Chong Zeng

Psoriasis is a recurrent chronic inflammatory disease by recurrence. Although considerable research has examined the relationship between ambient temperature and psoriasis, findings remain inconsistent. We conducted a retrospective cohort study in Foshan, China, using a distributed lag nonlinear model (DLNM) to investigate the relationship locally. We identified a W-shaped relationship between temperature and psoriasis incidence in Foshan, with both extreme low temperature (ELT) and extreme high temperatures (EHT) significantly increasing risk. After adjusting for particulate matter pollution as a confounder, ELT exposure showed the strongest single-day lagged effect on psoriasis onset at lag 2 (relative risk [RR] = 1.349; 95% confidence interval [CI]: 1.090-1.671). The cumulative lag effect for ELT peaked at lag 4 (RR = 1.761, 95% CI: 1.141-2.716), while EHT exposure reached its peak cumulative lag effect at lag 0 with RR = 1.165 (95% CI: 1.008-1.346). After adjusting for gaseous pollutants as potential confounders, ELT exposure showed the strongest single-day lagged effect at lag 2 (RR = 1.404; 95% CI: 1.128-1.746), and exposure to EHT demonstrated its peak cumulative lag effect at lag 0 (RR = 1.180; 95% CI: 1.018-1.369). Subgroup analyses further revealed that males were more susceptible to temperature fluctuations. Based on these findings, we conclude that temperature fluctuations significantly impact psoriasis in this region.

Objective: The psoriatic immune microenvironment (PIME) is central to psoriasis pathogenesis, yet its mechanistic drivers are incompletely defined. This study aimed to delineate immune cell infiltration patterns and identify pivotal disease‐related immune genes through a systematic analysis of the PIME. Methods: We evaluated the infiltration levels of 28 immune cell subtypes in 11 psoriasis‐related microarray datasets using single‐sample gene set enrichment analysis (ssGSEA). Subsequent differential expression, consensus clustering, and weighted gene co‐expression network analysis (WGCNA) were employed to identify key genes. These findings were validated using human psoriatic tissue samples and an imiquimod‐induced murine psoriasis model to construct a predictive model termed IMscore. Results: Our analysis identified five pivotal immune‐related differentially expressed genes (ImDEGs): CXCL8, CXCL9, CCL18, RGS1, and SAMSN1. A novel predictive model, IMscore, was constructed based on these ImDEGs to assess psoriasis risk. Furthermore, immune infiltration profiling and gene set enrichment analysis demonstrated that these ImDEGs are functionally associated with psoriasis‐related inflammatory pathways, validating the diagnostic utility of the IMscore framework. Conclusion: These results provide new insights into the immunological mechanisms underlying psoriasis and establish a multi‐gene signature with potential for improving early diagnosis and therapeutic development.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient outcomes. This study aims to construct and validate an RCC prediction model for at-risk individuals using machine learning (ML) based on routine clinical data. Data from the Quanzhou First Hospital Affiliated with Fujian Medical University between March 2014 and March 2024 were retrospectively collected, with 70% randomly assigned to the training cohort and 30% to the validation cohort. Univariate and hierarchical clustering methods were employed to identify discriminatory features to enable optimal ML algorithm selection. The performance of 7 kinds of ML algorithms-based models was evaluated based on sensitivity (recall), accuracy, F1-score, area under the receiver operating curve (AUC), discrimination, calibration, and clinical net benefit. The algorithm achieving the best AUC was selected for combination with recursive feature elimination to identify features that maximize model performance and stability. After that, the RCC prediction model was finally constructed, and the Shapley Additive Explanations method was used to visualize model characteristics and individual case predictions. Among those algorithms, the eXtreme Gradient Boosting algorithm achieving the best performance was selected for final construction. Combined with the recursive feature elimination method, it identified 21 clinically relevant variables, including age, total protein, albumin, total bilirubin, alanine aminotransferase, alkaline phosphatase, gamma-glutamyl transpeptidase, glucose, lactate dehydrogenase, creatine kinase-MB, creatinine, potassium-chloride ratio, sodium ion, calcium ion, eosinophil count, hemoglobin, platelet count, Systemic Immune-Inflammation Index, Pan-Immune-Inflammation Value, platelet–lymphocyte ratio, and sodium–chloride ratio for RCC model construction. Subsequently, a RCC prediction model and eXtreme Gradient Boosting using these 21 variables was built, achieving AUC of 0.955 (95% CI: 0.938–0.976) and an average precision of 0.923 in the validation cohort. The additional calibration curve showed high agreement between predicted and observed risks. Finally, the Shapley Additive Explanations method well demonstrated the importance of all model features and provided case-specific interpretation for clinicians. We developed and validated an ML model using routine clinical data for large-scale RCC screening. This cost-effective approach facilitates the early detection of and intervention for RCC, which may lead to improved clinical outcomes.

Psoriasis is a common chronic inflammatory skin disease characterized by epidermal keratinocyte hyperproliferation and persistent immune activation. Histone deacetylase 3 (HDAC3), a member of the class I HDAC family, plays critical roles in regulating immunity and inflammation. However, its precise expression profile and functional contribution to psoriasis pathogenesis remain poorly defined. We first performed bioinformatics analysis of HDAC3 expression using the Gene Expression Omnibus (GEO) database. Subsequently, we employed a combination of cellular and molecular techniques, including hematoxylin and eosin (H&E) staining, immunohistochemistry, flow cytometry, quantitative real-time PCR (qRT-PCR), western blotting, and transmission electron microscopy (TEM), to analyze the role of HDAC3 in IMQ-induced psoriasis-like inflammation in mice and in vitro psoriasis models. HDAC3 expression was significantly upregulated in psoriasis lesions of patients and in both in vitro and in vivo models of psoriasis. Pharmacological inhibition of HDAC3 using the specific inhibitor RGFP966 alleviated IMQ-induced skin inflammation in mice and suppressed psoriasis-like phenotypes in vitro. Mechanistically, HDAC3 upregulation in an inflammatory microenvironment promoted oxidative stress, disrupted mitochondrial structural integrity, and triggered mitochondrial DNA leakage into the cytosol, thereby activating the cGAS-STING pathway in keratinocytes. Our findings establish HDAC3 as a pivotal mediator of psoriasis pathogenesis through the cGAS-STING pathway via mitochondrial dysfunction. The role of HDAC3 in exacerbating epidermal hyperproliferation and inflammation highlights its potential as a therapeutic target. Targeting HDAC3 in keratinocytes may offer a novel strategy for preventing and treating psoriasis by modulating epigenetic regulation, mitochondrial homeostasis, and innate immune responses.

Disulfidptosis, a new form of cell death triggered by disulfide stress, is characterized by the collapse of cytoskeleton proteins and F-actin due to the intracellular accumulation of disulfides. This discovery will eventually aid in the development of therapeutic strategies against cancer.

Background: The role of circular RNAs in the pathogenesis of gastric cancer (GC) has been well documented by numerous studies. However, whether circ_0003789 plays a role during GC progression remains to be determined. Thus, this study aimed to investigate the biological functions of circ_0003789 during GC progression. Materials and Methods: Circ_0003789 expression was determined using quantitative real-time polymerase chain reaction in GC and matched para-carcinoma normal tissues. Functional experiments were performed to estimate changes in the proliferation, apoptosis, migration, and invasion of GC cells treated to silence circ_0003789. E-cadherin, vimentin, Wnt3a, and β-catenin expression was determined using immunofluorescence staining and western blot assays. Xenograft tumor growth and Ki67 expression were also evaluated in vivo. Results: Circ_0003789 was upregulated in GC tissues and cells, and its upregulation positively correlated with poor tumor differentiation, distal metastasis, and advanced clinical stage. Silencing circ_0003789 inhibited GC cell proliferation, migration, invasion, and the epithelial–mesenchymal transition (EMT), both in vitro and in vivo. Mechanistically, the Wnt/β-catenin signaling pathway was repressed by circ_0003789 silencing. Conclusions: Circ_0003789 facilitates GC progression by inducing the EMT through the Wnt/β-catenin signaling pathway.

Immunotherapy with immune checkpoint inhibitors had achieved great success. However, only a subset of patients responds positively to these therapies. The latest study published on Nature by Chou and colleagues found a new T cell subset from tumor-infiltrating T cells which lack PD-1 on the cell surface and potent cytotoxic activities against tumor cells. This finding provides a novel insight into the development of new therapies for tumors that do not respond to immune checkpoint blockade in the future.

Ferroptosis is a new form of programmed cell death, which achieved great breakthroughs in cell biology during past decade. However, the regulation of ferroptosis is yet to be identified thoroughly. The latest study published on Nature cell biology by Nguyen and colleagues found a new NADPH sensor, MARCHF6 an E3 ubiquitin ligase, mediates ferroptosis in tumor growth and animal development. This finding provides a novel insight into ubiquitin system and energy metabolism in regulation of ferroptosis, which may open up new avenues for tumor treatment.

SHARPIN is a tumor‐associated gene involved in the growth and proliferation of many tumor types. A function of SHARPIN in cholangiocarcinoma (CCA) is so far unclear. Here, we studied the role and function of SHARPIN in CCA and revealed its relevant molecular mechanism. The expression of SHARPIN was analyzed in cholangiocarcinoma tissues from patients using immunohistochemistry, quantitative PCR, and western blot analysis. Expression of SHARPIN was suppressed/overexpressed by siRNA silencing or lentiviral overexpression vector, and the effect on cell proliferation was determined by the CCK‐8 assay and flow cytometry. Accumulation of reactive oxygen species was measured with MitoTracker, and JC‐1 staining showed mitochondrial fission/fusion and mitochondrial membrane potential changes as a result of the silencing or overexpression. The ferroptosis marker solute carrier family 7 member 11 (SLC7A11), glutathione peroxidase 4 (GPX4), and the antioxidant enzymes superoxide dismutase 1 (SOD‐1) and SOD‐2 were analyzed by western blot. The results showed that SHARPIN expression was increased in CCA tissue, and this was involved in cell proliferation. SHARPIN silencing resulted in accumulated reactive oxygen species, reduced mitochondrial fission, and a reduced mitochondrial membrane potential. Silencing of SHARPIN inhibited the ubiquitination and degradation of p53, and downregulated levels of SLC7A11, GPX4, SOD‐1, and SOD‐2, all of which contributed to excessive oxidative stress that leads to ferroptosis. Overexpression of SHARPIN would reverse the above process. The collected data suggest that in CCA, SHARPIN‐mediated cell ferroptosis via the p53/SLC7A11/GPX4 signaling pathway is inhibited. Targeting SHARPIN might be a promising approach for the treatment of CCA.