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PubMed1994

Unemployment and ill health: understanding the relationship.

OBJECTIVE: To review research relevant to understanding the psychological, social, and biological pathways by which unemployment may affect health risk; to consider the importance of four specific mechanisms; and to indicate some directions for future research. CRITERIA FOR INCLUSION AND EXCLUSION OF PUBLISHED STUDIES: Studies were chosen to illustrate the development of four major hypotheses regarding the relationship between unemployment and ill health, as well as the present state of knowledge. The review therefore includes some much-cited "classics" drawn from a long time span. Where recent reviews already exist relevant to individual mechanisms, these are referred to. Recent (since 1987) reports were sought by searching the BIDS data base. Particular effort was made to locate studies which enabled alternative hypotheses to be evaluated, and to point out where existing evidence is inconsistent or incomplete, indicating the need for further research. CONCLUSIONS: To understand the relationship between unemployment and ill health and mortality, four mechanisms need to be considered: the role of relative poverty; social isolation and loss of self esteem; health related behaviour (including that associated with membership of certain types of "subculture"); and the effect that a spell of unemployment has on subsequent employment patterns.

Cause of Death↗

PubMed2026

Exogenous lactate ameliorates Aβ-induced energy deficit and neurotoxicity with increased mitochondrial TCA cycle carbon flux in SH-SY5Y cells.

A growing body of evidence has demonstrated the existence of metabolic dysfunction in neurodegenerative diseases, including Alzheimer's disease (AD), suggesting that deprivation of energy substrates impairs cellular dynamics. As glucose utilization declines in patients with AD, the need for alternative energy sources becomes crucial to sustain neuronal activities and prevent cell death induced by neurotoxic proteins, such as amyloid beta (Aβ) aggregates. In this context, lactate has been investigated as a potential alternative brain energy substrate in several studies, yet its impact on neuronal cells under Aβ-induced toxicity remains unclear. We confirmed significant suppression of energy production-related biological pathways by analyzing brain transcriptomic data of patients with AD. In subsequent in vitro studies, exogenous lactate treatment ameliorated neuron-like cell death caused by Aβ aggregates. Using a 13C stable isotope tracer, we verified cellular lactate uptake and its incorporation into tricarboxylic acid (TCA) cycle in neurons under the neurotoxic condition. 13C metabolic flux analysis further supported these findings by revealing that lactate treatment restored Aβ-suppressed mitochondrial TCA cycle fluxes. These metabolic improvements were accompanied by increased expression of mitochondrial proteins. These findings support lactate shuttling as a mechanism for supplying lactate-derived carbon to mitochondrial energy metabolism, which may improve neuronal resilience under Aβ-induced metabolic stress.NEW & NOTEWORTHY This study shows that lactate treatment attenuates Aβ-induced cell death in neuron-like cells and supports mitochondrial carbon metabolism. Glycolytic hypometabolism was observed in human AD brain transcriptome and Aβ-treated neuron-like cells. We confirmed that lactate replenished mitochondrial energetics, making neurons more resilient to neurotoxicity. Using 13C tracing and metabolic flux analysis, we found that lactate-derived carbon was incorporated into the TCA cycle and that lactate treatment was associated with restoration of Aβ-suppressed mitochondrial fluxes.

Humans↗

PubMed2025

Influence of Ancestral and Geographic Factors on Intracerebral Hemorrhage Risks Among Africans and Americans.

BACKGROUND: We investigated whether risk factors for intracerebral hemorrhage (ICH) among indigenous Africans (IA) would vary in prevalence and effect compared with self-reported African, Hispanic, and White Americans by comparing data from 2 independent population-based case-control studies conducted in West Africa and the United States. METHODS: We compared ICH risk factors common to the SIREN (Stroke Investigative Research and Educational Network: 1100 case-control pairs) and the ERICH (Ethnic/Racial Variation of Intracerebral Hemorrhage: 999 case-control pairs African American participants, 998 case-control pairs, Hispanic Americans, 1000 case-control pairs, White Americans) studies. Ethnicity/Race was self-reported. The effect measure of interest is the odds ratio (OR). To test for differences in the effects of the risk factors between the SIREN IA study population and each of the ERICH study populations, a test for heterogeneity was computed using the R program, metagen (version 4.9-6). RESULTS: ICH occurred at a younger age among IA (54.3±13.4 years), African Americans (58.0±12.7), and Hispanic Americans (58.9±14.3), compared with White Americans (69.1±13.9). The largest distinction was for hypertension, where IA exhibited a much larger risk of ICH than the American study population (OR, 67.02 [95% CI, 33.30-134.85]), African American (OR, 3.71 [95% CI, 2.53-5.44]); Hispanic (OR, 3.55 [95% CI, 2.54-4.92]), and White population (OR, 2.69 [95% CI, 1.95-3.69]). Current alcohol use exhibited increased risk in IA (OR, 2.24 [95% CI, 1.36-3.67]), but not in African Americans (OR, 0.63 [95% CI, 0.46-0.86]), Hispanic (OR, 0.87 [95% CI, 0.65-1.17]), and White Americans (OR, 0.51 [95% CI, 0.38-0.69]). CONCLUSIONS: Identical or comparable risk factors do not consistently result in the same disease risk across different cultures and regions. Therefore, to improve our understanding of the genetic determinants and biological pathways driving ICH risk, it is crucial to study multiple populations, including IA, while accounting for the influence of environmental and social factors.

Adult↗

PubMed2026

Genetically Predicted Muscle Mass and Function in Relation to Deep Vein Thrombosis: A Two-step Mendelian Randomization Study Highlighting the Mediating Role of BMI.

BackgroundSarcopenia is observationally linked to venous thromboembolism, but the causal architecture and underlying biological pathways remain largely unclear. This study investigated the causal effects of sarcopenia-related traits on lower extremity deep vein thrombosis (DVT) and quantified potential mediating mechanisms.MethodsWe performed two-sample bidirectional Mendelian randomization (MR) and two-step mediation MR using large-scale GWAS data from UK Biobank, EMBL-EBI, and FinnGen. Exposures included appendicular lean mass (ALM), leg fat-free mass (LFM), hand grip strength, and walking pace. Eighteen candidate mediators were screened for indirect pathways.ResultsGenetically predicted higher ALM was significantly associated with increased DVT risk (FinnGen: OR = 1.288, 95% CI: 1.215-1.365, P < 0.001). Similar positive associations were observed for LFM (OR = 1.920-1.954, P < 0.001). By contrast, muscle functional traits - grip strength and walking pace - demonstrated no consistent causal effects. Reverse MR confirmed a unidirectional relationship. Body mass index (BMI) emerged as a pivotal mediator, accounting for 7.58% - 10.50% of the ALM-DVT effect and 52.74% - 62.73% of the LFM-DVT effect. Notably, the independent effect of ALM was largely attenuated after adjusting for metabolic confounders in multivariable MR.ConclusionGenetic predisposition to high muscle mass, rather than functional strength, increases DVT risk. This relationship appears to be significantly driven by metabolic adiposity, suggesting that the "muscle-vascular-coagulation" interaction is partly explained by body-size-related metabolic burden. Risk stratification should integrate muscle mass evaluation with comprehensive metabolic health assessments.

Humans↗

PubMedDate not supplied

Non-dehalogenation mechanisms for excretion of radioiodine after administration of labeled antibodies.

In patients or mice with cancer the pharmacokinetic behavior of radioiodinated and radiometal chelated antibodies has been observed to be different. Rapid clearance from the tissues and excretion into the urine can occur after injection of radioiodinated antibodies. These observations have been interpreted to reflect in vivo dehalogenation of the antibody. This publication describes a variety of other mechanisms that can underlie these phenomena. These mechanisms include receptor uptake and catabolism of antibody and instability of the labeled antibody due to the labeling conditions. Specifically, the relative masses of chloramine-T and antibody in the iodination reaction mixture, the level of iodination of the antibody, and the amount of antibody administered to the recipient are all factors which can influence the clearance of radioiodinated antibody from the recipient. The final determinant for the different behavior of radioiodinated and In-111 metal chelated antibody relate to the different biologic pathways of indium when compared to iodine.

Animals↗

PubMed2025

Functional characterization of the MED12 p.Arg1138Trp variant in females: implications for neural development and disease mechanism.

BACKGROUND: Seven female individuals with multiple congenital anomalies, developmental delay and/or intellectual disability have been found to have a genetic variant of uncertain significance in the mediator complex subunit 12 gene (MED12 c.3412C>T, p.Arg1138Trp). The functional consequence of this genetic variant in disease is undetermined, and insight into disease mechanism is required. METHODS: We identified a de novo MED12 p.Arg1138Trp variant in a female patient and compared disease phenotypes with six female individuals identified in the literature. To investigate affected biological pathways, we derived two induced pluripotent stem cell (iPSC) lines from the patient: one expressing wildtype MED12 and the other expressing the MED12 p.Arg1138Trp variant. We performed neural disease modelling, transcriptomics and protein analysis, comparing healthy and variant cells. RESULTS: When comparing the two cell lines, we identified altered gene expression in neural cells expressing the variant, including genes regulating RNA polymerase II activity, transcription, pre-mRNA processing, and neural development. We also noted a decrease in MED12L expression. Pathway analysis indicated temporal delays in axon development, forebrain differentiation, and neural cell specification with significant upregulation of pre-ribosome complex gene pathways. CONCLUSION: In a human neural model, expression of MED12 p.Arg1138Trp altered neural cell development and dysregulated the pre-ribosome complex providing functional evidence of disease aetiology and mechanism in MED12-related disorders.

Humans↗

PubMed2026

Sugar-sweetened beverage consumption and incident depression: an exploratory multi-omics analysis of candidate biological mediators.

BACKGROUND: Depression is a leading cause of mental and physical disability globally, with its onset and progression influenced by a complex interplay of dietary, psychological, and biological factors. Recent research suggests a link between sugar-sweetened beverage (SSB) consumption and depression risk, although the potential biological pathways underlying this association remain poorly understood. METHODS: This study utilized data from 192,045 participants in the UK Biobank to examine the prospective association between SSB consumption and incident depression using Cox proportional hazards models. SSBs were defined as the sum of five beverage categories assessed via the Oxford WebQ 24-hour dietary recall. Directional consistency of the association was further examined across three external supporting datasets encompassing diverse populations: NHANES, YRBSS, and the Lianyungang Municipal School Health and Risk Factor Surveillance Study Dataset. We further investigated whether proteins, metabolites, inflammatory markers, and brain imaging phenotypes may serve as candidate mediators statistically consistent with mediation of the SSB-depression association. RESULTS: High SSB consumption was associated with an 18% higher risk of incident depression compared with non-consumers (HR = 1.18; 95% CI: 1.11-1.25), with consistent directional associations observed across external supporting datasets. A plasma proteomic signature comprising 229 proteins was constructed using elastic net regularization and was associated with an increased risk of incident depression. Exploratory mediation analyses identified 72 proteins, 36 metabolites, and 5 inflammatory markers as candidate mediators, with IL1RN showing the strongest protein-level candidate mediating effect (9.6%), and Unsaturation and neutrophil count showing the strongest metabolite- and inflammatory marker-level effects, respectively. CONCLUSIONS: This study provides preliminary evidence that proteins, metabolites, and inflammatory markers may serve as candidate mediators statistically consistent with mediation of the association between SSB consumption and incident depression. These findings are exploratory and hypothesis-generating, and future experimental studies are needed to validate these candidate pathways and assess their potential as targets for dietary interventions in depression prevention.

Humans↗

PubMed2026

Meta-ERS: an exposome-based risk score using non-genetic factors to guide osteoporosis prevention.

BACKGROUND: Osteoporosis is influenced by both genetic and environmental factors, yet the relative contribution of the exposome remains unclear. This study aimed to systematically identify non-genetic exposures related to osteoporosis and develop an exposome risk score (ERS) to evaluate individual osteoporosis susceptibility. METHODS: We conducted an exposome-wide analysis of 477,792 UK Biobank participants to identify key exposures associated with osteoporosis. The selected exposures were combined into a weighted Meta-ERS and validated in the Scotland/Wales cohort. The Meta-ERS was further compared with polygenic risk scores (PRS) and linked to plasma proteomics to explore underlying biological pathways. RESULTS: We identified 41 independent non-genetic exposures spanning socioeconomic status, mental health, sleep, diet, smoking, physical activity, environment, and marital status, with socioeconomic status and mental health emerging as the most significant drivers. Based on the identified exposures, we constructed eight domain-specific exposure risk scores and integrated them into a weighted Meta-ERS. The Meta-ERS (R2 = 5.1%; Proportion of Chi-Square = 14.3%) demonstrated an ability to explain osteoporosis variation that was on par with polygenic risk scores (R2 = 4.8%; Proportion of Chi-Square = 12.0%). Importantly, modifying unfavorable exposures mitigated the negative effect of PRS on osteoporosis, particularly among high PRS individuals (1.5- to 1.8-fold greater absolute risk reduction than in those with low PRS). Proteomic analyses further revealed potential mechanisms through which the exposome influences osteoporosis, including hormonal regulation, inflammation, ossification, muscle development, lipid metabolism, and accelerated bone aging. Among these, growth/differentiation factor 15 was identified as a key mediator protein, with a mediation proportion of 13.13%-36.52%. CONCLUSIONS: The Meta-ERS facilitates the quantification of individual osteoporosis risk and identifies modifiable exposures for targeted prevention. Its application can enable personalized risk stratification and guide lifestyle or environmental interventions.

Aged↗

PubMed2025

Alternative 3' UTR polyadenylation is disrupted in the rNLS8 mouse model of ALS/FTLD.

Recent research has highlighted widespread dysregulation of alternative polyadenylation in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP). Here, we identify significant disruptions to 3` UTR polyadenylation in the ALS/FTLD-TDP mouse model rNLS8 that correlate with changes in gene expression and protein levels through the re-analysis of published RNA sequencing and proteomic data. A subset of these changes are shared with TDP-43 knock-down mice suggesting depletion of endogenous mouse TDP-43 is a contributor to polyadenylation dysfunction in rNLS8 mice. Some conservation exists between alternative polyadenylation in rNLS8 mice and human disease models including in disease relevant genes and biological pathways. Together, these findings support both TDP-43 loss and toxic gain-of-function phenotypes as contributors to the neurodegeneration in rNLS8 mice, nominating its continued utility as a preclinical model for investigating mechanisms of neurodegeneration in ALS/FTLD-TDP.

Animals↗

PubMed2026

Improving recombinant protein productivity in CHO cells via multi-omics data integration.

Chinese hamster ovary (CHO) cells represent the dominant host system for the production of recombinant therapeutic proteins. In recent decades, extensive research has focused on process/media optimization and cell line engineering to improve both the productivity and quality of biopharmaceutical proteins produced in CHO cells. Nevertheless, the inherent complexity of biological pathways and the heterogeneous cellular responses to different environmental conditions have posed substantial challenges to traditional methodologies. Recent advances in omics technologies have enabled comprehensive characterization of CHO cell physiology, providing multidimensional molecular and phenotypic insights that facilitate the enhancement of recombinant protein production. This review first summarizes the methodologies and advances in CHO omics research, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics. It then examines contemporary approaches to integrate and analyze multi-omics data in CHO cells. The review further elucidates how these multi-omics datasets can be strategically applied across various developmental stages, including cell line selection, genetic engineering, expression vector design, and bioprocess optimization. Finally, we explore the transformative potential of integrating multi-omics with artificial intelligence and discuss promising future research directions in CHO cell studies. These emerging paradigms offer novel opportunities for data-driven cell engineering and bioprocess optimization in CHO-based biomanufacturing.

Bioprocessing↗

PubMed2024

A comprehensive analysis of ribonucleotide reductase subunit M2 for carcinogenesis in pan-cancer.

BACKGROUND: Although there is evidence that ribonucleotide reductase subunit M2 (RRM2) is associated with numerous cancers, pan-cancer analysis has seldom been conducted. This study aimed to explore the potential carcinogenesis of RRM2 in pan-cancer using datasets from The Cancer Genome Atlas (TCGA). METHODS: Data from the UCSC Xena database were analyzed to investigate the differential expression of RRM2 across multiple cancer types. Clinical data such as age, race, sex, tumor stage, and status were acquired to analyze the influence of RRM2 on the clinical characteristics of the patients. The role of RRM2 in the onset and progression of multiple cancers has been examined in terms of genetic changes at the molecular level, including tumor mutational burden (TMB), microsatellite instability (MSI), biological pathway changes, and the immune microenvironment. RESULTS: RRM2 was highly expressed in most cancers, and there was an obvious correlation between RRM2 expression and patient prognosis. RRM2 expression is associated with the infiltration of diverse immune and endothelial cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). Moreover, the cell cycle is involved in the functional mechanisms of RRM2. CONCLUSIONS: Our pan-cancer study provides a comprehensive understanding of the carcinogenesis of RRM2 in various tumors.

Humans↗

PubMed2026

Exploring cross-category relationships between symptoms in people with hypermobile EDS (hEDS) to identify disability patterns.

BACKGROUND: Hypermobile Ehlers-Danlos Syndrome (hEDS) is a connective tissue disorder with variable symptom presentation across multiple organ systems and significant morbidity. Little is known about hEDS etiology and identifying patterns of symptom co-occurrence can reveal previously unidentified relationships between phenotypes and inform studies of underlying disease pathophysiology for symptoms that may share functional biological pathways. In this exploratory analysis, we specifically assessed the distribution of symptoms in case and controls to identify clusters of co-occurring symptoms. METHODS: We have interrogated clinically relevant symptom areas in 47 females with hEDS, 36 age-matched female controls and 8 hypermobile patients without chronic pain. Studied symptoms include general health, mental health, body pain, vitality and energy, autonomic symptoms, bleeding, and gastrointestinal symptoms. We conducted hierarchal clustering on principle components (HCPC) to identify groups and compared the groups for the previously described symptoms. Radial plots were used to identify relationships between severe symptom categories. RESULTS: Our analysis reveals statistically significantly more severe symptoms in all categories in people with hEDS compared with age- and sex-matched controls and asymptomatic hypermobile patients. HCPC identified clearly separated Low, Moderate, and High symptom groups within participants. The Low dysfunction groups include nearly all controls and hypermobile patients without chronic pain. The High dysfunction group includes ~60% of people with hEDS, while around 40% are in the Moderate dysfunction cluster. Cluster solutions for all participants were stable with moderate fit (silhouette 0.64; Jaccard boot mean 0.91). Group level radial plots showed high bleeding severity across all symptom clusters, while disproportional severity of general health, physical function, limitation of role due to physical symptoms, pain, and social functioning deficits differentiates the High from Moderate and Low Dysfunction clusters. CONCLUSION: Using this analysis at the group level has revealed patterns suggesting a progression of disease symptoms. People with hypermobility do not uniformly have severe symptoms but instead have some symptoms that differentiate from non-hypermobile individuals. While exploratory, using a radar multi-symptom analysis may be used to evaluate disproportionately severe symptoms contributing to the patterns of global symptom severity. These include pain but also ability to perform roles, suggesting strong utility of physical and occupational therapies to emphasize coping. This may also allow better targeting of etiological studies and may have additional utility at an individual level to develop symptom management strategies.

Humans↗

PubMed2026

Systemic Proteome Profiling to Differentiate Primary Glomerular Diseases.

KEY POINTS: Plasma proteome profiling identified distinct signatures across biopsy-proven primary glomerular disease subtypes. An elastic net model using 93 proteins classified primary glomerular disease subtypes and controls, with external validation. Integrating proteomics with machine learning yields biologically interpretable insights in primary glomerular diseases. BACKGROUND: Primary GN is a heterogeneous group of kidney disorders where understanding of their pathophysiology remains incomplete. Despite the diagnostic potential of high-throughput proteomics, constrained proteomic depth and a reliance on binary comparisons have left the feasibility of using systemic signatures to differentiate multiple GN subtypes largely unexplored. METHODS: To identify protein signatures that noninvasively differentiate major primary glomerular disease subtypes and provide mechanistic insights, we performed large-scale systemic proteome profiling of 5416 plasma proteins via Olink Explore HT in a discovery cohort ( n =147) and an external validation cohort ( n =85) of Korean participants (mean age, 41±13 years; 46% female). The study population included patients with four GN subtypes-focal segmental glomerulosclerosis, IgA nephropathy, minimal change disease, and membranous nephropathy-alongside healthy controls. We developed a machine learning (ML) model using logistic regression with elastic net regularization to classify disease groups based on proteomic profiles and evaluated its performance in the independent validation cohort. RESULTS: Plasma proteome profiles were distinct among disease subtypes, emerging as a significant source of data variation independent of conventional markers such as eGFR or proteinuria levels. The ML model performed robustly in both the discovery and validation cohorts, achieving an area under the receiver operating characteristic curve >0.8 for differentiating minimal change disease, membranous nephropathy, and IgA nephropathy. The model, even without clinical information, correctly identified 93% of minimal change disease cases (14 of 15) and 63% of IgA nephropathy cases (20 of 32), but its performance was limited for focal segmental glomerulosclerosis, with only 21% of cases (three of 14) correctly classified. Functional analysis of key proteins highlighted distinct biologic pathways, such as hemostasis in minimal change disease. CONCLUSIONS: We identified distinct systemic proteome signatures for primary glomerular diseases, where disease subtype served as a major determinant of proteomic variance alongside conventional clinical markers. ML models demonstrated robust discriminatory performance for minimal change disease, membranous nephropathy, and IgA nephropathy, underscoring the potential for proteome-based classification.

Humans↗

PubMed2026

MS4A3 as a potential prognostic biomarker for colon cancer: integrated analysis of expression patterns and immune cell infiltration.

BACKGROUND: Membrane Spanning 4-Domains A3 (MS4A3) has been confirmed to possess significant tumor-suppressive potential in various malignancies. However, its expression characteristics and clinical prognostic value in colon cancer (CC) still lack systematic and in-depth investigation. This study aimed to systematically investigate the expression pattern, prognostic value, immune microenvironment association, and biological function of MS4A3 in CC through integrated bioinformatics analyses and experimental validation. METHODS: This study utilized The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) cohort to screen for genes significantly associated with CC and combined multiple independent Gene Expression Omnibus (GEO) datasets to validate the expression patterns and prognostic significance of MS4A3. Key biological pathways were identified through gene set enrichment analysis (GSEA), and tumor immune infiltration characteristics were evaluated using the CIBERSORT algorithm. Additionally, the expression of MS4A3 and its impacts on cellular functions were validated at the cellular level through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8), EdU, Transwell, and TUNEL assays. RESULTS: Analysis of public datasets revealed that MS4A3 is significantly downregulated in CC tissues, and its low expression is an independent risk factor for shortened overall survival (OS). GSEA indicated that MS4A3 downregulation is closely associated with the aberrant activation of the pentose phosphate pathway. Immune infiltration analysis showed that low MS4A3 expression is closely linked to the enrichment of M2 macrophages and neutrophils, as well as the upregulation of multiple immune checkpoint genes. In vitro experiments further confirmed that MS4A3 was lowly expressed in CC cell lines. Its overexpression significantly inhibited CC cell viability, proliferation, migration, and invasion, while simultaneously promoting cell apoptosis. CONCLUSIONS: MS4A3 expression is significantly decreased in CC tissues and is significantly correlated with poor prognosis, suggesting that this gene may serve as a potential prognostic biomarker.

MS4A3↗

PubMed2026

Preliminary Exploration on Melatonin-Mediated Protective Effects in Intracranial Aneurysms: Transcriptomic, Proteomic, and Metabolomic Profiling of Cerebral Vascular Tissues Combined with in vivo Animal Experiments.

BACKGROUND: Intracranial aneurysm (IA) is a life-threatening cerebrovascular disease with unclear molecular mechanisms and limited drug treatment. Our previous research has shown that melatonin (MLT) has potential protective effects in IA, but its mechanism remains unclear. The purpose of this study is to explore the pathological mechanism of IA and the therapeutic mechanism of MLT by integrating transcriptomic, proteomic and metabolomic analyses. METHODS: In this study, mouse models of IA were successfully established by combining elastase injection with angiotensin II infusion. C57BL/6 mice were divided into control, IA model, IA model+MLT, and IA model+nimodipine groups. The pathological conditions were evaluated by hematoxylin-eosin (HE) staining, TUNEL staining, and scanning electron microscopy. Transcriptomic (n=3 for each group), proteomic (n=3 for each group), and metabolomic (n=6 for each group) analyses were performed based on cerebral vascular tissue samples. The screening thresholds for differentially expressed genes and differentially expressed proteins were P <0.05 and fold change >1.5 and fold change <0.667. The screening criteria for differential metabolites were variable importance for the projection (VIP)> 1.0, fold change >1.2 and fold change <0.833, and P <0.05. RESULTS: MLT alleviated brain tissue damage, vascular endothelial damage, structural disruption, and apoptosis in IA mice. Transcriptomic, proteomic and metabolomic analyses identified numerous differential molecules. Functional annotation revealed that these molecules may be involved in biological pathways and processes such as immune inflammation, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress and metabolic pathways, thereby regulating the occurrence and development of IA or mediating the therapeutic effects of MLT. Furthermore, transcriptomic and proteomic analyses also suggest that there may be extensive post-transcriptional, translational and post-translational regulatory events in the progression of IA and the therapeutic effects of MLT. Integrated transcriptomic and proteomic analyses suggest that Npy may be a key molecule in regulating IA progression and mediating MLT therapeutic effects, and its potential value is further supported by our immunohistochemical validation results. CONCLUSION: Multi-omics integrative analysis preliminarily revealed that the potential mechanisms of MLT may involve the regulation of inflammatory response, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress, metabolic pathways, and post-transcriptional/translational regulation.

Animals↗

PubMed2026

Identification of JAML as an Immune-Associated Prognostic Marker in Non-Small Cell Lung Cancer.

INTRODUCTION: Non-small cell lung cancer (NSCLC) remains a major cause of cancer-related mortality worldwide, and the identification of novel prognostic biomarkers associated with tumor immunity is urgently needed. Junctional adhesion molecule-like (JAML), a member of the junctional adhesion molecule family, participates in leukocyte adhesion, migration, and T-cell activation. Although JAML has been implicated in immune regulation and tumor progression in other cancers, its expression pattern, prognostic significance, and association with the immune microenvironment in NSCLC remain unclear. This study aimed to investigate the clinical and immunological significance of JAML in NSCLC. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed to evaluate JAML expression patterns in NSCLC subtypes. The prognostic value of JAML was assessed using Kaplan-Meier survival analysis and Cox regression models. The association between JAML expression and immune cell infiltration was investigated using TIMER2.0, CIBERSORT, and TISIDB analyses. Functional enrichment analyses were performed to explore potential biological pathways associated with JAML expression. In addition, JAML expression was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) in paired NSCLC and adjacent normal tissues. RESULTS: JAML expression was significantly decreased in NSCLC tissues compared with normal tissues (P < 0.005), with the lowest expression observed in lung squamous cell carcinoma (LUSC) and reduced expression in lung adenocarcinoma (LUAD). Survival analysis demonstrated that patients with high JAML expression had significantly improved overall survival compared with those with low expression (univariate HR = 0.68, 95% CI: 0.54-0.86, P = 0.001; multivariate HR = 0.76, 95% CI: 0.57-1.00, P = 0.049). Immune infiltration analysis revealed that JAML expression was significantly associated with multiple immune cell populations, including CD8+ T cells (r = 0.42, P < 0.001), suggesting a close relationship between JAML expression and the tumor immune microenvironment. qRT-PCR validation confirmed that JAML expression was approximately 2.3-fold higher in adjacent normal tissues than in NSCLC tissues (P < 0.05). CONCLUSION: JAML is downregulated in NSCLC and its high expression is associated with favorable overall survival and distinct immune infiltration patterns. These findings indicate that JAML may serve as a potential prognostic biomarker and provide insights into the relationship between JAML expression and the tumor immune microenvironment in NSCLC.

JAML protein↗

PubMed1989

Clinical pharmacokinetics of non-opiate abused drugs.

The present review discusses the available data on the kinetic properties of non-opiate abused drugs including psychomotor stimulants, hallucinogens and CNS-depressants. Some of the drugs of abuse reviewed here are illicit drugs (e.g. cannabis, cocaine), while others are effective pharmacological agents but have the potential to be abused (e.g. benzodiazepines). Although some of the drugs mentioned in this review have been in use for centuries (e.g. caffeine, nicotine, cocaine, cannabis), knowledge of their kinetics and metabolism is very recent and in some cases still incomplete. This is partially due to the difficulties inherent in studying drugs of abuse in humans, and to the complex metabolism of some of these drugs (e.g. cannabis, caffeine) which has made it difficult to develop sensitive assays to determine biological pathways. Although drugs of abuse may have entirely different intrinsic pharmacological effects, the kinetic properties of such drugs are factors contributing to abuse and dependence. The pharmacokinetic properties that presumably contribute to self-administration and drug abuse include rapid delivery of the drug into the central nervous system and high free drug clearance. Kinetic characteristics also play an important role in the development of physical dependence and on the appearance of a withdrawal syndrome: the longer the half-life, the greater the likelihood of the development of physical dependence; the shorter the half-life, the earlier and more severe the withdrawal. The balance between these 2 factors, which has not yet been carefully studied, will also influence abuse patterns. The clinical significance of kinetic characteristics with respect to abuse is discussed where possible.

Amphetamines↗

PubMed2026

Quantitative Proteomic Analysis of APP/PS1 Transgenic Mice.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting the central nervous system (CNS), with its etiology still shrouded in uncertainty. The interplay of extracellular amyloid-β (Aβ) deposition, intracellular neurofibrillary tangles (NFTs) composed of tau protein, cholinergic neuronal impairment, and other pathogenic factors is implicated in the progression of AD. OBJECTIVE: The current study endeavors to delineate the proteomic landscape alterations in the hippocampus of an AD murine model, utilizing proteomic analysis to identify key physiological and pathological shifts induced by the disease. This endeavor aims to shed light on the underlying pathogenic mechanisms, which could facilitate early diagnosis and pave the way for novel therapeutic interventions for AD. METHODS: To dissect the proteomic perturbations induced by Aβ and Presenilin-1 (PS1) in the AD pathogenesis, we undertook a label-free quantitative (LFQ) proteomic analysis focusing on the hippocampal proteome of the APP/PS1 transgenic mouse model. Employing a multi-faceted approach that included differential protein functional enrichment, cluster analysis, and protein-protein interaction (PPI) network analysis, we conducted a comprehensive comparative proteomic study between APP/PS1 transgenic mice and their wild-type C57BL/6 counterparts. RESULTS: Mass spectrometry identified a total of 4817 proteins in the samples, with 2762 proteins being quantifiable. Comparative analysis revealed 396 proteins with differential expression between the APP/PS1 and control groups. Notably, 35 proteins exhibited consistent temporal regulation trends in the hippocampus, with concomitant alterations in biological pathways and PPI networks. CONCLUSIONS: This study presents a comparative proteomic profile of transgenic (APP/PS1) and wild-type mice, highlighting the proteomic divergences. Furthermore, it charts the trajectory of proteomic changes in the AD mouse model across the developmental stages from 2 to 12 months, providing insights into the physiological and pathological implications of the disease-associated genetic mutations.

Animals↗