👤 Ruyue Ma

Primary resistance to chimeric antigen receptor (CAR) T-cell therapies has limited their widespread application. Our prior genome-wide CRISPR/Cas9 screening revealed that the loss of CD58, a crucial intrinsic resistance factor in tumors, resulted in insufficient immune synapse formation and impaired CAR T-cell activation and cytotoxicity. However, the specific signaling pathway and transcriptional changes associated with CAR T-cell dysfunction have not been addressed. Here, we revealed that AP-1-mediated activation was attenuated in CAR T cells impaired by tumor CD58 loss, driving a decrease in mitochondrial biogenesis, metabolic kinetic impairment, mitochondrial membrane potential loss and ROS accumulation. Moreover, this AP-1 attenuation triggered death receptor-independent apoptosis through the intrinsic mitochondrial pathway. In seeking therapeutic strategies, we pharmacologically and genetically blocked three distinct inhibitory phosphatases positioned upstream of AP-1 signaling. Multifaceted validation has demonstrated that dual specificity phosphatase 6 (DUSP6) blockade is an effective approach to supplement AP-1 signaling while notably reducing CAR T-apoptosis and enhancing mitochondrial fitness, proliferation and long-term cytotoxicity. The transcriptomic profiles of DUSP6-ablated CAR T cells revealed markedly upregulated T-cell activation signatures and enriched metabolic pathways. Clinically, bulk and single-cell RNA-seq analyses revealed that DUSP6 was downregulated in patients who responded to T-cell-based immunotherapy, implying its relevance to patient outcomes. Our findings repositioned CD58 not merely as an immune synapse component but also a metabolic checkpoint in CAR T-cell biology, the loss of which triggers AP-1-dependent mitochondrial derangement and creates a permissive landscape for intrinsic apoptosis, which can be ameliorated by ablation of the inhibitory phosphatase DUSP6. Crucially, DUSP6 ablation represents a promising engineering target to potentiate CAR T-cell efficacy in broader applications. Show less

Long-term antigen-specific data in PMN among Chinese populations remain limited. This study evaluated six target antigens and their clinical significance during extended follow-up. We retrospectively analyzed 132 treatment-naïve PMN patients diagnosed by biopsy (2010-2018) and followed for a median of 62.9 months. Renal tissue expression of PLA2R, THSD7A, NELL-1, PCDH7, EXT1, and EXT2 was assessed by immunohistochemistry, and serum anti-PLA2R antibodies were measured by ELISA. Associations between antigen profiles and 5-year outcomes (remission, renal survival, malignancy) were evaluated. PLA2R was the predominant antigen (84.1%), followed by THSD7A (5.3%) and NELL-1 (0.76%); no PCDH7, EXT1, or EXT2 positivity was detected. PLA2R-negative patients were more often female (71.4% vs. 36.0%, This >5-year Chinese PMN cohort provides the first comprehensive analysis of six target antigens. PLA2R remains predominant, while PLA2R-negative patients distinct immunopathologic features yet favorable long-term outcomes. A population-specific anti-PLA2R cutoff showed good diagnostic performance for predicting tissue antigen deposition. Rare antigens were infrequent and their malignancy associations require cautious interpretation. These findings provide long-term antigen-specific data supporting antigen-guided, population-adapted precision management of PMN. Show less

Porcine enteric coronaviruses, including porcine deltacoronavirus (PDCoV), porcine epidemic diarrhea virus (PEDV), swine acute diarrhea syndrome coronavirus (SADS-CoV), and transmissible gastroenteritis coronavirus (TGEV), can cause acute diarrhea, vomiting, dehydration, and high mortality in suckling piglets. Recent studies revealing human PDCoV infections and the potential of SADS-CoV to penetrate human cell lines have heightened apprehensions about the zoonotic transmission risks of these viruses. While heparan sulfate (HS) serves as a receptor in PDCoV binding, the key host genes involved in HS biogenesis and the specific molecular mechanisms underlying this process have not been fully examined. Enzymes involved in HS biosynthesis, including SLC35B2, EXT1, and NDST1, were identified as critical host factors via the use of CRISPR-Cas9 knockout cells. Moreover, inhibition assays using heparin sodium, a competitive HS mimic, demonstrated dose-dependent reductions in PDCoV infection Show less

Perioperative neurocognitive disorder (PND) is one of the most prevalent neurological complications in elderly surgical patients. Dysregulated lipid metabolism is a hallmark of aging and is strongly associated with cognitive dysfunction. This study aimed to investigate whether ω-6 polyunsaturated fatty acid (PUFA) metabolism contribute to PND and examined whether fatty acid desaturase 1 (FADS1) represents a key regulatory link between fatty acid metabolism and PND in aged mice. An anesthesia/surgery-induced cognitive dysfunction model was established Anesthesia/surgery significantly upregulated hippocampal FADS1 expression (1.91-fold [0.37] vs. 1.00-fold [0.43]; These findings highlight anesthesia/surgery could disrupt ω-6 PUFA metabolism, notably activating the PGD The online version contains supplementary material available at 10.1186/s12974-025-03678-y. Show less

Hepatocellular carcinoma (HCC) is a major malignancy with rising global incidence and mortality. Clinical treatment is limited by molecular heterogeneity and drug resistance. In recent years, endocrine-disrupting chemicals (EDCs) have attracted attention as emerging risk factors, but systematic pathogenic evidence for their roles in HCC initiation and progression remains insufficient. First, we predicted potential targets of EDCs using SwissTargetPrediction, STITCH, and ChEMBL, and intersected them with differentially expressed genes and key module genes from WGCNA in the GEO database to screen candidate key genes. Second, based on these candidates, we constructed diagnostic models using 14 machine-learning algorithms and evaluated feature importance via the SHAP framework to identify key biomarkers and their functional contributions. Molecular docking and molecular dynamics simulations were used to validate interaction mechanisms between EDCs and key target proteins. We then built a multivariable Cox proportional hazards model in the TCGA-LIHC cohort and performed stratified survival analysis, somatic mutation profiling, and immune evasion characterization. Subsequently, we evaluated the tumor immune microenvironment using CIBERSORT and ssGSEA, and integrated single-cell transcriptomic data to resolve cell-subtype heterogeneity, target expression distributions, and cell-cell communication. Meanwhile, we integrated the GDSC drug-sensitivity database to evaluate associations between risk scores and drug response, and conducted pan-cancer analyses to examine cross-cancer applicability. We identified 18 genes jointly associated with EDCs and HCC, significantly enriched in AMPK, p53, and FoxO signaling pathways and cell cycle-related pathways. Among models built with 14 machine-learning algorithms, CatBoost showed the best discriminative performance and identified CCNB2 and AKR1C3 as core driver genes. Docking and dynamics simulations indicated strong binding affinities and stable binding conformations between EDCs and target proteins including CCNB1 (-8.9 kcal/mol), AKR1C3 (-8.4 kcal/mol), and FADS1 (-8.5 kcal/mol). A multivariable Cox risk model based on nine key genes served as an independent prognostic predictor for HCC (HR = 1.746, 95% CI: 1.477-2.064, P < 0.001). The nomogram achieved AUCs of 0.836, 0.810, and 0.788 at 1, 3, and 5 years, respectively, indicating good predictive performance. The high-risk group was significantly associated with high tumor mutational burden (TMB), TP53 mutations, and low immune evasion scores. Regarding the tumor immune microenvironment, CIBERSORT and ssGSEA analyses showed marked enrichment of Tregs and M0 macrophages, while most effector immune cells and functions were suppressed. Single-cell transcriptomics further showed enrichment of endothelial cells, fibroblasts, hepatocytes, and macrophages in HCC tissues, with notable reductions in T cells, B cells, NK cells, and neutrophils, indicating an immunosuppressive microenvironment with stromal remodeling. Cell-cell communication analysis indicated that the MIF-CD74 receptor axis is central in immune-cell interactions. Drug-sensitivity analysis suggested that the high-risk group was more sensitive to GDC0810, BPD-00008900, and Fulvestrant, indicating potential beneficiary populations. Pan-cancer analysis showed that the risk model also had diagnostic and prognostic value in LUAD, KIRP, KIRC, and KICH, suggesting cross-cancer generalizability. This study systematically reveals that EDCs promote HCC initiation and progression by perturbing cell cycle, metabolic, and immune homeostasis through multi-target, multi-pathway mechanisms. The nine-gene risk model demonstrates superior performance in HCC diagnosis and prognosis and shows potential clinical translational value in drug-sensitivity prediction and pan-cancer analyses. This work provides a new perspective at the intersection of environmental toxicology and precision oncology and informs individualized therapeutic strategies. Show less

Approximately 40% of patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-), advanced breast cancer (ABC) have PIK3CA alterations, which contributes to endocrine therapy resistance. Alpelisib, an α-selective phosphatidylinositol 3-kinase inhibitor and degrader, given in combination with fulvestrant, is approved for the treatment of PIK3CA-mutated, HR+, HER2- ABC, based on the SOLAR-1 trial. Aside from PIK3CA, other gene alterations are associated with poor prognosis and limited response to treatment in this patient population. In this retrospective analysis, we performed tissue-based next-generation sequencing of 398 patients (237 PIK3CA-altered, 161 PIK3CA-wild type) from SOLAR-1. Progression-free survival (PFS) correlative analysis was performed in the PIK3CA-altered cohort. PIK3CA-altered and PIK3CA-wild type tumors had distinct genomic profiles. In the PIK3CA-altered cohort, patients who received alpelisib plus fulvestrant had a median PFS (mPFS) of 11.01 months versus 5.55 months for those receiving placebo plus fulvestrant (P=0.0004). Patients in the lowest tumor mutational burden quartile as well as those with FGFR1 or FGFR2 alterations derived greater PFS benefit from alpelisib plus fulvestrant versus placebo plus fulvestrant (18.5 versus 3.22 months; HR 0.38; 95% CI 0.21-0.68. FGFR1 12.71 versus 3.75 months; HR 0.38; 95% CI 0.17-0.81; P=0.32. FGFR2: 9.63 versus 2.78 months; HR 0.31; 95% CI 0.1-0.94; P=0.29); patients with MYC or RAD21 alterations derived limited PFS benefit. Cox and multi-task machine learning models identified lower Eastern Cooperative Oncology Group performance status, prior cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) treatment, and PTEN or TP53 alterations among the most deleterious factors for PFS in the PIK3CA-altered cohort. Alpelisib plus fulvestrant provides clinical benefit for patients with PIK3CA-altered, HR+, HER2- ABC across a range of concomitant alterations, including those previously implicated in endocrine therapy or CDK4/6i resistance. Machine learning models identified factors including gene mutations that influenced PFS. Show less

This study aims to investigate the effect of exosomes derived from olfactory mucosa mesenchymal stem cells (OM-MSCs-Exo) on microglial polarization and its potential therapeutic role in Alzheimer's disease (AD). OM-MSCs-Exo were isolated and purified from the mice olfactory mucosa, followed by phenotypic characterization. Proteins transferred by OM-MSCs-Exo were screened using proteomic analysis. The AD model was established in microglial cells and mice with Aβ Show less

Fibroblast growth factor receptor 2 (FGFR2) has gained recognition as a compelling therapeutic target in oncology. We present LHQ766, a novel orally bioavailable FGFR2 inhibitor demonstrating exceptional potency and selectivity, through optimization of our previously reported FGFR2 inhibitor 7. The structures and purity of all target compounds were confirmed by Show less

This study aims to demonstrate the effect of toadflax (bufalin) on erlotinib resistance in nonsmall cell lung cancer (NSCLC) by inhibiting the fibroblast growth factor receptor (FGFR). The microfluidic mobility transferase and caliper mobility-shift assays were employed to detect the FGFR inhibition by bufalin and the binding reversibility. Further, the inhibitory effects of bufalin were determined in HCC827 and HCC827/ER cells in vitro , investigating relative FGFR overexpression by quantitative reverse transcriptase-PCR (RT-qPCR) and FGFR downstream proteins, that is, FGFR substrate 2 (FRS2), extracellular signal-regulated kinase (ERK), and S6 by western blot analysis. Finally, HCC827/ER-inoculated xenograft tumors were constructed to observe the effects of bufalin and bufalin + erlotinib intervention on tumor growth. Bufalin inhibited FGFR by reversibly binding to FGFR1. In addition, the western blot analysis indicated a significant reduction in the expression levels of FGFR, FRS2, ERK, and S6 proteins in HCC827 and HCC827/ER cells, increasing the expression levels of apoptotic caspase-3 and poly-(ADP-ribose) polymerase proteins. Bufalin + erlotinib combination significantly inhibited the apoptosis of HCC827/ER cells and subsequent tumor growth in vivo . In addition, FGFR overexpression significantly reversed the sensitivity of bufalin to HCC827/ER cells, promoting the value-addition of HCC827/ER cells. Further, bufalin + erlotinib significantly reduced the growth of erlotinib-resistant HCC827/ER tumors, induced apoptosis, and inhibited the expression of FGFR and p-ERK proteins. These findings indicated that bufalin could reverse the erlotinib resistance in NSCLC by inhibiting the FGFR expression. Show less

The signaling pathways of inflammatory pain are widely explored, but practical clinical approaches to ameliorate pain remain inadequate. Quantitative PCR (qPCR) and ELISA methods were applied to measure the concentration of interleukin (IL)-27 in the inflammatory pain mouse model. Flow cytometry was conducted to identify the source of IL-27. Bone marrow-derived macrophages were stimulated by IL-27, IL-4, lipopolysaccharide, and/or interferon-gamma, followed by qPCR to assess pro-inflammatory and pro-resolving markers' dynamic expression. Then, the molecule profiling of IL-27-primed macrophages was determined using transcriptomic and proteomic sequencing. The Agilent Seahorse XF analyzer calculated energy metabolism indicators. The adoptive cell transfer method was used to verify that forkhead box class O3 (FoxO3) mediates alternatively activated macrophage differentiation induced by IL-27-Ucp2, contributing to alleviating pain sensation in mice. IL-27 is highly expressed centrally and peripherally in rodent pain models. Selective downregulation of IL-27 intensifies pain sensitivity in mice. In macrophages, IL-27 promotes the secretion of anti-inflammatory molecules, such as Arginase-1. Further, transcriptome, energy metabolic examination, and proteome analyses identified that IL-27 restructures the metabolism in macrophages, which is mediated by uncoupling protein 2 (Ucp2) and subsequently activates transcription factor FoxO3. Conditional knockdown of FoxO3 (si-FoxO3) in macrophages refrains the production of anti-inflammatory genes These findings reveal that the IL-27-Ucp2-FoxO3 axis regulates macrophage plasticity distinct from the canonical IL-4-mediated pathway through metabolic rewiring and facilitates alleviating Inflammatory pain. Show less

Colorectal cancer (CRC) remains a major global health challenge, underscoring the need for reliable biomarkers to improve prognosis and therapeutic stratification. In this study, we comprehensively investigated the expression pattern, clinical significance, molecular functions, and immunological implications of LINGO1 in CRC. Integrative analyses of TCGA and GEO datasets, together with validation in 72 clinical CRC samples, demonstrated that LINGO1 is markedly overexpressed in tumors and strongly associated with advanced clinicopathological features and poor patient outcomes. Functional experiments revealed that both knockdown of LINGO1 in SW480 and LoVo cells and overexpression of LINGO1 in HCT116 cells significantly modulate malignant phenotypes, including proliferation, migration, invasion, and angiogenic capacity. Transcriptome-wide and pathway enrichment analyses further indicated that high LINGO1 expression is linked to epithelial-mesenchymal transition, angiogenesis, Wnt/β-catenin signaling, and other oncogenic pathways. Immunogenomic profiling, supported by multiplex immunofluorescence staining, showed that elevated LINGO1 is associated with an immunosuppressive tumor microenvironment characterized by reduced CD8⁺ T-cell infiltration and diminished GZMB expression, alongside upregulation of multiple immune checkpoint molecules. Collectively, our findings identify LINGO1 as a novel oncogenic driver and immune-modulatory biomarker in colorectal cancer, with potential value for prognosis and therapeutic targeting. Show less

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by irreversible cognitive decline and synaptic dysfunction and represents the most prevalent etiology of dementia, accounting for an estimated 60-70% of all clinically diagnosed cases worldwide. The growing focus on microglia-neuron interactions in AD research highlights their diverse, region-specific responses, which are driven by the functional and pathological heterogeneity across different brain regions. Therefore, investigating the interactions between microglia and neurons is of crucial importance. To explore the regional heterogeneity of microglia-neuron crosstalk in AD, we integrated human single-nucleus RNA sequencing data from the prefrontal cortex (PFC), hippocampus (HPC), and occipital lobe (OL) provided by the ssREAD database. Our study delineated four microglial subtypes and uncovered a pseudotime trajectory activation trajectory leading to the disease-associated microglia (DAM) phenotype. The transition along this trajectory is driven and stabilized by a key molecular switch: the coordinated downregulation of inhibitory factors (e.g., LINGO1) and upregulation of immune-effector and antigen-presentation programs, which collectively establish the pro-inflammatory DAM state. Furthermore, we observed that each brain region displayed unique microglia-neuron communication patterns in response to AD pathology. The PFC and OL engage a THY1-ITGAX/ITGB2 signaling axis; the HPC predominantly utilizes the PTPRM pathway. Notably, THY1 dysregulation strongly correlates with pathology in the PFC, HPC, and OL, suggesting that microglia-neuron crosstalk in AD possesses both heterogeneity and commonality. The main contribution of this study is the systematic characterization of region-specific microglia-neuron interactions and the identification of THY1 as a potential mediator that may be targeted therapeutically to modulate microglial function in affected brain regions. Show less

Lipoprotein(a) [Lp(a)] has emerged as a critical determinant of residual cardiovascular risk. However, its impact on plaque morphology remains underinvestigated. This study aimed to elucidate the relationship between the serum Lp(a) levels, coronary plaque vulnerability, and vascular remodeling characteristics by utilizing intravascular ultrasound (IVUS). We retrospectively enrolled 292 consecutive patients with coronary artery disease who underwent IVUS. Target lesions were classified into vulnerable (n = 83) or stable (n = 209) plaque groups based on the IVUS criteria. Multivariate binary logistic regression was performed to identify independent predictors. The morphological parameters were further compared between the high (＞18.8 mg/dL) and low (≤ 18.8 mg/dL) Lp(a) groups. The vulnerable plaque group exhibited significantly higher median serum Lp(a) levels than the stable group (14.56 vs. 11.04 mg/dL, P = 0.011). After adjusting for age, sex, LDL-C, smoking, diabetes, and hypertension, Lp(a) ＞18.8 mg/dL remained an independent predictor of plaque vulnerability (OR = 1.76; 95% CI: 1.00-3.07; P = 0.049). Notably, the LDL-C levels did not predict vulnerability in this cohort. Furthermore, the high Lp(a) group demonstrated significantly larger vascular dimensions (EEM CSA: 14.67±4.95 vs. 13.22±4.20 mm Elevated serum Lp(a) levels are independent predictors of coronary plaque vulnerability. The underlying mechanism involves Lp(a) promoting compensatory vascular enlargement, accompanied by an increased plaque volume. These findings underscore the necessity of Lp(a) screening to identify any residual risk, particularly in patients with effectively controlled low-density lipoprotein cholesterol (LDL-C). Show less

We examined whether the excess cardiovascular disease (CVD) risk among adults with steatotic liver disease (SLD) subtypes could be reduced or eliminated through joint control of low-density lipoprotein cholesterol (LDL-C), lipoprotein(a) [Lp(a)], and high-sensitivity C-reactive protein (hs-CRP). This prospective cohort study included 291,995 participants from the UK Biobank, comprising 77,187 with metabolic dysfunction-associated steatotic liver disease (MASLD), 22,190 with metabolic dysfunction and alcohol-associated liver disease (MetALD), 5474 with alcohol-associated liver disease (ALD), and 187,144 without SLD. Cox proportional hazards models were used to assess CVD risk associated with numbers of LDL-C, Lp(a), and hs-CRP controlled within the target range. During 12 years of median follow-up, 24,251 CVD events were documented, with 19,661 coronary heart disease and 5600 stroke. Among individuals with various SLD subtypes, those with all three factors controlled had the lowest risks of CVD, with HRs (95% CIs) of 0.65 (0.58, 0.72) in MASLD, 0.61 (0.49, 0.76) in MetALD, and 0.57 (0.35, 0.93) in ALD when comparing to zero-factor control. In addition, among individuals with SLD subtypes achieving all three factors within target ranges, the HRs (95% CIs) of CVD were 0.97 (0.88, 1.07) in MASLD, 0.90 (0.75, 1.08) in MetALD, and 0.63 (0.42, 0.95) in ALD, as compared with non-SLD controls. Similar association patterns were observed for coronary heart disease and stroke. Participants with various SLD subtypes who had optimally controlled LDL-C, Lp(a), and hs-CRP showed no excess or even lower risk of CVD as compared with the general population. Not available. Show less

Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, including circulating monocytes and tissue-resident macrophages, and integrates with host genomes to form stable viral reservoirs. To achieve a functional HIV cure, latency-promoting agents (LPAs) have been developed for the "block-and-lock" strategy to reinforce deep HIV-1 latency and permanently silence proviruses. However, most LPAs have been tested mainly in CD4 Show less

Obesity results from the interaction of polygenic susceptibility and environmental factors. Given this complex etiology, physical activity (PA) remains a cornerstone of cost-effective intervention strategies. This longitudinal natural experiment investigated how PA modifies the effects of genetic predisposition on obesity in Chinese youth. We conducted a 4-year natural experiment leveraging curriculum-driven PA disparities in a specialized arts school (n = 591), creating distinct high-PA (HPA) and low-PA (LPA) exposure groups. Weighted genetic risk scores (WGRSs) were calculated from 13 Asian-derived obesity-related single-nucleotide polymorphisms. Annual anthropometric, metabolic, and lifestyle data were analyzed using generalized linear mixed models to assess gene-PA interactions on obesity. The WGRS predicted baseline obesity measures, with each unit increase associated with a 0.21-kg/m² higher BMI. Over the natural experiment period, BMI increases in the HPA group were smaller than in the LPA group. After adjusting for age, sex, ethnicity, and dietary factors, significant WGRS-PA interactions were observed for BMI trajectories. Participants with higher genetic risk for obesity experienced greater BMI and weight reduction benefits from sustained long-term PA. In summary, the present study identified a significant interaction effect between PA levels and WGRS in modifying BMI trajectories. Genetic susceptibility significantly modifies the protective effects of long-term PA on BMI progression in this cohort of Chinese youth. Show less

To identify latent profiles of Fear of Progression (FoP) in parents of children with cancer, explore their associated factors, and test the mediating role of Sense of Coherence (SOC) between FoP and psychological distress (PD). A cross-sectional study was conducted with 273 parents of children with cancer in China. We used latent profile analysis (LPA) to identify FoP profiles, multinomial logistic regression to determine associated factors, and mediation analysis to test the role of SOC. Three distinct FoP profiles were identified: medication sensitive with low fear (38%), treatment sensitive with moderate fear (21%), and overall high fear (41%). These profiles were significantly differentiated by disease-related (e.g., treatment history), individual-related, and interpersonal-related (e.g., self-disclosure) factors. Across the sample, higher FoP was associated with greater PD. Importantly, mediation analyses revealed that SOC significantly mediated the relationship between FoP and PD for the moderate and high FoP profiles, but not for the low LoP profile. Parents of children with cancer exhibit heterogeneous FoP profiles. SOC acts as a crucial mediator between FoP and PD, particularly for parents with moderate and high FoP profiles. These findings underscore the importance of screening for specific FoP profiles and suggest that tailored interventions designed to enhance SOC could effectively reduce PD in high-risk parents. Show less

To evaluate the predictive value of novel lipid parameters for coronary lesion severity in pCAD and to develop a nomogram-based prediction model. Patients newly diagnosed with pCAD at Qingdao Municipal Hospital (2021-2024) were enrolled and randomly assigned to training and validation cohorts in a 7:3 ratio. Coronary lesion severity was assessed using the Gensini score (GS), with patients stratified into mild or significant stenosis groups. Spearman correlation analysis was performed between GS and lipid parameters. Key predictors were selected using LASSO regression, and independent risk factors were identified by multivariable logistic regression to construct the nomogram model. The model's discrimination, calibration, and clinical utility were evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Lp(a), non-HDL-C, RC, FFA, and BAR were positively correlated with GS (r = 0.34, 0.34, 0.18, 0.19, 0.18; all The proposed nomogram provides an effective tool for identifying pCAD patients with severe coronary artery stenosis, demonstrating robust predictive accuracy and potential clinical utility. Show less

Previous studies have indicated that Kinesiophobia is associated with adherence to exercise rehabilitation. Given the multifaceted impact of Kinesiophobia and the complex diversity of individual characteristics, existing research struggles to identify the distinct features of Kinesiophobia. Latent Profile Analysis (LPA) identifies individuals’ latent traits based on their response patterns to observable measures, grouping individuals with similar symptom profiles into different categories, thereby better distinguishing differences among individuals. However, there is currently a lack of research on the kinesiophobia in the out-of-hospital early rehabilitation phase after Percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Therefore, the aim of this study is to investigate kinesiophobia in the out-of-hospital early rehabilitation phase after Percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD), classify it based on latent profile analysis, and explore the related factors of Kinesiophobia in CHD patients across different categories. This study selected coronary heart disease patients who were in the early outpatient rehabilitation stage after receiving PCI treatment at a tertiary hospital as the survey subjects. Latent Profile Analysis (LPA) was employed to fit potential classes of kinesiophobia among these patients. Chi-square tests, Kruskal-Wallis tests, and multinomial logistic regression were utilized to explore the factors influencing different kinesiophobia profiles in these patients. A total of 293 survey subjects were included, the age of the 293 patients was 62.31 ± 11.49 years, Males represent 77% of the total population. The results of potential profile analysis revealed that kinesiophobia in the out-of-hospital early rehabilitation phase of CHD in PCI-treated patients could be divided into three potential categories: the low kinesiophobia-exercise avoidance group (52.1%), the medium kinesiophobia-danger perception group (41.6%), and the high kinesiophobia-dysfunction group (6.3%). The logistic regression analysis results revealed that age, mode of residence, chronic comorbidities, polypharmacy, and debilitation were influential factors for different categories of kinesiophobia in the out-of-hospital early rehabilitation phase of CHD patients undergoing PCI. There is obvious group heterogeneity in kinesiophobia in the out-of-hospital early rehabilitation phaseof CHD patients undergoing PCI, and healthcare professionals should carry out individualized intervention Strategies to reduce the degree of kinesiophobia in patients on the basis of the characteristics and influencing factors of different categories. Show less

While family resilience is a recognized determinant of adaptation following stroke, the distinct, empirically derived profiles of family resilience among Chinese stroke survivor-caregiver dyads have not been clearly delineated. Identifying these profiles and their determinants is crucial for developing targeted interventions. To identify latent profiles of family resilience and examine the socio-demographic and clinical factors associated with profile membership among stroke patient-caregiver dyads in China. In this cross-sectional study, a convenience sample of 773 stroke survivor-caregiver dyads was recruited from three hospitals in Zhejiang Province, China. Latent profile analysis (LPA) was conducted on the 20-item Family Resilience Questionnaire (FRQ). Multinomial logistic regression was used to determine factors associated with profile membership. LPA supported a four-profile solution: Profile 1 "Low-Functioning Families" (22%), Profile 2 "Moderately Resilient - Low Cohesive Families" (24%), Profile 3 "Highly Resilient - Well-Functioning Families" (31%), and Profile 4 "High-Functioning - Optimistically Resilient Families" (24%). Multinomial logistic regression revealed that lower caregiver competence (higher FCTI scores) was strongly associated with profile membership (standardized aORs ranged from 2.58 to 43.19), whereas higher perceived social support (PSSS) was a significant protective factor (standardized aORs ranged from 0.03 to 0.19). Caregiver relationship and payment source were also significantly associated with profile membership. Family resilience among Chinese stroke families manifests in four distinct profiles, which are differentiated predominantly by caregiver competence and perceived social support. Our findings advocate for a precision family support paradigm, shifting from one-size-fits-all approaches to interventions tailored to distinct resilience profiles. Given the strong association, intervention programs should prioritize enhancing core caregiver competencies as a primary leverage point for building family resilience. Show less

Adolescence is a critical period for rapid emotional and cognitive development. Depression and cognitive impairment frequently co-occur in this population, yet their comorbidity patterns and symptom-level interactions remain insufficiently explored. A total of 2,244 students (mean age = 16.8 ± 0.84 years; 1,218 males, 1,026 females) from a high school in Heilongjiang Province, China, were recruited. Depressive symptoms and cognitive impairment were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and the Perceived Deficits Questionnaire–Depression (PDQ-D). Latent profile analysis (LPA) was applied to identify subgroups, followed by network analysis to examine central symptoms (expected influence, EI), bridge symptoms (bridge expected influence, BEI), and network differences (NCT). The optimal LPA model identified three comorbidity subgroups: low, moderate, and high. NCT revealed significant differences in network structure and global strength between the low–moderate (S = 1.514, Adolescent Depression and Cognitive Impairment can be classified into low, moderate, and high comorbidity subgroups. Somatic symptoms emerged as the central symptom, while prospective memory impairment and interpersonal problems were identified as key bridge symptoms, suggesting potential intervention targets for early screening and stratified treatment. Not applicable. The online version contains supplementary material available at 10.1186/s12888-026-07946-w. Show less

Flourishing is a key positive psychological construct that has been linked to favorable health-related outcomes in patients with inflammatory bowel disease in prior research. However, current research often overlooks the variations in flourishing levels within this population, as well as the mechanisms through which flourishing interacts with disease progression. This study aimed to identify latent categories of flourishing among patients with inflammatory bowel disease and to analyze the potential influencing factors. This study employed a cross-sectional, descriptive exploratory design involving 316 patients diagnosed with inflammatory bowel disease. Data collection was carried out using a general information questionnaire, the Flourishing Scale (FS), the IBD Self-Efficacy Scale (IBD-SES), the Resilience Scale for Inflammatory Bowel Disease (RS-IBD), and the Social Support Rating Scale (SSRS). Latent profile analysis (LPA) was utilized to identify potential subgroups exhibiting flourishing, while multiple logistic regression analysis was conducted to evaluate the influencing factors. The flourishing of individuals with inflammatory bowel disease was classified into three latent groups: the low flourishing-low support beneficiary group ( Patients with inflammatory bowel disease demonstrate three distinct latent categories of flourishing. Healthcare professionals should implement more accurate and targeted intervention measures based on the characteristics and influencing factors of different potential categories, in order to improve the flourishing levels of patients with inflammatory bowel disease. Show less

Carboxymethylcellulose (CMC), a common food emulsifier, induces microbiota dysbiosis and systemic inflammation; however, its impact on transplant immunity remains unclear. Allogenic heart rejection was observed in CMC-fed recipient mice, with increased abundance of lysophosphatidic acid (LPA)-producing bacteria and increased serum LPA concentration. CMC-induced transplant rejection was caused by the gut microbiota, as confirmed by fecal microbiota transplantation and gut microbiota depletion. Furthermore, LPA-treated macrophages demonstrated a proinflammatory ability to accelerate allograft rejection in cytotoxic T lymphocyte-associated protein 4 immunoglobulin-induced allograft survival by upregulating glycolysis. Conversely, the administration of a glycolysis inhibitor resulted in allograft survival and abrogated the detrimental effect of LPA. Mass spectrometry and single-cell RNA sequencing confirmed that transplant patients with rejection showed significantly elevated serum LPA levels and LPA receptor 6 (LPAR6) expression in graft-infiltrate macrophages. Mechanistically, LPA preferentially promoted LPAR6 expression, which interacted with Rho-associated protein kinase 2 to activate the mammalian target of rapamycin/hypoxia-inducible factor 1-alpha pathway, thereby enhancing glycolysis and inducing proinflammatory macrophage polarization. Treatment with Ki16425, an LPAR antagonist, prolonged allograft survival in CMC-fed recipients. Our findings reveal a major detrimental effect of CMC on macrophage physiology and suggest that controlling LPAR6 expression or glycolysis in macrophages may improve allograft survival in transplant recipients. Show less

To evaluate the current status and latent profiles of caregiver self-care contributions for patients with chronic obstructive pulmonary disease (COPD) and examine the associations between demographic characteristics, health literacy, confidence in self-care contributions, family intimacy, and profile membership. We recruited 275 dyads of patients with COPD and their family caregivers from five tertiary hospitals between May and November 2022 using convenience sampling. Latent profile analysis (LPA) was used to identify distinct profiles of caregiver self-care contributions. Univariate analysis and multinomial logistic regression were subsequently conducted to examine associations between participant characteristics and profile membership. LPA identified four distinct profiles of caregiver self-care contributions: low-contributing, under-monitored, maintenance-prioritized, and high-contributing. Significant differences were observed across these profiles in terms of patients' symptom severity, exacerbation frequency, number of hospitalizations, caregivers' education levels, caregiving duration, health literacy, confidence in self-management contributions, and family intimacy using univariate analysis. Multinomial logistic regression analysis revealed that caregivers' education levels, caregiving duration, confidence in self-management contributions, and health literacy were significant predictors of profile membership. Caregiver self-care contributions for patients with COPD can be characterized by four distinct profiles, with caregivers' educational level, health literacy, and confidence in self-management identified as key factors associated with profile membership. Show less

Non-suicidal self-injury (NSSI) is highly prevalent among adolescents with depression, yet the heterogeneity of underlying temperamental risk factors remains poorly understood. Traditional variable-centered approaches fail to capture how distinct affective temperaments co-occur within individuals. This study aimed to identify latent profiles of affective temperaments and examine their association with NSSI, exploring the statistical mediating role of cognitive emotion regulation (CER). A cross-sectional study was conducted from February 2025 to September 2025 at the First Hospital of Hebei Medical University. A total of 290 adolescents (aged 10–19) diagnosed with Major Depressive Disorder were recruited, with 282 valid responses included in the final analysis. Participants completed the TEMPS-A, CERQ, and ASHS. Latent Profile Analysis (LPA) was utilized to identify temperament subgroups. Mediation analysis with bootstrapping was performed to test the indirect effects of CER strategies. LPA identified three distinct profiles: Resilient/Low-risk (Class 1, 32.6%), Anxious-Depressive (Class 2, 46.1%), and Mixed-Dysregulated (Class 3, 21.3%). The Mixed-Dysregulated group, characterized by simultaneous elevations in depressive, anxious, irritable, and cyclothymic temperaments, exhibited the highest frequency (45.2 ± 21.3 times/year) and prevalence (98.8%) of NSSI compared to other groups ( The findings delineate a specific “Mixed-Dysregulated” risk phenotype within adolescent depression that is associated with severe NSSI. Interventions should move beyond standard depression care to target cognitive flexibility and emotional regulation skills. Statistical mediation analysis suggests that this risk is mediated by maladaptive cognitive emotion regulation strategies. Not applicable. Show less

China's total fertility rate has reached a critically low level, dropping to approximately 1.0 by the end of 2023which is significantly below the population replacement level of 1.5. This decline reflects a marked reduction in fertility intention among reproductive-aged women, exacerbating population aging and threatening long-term labor supply and social sustainability. Despite policy adjustments and governmental support initiatives, intended outcomes have not been realized. Current literature largely focuses on isolated determinants of fertility intention, overlooking heterogeneity within the population. Moreover, the pathways through which psychosocial factors operate across different subgroups remain poorly understood. Data for this study were derived from the 2021 Psychological and Behavioral Investigation of Chinese Residents (PBICR 2021), a nationally representative cross-sectional survey. Latent profile analysis (LPA) was employed to identify subtypes of fertility intention among reproductive-aged women, followed by multinomial logistic regression, which examined factors associated with different profiles. Among 2,973 reproductive-aged female participants, three distinct fertility intention profiles were identified via latent profile analysis: the Fertility Intention Decline Group (25.1%), the Low Fertility Intention Group (51.3%), and the High Fertility Intention Group (23.6%). Multinomial logistic regression analysis revealed that, compared with the Fertility Intention Decline Group, the Low Fertility Intention Group was significantly associated with family type, aged 20-40 years, residential location, having 2 children, and retirement status (all Fertility intention among reproductive-aged women demonstrates significant heterogeneity. This study identified three distinct latent profiles, each characterized by unique patterns of influencing factors. The findings highlight the necessity of moving beyond one-size-fits-all policy approaches and emphasize the importance of developing tailored interventions that account for the specific characteristics and determinants of each subgroup. Show less

Digital literacy has become a core competency for nursing professionals, enabling them to adapt to modern healthcare environments and engage effectively with emerging technologies. It is closely linked to innovative behavior, which is essential for problem solving and advancing nursing practice. Despite its importance, limited research has examined differences in digital literacy among undergraduate nursing students and how these differences influence innovation. A cross-sectional study was conducted using a convenience sample of 450 undergraduate nursing students from four universities in Anhui Province, China. Participants completed a general information questionnaire, the Undergraduate Digital Literacy Scale, and the Innovative Behavior Scale. Latent profile analysis (LPA) was employed to classify students into distinct digital literacy profiles, while logistic regression and one-way ANOVA were used to explore factors influencing profile membership and the relationship between digital literacy and innovative behavior. Three latent profiles were identified: a "Low Digital Literacy" group (34.1%), a "Moderate Digital Literacy" group (15.9%), and a "High Digital Literacy" group (50.0%). Significant differences were observed across profiles in relation to gender, age, academic year, and frequency of artificial intelligence (AI) use in the past 6 months. Importantly, students with higher digital literacy consistently exhibited stronger innovative behavior ( Digital literacy among undergraduate nursing students is heterogeneous and shaped by demographic and experiential factors. Targeted educational interventions tailored to distinct literacy profiles are needed to bridge gaps, promote equity, and strengthen innovation. By integrating AI and advanced digital tools into nursing curricula, educators can enhance students' competencies and better prepare them to thrive in an increasingly digital and intelligent healthcare landscape. Show less

Major depressive disorder (MDD) in adolescents is a critical public health concern, yet objective diagnostic biomarkers remain lacking. We conducted an integrative lipidomics study across human cohorts and a chronic unpredictable mild stress (CUMS) rat model. Targeted UPLC-MS/MS profiling was applied to a training cohort (95 MDD, 40 controls), and untargeted UPLC-HRMS profiling to an independent cohort (56 MDD, 37 controls). Candidate biomarkers were identified using univariate tests, partial least squares discriminant analysis, and three feature-selection methods (Boruta, LASSO, RFE), with predictive performance evaluated by cross-validation and external replication. Translational relevance was examined in CUMS rats through behavioral assays and lipidomic profiling of serum and brain tissues. Pathway enrichment and regression models explored metabolic context and clinical associations. In the training cohort, we found that 244 lipids were significantly altered, highlighting altered glycerophospholipid, glycerolipid, and sphingolipid metabolism. A 29-lipid panel achieved 90.4% cross-validation accuracy, while a reduced 7-lipid subset reached 94.8%. In the validation cohort, an 8-lipid panel achieved 71.2% accuracy, and a minimal 2-lipid set-LPA(18:2) and SPH(d16:1)-reached 72.1%. Cross-species analysis confirmed consistent downregulation of SPH(d16:1) in serum of both humans and rats, and of LPC(0:0/16:0) specifically in the rat prefrontal cortex. Regression analyses linked sex, age, and anxiety severity to lipid alterations. This cross-platform, cross-species study identifies reproducible lipid signatures of adolescent MDD, highlights SPH(d16:1) and LPC(0:0/16:0) as translational biomarkers, and implicates glycerophospholipid metabolism in MDD pathophysiology, providing a foundation for biomarker-guided diagnostics and therapeutics. Show less