星标 ★ IPO日报 精彩文章第一时间推送 "如果老爷子早四个月把体检报告递给儿子，或许肿瘤只有三公分大时就开刀切掉根治 了。"东方肝胆外科医院肝外四科主任医师伍路说这话时，无影灯刚熄，手术室只剩监护仪的 滴答声。 那滴答声像倒放的时钟，把上海宝山一位六十多岁患者的四个月空白一点点推回眼前。有一 年九月，患者接受上海政府为65岁及以上常住居民每年免费提供一次的体检，这项活动属于 国家基本公共卫生服务项目，从2009年就在全国统一实施；十月，医生提醒患者肝有点问 题，注意查看报告并往大医院检查，彼时肿瘤大小约三公分；次年二月份，患者和儿子一起 吃年夜饭，正月十五元宵节后，前往东方肝胆外科医院就诊，肿瘤接近满肝。 政府免费筛查的红章盖得清晰，体检报告记录的三公分肿瘤像个不定时炸弹，却被塞进抽屉 整整四个月，等到儿子在年夜饭后翻开，父亲的世界已经濒临塌方。 伍路把那份"拖了四个月才就诊"的病例刻在心里，提醒来看诊的病人，也尽力科普给遇到的 每一个人："肿瘤不等人，早诊早治才是抢回时间的第一张多米诺骨牌。" "早癌手术没故事" 三十九岁的伍路身形修长，肩背笔直得像刚拆封的手术刀，眼里的光如同无影灯一般亮而 稳，语速清 ...

Core Viewpoint - The integration of multimodal neuroimaging and artificial intelligence (AI) is revolutionizing the early diagnosis and personalized treatment of neuropsychiatric disorders, addressing the challenges posed by their complex pathology and clinical heterogeneity [2][6]. Multimodal Neuroimaging: A Comprehensive Brain Examination - Traditional single-modality brain examinations are limited, while multimodal imaging can decode the brain from structural, functional, and molecular dimensions, enabling early intervention [7][8]. - Structural imaging (e.g., MRI) reveals brain tissue volume and cortical thickness, functional imaging (e.g., fMRI, EEG) captures neuronal activity, and molecular imaging (e.g., PET) tracks pathological markers like amyloid proteins, providing early warnings for conditions like Alzheimer's disease [9]. AI as a Puzzle Solver - AI demonstrates three key capabilities in handling vast heterogeneous data: feature fusion (early, mid, and late fusion), deep learning models, and clinical prediction tools, significantly enhancing diagnostic accuracy [12][13]. - For instance, multimodal AI models have improved early Alzheimer's diagnosis accuracy to 92.7%, surpassing single-modality methods by over 15% [13]. Practical Achievements: AI's Impact - AI has achieved high diagnostic accuracy, distinguishing Alzheimer's from Lewy body dementia at 87% and predicting epilepsy seizures with over 98% accuracy [14]. - It can predict the efficacy of depression medications with 89% accuracy and assess cognitive decline rates [15]. - AI identified three subtypes in over 2,000 bipolar disorder patients, guiding personalized treatment approaches [16]. Challenges and Breakthroughs: Path to Clinical Application - The integration of multimodal neuroimaging data faces challenges such as data availability, heterogeneity, and AI model interpretability, compounded by issues like class imbalance, algorithm bias, and data privacy [20]. - Addressing these challenges is crucial for developing robust AI models based on multimodal neuroimaging [20]. Future Research Directions - The future of AI in neuropsychiatric disorders includes the development of transformer models for cross-modal data processing, dynamic monitoring of brain network changes, and creating lightweight models for clinical use [23][24]. - Despite significant advancements, further exploration of clinical effectiveness and usability is needed to transition from research to practical applications [24].

Core Viewpoint - The Trump administration's policies are significantly undermining U.S. scientific research and funding, leading to widespread concerns about the future of science in the country [1][3][11]. Group 1: Impact on Federal Research Funding - The Trump administration has threatened to cut billions in funding for research universities and has already terminated over 1,000 grants in critical areas such as climate change and cancer research [1][20]. - The proposed 2026 budget may drastically reduce federal scientific investments, with potential cuts of 50% to NASA's science budget and 40% to the National Institutes of Health (NIH) [2][22]. - The NIH, which received nearly $48 billion in funding, is crucial for U.S. research, having funded over 99% of drugs approved from 2010 to 2019 [9][31]. Group 2: Scientific Community's Response - A public letter from approximately 1,900 members of the National Academies of Sciences, Engineering, and Medicine expressed alarm over the damage to U.S. science, with 94% of surveyed scientists worried about the future [3][37]. - The scientific community is concerned that the dismantling of federal support will lead to a significant decline in innovation and competitiveness, with many researchers considering opportunities abroad [26][27]. Group 3: Long-term Consequences - Experts warn that the damage inflicted by the Trump administration could take decades to reverse, with a significant loss of knowledge and talent in the scientific workforce [7][19]. - The reduction in federal funding is expected to hinder technological innovation, affecting industries reliant on research and development [31][32]. - The shift towards private funding may not adequately replace government support, particularly for high-cost, large-scale research projects [33][34]. Group 4: University and Research Institution Challenges - U.S. universities are facing unprecedented challenges due to funding cuts and political pressures, with many institutions already tightening graduate admissions and research funding [21][24]. - The Trump administration's stance on federal funding has created a hostile environment for research, leading to fears of a decline in the quality and quantity of scientific output [25][30]. - The potential loss of international talent is a significant concern, as many foreign researchers are reconsidering their plans to study or work in the U.S. due to the current political climate [26][27].