Open Access Published by De Gruyter

Ahead of Print / Just Accepted

Issue of Medical Review

Submit manuscript

Contents
Journal Overview

Open Access November 29, 2023

In silico protein function prediction: the rise of machine learning-based approaches

Jiaxiao Chen, Zhonghui Gu, Luhua Lai, Jianfeng Pei

More Download PDF

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.

Open Access November 28, 2023

The application of artificial intelligence in the management of sepsis

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

More Download PDF

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.

Open Access November 17, 2023

New insights into non-invasive screening of esophageal squamous cell carcinoma

Ye Gao, Luowei Wang, Zhaoshen Li

Download PDF

Open Access November 1, 2023

Assessment of commonly used tests in experimental depression studies according to behavioral patterns of rodents

Zafer Sahin

More Download PDF

Abstract

Considering the main factor that causes or triggers depression in humans is stress. Several stress factors are applied to form depression-like symptoms in rodents. Depression tests are used to analyze the nature and patterns of depression. Well-founded modeling and versatile evaluation of tests are necessary to investigate a hypothesis that is related to depression. It is impossible to model or test all aspects of depression in humans by using experimental animals. As a result, the aims of the study should be determined specifically in depression models. The correct interpretation of the tests that are suitable for these aims is indispensable for the reliability of the data. To achieve this goal, the biological basis of the depression-related behaviors of animals should be well known. In this review, model and test concepts related to depression are discussed and behavioral patterns of rodents are explained with several examples.

Open Access November 1, 2023

Macrophages and microglia in inflammation and neuroinflammation underlying different pain states

Ouyang Chen, Xin Luo, Ru-Rong Ji

More Download PDF

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.

Open Access October 10, 2023

Immunotherapeutic approaches for systemic lupus erythematosus: early overview and future potential

Hongpeng Huang

More Download PDF

Abstract

Systemic lupus erythematosus (SLE) is a complex autoimmune disease. Current SLE therapies include immunosuppressants, antimalarial drugs, non-steroidal anti-inflammatory drugs (NSAIDs), and corticosteroids, but these treatments can cause substantial toxicities to organs and may not be effective for all patients. In recent years, significant progress has been made in the treatment of SLE using immunotherapy, including Benlysta and Saphnelo. These advances in immunotherapy hold promise for SLE patients, providing new therapeutic options that may offer better clinical benefit and effectiveness. Simultaneously, several new biological therapies focusing on cytokines, peptides, targeted antibodies, and cell-based approaches are under clinical evaluation and have shown immense potential for the treatment of SLE. However, the complexity of SLE immunopathogenesis and disease heterogeneity present significant challenges in the development of effective immunological therapies. This review aims to discuss past experiences and understanding of diverse immunological targeting therapies for SLE and highlight future perspectives for the development of novel immunological therapies.

Open Access October 6, 2023

An overview of recent advances and challenges in predicting compound-protein interaction (CPI)

Yanbei Li, Zhehuan Fan, Jingxin Rao, Zhiyi Chen, Qinyu Chu, Mingyue Zheng, Xutong Li

More Download PDF

Abstract

Compound-protein interactions (CPIs) are critical in drug discovery for identifying therapeutic targets, drug side effects, and repurposing existing drugs. Machine learning (ML) algorithms have emerged as powerful tools for CPI prediction, offering notable advantages in cost-effectiveness and efficiency. This review provides an overview of recent advances in both structure-based and non-structure-based CPI prediction ML models, highlighting their performance and achievements. It also offers insights into CPI prediction-related datasets and evaluation benchmarks. Lastly, the article presents a comprehensive assessment of the current landscape of CPI prediction, elucidating the challenges faced and outlining emerging trends to advance the field.

Open Access October 3, 2023

Bayesian approach for design and analysis of medical device trials in the era of modern clinical studies

Han Cao, Chen Yao, Ying Yuan

More Download PDF

Abstract

Medical device technology develops rapidly, and the life cycle of a medical device is much shorter than drugs. It is necessary to evaluate the safety and effectiveness of a medical device in a timely manner to keep up with technology flux. Bayesian methods provides an efficient approach to addressing this challenge. In this article, we review the characteristics of the Bayesian approach and some Bayesian designs that were commonly used in medical device regulatory setting, including Bayesian adaptive design, Bayesian diagnostic design, Bayesian multiregional design, and Bayesian label expansion study. We illustrate these designs with medical devices approved by the US Food and Drug Administration (FDA). We also review several innovative Bayesian information borrowing methods, and briefly discuss the challenges and future directions of the Bayesian application in medical device trials. Our objective is to promote the use of the Bayesian approach to accelerate the development of innovative medical devices and their accessibility to patients for effective disease diagnoses and treatments.

Open Access September 25, 2023

Evidence-based rehabilitation medicine: definition, foundation, practice and development

Jinlong Zhang, Chengqi He

More Download PDF

Abstract

To determine the definition, foundation, practice, and development of evidence-based rehabilitation medicine (EBRM) and point out the development direction for EBRM. Retrieve the database of PubMed, Cochrane Library, Embase, China national knowledge infrastructure (CNKI), Wanfang, and China science and technology journal database (CSTJ). The search was conducted from the establishment of the database to June 2023. The key words are “rehabilitation medicine and evidence based” in Chinese and English. After reading the abstract or full text of the literature, a summary analysis is conducted to determine the definition, foundation, practice, and development of EBRM. A total of 127 articles were included. The development of 14 sub majors in EBRM are not balanced, evidence-based musculoskeletal rehabilitation medicine (EBMRM) (31 articles, mainly focuses on osteoarthritis, osteoporosis and musculoskeletal pain), evidence-based neurorehabilitation medicine (EBNM) (34 articles, mainly concentrated in stroke, traumatic brain injury and spinal cord injury) and evidence-based education rehabilitation medicine (EBEDRM) (17 articles, mainly focuses on educational methodology), evidence-based nursing rehabilitation medicine (EBNRM) (2 articles), evidence-based engineering rehabilitation medicine (EBENRM) (7 articles), evidence-based traditional Chinese rehabilitation medicine (EBTCRM) (3 articles), evidence-based internal rehabilitation medicine (EBIRM) (11 articles), evidence-based intensive care rehabilitation medicine (EBICRM) (4 articles), evidence-based oncology rehabilitation medicine (EBORM) (6 articles), evidence-based physical therapy medicine (EBPTM) (3 articles), evidence-based cardiopulmonary rehabilitation medicine (EBCRM) (6 articles), evidence-based speech therapy medicine (EBSTM)/evidence-based occupation therapy medicine (EBOTM)/evidence-based geriatric rehabilitation medicine (EBGRM) (1 article). The EBMRM, EBNM and EBEDRM are relatively well developed. The development of EBNRM, EBENRM, EBTCRM, EBIRM, EBICRM, EBGRM, EBORM, EBCRM, EBPTM, EBSTM and EBOTM is relatively slow, indicating these eleven fields should be pay more attention in future.

Open Access September 21, 2023

The mTOR pathway in the antiphospholipid syndrome

Lanlan Ji, Zhuoli Zhang, Andras Perl

More Download PDF

Abstract

This perspective discussed the available evidence on the involvement of mTOR pathway in antiphospholipid syndrome (APS), from the aspects of endothelial cells, platelets, monocytes and anti-phospholipid antibodies (PLs), which may lead to future therapeutic applications of mTOR inhibition in APS.

Open Access September 20, 2023

Iron oxide nanoparticles in magnetic drug targeting and ferroptosis-based cancer therapy

Quazi T. H. Shubhra

More Download PDF

Abstract

Iron oxide (IO) nanoparticles (NPs) have gained significant attention in the field of biomedicine, particularly in drug targeting and cancer therapy. Their potential in magnetic drug targeting (MDT) and ferroptosis-based cancer therapy is highly promising. IO NPs serve as an effective drug delivery system (DDS), utilizing external magnetic fields (EMFs) to target cancer cells while minimizing damage to healthy organs. Additionally, IO NPs can generate reactive oxygen species (ROS) and induce ferroptosis, resulting in cytotoxic effects on cancer cells. This article explores how IO NPs can potentially revolutionize cancer research, focusing on their applications in MDT and ferroptosis-based therapy.

Open Access September 15, 2023

Nanostructured boron agents for boron neutron capture therapy: a review of recent patents

Xiyin Zhang, Yusheng Lin, Narayan S. Hosmane, Yinghuai Zhu

More Download PDF

Abstract

Boron neutron capture therapy (BNCT) is a potential radiation therapy modality for cancer, and tumor-targeted stable boron-10 ( 10 B) delivery agents are an important component of BNCT. Currently, two low-molecular-weight boron-containing compounds, sodium mercaptoundecahydro- closo -dodecaborate (BSH) and boronophenylalanine (BPA), are mainly used in BNCT. Although both have suboptimal tumor selectivity, they have shown some therapeutic benefit in patients with high-grade glioma and several other tumors. To improve the efficacy of BNCT, great efforts have been devoted for the development of new boron delivery agents with better uptake and favorable pharmacokinetic profiles. This article reviews the application and research progress of boron nanomaterials as boron carriers in boron neutron capture therapy and hopes to stimulate people’s interest in nanomaterial-based delivery agents by summarizing various kinds of boron nanomaterial patents disclosed in the past decade.

About this journal

Objective

CN: CN 10-1793/R
On-line ISSN: 2749-9642
Print ISSN: 2097-0733 (applies for copies in China)

Medical Review is a peer reviewed open access journal affiliate to Peking University Health Science Center. MR publishes high-quality internationally competitive review articles on cutting-edge progress and achievement from various areas of medical science, specifically focuses on clinical medicine, basic medicine, preventive medicine, medical ethics and multidisciplinary and emerging topics. MR is also committed to promote fundamental benefits among medical research communities, decision-makers and the public by conscientiously reviewing strategical and macro-level policies on medical-related issues and public health.

Your benefits

State-of-the-art research in physiology and pharmacology
Integrative approach to descriptive and behavioral studies
Leading-edge techniques
High quality peer-review

Topics

Clinical medicine
Basic medicine
Preventive medicine
Medical ethics

Article formats

Research Article
Review
Editorial
Research Highlight
Perspective
News and Comments
Scientists Forum
Letter

Virtual Collections

Cancer Research