Specific Subpopulations Research Articles

Association between serum carotenoids levels and endometriosis risk: evidence from the National Health and Nutrition Examination Survey

BackgroundThe relationship between serum levels of carotenoids and endometriosis remains largely unknown. The aim of this study is to assess the association between serum levels of major carotenoids (α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin, and trans-lycopene) and the risk of endometriosis in US women.MethodsThe data were obtained from the 2001–2006 National Health and Nutrition Examination Surveys (NHANES), which included a total of 3,636 women aged 20 to 54. Serum levels of α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin, and trans-lycopene were measured using high performance liquid chromatography (HPLC) with photodiode array detection. Endometriosis was defined as self-report. Weighted multivariate logistic regression analyses were conducted to evaluate the associations of the serum levels of the major carotenoids with endometriosis risk. Additionally, restricted cubic spline (RCS) was employed to assess the possibility of nonlinear associations. Finally, subgroup analyses were utilized to estimate the influence of several covariates on the associations.ResultsWeighted multivariate logistic regression analyses showed that, after adjusting for all covariates taken into account, there was a significant association between serum lutein/zeaxanthin levels and reduced risk of endometriosis (Quartile 3 vs. Quartile 1: odds ratio [OR] = 0.62, 95% confidence interval [CI]: 0.42–0.90; Quartile 4 vs. Quartile 1: OR = 0.54, 95% CI: 0.36–0.81, P for trend = 0.001). However, no significant associations of serum levels of other carotenoids with endometriosis were found in multivariable-adjusted models that included all covariates. RCS analysis did not reveal any non-linear relationships. Subgroup analyses indicated that the inverse association between serum lutein/zeaxanthin levels and reduced endometriosis risk was significant only in individuals under 40 years of age, in both White and non-White populations, in smokers, and among those who had ever used oral contraceptives.ConclusionSerum lutein/zeaxanthin levels may offer protective effects against endometriosis in specific subpopulations. Further prospective research is necessary to validate these findings.

How I approach pharmacological thromboprophylaxis in children.

The incidence of venous thromboembolism in children continues to rise, with the most recent analysis from the Pediatric Hospital Information Systems database in the United States reporting a 200-fold increase in pediatric hospitalization-related venous thromboembolism diagnoses over the past two decades. In the past decade, several pediatric venous thromboembolism risk prediction models have been published, in some cases derived from multi-institutional data and multicenter randomized clinical trials of thromboembolism prevention in specific pediatric subpopulations have been conducted. Yet, apart from children hospitalized for COVID-19, guidelines for thromboprophylaxis (TP) in children that address several distinct at-risk subpopulations and settings for venous thromboembolism are presently lacking. It is becoming increasingly apparent that approaches to pharmacological TP for hospitalized children should be risk-stratified regarding a priori risks of both venous thromboembolism and clinically-relevant bleeding. In this manuscript, we present model cases of common inpatient clinical scenarios and review the evidence related to venous thromboembolism risk models and pharmacological TP clinical trials in children, describing a pragmatic approach to pharmacological TP for each scenario. We then conclude by describing our evidence-informed, subpopulation- and setting-specific approach to pharmacological TP for the clinical scenarios and reviewing critical knowledge gaps well-suited for future pediatric trials to inform thromboprophylaxis in children.

A systematic literature review of studies assessing first-line (1L) treatments in patients with advanced, grade 2/3 (G2/G3) gastroenteropancreatic neuroendocrine tumors (GEP-NETs).

663 Background: There is no universally accepted standard of care for newly diagnosed patients with G2/G3 advanced GEP-NETs. The phase 3 NETTER-2 trial showed that [ 177 Lu]Lu-DOTA-TATE plus long-acting octreotide demonstrated a significant improvement in progression-free survival (PFS) vs. high-dose long-acting octreotide alone in this patient population. We conducted a comprehensive review of the published literature to summarize the available evidence on other 1L treatments assessed in advanced, well-differentiated, G2/G3 GEP-NETs. Methods: Embase, MEDLINE, and CENTRAL were systematically searched (until Jan 2024) to identify relevant clinical trials and observational studies assessing 1L systemic therapies among adults with advanced, well-differentiated, G2/G3 GEP-NETs. Key conferences from the past three years were also reviewed. Comparators of interest included somatostatin analogues (SSAs; octreotide and lanreotide), targeted therapies (sunitinib and everolimus), and chemotherapies (CAPTEM, STZ+5-FU, FOLFIRI, and platinum-based therapies). Studies with mixed patient populations were also included if ≥80% of the study participants matched the eligibility criteria. The 2022 WHO classification system was applied in studies with available Ki-67 index data but lacking grade information. Results: A total of 31 studies met the review eligibility criteria (three randomized controlled trials, one open-label extension study, three single-arm trials, and 24 observational studies). None of the included studies entirely matched the NETTER-2 population but provided data only for specific sub-populations. The included studies were categorized either by overall GEP-NET (n=16) or pancreatic-NET only population (n=15) with no study exclusively assessing gastrointestinal-NET patients. Majority of the comparator studies assessed chemotherapies (n=14), followed by SSAs (n=10), targeted therapies (n=3), a combination of targeted therapy and chemotherapy (n=1), and mixed treatments (n=2). Heterogeneity was also observed in terms of patient characteristics (data reported only in 12 studies), sample size (<50 patients in 20 studies), and disease grade (G2/G3: nine studies, G2 only: 12 studies, and G3 only: 10 studies). Grading was derived using Ki-67 index in two studies. Majority of the studies reported PFS data (n=22), with nine studies providing data for both PFS and overall survival (OS); Kaplan-Meier curves for PFS and OS were reported for only 13 and four studies, respectively. Conclusions: This systematic literature review highlights a substantial evidence gap and an unmet need in 1L treatment of G2/G3 GEP-NETs. Robust quantitative comparison of NETTER-2 data with published evidence on other 1L treatments was largely restricted by low sample sizes and the aforementioned heterogeneity.

Nation-wide cross-sectional study of participation and predictors of enjoyment among Australian adult walking sport participants.

This study examined participation and predictors of walking sports enjoyment among Australian adult walking sport participants. An online cross-sectional survey assessed walking sport participation, enjoyment, and barriers and motives to participation. Physical activity behavior and motivations were also assessed. The sample comprised 294 walking sport participants (Mage=62.9±10.5years). Participants engaged in a variety of walking sports (e.g., football, netball, and basketball) and largely did so one occasion per week (for ≤3h). Our findings suggest that typically walking sport participants are female (60.1%), aged ≥60years (54.7%), in married/de facto relationships (73.4%), reside in higher socioeconomic status areas, and are sufficiently active (i.e., ≥150min of activity per week; 91.0%). The most endorsed barrier to walking sport participation was physical health (19.7%), while fun/enjoyment (90.5%) was the most endorsed motive. The regression analyses showed that gender (being female; β=0.17), older age (≥60years; β=-0.21), and intrinsic motivation for physical activity (β=0.23) were significant predictors of walking sport enjoyment. Ongoing efforts to ensure that walking sports are a positive experience for all are necessary. The provision of walking sport offerings that integrate elements (e.g., social connectedness) known to be of value to specific subpopulations may be important to fostering enjoyment.

The profiles of immunosuppressive microenvironment in the Lauren intestinal-type gastric adenocarcinoma

BackgroundGastric adenocarcinoma (GAC), particularly the Lauren intestinal-type GAC (IGAC), leads to significant mortality in China due to the limited effectiveness of current treatments. This study aims to investigate the mechanisms of immune suppression in IGAC to identify potential targets for enhancing immunotherapy outcomes.MethodsPerforming an extensive collection and re-analysis of single-cell RNA sequencing (scRNA-seq) of tumor tissues and the corresponding noncancerous mucosae from 15 Chinese patients diagnosed with IGAC, we identified cell subpopulations involved in immune suppression within the tumor microenvironment (TME). We further validated our findings using spatially resolved transcriptomics (SRT), immunofluorescence (IF), and flow cytometry (FCM) on tissues from IGAC patients.ResultsWe demonstrated that the TME of IGAC harbors CD8+ exhausted T cells (Texs) and various subtypes that mediate immunity. We identified specific subpopulations of Texs (HAVCR2+VCAM1+) and regulatory T cells (Tregs) (LAYN+TNFRSF4+) contributing to immune suppression. Furthermore, TNFRSF12A+ cancer-associated fibroblasts (CAFs), CTSB+ macrophages, and SOD2+ monocytes were found to be involved in maintaining the immunosuppressive milieu. SRT and IF assays confirmed the presence and colocalization of these cell types within the tumor tissues, highlighting their functional interactions. FCM assays indicated that the prevalence of HAVCR2+VCAM1+ Texs and LAYN+TNFRSF4+ Tregs in tumor tissues was positively associated with IGAC progression.ConclusionsDetailed profiles of immunosuppressive cell subpopulations in IGAC provide valuable insights into the complexity and heterogeneity of immunosuppression. These findings underscore the necessity for targeted strategies that disrupt specific immunosuppressive pathways, potentially enhancing the efficacy of immunotherapeutic interventions in IGAC.

Educational Disparities in Age-related Hearing Loss and Hearing Aid Use across Age, Gender, and European Region.

Affecting one in five adults in Europe, hearing loss (HL) is linked to adverse health outcomes, including dementia. We aim to investigate educational inequalities in hearing health in Europe and how these inequalities change with age, gender, and region. Utilizing 2004-2020 data from the Harmonised Survey of Health, Ageing, and Retirement in Europe (SHARE), a representative sample of Europeans aged 50 and above, we analyse: 1) age-standardized prevalence of HL and hearing aid (HA) use among eligible individuals; 2) educational inequalities therein using the Relative Index of Inequality (RII) across age, gender, and European regions. The prevalence of self-reported HL increases with age, is greater among men, and is consistently higher among those with lower levels of education. At age 50-64, particularly in Southern and Eastern Europe, low-educated women experience more than three times the risk of HL compared to highly educated women. These inequalities diminish as women age. Northern Europe is a front-runner in meeting HA needs. Southern and Eastern Europe lag behind, with less than two in ten individuals eligible for HAs utilizing them. Substantial variations in the educational gradient of hearing health across age, gender, and European regions underscore the importance of targeting specific subpopulations in efforts to mitigate health inequalities. Of particular concern is the regional discrepancy between the prevalence of HL and the use of HAs. The example of Northern Europe suggests that there is unused potential to improve healthy ageing in Europe through enhanced access to HAs.

Systematic review and quantitative meta-analysis of age-dependent human T-lymphocyte homeostasis

ObjectiveTo evaluate and quantitatively describe age-dependent homeostasis for a broad range of total T-cells and specific T-lymphocyte subpopulations in healthy human subjects.MethodsA systematic literature review was performed to identify and collect relevant quantitative information on T-lymphocyte counts in human blood and various organs. Both individual subject and grouped (aggregated) data on T-lymphocyte observations in absolute and relative values were digitized and curated; cell phenotypes, gating strategies for flow cytometry analyses, organs from which observations were obtained, subjects’ number and age were also systematically inventoried. Age-dependent homeostasis of each T-lymphocyte subpopulation was evaluated via a weighted average calculation within pre-specified age intervals, using a piece-wise equal-effect meta-analysis methodology.ResultsIn total, 124 studies comprising 11722 unique observations from healthy subjects encompassing 20 different T-lymphocyte subpopulations – total CD45+ and CD3+ lymphocytes, as well as specific CD4+ and CD8+ naïve, recent thymic emigrants, activated, effector and various subpopulations of memory T-lymphocytes (total-memory, central-memory, effector-memory, resident-memory) – were systematically collected and included in the final database for a comprehensive analysis. Blood counts of most T-lymphocyte subpopulations demonstrate a decline with age, with a pronounced decrease within the first 10 years of life. Conversely, memory T-lymphocytes display a tendency to increase in older age groups, particularly after ~50 years of age. Notably, an increase in T-lymphocyte numbers is observed in neonates and infants (0 – 1 year of age) towards less differentiated T-lymphocyte subpopulations, while an increase into more differentiated subpopulations emerges later (1 – 5 years of age).ConclusionA comprehensive systematic review and meta-analysis of T-lymphocyte age-dependent homeostasis in healthy humans was performed, to evaluate immune T-cell profiles as a function of age and to characterize generalized estimates of T-lymphocyte counts across age groups. Our study introduces a quantitative description of the fundamental parameters characterizing the maintenance and evolution of T-cell subsets with age, based on a comprehensive integration of available organ-specific and systems-level flow cytometry datasets. Overall, it provides the most up-to-date view of physiological T-cell dynamics and its variance and may be used as a consistent reference for gaining further mechanistic understanding of the human immune status in health and disease.

Integrative deep immune profiling of the elderly reveals systems-level signatures of aging, sex, smoking, and clinical traits.

Aging increases disease susceptibility and reduces vaccine responsiveness, highlighting the need to better understand the aging immune system and its clinical associations. Studying the human immune system, however, remains challenging due to its complexity and significant inter-individual variability. We conducted an immune profiling study of 550 elderly participants (≥60 years) and 100 young controls (20-40 years) from the RESIST Senior Individuals (SI) cohort. Extensive demographic, clinical, and laboratory data were collected. Multi-color spectral flow cytometry and 48-plex plasma cytokine assays were used for deep immune phenotyping. Data were analyzed using unsupervised clustering and multi-dataset integration approaches. We studied 97 innate and adaptive immune cell populations, revealing intricate age- and sex-related changes in the elderly immune system. Our large sample size allowed detection of even subtle changes in cytokines and immune cell clusters. Integrative analysis combining clinical, laboratory, and immunological data revealed systems-level aging signatures, including shifts in specific immune cell subpopulations and cytokine concentrations (e.g., HGF and CCL27). Additionally, we identified unique immune signatures associated with smoking, obesity, and diseases such as osteoporosis, heart failure, and gout. This study provides one of the most comprehensive immune profiles of elderly individuals, uncovering high-resolution immune changes associated with aging. Our findings highlight clinically relevant immune signatures that enhance our understanding of aging-related diseases and could guide future research into new treatments, offering translational insights into human health and aging. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy-EXC 2155-project number 390874280.

Single-cell RNA sequencing highlights the role of distinct natural killer subsets in sporadic amyotrophic lateral sclerosis

BackgroundNeuroinflammation plays a major role in amyotrophic lateral sclerosis (ALS), and cumulative evidence suggests that systemic inflammation and the infiltration of immune cells into the brain contribute to this process. However, no study has investigated the role of peripheral blood immune cells in ALS pathophysiology using single-cell RNA sequencing (scRNAseq).MethodsWe aimed to characterize immune cells from blood and identify ALS-related immune alterations at single-cell resolution. For this purpose, peripheral blood mononuclear cells (PBMC) were isolated from 14 ALS patients and 14 cognitively unimpaired healthy individuals (HC), matched by age and gender, and cryopreserved until library preparation and scRNAseq. We analyzed differences in the proportions of PBMC, gene expression, and cell-cell communication patterns between ALS patients and HC, as well as their association with plasma neurofilament light (NfL) concentrations, a surrogate biomarker for neurodegeneration. Flow cytometry was used to validate alterations in cell type proportions.ResultsWe identified the expansion of CD56dim natural killer (NK) cells in ALS (fold change = 2; adj. p-value = 0.0051), mainly driven by a specific subpopulation, NK_2 cells (fold change = 3.12; adj. p-value = 0.0001), which represent a mature and cytotoxic CD56dim NK subset. Our results revealed extensive gene expression alterations in NK_2 cells, pointing towards the activation of immune response (adj. p-value = 9.2 × 10− 11) and the regulation of lymphocyte proliferation (adj. p-value = 6.46 × 10− 6). We also identified gene expression changes in other immune cells, such as classical monocytes, and distinct CD8 + effector memory T cells which suggested enhanced antigen presentation via major histocompatibility class-II (adj. p-value = 1.23 × 10− 8) in ALS. The inference of cell-cell communication patterns demonstrated that the interaction between HLA-E and CD94:NKG2C from different lymphocytes to NK_2 cells is unique to ALS blood compared to HC. Finally, regression analysis revealed that the proportion of CD56bright NK cells along with the ALSFRS-r, disease duration, and gender, explained up to 76.4% of the variance in plasma NfL levels.ConclusionOur results reveal a signature of relevant changes occurring in peripheral blood immune cells in ALS and underscore alterations in the proportion, gene expression, and signaling patterns of a cytotoxic and terminally differentiated CD56dim NK subpopulation (NK_2), as well as a possible role of CD56bright NK cells in neurodegeneration.

A Primer on Proteomic Characterization of Intercellular Communication in a Virus Microenvironment.

Intercellular communication is fundamental to multicellular life and a core determinant of outcomes during viral infection, where the common goals of virus and host for persistence and replication are generally at odds. Hosts rely on encoded innate and adaptive immune responses to detect and clear viral pathogens, while viruses can exploit or disrupt these pathways and other intercellular communication processes to enhance their spread and promote pathogenesis. While virus-induced signaling can result in systemic changes to the host, striking alterations are observed within the cellular microenvironment directly surrounding a site of infection, termed the virus microenvironment (VME). Mechanisms employed by viruses to condition their VMEs are emerging and are critical for understanding the biology and pathologies of viral infections. Recent advances in experimental approaches, including proteomic methods, have enabled study of the VME in unprecedented detail. In this review article, we provide a primer on proteomic approaches used to study how viral infections alter intercellular communication, highlighting the ways in which these approaches have been implemented and the exciting biology they have uncovered. First, we consider the different molecules secreted by an infected cell, including proteins, either soluble or contained within extracellular vesicles, and metabolites. We further discuss the modalities of interactions facilitated by alteration at the cell surface of infected cells, including immunopeptide presentation and interactions with the extracellular matrix. Finally, we review spatial profiling approaches that have allowed distinguishing how specific subpopulations of cells within a VME respond to infection and alter their protein composition, discussing valuable insights these methods have offered.

Single-cell atlas reveals multi-faced responses of losartan on tubular mitochondria in diabetic kidney disease

Background and ObjectiveMitochondria are crucial to the function of renal tubular cells, and their dynamic perturbation in many aspects is an important mechanism of diabetic kidney disease (DKD). Single-nucleus RNA sequencing (snRNA-seq) technology is a high-throughput sequencing analysis technique for RNA at the level of a single cell nucleus. Here, our DKD mouse kidney single-cell RNA sequencing conveys a more comprehensive mitochondrial profile, which helps us further understand the therapeutic response of this unique organelle family to drugs.MethodsAfter high fat diet (HFD), mice were intraperitoneally injected with streptozotocin (STZ) to induce DKD, and then divided into three subsets: CON (healthy) subset, DKD (vehicle) subset, and LST (losartan; 25 mg/kg/day) subset. Divide HK-2 cell into LG (low glucose; 5 mM) and HG (high glucose; 30 mM) and HG + LST (losartan; 1 µ M) subsets. snRNA-seq was performed on the renal tissues of LST and DKD subset mice. To reveal the effects of losartan on gene function and pathway changes in renal tubular mitochondria, Gene Ontology (GO) enrichment analysis and GSEA/GSVA scoring were performed to analyze the specific response of proximal tubular (PT) cell mitochondria to losartan treatment, including key events in mitochondrial homeostasis such as mitochondrial morphology, dynamics, mitophagy, autophagic flux, mitochondrial respiratory chain, apoptosis, and ROS generation. Preliminary validation through in vitro and in vivo experiments, including observation of changes in mitochondrial morphology and dynamics using probes such as Mitotracker Red, and evaluation of the effect of losartan on key events of mitochondrial homeostasis perturbation using electron microscopy, laser confocal microscopy, immunofluorescence, and Western blotting. Detection of autophagic flux in cells by transfecting Ad-mCherry-GFP-LC3B dual fluorescence labeled adenovirus. Various fluorescent probes and energy detector are used to detect mitochondrial apoptosis, ROS, and respiration of mitochondrion.ResultsThrough the single-cell atlas of DKD mouse kidneys, it was found that losartan treatment significantly increased the percentage of PT cells. Gene Ontology (GO) enrichment analysis of differentially expressed genes showed enrichment of autophagy of mitochondrion pathway. Further GSEA analysis and GSVA scoring revealed that mitophagy and other key mitochondrial perturbation events, such as ROS production, apoptosis, membrane potential, adenosine triphosphate (ATP) synthesis, and mitochondrial dynamics, were involved in the protective mechanism of losartan on PT cells, thereby improving mitochondrial homeostasis. Consistent results were also obtained in mice and cellular experiments. In addition, we highlighted a specific renal tubular subpopulation with mitophagy phenotype found in single-cell data, and preliminarily validated it with co-localization and increased expression of Pink1 and Gclc in kidney specimens of DKD patients treated with losartan.ConclusionsOur research suggests that scRNA-seq can reflect the multifaceted mitochondrial landscape of DKD renal tubular cells after drug treatment, and these findings may provide new targets for DKD therapy at the organelle level.

The Future of HIV: Challenges in meeting the 2030 Ending the HIV Epidemic in the U.S. (EHE) reduction goal.

To predict the burden of HIV in the United States (US) nationally and by region, transmission type, and race/ethnicity through 2030. Using publicly available data from the CDC NCHHSTP AtlasPlus dashboard, we generated 11-year prospective forecasts of incident HIV diagnoses nationally and by region (South, non-South), race/ethnicity (White, Hispanic/Latino, Black/African American), and transmission type (Injection-Drug Use, Male-to-Male Sexual Contact (MMSC), and Heterosexual Contact (HSC)). We employed weighted (W) and unweighted (UW) n-sub-epidemic ensemble models, calibrated using 12 years of historical data (2008-2019), and forecasted trends for 2020-2030. We compared results to identify persistent, concerning trends across models. We projected substantial decreases in incident HIV diagnoses nationally (W: 27.9%, UW: 21.9%), and in the South (W:18.0%, UW: 9.2%) and non-South (W: 21.2%, UW: 19.5%) from 2019 to 2030. However, concerning nondecreasing trends were observed nationally in key sub-populations during this period: Hispanic/Latino persons (W: 1.4%, UW: 2.6%), Hispanic/Latino MMSC (W: 9.0%, UW: 9.9%), people who inject drugs (PWID) (W: 25.6%, UW: 9.2%), and White PWID (W: 3.5%, UW: 44.9%). The rising trends among Hispanic/Latino MMSC and overall PWID were consistent across the South and non-South regions. Although the forecasted national-level decrease in the number of incident HIV diagnoses is encouraging, the US is unlikely to achieve the Ending the HIV Epidemic in the US goal of a 90% reduction in HIV incidence by 2030. Additionally, the observed increases among specific subpopulations highlight the importance of a targeted and equitable approach to effectively combat HIV in the US.

Relationship between influenza-related experience and current vaccination outcome

BackgroundThis study investigated how a person’s influenza-related experience, together with demographic, socioeconomic, and health-related factors, was associated with their current vaccination decisions.MethodsThe analysis used ten panels of the Medical Expenditure Panel Survey (MEPS) from 2006 to 2016. Linear and logistic probability models were estimated to predict influenza vaccination using a person’s vaccination status in the previous year and history of influenza infection, adjusting for demographics, socioeconomic variables, general health status, and healthcare access. The models used two-way and three-way interactions with race/ethnicity, income, education, health status, and elderly status to examine changing relationships of flu-related experience across these variables.ResultsPrevious vaccination was the most important predictor, with an increase of 63.0–71.8% probability of vaccination in the next year. Infection history could either increase or decrease the impact of past vaccination depending on race/ethnicity, income, education level, health status, and age. There were significant disparities across demographic, socioeconomic, and health-related variables.ConclusionVaccination promotion efforts could focus on those who have not been vaccinated in the past and on specific sub-populations, such as people who are Hispanic, people with lower education levels, the population aged 65 and above, and families with low-income levels. Although past infection is a predictor for some population groups, its magnitude is small and is often not a significant determinant.

Spatially resolved transcriptomics reveals gene expression characteristics in uveal melanoma

PurposeUveal melanoma (UM) is the most common intraocular malignancy in adults. Previous studies have examined the intra-tumoral heterogeneity. However, the spatial distribution of tumor cells within the tumor microenvironment and its relationship with tumor progression still remains largely unclear. Our study aimed to analyze the correlation between cell distribution patterns and the prognosis of UM.MethodsIn this paper, we performed spatial transcriptomics (ST) sequencing on two UM samples to describe the different cellular distribution patterns. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) functional enrichment analysis, and protein–protein interaction (PPI) network were performed to define the biological function of each cluster. Differentially expressed genes (DEGs) and survival analysis based on datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database further confirmed the correlation between cellular distribution and clinical prognosis.ResultsWe found two different patterns of tumor cell distribution. The focal tumor cells have a distinct ribosome synthesis and rRNA pathway. In contrast, the subpopulation tented to distribute diffusely was related to fatty acids metabolism profile, presumably supporting tumor growth by providing energy. The scattered tumor cell cluster was associated with malignant biological behaviors and was involved in extensive cellular interactions, including COLLAGEN. Moreover, pseudo-time analysis showed that migration started from the basal region through cell differentiation. According to the TCGA and GEO database, genes expressed characteristically in the scattered tumor cell cluster were related to poor prognosis.ConclusionsOur study drew the ST maps for UM for the first time. These findings revealed the distribution patterns of tumor cells associated with different biological functions and pointed towards specific tumor subpopulations with higher invasiveness as potential therapeutic targets. Together, our study displayed an overview of UM transcriptome and explored the intra-tumoral heterogeneity of UM at the spatial level.

Absolute number of three populations of interneurons and all GABAergic synapses in the human hippocampus.

The human hippocampus, essential for learning and memory, is implicated in numerous neurological and psychiatric disorders, each linked to specific neuronal subpopulations. Advancing our understanding of hippocampal function requires computational models grounded in precise quantitative neuronal data. While extensive data exist on the neuronal composition and synaptic architecture of the rodent hippocampus, analogous quantitative data for the human hippocampus remain very limited. Given the critical role of local GABAergic interneurons in modulating hippocampal functions, we employed unbiased stereological techniques to estimate the density and total number of three major GABAergic cell types in the male and female human hippocampus: parvalbumin (PV)-expressing, somatostatin (SOM)-positive, and calretinin (CR)-positive interneurons. Our findings reveal an estimated 49,400 PV-positive, 141,500 SOM-positive, and 250,600 CR-positive interneurons per hippocampal hemisphere. Notably, CR-positive interneurons, which are primarily interneuron-selective in rodents, were present in humans at a higher proportion. Additionally, using 3-dimensional electron microscopy, we estimated approximately 25 billion GABAergic synapses per hippocampal hemisphere, with PV-positive boutons comprising around 3.5 billion synapses, or 14% of the total GABAergic synapses. These findings contribute crucial quantitative insights for modeling human hippocampal circuits and understanding its complex regulatory dynamics.Significance Statement Understanding the operating principles of cortical networks is a major goal in neuroscience, requiring a detailed description of cortical neurons, including their proportions, densities, and, most critically, their absolute numbers. Such precise quantification is essential for constructing predictive computational models of neuronal circuits. In this study, we present the density and total number of three major, non-overlapping GABAergic cell groups across each layer of the human hippocampus. Additionally, we quantify the total number of all GABAergic boutons and synapses, as well as separately quantifying those originating from parvalbumin (PV)-positive cells within each of the 15 hippocampal layers. This dataset provides a foundational framework for accurately modeling hippocampal inhibition at the cellular level.

Effect of perioperative methylprednisolone administration on postoperative pleural effusion in older patients with non-small cell lung cancer

BackgroundIt remains uncertain whether the utilization of methylprednisolone during surgery effectively mitigates the occurrence of adverse outcomes. To examine the association between perioperative methylprednisolone administration and postoperative pleural effusion and pneumonia in older patients with non-small cell lung cancer.MethodsA retrospective cohort study included non-small cell lung cancer patients aged 65 years or older undergoing thoracic surgery between January 2012 and December 2019 in China. Primary outcome was pleural effusion. Secondary outcome was postoperative pneumonia. Multivariate logistic regression models assessed the independent effects of various factors on pleural effusion and pneumonia. Propensity score matching (PSM) method reduced selection bias enhancing causal inference validity. Subgroup analyses identified potential effect heterogeneity in specific sub-populations.ResultsA total of 1951 older patients with non-small cell lung cancer were included. The incidence of postoperative pleural effusion in the methylprednisolone group before and after PSM matching was significantly lower than that in the control group (before PSM: 9.4% vs. 19.2, P < 0.001; after PSM: 9.8% vs. 18.2%, P < 0.001). There was no statistically significant difference in the incidence of postoperative pneumonia between the two groups before and after matching. After adjusting all the variables and PSM, we found that intraoperative methylprednisolone was associated with a reduction in postoperative pleural effusion in older patients with non-small cell lung cancer [odds ratio (OR) = 0.48, P < 0.001; OR = 0.47, P < 0.001]. Perioperative methylprednisolone showed consistent protective effects in all sub-populations of gender, age, surgery duration, and smoking (P all < 0.05). Logistic regression models and PSM found that methylprednisolone was not associated with postoperative pneumonia and long-term survival in older patients with non-small cell lung cancer.ConclusionPerioperative methylprednisolone was associated with reducing the occurrence of postoperative pleural effusions in older patients with non-small volume lung cancer, but it was not associated with pneumonia or long-term survival outcomes.

Identification of a novel disulfidptosis-related gene signature in osteoarthritis using bioinformatics analysis and experimental validation

Osteoarthritis (OA) is a degenerative bone disease characterized by the destruction of joint cartilage and synovial inflammation, involving intricate immune regulation processes. Disulfidptosis, a novel form of programmed cell death, has recently been identified; however, the effects and roles of disulfidptosis-related genes (DR-DEGs) in OA remain unclear. We obtained six OA datasets from the GEO database, using four as training sets and two as validation sets. Differential expression analysis was employed to identify DR-DEGs, and unique molecular subtypes of OA were constructed based on these DR-DEGs. Subsequently, the immune microenvironment of OA patients was comprehensively analyzed using the “CIBERSORT” algorithm for immune infiltration. Various machine learning algorithms were utilized to screen characteristic DR-DEGs, and nomogram models and ROC curves were built based on these genes. The scRNA dataset (GSE169454) was used to classify chondrocytes in OA samples into distinct cell types, further exploring the gene distribution and correlation of characteristic DR-DEGs with specific cell subpopulations. Moreover, the expression levels of four characteristic DR-DEGs were validated through OA cell models and rat models. In our study, we identified 10 DR-DEGs with significant differences in expression within OA samples. Based on these DR-DEGs, two distinct molecular subtypes were recognized (cluster 1 and 2). ZNF484 and NDUFS1 were found to be significantly overexpressed in subtype 1, while the infiltration abundance of activated mast cells was markedly elevated in subtype 2. Moreover, significant differences were observed in the infiltration proportions of 11 immune cell types between OA and control samples, with 9 DR-DEGs demonstrating substantial correlations with immune cell infiltration levels. Further analysis of the scRNA dataset revealed that SLC3A2 and NDUFC1 were predominantly expressed in the preHTC subpopulation. All 10 DR-DEGs exhibited notably higher expression in the EC subpopulation across various cell types. The proportion of EC subgroups with high SLC3A2 expression increased, mainly enriching pathways related to inflammation, such as the IL-17 signaling pathway and TGF-beta signaling pathway. Using machine learning, we identified four characteristic DR-DEGs, which, in combination with the nomogram and ROC models, demonstrated promising performance in the diagnosis of OA. Additionally, in vivo validation confirmed a significant elevation of PPM1F expression in OA models. This study identified DR-DEGs as potential biomarkers for the diagnosis and classification of OA and provided a preliminary understanding of their role in the immune microenvironment. However, further experimental and clinical studies are required to validate their diagnostic value and therapeutic potential.

Organ-on-a-chip: Quo vademus? Applications and regulatory status.

Organ-on-a-chip systems, also referred to as microphysiological systems (MPS), represent an advance in bioengineering microsystems designed to mimic key aspects of human organ physiology and function. Drawing inspiration from the intricate and hierarchical architecture of the human body, these innovative platforms have emerged as invaluable in vitro tools with wide-ranging applications in drug discovery and development, as well as in enhancing our understanding of disease physiology. The facility to replicate human tissues within physiologically relevant three-dimensional multicellular environments empowers organ-on-a-chip systems with versatility throughout different stages of the drug development process. Moreover, these systems can be tailored to mimic specific disease states, facilitating the investigation of disease progression, drug responses, and potential therapeutic interventions. In particular, they can demonstrate, in early-phase pre-clinical studies, the safety and toxicity profiles of potential therapeutic compounds. Furthermore, they play a pivotal role in the in vitro evaluation of drug efficacy and the modeling of human diseases. One of the most promising prospects of organ-on-a-chip technology is to simulate the pathophysiology of specific subpopulations and even individual patients, thereby being used in personalized medicine. By mimicking the physiological responses of diverse patient groups, these systems hold the promise of revolutionizing therapeutic strategies, guiding them towards tailored intervention to the unique needs of each patient. This review presents the development status and evolution of microfluidic platforms that have facilitated the transition from cells to organs recreated on chips and some of the opportunities and applications offered by organ-on-a-chip technology. Additionally, the current potential and future perspectives of these microphysiological systems and the challenges this technology still faces are discussed.

Heterogeneity of late endosome/lysosomes shown by multiplexed DNA-PAINT imaging.

Late endosomes/lysosomes (LELs) are crucial for numerous physiological processes and their dysfunction is linked to many diseases. Proteomic analyses have identified hundreds of LEL proteins; however, whether these proteins are uniformly present on each LEL, or if there are cell-type-dependent LEL subpopulations with unique protein compositions is unclear. We employed quantitative, multiplexed DNA-PAINT super-resolution imaging to examine the distribution of seven key LEL proteins (LAMP1, LAMP2, CD63, Cathepsin D, TMEM192, NPC1, and LAMTOR4). While LAMP1, LAMP2, and Cathepsin D were abundant across LELs, marking a common population, most analyzed proteins were associated with specific LEL subpopulations. Our multiplexed imaging approach identified up to eight different LEL subpopulations based on their unique membrane protein composition. Additionally, our analysis of the spatial relationships between these subpopulations and mitochondria revealed a cell-type-specific tendency for NPC1-positive LELs to be closely positioned to mitochondria. Our approach will be broadly applicable to determining organelle heterogeneity with single organelle resolution in many biological contexts.

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning

Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. This study leverages single-cell sequencing and machine learning to unravel the complex cellular and molecular mechanisms underlying pulmonary fibrosis, aiming to improve diagnostic accuracy and uncover potential therapeutic targets. By analyzing lung tissue samples from pulmonary fibrosis patients, we identified distinct cellular phenotypes and gene expression patterns that contribute to the fibrotic process. Notably, our findings revealed a significant enrichment of activated B cells, CD4 T cells, macrophages, and specific fibroblast subpopulations in fibrotic versus normal lung tissue. Machine learning analysis further refined these observations, resulting in the development of a diagnostic model with enhanced precision, based on key gene signatures including TMEM52B, PHACTR1, and BLVRB. Comparative analysis with existing diagnostic models demonstrates the superior accuracy and specificity of our approach. Through In vitro experiments involving the knockdown of PHACTR1, TMEM52B, and BLVRB genes demonstrated that these genes play crucial roles in inhibiting the expression of α-SMA and collagen in lung fibroblasts induced by TGF-β. Additionally, knockout of the PHACTR1 gene reduced inflammation and collagen deposition in a bleomycin-induced mouse model of pulmonary fibrosis in vivo. Additionally, our study highlights novel gene signatures and immune cell profiles associated with pulmonary fibrosis, offering insights into potential therapeutic targets. This research underscores the importance of integrating advanced technologies like single-cell sequencing and machine learning to deepen our understanding of pulmonary fibrosis and pave the way for personalized therapeutic strategies.