We aim to explore the associations between dietary zinc intake and hyperuricemia (HU) in United States (US) adults. 24,975 US adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2014 were stratified into quintiles based on zinc intake. All dietary intake measured through 24-h dietary recalls. Multivariable logistic regression analysis was performed to examine the association between zinc intake and HU after adjustment for possible confounders. For males, compared with respondents consuming less than 7.33 mg zinc daily, the adjusted odds ratios (ORs) were 0.83 (95% CI, 0.71, 0.97) among those consuming 10.26–13.54 mg zinc daily, 0.78 (95% CI, 0.63–0.96) among those consuming 18.50 mg or greater, and p for the trend was 0.0134. For females, compared with respondents consuming less than 5.38 mg zinc daily, the OR was 0.78 (95% CI, 0.63, 0.97) among those consuming 9.64–12.93 mg zinc daily, and p for the trend was 0.3024. Our findings indicated that dietary zinc intake is inversely associated with HU in US men and women, independent of some major confounding factors.

Glioblastoma multiforme (GBM) is a common malignancy with poor prognosis, and exhausted T (TEX) cells, a subset of T cells characterized by progressive loss of effector functions, play a critical role in its progression. This study aimed to investigate the impact of TEX-related genes on immune function, prognosis, and drug sensitivity in GBM through multiomics analysis. Initially, we identified a novel set of TEX-related genes specific to GBM and screened hub genes (CCL5, IL18, CXCR6, FCER1G, TNFSF13B) using conventional statistical methods combined with machine learning. A prognostic risk model was subsequently constructed based on TCGA data and validated in the CGGA cohort. Single-cell and pharmacogenomic analyses revealed significant differences in tumor microenvironment composition and drug sensitivity between risk groups. Notably, Palbociclib emerged as a potential therapeutic agent targeting the novel discovered biomarker CCL5. RT-qPCR results showed that T cells with low CCL5 expression exhibited reduced expression of immune checkpoint-related genes (PD1, TIM3, LAG3) and increased expression of CD28, suggesting enhanced immune function. In conclusion, our findings highlight five hub genes as prognostic markers that could stratify GBM patients with different immune landscapes and levels of drug sensitivity. Furthermore, experimental results suggest that low CCL5 expression could alleviate T cell exhaustion and represent a promising therapeutic target, offering new strategies for improving GBM prognosis.

Bulk RNA-sequencing (bulk RNA-seq) averages gene expression across cell mixtures, obscuring single-cell heterogeneity and spatial architectures essential for understanding pathological processes. We developed HistoMap, a deep learning-based framework for single-cell spatial deconvolution. The model employs a two-stage pipeline: first, reconstructing high-fidelity single-cell profiles from bulk data using a β-variational autoencoder, and second, utilizing a Histological Vision Transformer (H-ViT) to map these cells to tissue coordinates via dual guidance from transcriptomic references and H&E-stained morphological constraints. HistoMap demonstrated superior performance across diverse human tissues, achieving a Pearson Correlation Coefficient (PCC) of 0.800 on external validation. Application to 14 colorectal cancer cases revealed a Macro_SPP1-mediated desmoplastic barrier. SPP1+ macrophages act as spatial hubs at the invasive front, forming a physical “sequestration belt” that functionally excludes cytotoxic T cells from the tumor core. HistoMap successfully bridges bulk RNA-seq and spatial single-cell architectures. Our findings provide a molecular rationale for immune checkpoint blockade resistance and identify the SPP1-fibroblast axis as a pivotal target for therapeutic sensitization.

Purpose: To characterize Subjective Cognitive Decline (SCD) in Parkinson’s disease (PD) and its progression, as well as to assess the impact of rehabilitation training programs on cognitive function in PD patients. Patients and Methods: The study involved 42 patients diagnosed with PD. Participants underwent evaluation using a neuropsychological protocol and were subsequently classified into two groups: those with SCD (PD-SCD⁺, n= 22) or those without (PD-SCD⁻, n= 20). After an average follow-up period of 3.0 years (2.7– 4.6 years), cognitive assessments were reiterated with the same group of subjects. Following the re-assessment, all 42 patients participated in a six-month rehabilitation training program, concluding with the reevaluation of cognitive performance. Results: In the follow-up assessment, it was observed that PD-SCD⁺ experienced a more pronounced annual decline in cognitive function, as measured by the Chinese-Beijing version of Montreal Cognitive Assessment (BJ-MoCA) test and semantic fluency, compared to PD-SCD⁻. A stepwise logistic regression analysis identified low MMSE scores (P< 0.001), elevated HAMD scores (P= 0.008), male gender (P= 0.026), and the presence of SCD (P= 0.022) associated with diminished language skills in PD patients. Both groups of PD patients exhibited improvements in BJ-MoCA scores after participating a six-month rehabilitation training program. Particularly notable is the statistically significant improvement in language skills observed in patients with PD-SCD⁺ compared to PD-SCD⁻ patients following rehabilitation training. Conclusion: As PD progresses, individuals with PD-SCD⁺ tend to experience more pronounced cognitive decline compared to those with PD-SCD⁻. Semantic fluency emerges as a crucial component for assessing the cognitive subset of PD, potentially serving as an indicator of cognitive decline in individuals with PD. Evidence suggests that rehabilitation training is a viable intervention for individuals diagnosed with PD. This intervention not only improves various cognitive domains but also leads to more substantial enhancements in language skills.