Medical review (Berlin, Germany)最新文献_第2页

The new era of cardiovascular research: revolutionizing cardiovascular research with 3D models in a dish. 心血管研究的新时代：利用碟中三维模型彻底改变心血管研究。

Medical review (Berlin, Germany) Pub Date : 2024-02-20 eCollection Date: 2024-02-01 DOI: 10.1515/mr-2023-0059

Yuan Yang, Hao Yang, Fedir N Kiskin, Joe Z Zhang

{"title":"The new era of cardiovascular research: revolutionizing cardiovascular research with 3D models in a dish.","authors":"Yuan Yang, Hao Yang, Fedir N Kiskin, Joe Z Zhang","doi":"10.1515/mr-2023-0059","DOIUrl":"10.1515/mr-2023-0059","url":null,"abstract":"Cardiovascular research has heavily relied on studies using patient samples and animal models. However, patient studies often miss the data from the crucial early stage of cardiovascular diseases, as obtaining primary tissues at this stage is impracticable. Transgenic animal models can offer some insights into disease mechanisms, although they usually do not fully recapitulate the phenotype of cardiovascular diseases and their progression. In recent years, a promising breakthrough has emerged in the form of in vitro three-dimensional (3D) cardiovascular models utilizing human pluripotent stem cells. These innovative models recreate the intricate 3D structure of the human heart and vessels within a controlled environment. This advancement is pivotal as it addresses the existing gaps in cardiovascular research, allowing scientists to study different stages of cardiovascular diseases and specific drug responses using human-origin models. In this review, we first outline various approaches employed to generate these models. We then comprehensively discuss their applications in studying cardiovascular diseases by providing insights into molecular and cellular changes associated with cardiovascular conditions. Moreover, we highlight the potential of these 3D models serving as a platform for drug testing to assess drug efficacy and safety. Despite their immense potential, challenges persist, particularly in maintaining the complex structure of 3D heart and vessel models and ensuring their function is comparable to real organs. However, overcoming these challenges could revolutionize cardiovascular research. It has the potential to offer comprehensive mechanistic insights into human-specific disease processes, ultimately expediting the development of personalized therapies.","PeriodicalId":74151,"journal":{"name":"Medical review (Berlin, Germany)","volume":"4 1","pages":"68-85"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10954298/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140186846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nanotechnology-based delivery systems to overcome drug resistance in cancer. 基于纳米技术的给药系统，克服癌症耐药性。

Medical review (Berlin, Germany) Pub Date : 2024-02-20 eCollection Date: 2024-02-01 DOI: 10.1515/mr-2023-0058

Harsh Patel, Jiaxin Li, Letao Bo, Riddhi Mehta, Charles R Ashby, Shanzhi Wang, Wei Cai, Zhe-Sheng Chen

引用次数: 0

The role of clinical trials in advancing reproductive medicine: a comprehensive overview. 临床试验在生殖医学发展中的作用：全面概述。

Medical review (Berlin, Germany) Pub Date : 2023-12-05 eCollection Date: 2023-10-01 DOI: 10.1515/mr-2023-0053

Tian Tian, Jie Qiao

引用次数: 0

In silico protein function prediction: the rise of machine learning-based approaches. 硅学蛋白质功能预测：基于机器学习方法的兴起。

Medical review (Berlin, Germany) Pub Date : 2023-11-29 eCollection Date: 2023-12-01 DOI: 10.1515/mr-2023-0038

Jiaxiao Chen, Zhonghui Gu, Luhua Lai, Jianfeng Pei

{"title":"In silico protein function prediction: the rise of machine learning-based approaches.","authors":"Jiaxiao Chen, Zhonghui Gu, Luhua Lai, Jianfeng Pei","doi":"10.1515/mr-2023-0038","DOIUrl":"10.1515/mr-2023-0038","url":null,"abstract":"Proteins function as integral actors in essential life processes, rendering the realm of protein research a fundamental domain that possesses the potential to propel advancements in pharmaceuticals and disease investigation. Within the context of protein research, an imperious demand arises to uncover protein functionalities and untangle intricate mechanistic underpinnings. Due to the exorbitant costs and limited throughput inherent in experimental investigations, computational models offer a promising alternative to accelerate protein function annotation. In recent years, protein pre-training models have exhibited noteworthy advancement across multiple prediction tasks. This advancement highlights a notable prospect for effectively tackling the intricate downstream task associated with protein function prediction. In this review, we elucidate the historical evolution and research paradigms of computational methods for predicting protein function. Subsequently, we summarize the progress in protein and molecule representation as well as feature extraction techniques. Furthermore, we assess the performance of machine learning-based algorithms across various objectives in protein function prediction, thereby offering a comprehensive perspective on the progress within this field.","PeriodicalId":74151,"journal":{"name":"Medical review (Berlin, Germany)","volume":"3 6","pages":"487-510"},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10808870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139572259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The application of artificial intelligence in the management of sepsis. 人工智能在败血症管理中的应用。

Medical review (Berlin, Germany) Pub Date : 2023-11-28 eCollection Date: 2023-10-01 DOI: 10.1515/mr-2023-0039

Jie Yang, Sicheng Hao, Jiajie Huang, Tianqi Chen, Ruoqi Liu, Ping Zhang, Mengling Feng, Yang He, Wei Xiao, Yucai Hong, Zhongheng Zhang

{"title":"The application of artificial intelligence in the management of sepsis.","authors":"Jie Yang, Sicheng Hao, Jiajie Huang, Tianqi Chen, Ruoqi Liu, Ping Zhang, Mengling Feng, Yang He, Wei Xiao, Yucai Hong, Zhongheng Zhang","doi":"10.1515/mr-2023-0039","DOIUrl":"10.1515/mr-2023-0039","url":null,"abstract":"Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to healthcare worldwide. Patients afflicted by severe sepsis or septic shock are customarily placed under intensive care unit (ICU) supervision, where a multitude of apparatus is poised to produce high-granularity data. This reservoir of high-quality data forms the cornerstone for the integration of AI into clinical practice. However, existing reviews currently lack the inclusion of the latest advancements. This review examines the evolving integration of artificial intelligence (AI) in sepsis management. Applications of artificial intelligence include early detection, subtyping analysis, precise treatment and prognosis assessment. AI-driven early warning systems provide enhanced recognition and intervention capabilities, while profiling analyzes elucidate distinct sepsis manifestations for targeted therapy. Precision medicine harnesses the potential of artificial intelligence for pathogen identification, antibiotic selection, and fluid optimization. In conclusion, the seamless amalgamation of artificial intelligence into the domain of sepsis management heralds a transformative shift, ushering in novel prospects to elevate diagnostic precision, therapeutic efficacy, and prognostic acumen. As AI technologies develop, their impact on shaping the future of sepsis care warrants ongoing research and thoughtful implementation.","PeriodicalId":74151,"journal":{"name":"Medical review (Berlin, Germany)","volume":"3 5","pages":"369-380"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10811352/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139572195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New insights into non-invasive screening of esophageal squamous cell carcinoma. 食管鳞状细胞癌无创筛查的新见解。

Medical review (Berlin, Germany) Pub Date : 2023-11-17 eCollection Date: 2023-10-01 DOI: 10.1515/mr-2023-0045

Ye Gao, Luowei Wang, Zhaoshen Li

引用次数: 0

Current state of stem cell research in non-human primates: an overview 非人类灵长类动物干细胞研究现状综述

Medical review (Berlin, Germany) Pub Date : 2023-11-06 DOI: 10.1515/mr-2023-0035

Junmo Wu, Yuxi Shi, Shanshan Yang, Zengli Tang, Zifan Li, Zhuoyao Li, Jiawei Zuo, Weizhi Ji, Yuyu Niu

引用次数: 0

Assessment of commonly used tests in experimental depression studies according to behavioral patterns of rodents 基于啮齿类动物行为模式的实验性抑郁症研究常用测试评估

Medical review (Berlin, Germany) Pub Date : 2023-11-01 DOI: 10.1515/mr-2023-0018

Zafer Sahin

引用次数: 0

Macrophages and microglia in inflammation and neuroinflammation underlying different pain states 不同疼痛状态下炎症和神经炎症中的巨噬细胞和小胶质细胞

Medical review (Berlin, Germany) Pub Date : 2023-11-01 DOI: 10.1515/mr-2023-0034

Ouyang Chen, Xin Luo, Ru-Rong Ji

{"title":"Macrophages and microglia in inflammation and neuroinflammation underlying different pain states","authors":"Ouyang Chen, Xin Luo, Ru-Rong Ji","doi":"10.1515/mr-2023-0034","DOIUrl":"https://doi.org/10.1515/mr-2023-0034","url":null,"abstract":"Abstract Pain is a main symptom in inflammation, and inflammation induces pain via inflammatory mediators acting on nociceptive neurons. Macrophages and microglia are distinct cell types, representing immune cells and glial cells, respectively, but they share similar roles in pain regulation. Macrophages are key regulators of inflammation and pain. Macrophage polarization plays different roles in inducing and resolving pain. Notably, macrophage polarization and phagocytosis can be induced by specialized pro-resolution mediators (SPMs). SPMs also potently inhibit inflammatory and neuropathic pain via immunomodulation and neuromodulation. In this review, we discuss macrophage signaling involved in pain induction and resolution, as well as in maintaining physiological pain. Microglia are macrophage-like cells in the central nervous system (CNS) and drive neuroinflammation and pathological pain in various inflammatory and neurological disorders. Microglia-produced inflammatory cytokines can potently regulate excitatory and inhibitory synaptic transmission as neuromodulators. We also highlight sex differences in macrophage and microglial signaling in inflammatory and neuropathic pain. Thus, targeting macrophage and microglial signaling in distinct locations via pharmacological approaches, including immunotherapies, and non-pharmacological approaches will help to control chronic inflammation and chronic pain.","PeriodicalId":74151,"journal":{"name":"Medical review (Berlin, Germany)","volume":"61 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Current status and future perspective of natural killer cell therapy for cancer 自然杀伤细胞治疗癌症的研究现状及展望

Medical review (Berlin, Germany) Pub Date : 2023-10-24 DOI: 10.1515/mr-2023-0031

Xiangyu Zhao, Minghao Lin, Xiaojun Huang

引用次数: 0