ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a major cause of chronic kidney disease and kidney failure. IgAN exhibits marked heterogeneity in clinical presentation, histopathology, and pathogenic mechanisms, contributing to variable treatment responses and prognosisamong patients. Precise risk assessment and individualized intervention are therefore of critical importance. This review systematically traces the evolution of IgAN management from traditional risk stratification toward biomarker-driven precision medicine. We first review the clinical utility and limitations of established risk stratification tools, including the KDIGO guidelines, the Oxford MEST-C classification, and the International IgAN Prediction Tool. We then discuss emerging biomarkers closely linked to disease pathogenesis, including galactose-deficient IgA1 (Gd-IgA1), anti-Gd-IgA1 autoantibodies, B cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), and complement components, as well as the targeted therapies they have informed. In addition, urinary biomarkers and multi-omics approaches show promise for dynamic disease monitoring and individualized risk stratification.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.

Alzheimer's disease (AD), a progressive dementia, is one of the most common neurodegenerative diseases. Clinical trial results of amyloid-β (Aβ) and tau regulators based on the pretext of straightforward amyloid and tau immunotherapy were disappointing. There are currently no effective strategies for slowing the progression of AD. Herein, we spotlight the dysregulation of lipid metabolism, particularly the elevation of ceramides (Cers), as a critical yet underexplored facet of AD pathogenesis. Our study delineates the role of Cers in promoting microglial pyroptosis, a form of programmed cell death distinct from apoptosis and necroptosis, characterized by cellular swelling, and membrane rupture mediated by the NLRP3 inflammasome pathway. Utilizing both in vivo experiments with amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic mice and in vitro assays with BV-2 microglial cells, we investigate the activation of microglial pyroptosis by Cers and its inhibition by icariin (ICA), a flavonoid with known antioxidant and anti-inflammatory properties. Our findings reveal a significant increase in Cers levels and pyroptosis markers (NOD-like receptor family, pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein containing a caspase recruitment domain, caspase-1, gasdermin D (gasdermin D (GSDMD)), and interleukin-18 (IL-18)) in the brains of AD model mice, indicating a direct involvement of Cers in AD pathology through the induction of microglial pyroptosis. Conversely, ICA treatment effectively reduces these pyroptotic markers and Cer levels, thereby attenuating microglial pyroptosis and suggesting a novel therapeutic mechanism of action against AD. This study not only advances our understanding of the pathogenic role of Cers in AD but also introduces ICA as a promising candidate for AD therapy, capable of mitigating neuroinflammation and pyroptosis through the cyclooxygenase-2 (COX-2)-NLRP3 inflammasome-gasdermin D (GSDMD) axis. Our results pave the way for further exploration of Cer metabolism disorders in neurodegenerative diseases and highlight the therapeutic potential of targeting microglial pyroptosis in AD.

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors

Mitophagy,a special form of selective autophagy,plays a significant role in the pathogenesis of atherosclerosis by regulating cellular lipid metabolism,inflammation,and oxidative stress.However,its regulatory mech-anism is complex and has not been fully elucidated.Notably,many drugs and herbal ingredients exhibit anti-atherosclerot-ic effects by modulating mitophagy in macrophages,vascular endothelial cells,and vascular smooth muscle cells,offering potential new avenues for the prevention and treatment of atherosclerosis.In this article,we review the role of mitophagy in regulating cellular functions and the progression of atherosclerosis,as well as summarize potential therapeutic drugs that may contribute to anti-atherosclerosis by modulating mitophagy.Our aim is to provide a new literature basis for further ex-ploration of the role of mitophagy in atherosclerosis.

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

Objective:To investigate the risk factors influencing mortality in neonates undergoing continuous renal replacement therapy (CRRT).Methods:This retrospective study included 34 neonates with a corrected age of≤28 days who received CRRT at the Affiliated Children's Hospital of Xiangya School of Medicine, Central South University, from January 2019 to December 2023. The neonates were divided into a mortality group ( n=16) and a survival group ( n=18) based on whether they died during CRRT. Pre-CRRT blood biochemical indices, general condition, CRRT treatment modes, parameters, and related complications were analyzed using t-tests, Wilcoxon signed-rank tests, and Chi-square tests. Logistic stepwise regression analysis was used to screen for risk factors associated with CRRT mortality. Results:The mortality rate among the 34 neonates was 48.6% (16/34), with a median CRRT age of 17 days (range: 2-33 days). Eleven neonates (32.3%) were preterm, with the youngest gestational age being 27 weeks and the lowest weight before CRRT initiation being 1 700 g. The mortality group had lower urine output 6-12 hours before CRRT initiation and lower critical illness scores compared to the survival group [0.05 (0.02-1.00) ml/(kg·h) vs. 0.50 (0.20-1.05) ml/(kg·h), (64.50±7.10) scores vs. (77.67±3.65) scores, Z or t values were 10.97 and 3.91, respectively]. However, the vasoactive inotropic score (VIS), proportion of coma, and levels of blood potassium, alanine aminotransferase, aspartate aminotransferase, blood ammonia, blood lactic acid, and activated partial thromboplastin time (APTT) were higher in the mortality group compared to the survival group [ (86.88±15.80) scores vs. (55.56±24.31) scores, 11/16 vs. 1/18, (7.02±1.73) mmol/L vs. (5.88±1.53) mmol/L, 274.55(132.50-664.98) U/L vs. 31.10(19.03-110.70) U/L, 688.20 (449.73-3 618.13) U/L vs. 96.65 (44.15-439.00) U/L, 232.75 (70.33-1 310.85) μmol/L vs.77.70 (49.78-919.05) μmol/L, (11.17±3.36) U/L vs. (7.99±2.67) U/L, and (99.57±39.74) s vs. (60.97±31.25) s, with t, χ2, or Z values of－4.39, 14.81,－2.03,－2.72,－11.81,－3.89,－3.06, and－3.17, respectively] (all P<0.05). Logistic regression analysis revealed that pre-treatment VIS value ( OR=1.150, 95% CI: 1.035-1.278), and blood ammonia level ( OR=1.004, 95% CI: 1.002-1.009) were independent risk factors for mortality (both P<0.05). Conclusions:Neonatal CRRT mortality is associated with pre-treatment VIS scores and blood ammonia levels. Attention should be paid to a rapid decreases in urine output, the intensity of vasopressor support, and elevated levels of blood ammonia, blood lactic acid, transaminases, and APTT at the initiation of treatment.