Health and Metabolism

Pathogenic Mechanisms and Treatment Advancements of Sjogren’s Syndrome

2025-05-19T10:02:46+08:00

Sjogren’s syndrome (SS) is one of the most common chronic autoimmune diseases primarily affecting the salivary and lacrimal glands, leading to dry mouth and dry eyes, with systemic involvement in severe cases. This article provides an overview of the pathogenic mechanisms underlying SS, including genetic predisposition, immune dysregulation, cytokine imbalances, autoantibody production, and metabolic alterations. Additionally, advancements in treatment strategies are discussed, ranging from symptomatic relief to targeted biological therapies, such as B-cell depletion and cytokine modulation. While significant progress has been made in understanding the pathological mechanisms of SS, challenges persist in disease classification, biomarker identification, and therapeutic development. Future research is needed to focus on refining diagnostic criteria and exploring novel therapeutic interventions to improve disease management and patient outcomes.

From Clinical to Basic Research: The Neuroprotective Effects and Mechanisms of Caffeine

2025-04-02T09:57:36+08:00

Review

From Clinical to Basic Research: The Neuroprotective Effects and Mechanisms of Caffeine

Lijing Wang andLinxi Wang *

Department of Endocrinology and Metabolism, Fujian Institute of Endocrinology, Fujian Medical University Union Hospital, Fuzhou 350001, China

* Correspondence: wanglinxi@fjmu.edu.cn

Received: 15 October 2024; Revised: 31 October 2024; Accepted: 21 February 2025; Published: 1 April 2025

Abstract: Caffeine is the most widely used psychoactive substance in the world, is present in various beverages such as coffee, tea, and energy drinks. Its basic chemical structure contains methylxanthine active components. As a non-selective central adenosine receptor antagonist, caffeine exerts a broad range of pharmacological effects, including antioxidant, anti-inflammatory, and neuroprotective functions. Epidemiological studies and clinical reports suggest that caffeine consumption is closely associated with a reduced risk of neurodegenerative diseases including Alzheimer’s disease, Parkinson’s disease, and dementia. Additionally, caffeine has shown potential benefits in regulating cognitive function, improving depressive symptoms, and reducing the risk of stroke. Although the neuroprotective mechanisms of caffeine remain unclear, current research has revealed that it exerts its effects through multiple signaling pathways, including the inhibition of adenosine A_2A receptors, the suppression of neuroinflammation, and the modulation of synaptic plasticity. This paper discusses the recent advancements in research on the neuroprotective effects of caffeine and explores its potential mechanisms and applications in Alzheimer’s disease, Parkinson’s disease, stroke, and depression.

Vascular and Metabolic Responses to Elevated Circulating PDGF-BB in Mice: A Multiparametric MRI Study

2025-04-02T14:51:25+08:00

Article

Vascular and Metabolic Responses to Elevated Circulating PDGF-BB in Mice: A Multiparametric MRI Study

Xiuli Yang ^1,†, Jiekang Wang ^2,3,†, Yuguo Li ^1,4, Mei Wan ^2,3,*, Zhiliang Wei ^1,4,*

¹ Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

² Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

³ Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

⁴ F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD 21205, USA

* Correspondence: mwan4@jhmi.edu (M.W.); zhiliang.wei@jhu.edu (Z.W.)

† These authors contributed equally to this work.

Received: 20 November 2024; Revised: 20 December 2024; Accepted: 22 January 2025; Published: 11 February 2025

Abstract: Elevated circulating platelet-derived growth factor-BB (PDGF-BB) has been implicated in the development of various aged-related pathologies and is recognized as a potential pro-aging factor. Although numerous studies have explored the pathological roles of the PDGF-BB/PDGFRβ signaling pathway, few investigations have dissected its function in neurofunctional responses to elevated circulating PDGF-BB, primarily because in-vivo measurements are generally required to assess neurofunction. To address this knowledge gap, we characterized the vascular and metabolic responses to elevated circulating PDGF-BB in vivo using multiparametric non-invasive non-contrast MRI techniques in a conditional Pdgfb transgenic mouse model (Pdgfb^cTG) at 6 months of age. Results indicated that Pdgfb^cTG mice exhibited decreased cerebral blood flow (p = 0.025), elevated oxygen extraction (p = 0.002), and increased metabolic rate of oxygen (p = 0.035), mirroring the changes observed in human aging. The rate of change in vascular and metabolic measurements in the model mice was significantly higher (≥200.3%) compared to that of naturally aged mice. This study provides neurofunctional evidence that elevated circulating PDGF-BB accelerates neurovascular aging.

Targeting Cellular DNA Damage Response in Cancer and Bacterial Infections: Current Progress, Challenges, and Opportunities

2025-04-03T16:21:55+08:00

Review

Targeting Cellular DNA Damage Response in Cancer and Bacterial Infections: Current Progress, Challenges, and Opportunities

Ranxun Lin ¹, Xu Zhang ¹, Qinwei Zhu ¹, Xuening Chen ¹, Lin Dai ¹, Longheng Li ¹, Zuoan Li ², and Zhonghui Lin ^1,*

¹College of Chemistry, Fuzhou University, Fuzhou 350108, China

²Shengli Clinical Medical College of Fujian Medical University, Department of Emergency, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fujian Provincial Key Laboratory of Emergency Medicine, Fuzhou 350108, China

* Correspondence: zhonghui.lin@fzu.edu.cn

Received: 20 November 2024; Revised: 30 December 2024; Accepted: 21 February 2025; Published: 3 April 2025

Abstract: Effective cancer treatment remains challenging due to the genomic instability of tumors and the frequent emergence of resistance. Traditional approaches such as radiotherapy, chemotherapy, and immunotherapy face limitations in addressing tumor heterogeneity and resistance mechanisms. Targeting the DNA damage response (DDR) pathway has emerged as an innovative strategy, either as monotherapy or in combination with conventional treatments. DDR-targeted therapies, including poly-ADP-ribose polymerase (PARP) inhibitors, have shown promise in reducing tumor growth and enhancing patient outcomes. Emerging targets such as ATM, ATR, CHK1/2, WRN, and PARG, coupled with cutting-edge technologies like CRISPR and proteolysis-targeting chimeras (PROTACs), have opened new avenues for precise and effective cancer treatment. Furthermore, combining DDR inhibitors with established therapies, such as immune checkpoint inhibitors, has demonstrated synergistic benefits, improving therapeutic efficacy and overcoming resistance. Beyond cancer, DDR inhibitors also offer the potential to combat bacterial pathogens by exploiting vulnerabilities in microbial DNA repair systems. This review focuses on the major advantages, challenges, and future directions of DDR-targeted therapies in cancer and bacterial infections. We also discuss the integration of these therapies with traditional approaches, highlighting their potential to enhance therapeutic outcomes across diverse applications.

Strategies for Tag Design and Removal in the Expression and Purification of Recombinant Proteins

2025-04-09T09:37:57+08:00

Review

Strategies for Tag Design and Removal in the Expression and Purification of Recombinant Proteins

Jiayi Xie ^1,², Hongyi Fan ³, and Qingshan Bill Fu ^1,²^,*

¹School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China

²Shanghai Institute of Materia Medica, Zhongshan Institute for Drug Discovery, Chinese Academy of Sciences, Zhongshan 528400, China

³School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 511400, China

* Correspondence: fuqingshan@simm.ac.cn

Received: 19 December 2024; Revised: 10 January 2025; Accepted: 14 February 2025; Published: 8 April 2025

Abstract: Recombinant proteins find extensive applications in the biomedical and industrial fields, and efficient protein purification is often critical for achieving their functional value. Adding specific tags to the target proteins significantly enhances expression and purification efficiency and reduces time and costs. Tags can be classified into interfering and non-interfering tags, based on their effect on protein function during purification. However, interfering tags may need to be removed after purification to prevent interference with the protein’s function in downstream applications, presenting challenges for the design and utilization of tagged fusion proteins. In this article, we discuss the recent advancements in solubility tags and controllable aggregation tags, which have emerged as powerful tools to improve purification efficiency and address these challenges. We further outline strategies for optimal tag design and on-demand cleavage, and emphasize emerging trends, technical features, and forthcoming challenges that are shaping the future of tagged fusion protein production.

Exploring the Association between Epstein-Barr Virus and Systemic Lupus Erythematosus: Insights into Viral Triggers

2025-04-11T16:51:54+08:00

Commentary

Exploring the Association between Epstein-Barr Virus and Systemic Lupus Erythematosus: Insights into Viral Triggers

Ling Zhong and Xiao Zhang *

College of Pharmacy, Chongqing Medical University, Chongqing 400016, China

* Correspondence:zhangxiao@cqmu.edu.cn

Received: 26 November 2024; Revised: 24 December 2024; Accepted: 17 February 2025; Published: 11 April 2025

Abstract: Epstein-Barr virus (EBV) is ubiquitous in humans, which infects more than 90% of adults globally. Beyond its established association with malignancies, EBV infection is linked to several autoimmune diseases including systemic lupus erythematosus (SLE), multiple sclerosis (MS), rheumatoid arthritis and Sjögren syndrome. SLE is characterized by systemic inflammation and multiorgan damage with unpredictable relapsing-remitting clinical course. Although significant evidence supports EBV infection as a contributing factor in SLE pathogenesis, the exact mechanisms linking EBV to SLE onset remain to be fully elucidated. Molecular mimicry is among the potential factors that may drive SLE development. Importantly, given this association, development of therapies targeting EBV is promising for novel SLE treatment.

The Metabolic Underpinnings of Retinal Health and Disease: A Focus on Photoreceptor Cells

2025-04-14T17:14:55+08:00

Review

The Metabolic Underpinnings of Retinal Health and Disease: A Focus on Photoreceptor Cells

Jianbo Jin ^1,2, Qiuping Liu ^3,*, and Cheng Li ^1,2,4,*

¹Eye Institute & Affiliated Xiamen Eye Center, School of Medicine, Xiamen University, Xiamen 361102, China

²Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Xiamen 361102, China

³Department of Ophthalmology, The First Affiliated Hospital of University of South China, Hengyang Medical School, University of South China, Hengyang 421001, China

⁴Shen Zhen Research Institute, Xiamen University, Shenzhen 518057, China

* Correspondence: liuqiuping1983@gmail.com (Q.L.); cheng-li@xmu.edu.cn (C.L.)

Received: 27 October 2024; Revised: 9 December 2024; Accepted: 19 February 2025; Published: 14 April 2025

Abstract: The photoreceptor cells of the retina, encompassing rods and cones, are pivotal in the transduction of light signals into chemical ones, thereby initiating the visual process. This review explores the metabolic bedrock of these cells, which are not only crucial for preserving retinal health but are also susceptible to metabolic stress, precipitating a spectrum of retinal pathologies. The manuscript elucidates the intricate metabolic processes of photoreceptor cells, the synergistic metabolic interplay between photoreceptors and the retinal pigment epithelium (RPE), and appraises the metabolic shifts within photoreceptor cells under conditions of photic injury and diverse pathological states, as well as the ramifications of these metabolic perturbations for retinal function. The review culminates with a prospective horizon scan of research in photoreceptor cell metabolism, charting anticipated investigative trajectories.

Application of LLMs/Transformer-Based Models for Metabolite Annotation in Metabolomics

2025-04-25T17:44:09+08:00

Review

Application of LLMs/Transformer-Based Models for Metabolite Annotation in Metabolomics

Yijiang Liu ¹^,^†, Feifan Zhang ²^,^†, Yifei Ge ², Qiao Liu ³, Siyu He ⁴, and Xiaotao Shen ^1,2^,5,*

¹School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University,
Singapore 637459, Singapore

²Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore

³Department of Statistics, Stanford University School of Medicine, Palo Alto, CA 94304, USA

⁴Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94304, USA

⁵Singapore Phenome Center, Nanyang Technological University, Singapore 636921, Singapore

* Correspondence: xiaotao.shen@ntu.edu.sg

† These authors contributed equally to this work.

Received: 20 December 2024; Revised: 6 January 2025; Accepted: 3 March 2025; Published: 15 April 2025

Abstract: Liquid Chromatography-Mass Spectrometry (LC-MS) untargeted metabolomics has become a cornerstone of modern biomedical research, enabling the analysis of complex metabolite profiles in biological systems. However, metabolite annotation, a key step in LC-MS untargeted metabolomics, remains a major challenge due to the limited coverage of existing reference libraries and the vast diversity of natural metabolites. Recent advancements in large language models (LLMs) powered by Transformer architecture have shown significant promise in addressing challenges in data-intensive fields, including metabolomics. LLMs, which when fine-tuned with domain-specific datasets such as mass spectrometry (MS) spectra and chemical property databases, together with other Transformer-based models, excel at capturing complex relationships and processing large-scale data and significantly enhance metabolite annotation. Various metabolomics tasks include retention time prediction, chemical property prediction, and theoretical MS² spectra generation. For example, methods such as LipiDetective and MS2Mol have shown the potential of machine learning in lipid species prediction and de novo molecular structure annotation directly from MS² spectra. These tools leverage transformer principles and their integration with LLM frameworks could further expand their utility in metabolomics. Moreover, the ability of LLMs to integrate multi-modal datasets—spanning genomics, transcriptomics, and metabolomics—positions them as powerful tools for systems-level biological analysis. This review highlights the application and future perspectives of Transformer-based LLMs for metabolite annotation of LC-MS metabolomics incorporating with multiomics. Such transformative potential paves the way for enhanced annotation accuracy, expanded metabolite coverage, and deeper insights into metabolic processes, ultimately driving advancements in precision medicine and systems biology.