Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.

Objective: To investigate the nutritional status and influencing factors among Tibetan and Mongolian children and adolescents aged 7-18 years in high-altitude regions, so as to provide evidence for early prevention and control of malnutrition in this population. Methods: From May to June 2022, a cluster sampling method was employed to recruit 1 019 Tibetan and Mongolian children and adolescents aged 7-18 years from two primary and secondary schools in Golmud City. Physical examinations, dietary frequency questionnaires, and physical activity assessments were conducted. Nutritional status was classified as obesity, combined overweight/obesity, underweight, or central obesity according to national standards including Screening for Overweight and Obesity among School-age Children and Adolescents, Screening Standard for Malnutrition of School-age Children and Adolescents, Blue Book on Obesity Prevention and Control in China. Chi-square tests, t-test and Logistic regression analyses were performed to identify factors associated with different nutritional statuses. Results: The detection rates of obesity, combined overweight/obesity, underweight, and central obesity were 8.0%, 18.1%, 5.2%, and 19.7%, respectively. The height of children and adolescents across all age groups was generally lower than the national standard values. Tibetan participants exhibited significantly lower height-for-age Z-scores (HAZ)(9-10, 13-17 years, Z =2.01, 2.78, 4.16, 3.38, 4.12, 3.63, 3.00) and BMI-for-age Z-scores (BAZ) compared to Mongolian participants ( Z =-2.95, -2.47, -2.31, -2.89, -2.14, -2.17)( P < 0.05 ). Multivariate Logistic regression revealed that Mongolian children and adolescents had higher risks of obesity ( OR =2.20) and combined overweight/obesity ( OR = 2.18 ) ( P <0.05). Additionally, insufficient moderate-to-vigorous physical activity (MVPA) was associated with an increased risk of central obesity ( OR =1.48, P <0.05), compared with children and adolescents who meet the standard of MVPA. Conclusions The rates of overweight and obesity among Tibetan and Mongolian children and adolescents in Golmud City are higher, influenced by multiple factors. Nutrition interventions and physical activity strategies tailored to ethnic characteristics should be implemented, with emphasis on promoting MVPA to improve nutritional outcomes in this population.

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Alzheimer's disease (AD) is a neurodegenerative disease with clinical hallmarks of progressive cognitive impairment. Synergistic effects of the Aβ-Tau cascade reaction are tightly implicated in AD pathology, and microglial NLRP3 inflammasome activation drives neuronal tauopathy. However, the underlying mechanism of how Aβ mediates NLRP3 inflammasome remains unclear. Herein, we determined that oligomeric Aβ (o-Aβ) bound to microglial Kv2.1 and promoted Kv2.1-dependent potassium efflux to activate NLRP3 inflammasome resulting in neuronal tauopathy by using Kv2.1 inhibitor drofenine (Dfe) as a probe. The underlying mechanism has been intensively investigated by assays with Kv2.1 knockdown in vitro (si-Kv2.1) and in vivo (AAV-ePHP-si-Kv2.1). Dfe deprived o-Aβ of its capability to promote microglial NLRP3 inflammasome activation and neuronal Tau hyperphosphorylation by inhibiting the Kv2.1/JNK/NF-κB pathway while improving the cognitive impairment of 5×FAD-AD model mice. Our results have highly addressed that the Kv2.1 channel is required for o-Aβ-driven microglial NLRP3 inflammasome activation and neuronal tauopathy in AD model mice and highlighted that Dfe as a Kv2.1 inhibitor shows potential in the treatment of AD.

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

The ventral anterior (VA) nucleus of the thalamus is a major target of the basal ganglia and is closely associated with the pathogenesis of Parkinson's disease (PD). Notably, the VA receives direct innervation from the hypothalamic histaminergic system. However, its role in PD remains unknown. Here, we assessed the contribution of histamine to VA neuronal activity and PD motor deficits. Functional magnetic resonance imaging showed reduced VA activity in PD patients. Optogenetic activation of VA neurons or histaminergic afferents significantly alleviated motor deficits in 6-OHDA-induced PD rats. Furthermore, histamine excited VA neurons via H1 and H2 receptors and their coupled hyperpolarization-activated cyclic nucleotide-gated channels, inward-rectifier K⁺ channels, or Ca²⁺-activated K⁺ channels. These results demonstrate that histaminergic afferents actively compensate for Parkinsonian motor deficits by biasing VA activity. These findings suggest that targeting VA histamine receptors and downstream ion channels may be a potential therapeutic strategy for PD motor dysfunction.
Animals ; Histamine/metabolism* ; Male ; Oxidopamine/toxicity* ; Rats ; Ventral Thalamic Nuclei/physiopathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Parkinson Disease/metabolism* ; Neurons/physiology* ; Humans ; Optogenetics

The Healthy China 2030 Plan set the goal of reducing premature deaths from diabetes by 30% by 2030. However, there has been a lack of assessment of premature mortality for diabetes since the action plan was issued. This study used data from the Global Burden of Disease Study 2021, calculated the premature deaths for diabetes by sex, provinces, and subtypes from 1990 to 2021. We explored the temporal trend of premature mortality using the average annual percent change (AAPC) for different sexes, provinces, and subtypes from 1990 to 2021. Furthermore, we predicted premature mortality for diabetes through 2030 for China and its provinces according to the average annual change rate from 2010 to 2021. There was a first slow upward trend in premature mortality for diabetes from 0.5% in 1990 to 0.6% in 2004, and then a decline until 2021 with premature mortality of 0.4%. By 2030, only Fujian (30.3%) will achieve the desired level of reduction, with only seven provinces meeting the target for females and none for males. There is a large range in the degree of decline between inland and coastal regions, showing obvious geographic differences, and there should be a focus on balancing medical resources.
Humans ; China/epidemiology* ; Female ; Male ; Mortality, Premature/trends* ; Diabetes Mellitus/mortality* ; Goals ; Middle Aged ; Adult

Objective: To analyze the serological characteristics of anti-Mur antibodies and investigate the distribution frequency of the Mur antigen among voluntary blood donors in Shiyan, thereby providing a basis for guiding clinical transfusion and establishing a Mur blood type database. Methods: ABO blood grouping of donors and patients was performed using an automated blood typing analyzer and the gel card method, respectively. Unexpected antibody screening and identification were performed using the saline, tube anti-human globulin, and polybrene methods. The specificity of anti-Mur antibodies was confirmed using Fisher's exact probability test. Plasma treated with 2-mercaptoethanol was used to distinguish IgM and IgG antibodies. IgM and IgG anti-Mur titers were determined by the saline tube method and the anti-human globulin tube method, respectively, at 4℃, room temperature, and 37℃. A total of 1 659 donor red blood cell samples were initially screened for the Mur antigen phenotype using three samples of human-derived anti-Mur plasma by the micro-tube method. Donors who tested positive for Mur antigen were further tested by the direct antiglobulin test (DAT); those with negative results were confirmed for Mur antigen by the gel card and polybrene methods. Results: Three blood samples were identified to contain mixed IgG and IgM anti-Mur antibodies. The titers of both IgM and IgG anti-Mur antibodies were highest at 4℃, intermediate at room temperature, and lowest at 37℃. The positive frequency of the Mur antigen among voluntary blood donors in Shiyan was 1.99% (33/1 659). Conclusion: anti-Mur antibodies were detected in both blood donors and patients in our region. The Mur antigen shows a certain distribution frequency among voluntary blood donors in Shiyan. Screening for the Mur blood type and establishing a corresponding database could enhance transfusion safety.