: Integrates multi-laser excitation and high-parameter fluorescence detection for complex sample analysis, widely used in immunology and precision medicine [2][3]. - Desktop fluorescence correlation spectroscopy: A high-sensitivity instrument for real-time analysis of single fluorescent molecules in solution, applicable in molecular biology and drug development [4]. Additional Equipment and Services - The procurement list includes various advanced instruments such as high-dimensional flow cytometers, high-resolution imaging systems, and electronic beam evaporation systems, all aimed at supporting cutting-edge research [6][10]. - Each equipment item comes with specific quality and service requirements, including installation, training, and a minimum three-year warranty [7][9][10]. Institutional Background - SMART is a national-level medical research institution established by the Shenzhen government, aiming to integrate research, translation, talent cultivation, and funding support, modeled after the NIH [12][13]. - The institution focuses on major disease prevention, cutting-edge medical technology, and sustainable health research, with a flexible staffing mechanism to attract top talent [14][15].

Core Viewpoint - The recent study from Sun Yat-sen University highlights the significant role of greenspace in mitigating the global disease and economic burdens associated with non-communicable diseases (NCDs) [4][6]. Summary by Sections Non-Communicable Diseases (NCDs) - NCDs are the primary threat to global public health, causing 42 million deaths in 2021, which accounts for 75% of total global deaths [6]. - It is projected that from 2011 to 2030, NCDs will result in over $30 trillion in economic losses globally, imposing heavy burdens on families, healthcare systems, and society [6]. Importance of Greenspace - Greenspace, including forests, parks, and gardens, plays a crucial role in human health and disease prevention [6]. - Increased exposure to greenspace is associated with a reduced risk of various NCDs, such as cardiovascular diseases, diabetes, cancer, and mental health issues [6]. - The benefits of greenspace may stem from ecological, biological, psychological, and social pathways, including reduced air pollution and enhanced social cohesion [6]. Research Limitations and Gaps - Previous studies on the relationship between greenspace and NCDs have been limited to specific geographic areas, restricting the applicability of findings to broader populations [7]. - There is a lack of comprehensive research quantifying the potential health and economic benefits of increasing greenspace on a global scale [7][8]. Key Findings of the Study - The study analyzed data from 204 countries/regions between 2000 and 2021, using mixed-effects regression models to assess the association between greenspace and NCD-related mortality and disability-adjusted life years (DALYs) [8]. - Results indicate that larger greenspace areas correlate with lower burdens of NCDs [8]. - If greenspace had been maintained at optimal levels over the past two decades, it could have potentially prevented 1.66 million NCD-related deaths and 37.68 million DALYs, saving nearly $10 billion [8]. Implications for Policy - The findings provide invaluable information for policymakers and practitioners, suggesting that greenspace initiatives should be integrated into national policy-making and resource allocation to alleviate the disease and economic burdens of NCDs globally [10].

7月23日，国际顶尖期刊《自然·医学》（Nature Medicine）在线发表了新疆维吾尔自治区人民医院杨毅宁教授团队联合清华大学底骞副教授、马为之助 理教授团队的研究成果——"基于大语言模型的大规模人群生物年龄预测"。 研究整合了中、英、美三国六大健康数据库，包括英国生物银行，美国国家健康与营养调查，中国健康与养老追踪调查、中国老年健康调查、中国家庭 追踪调查，以及清华大学与新疆维吾尔自治区人民医院共同建立的天山数字化自然人群队列，总样本量超1000万人，是全球最大规模同类研究之一。 "新疆作为国家重要能源基地，充沛电力为高强度计算提供坚实保障，优良自然条件利于数据中心建设和网络优化。"底骞表示。在自治区卫生健康委、 疾控部门及各级政府支持下，团队严格遵守数据安全法规，依托中国移动新疆分公司以及华为昇腾的强大算力，成功完成海量全球多中心数据的汇聚、治理 与分析，充分证明新疆凭借"数据+算力+政策"优势，具备实现科技"弯道超车"的巨大潜力。 7月25日，新疆维吾尔自治区人民医院、清华大学联合发布天山悦康大模型。利用研究成果，自治区人民医院和清华大学在相关数据资源基础上，进一步研 发出了天山悦康大模型，给予个 ...

Core Viewpoint - The article discusses a groundbreaking research study that introduces a large language model (LLM)-based biological age prediction method, which estimates overall and organ-specific aging through health examination reports, aiming to enhance health management for the general public [3][4][5]. Group 1: Research Background and Importance - Accurately assessing an individual's aging level is crucial for identifying health risks and preventing age-related diseases, yet current aging indicators face methodological limitations and lack broad applicability [2][8]. - Aging is a major risk factor for mortality and chronic diseases, contributing significantly to societal health burdens, and understanding both overall and organ-specific aging is essential for comprehensive health assessments [7]. Group 2: Methodology and Framework - The research team developed a novel framework that converts health examination data (e.g., blood pressure, liver function) into textual reports for input into a large language model (e.g., Llama3), which analyzes numerous indicators to produce two key outputs: overall biological age and organ-specific ages for six major organs [10][11]. - The LLM does not rely on preset formulas but utilizes a pre-trained medical knowledge base to intelligently infer aging metrics based on individual health details [12]. Group 3: Validation and Results - The study validated its predictive framework using data from over 10 million individuals across six major databases, achieving impressive accuracy rates: 75.7% for predicting all-cause mortality risk, 70.9% for coronary heart disease risk, and 81.2% for liver cirrhosis risk, outperforming traditional models [15][20]. - The age difference predicted by the LLM correlates with increased health risks, with each additional year in predicted age raising all-cause mortality risk by 5.5% and coronary heart disease risk by 7.2% [16]. Group 4: Clinical Applications and Innovations - The research introduces a disease radar warning system, revealing that an increase in cardiovascular age difference correlates with a 45% increase in coronary heart disease risk, while liver age difference correlates with a 63% increase in liver cirrhosis risk [19]. - The study identifies 322 key proteins as potential "aging accelerators," with 56.7% being new targets linked to mortality risk, highlighting the predictive power of the LLM in personalized health management [19]. - By analyzing three years of continuous health examination data, the LLM can generate individual aging rate curves, improving disease outbreak predictions by three times compared to single examination assessments [19].

Group 1 - The UK Biobank has completed the largest human imaging project globally, scanning 100,000 volunteers over 11 years, generating over 1 billion high-resolution medical images [1] - The project began in 2014 with a pilot involving 7,000 volunteers and officially launched in 2016, where each volunteer underwent approximately 5 hours of imaging [1] - The imaging data includes over 12,000 MRI images per volunteer, covering the brain, heart, abdomen, and measurements of bone density and body fat [1] Group 2 - Since 2015, the imaging data has been made available to global researchers, resulting in over 1,300 peer-reviewed papers published based on this data [2] - The second phase of the project started in 2022, aiming to re-scan 60,000 participants to observe changes over time, expected to be completed by 2029 [2] - The chief researcher, Rory Collins, emphasized that this unprecedented scale of imaging is making "invisible disease processes" visible and redefining understanding of health, aging, and risk prediction [2]

Group 1 - The integration of traditional Chinese medicine (TCM) and Western medicine is evolving due to the accumulation of life data and advancements in artificial intelligence (AI) analysis techniques [1][2] - The shift in Western medical research from a micro to a systemic and macro perspective is reflected in publications since 2012 in the journal "Cell," indicating a growing collaboration between TCM and Western medicine [1] - AI and big data are enabling a more objective approach to TCM, allowing for precise translations of pathological representations into TCM theories [2] Group 2 - The concept of personalized treatment, or "one person, one policy," is becoming feasible as machine learning and algorithms assist in tailoring treatments based on detailed patient data [3] - The intersection of multiple disciplines, including materials science and engineering, is expected to transform the administration of TCM formulations, enhancing the understanding of their mechanisms [3] - A paradigm shift in medical research is anticipated, driven by the integration of new technologies and methods, which will redefine scientific perspectives and methodologies [3][4]

Core Viewpoint - Researchers at the Cedars-Sinai Medical Center have developed a "chip-based ALS" disease model using stem cells from ALS patients, which may reveal the causes of this mysterious and deadly disease and facilitate the development of effective treatments [1] Group 1 - The new model aims to uncover the underlying mechanisms of amyotrophic lateral sclerosis (ALS) [1] - The research utilizes stem cells derived from patients, indicating a personalized approach to studying the disease [1] - The development of this model could lead to significant advancements in ALS treatment options [1]

Core Viewpoint - The establishment of the Wu Mengchao Academy aims to promote the spirit of the renowned Chinese liver surgeon, emphasizing the importance of clinical service over mere academic achievements [1][4]. Group 1: Wu Mengchao's Contributions - Wu Mengchao is recognized as the "Father of Chinese Liver Surgery" and has made significant contributions to the field, including leading a team that achieved numerous medical firsts and breakthroughs [2]. - The academy showcases 15 major medical achievements by Wu Mengchao, including the world record for the largest liver tumor resection, with a specimen weighing 18 kilograms [2]. Group 2: Educational Initiatives - The academy features interactive exhibits, including a handprint area where visitors can engage with Wu Mengchao's legacy, symbolizing their role as spiritual successors [3]. - A digital representation of Wu Mengchao allows visitors to engage in conversations, fostering a connection between past and present medical practitioners [3][4]. Group 3: Legacy and Recognition - Wu Mengchao is the first recipient of a named asteroid in the field of medicine in China, symbolizing his 76 years of dedication to healthcare [4]. - The establishment of the academy serves as a lasting tribute to Wu Mengchao's life and work, setting a spiritual benchmark for future generations of medical professionals [4][5].

Core Insights - The articles highlight the significant role of technology and innovation in driving high-quality development in Henan province, emphasizing the contributions of local scientists and researchers [1][18] - The focus is on various technological advancements, including distributed optical fiber monitoring systems, medical research, food science, and new display technologies, showcasing the diverse fields where innovation is taking place [2][5][13] Group 1: Technology and Innovation - The Harbin Institute of Technology's Zhengzhou Research Institute has developed a distributed optical fiber monitoring system that enhances the safety of energy transmission networks in Henan and nationwide [2][5] - The team led by Professor Dong Yongkang has achieved a 1000-fold improvement in time response and spatial resolution in fiber monitoring technology, breaking foreign monopolies and leading in performance metrics [5][6] - The establishment of a femtosecond laser micro-nano sensing research platform in Henan aims to meet the growing market demand for advanced sensing technologies [6] Group 2: Medical Research - Li Lei, a researcher at the Henan Provincial Academy of Medical Sciences, focuses on sepsis, a significant medical challenge, and has successfully attracted a team of researchers to the province [7][8] - The supportive research environment in Henan, including rapid resolution of administrative issues, has facilitated talent retention and development in the medical field [7][8] Group 3: Food Science - Liu Kunlun, Dean of the College of Grain and Oil Food Engineering at Henan University of Technology, emphasizes the importance of food science in addressing the health needs of an aging population [11][12] - His research on selenium and peptides aims to enhance antioxidant properties, with applications already in six enterprises, showcasing the practical impact of food science research [12] Group 4: Display Technology - The New Display Technology Research Institute in Henan is focusing on AR/VR technologies, aiming to develop the world's first OLED-based AR glasses through collaboration with various universities and tech companies [13][17] - The institute's work on quantum dot technology and Mini/MicroLED displays is positioned to address both material and device challenges in the display sector [16][17] Group 5: Overall Impact of Technology - The articles collectively illustrate how technological advancements are integral to Henan's economic growth and modernization efforts, with a strong emphasis on collaboration between academia and industry [18] - The commitment to innovation is reflected in the establishment of research platforms and the attraction of talent, which are essential for sustaining high-quality development in the region [18]