Objective To comprehensively investigate the levels of exposure and distribution characteristics of trihalomethanes (THMs) in drinking water in Guangzhou City, and evaluate the health risks of different groups of children, adolescents and adults, and to provide data and evidence for protecting human health and promoting risk control of drinking water. Methods According to the technical requirements of the ^"Standards for Drinking Water Quality Testing Methods^" (GB/T 5750-2023), the concentration of THMs, including trichloromethane (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM), and tribromomethane (TBM) in drinking water in Guangzhou City from 2023-2024 were detected. The health risk model recommended by USEPA was used for risk assessment．Results TCM, BDCM and DBCM were detected in the factory water and terminal water, with TCM contributing the most. There was a statistically significant difference (P<0.05) between the wet and dry seasons, and the concentration of TCM in the wet season was higher than that in the dry season. Among the multiple exposure factors, the amount of exposure through drinking water intake was much greater than that through skin absorption. The carcinogenic risk index of THMs for children, adolescents, and adults was 22.0×10^-6, 12.2×10^-6, and 11.4×10^-6, respectively, while the non-carcinogenic risk was less than 1. Conclusion The exposure risks of THMs in children, adolescents, and adults is within an acceptable range, but monitoring needs to be strengthened, with a particular focus on children.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective: To explore the changes of mechanosensitive channels Piezos (Piezo 1 and Piezo 2) in neurogenic bladder (NB) of young rats and their effects，so as to provide reference for clinical search of new therapeutic targets. Methods: A total of 30 female young SD rats were divided into 5 groups based on random number table method：sham operation group (sham)，2-week nerve transection group (NB-2W)，6-week nerve transection group (NB-6W)，2-week nerve transection + Piezos inhibitor group (NB-P-2W) and 6-week nerve transection + Piezos inhibitor group (NB-P-6W)，with 6 rats in each group.The NB models were constructed by transecting the L6 and S1 spinal nerves of young rats.The NB-2W and NB-6W groups were not intervened after modeling，while the NB-P-2W and NB-P-6W groups were intraperitoneally injected with Piezos inhibitor GsMTx4 (10 mg/kg) every 2 days after modeling.Bladder cystometry and ultrasound were performed after 2 and 6 weeks of transection.The expressions of Piezos and fibrosis-related indexes (Collagen Ⅰ and α-smooth muscle actin) were detected in bladder tissues. Results: The results of bladder cystometry showed that the basal bladder pressure in NB-2W group was significantly increased，while it was slightly decreased but was still higher in NB-6W group than in the sham group (P<0.05).Basal bladder pressure was lower in NB-P-2W group than in NB-2W group，but was higher than that in the sham group; basal bladder pressure was lower in NB-P-6W group than in NB-6W group，but higher than that in the sham group (P<0.05).Compared with the sham group，the NB-2W and NB-6W groups had firstly increased and then decreased maximum cystometric capacity (MCC) (P<0.05).Compared with NB-2W group，NB-P-2W group had lower bladder leakage point pressure (BLPP)，but higher MCC and bladder compliance (BC) (P<0.05).Compared with NB-6W group，NB-P-6W group had significantly lower BLPP but higher MCC and BC (P<0.05).HE and MASSON staining and ultrasound results showed that，with the extension of nerve transection time，bladder fibrosis gradually worsened，the bladder wall became rough and thickened，calculi were visible inside，and hydronephrosis gradually appeared; the degree of fibrosis in NB-P-2W and NB-P-6W groups was less than that in NB-2W and NB-6W groups，and no hydronephrosis was observed in the upper urinary tract.In addition，Western blotting and immunohistochemical results showed that NB-2W and NB-6W groups had significantly higher relative expression levels of Piezos，Collagen Ⅰ and α-SMA than the sham group (P<0.01)，while NB-P-2W and NB-P-6W groups had lower relative expression levels of Piezos,Collagen Ⅰ and α-SMA than NB-2W and NB-6W groups (P<0.01). Conclusion: The increased expressions of mechanosensitive channels Piezos in NB young rats may be involved in the progression of bladder fibrosis，but its mechanism needs further study.

Objective: To investigate the influencing factors of overactive bladder (OAB) in college freshmen and the impacts of OAB on their mental health, quality of life and social interaction. Methods: An epidemiological questionnaire survey was conducted in an anonymous manner on the prevalence of OAB among 5300 freshmen aged 17 to 22 years enrolled in the 2023—2024 academic year in Xinxiang Medical University and Sanquan College of Xinxiang Medical University.The questionnaire included questions on basic information, history of urinary tract infection, constipation, smoking, history of alcohol consumption, history of coffee/strong tea drinking, history of carbonated beverage drinking, redundant prepuce, phimosis, holding urine, chronic insomnia, self-rating anxiety scale (SAS), quality of life score (QoL), and social avoidance and distress scale (SADS).The influencing factors of OAB were analyzed with multivariate logistic regression analysis.The subjects were grouped according to whether they had OAB, and the differences in SAS, QoL and SADS between the OAB group and non-OAB group were compared.The impacts of OAB on the anxiety level, quality of life, and social interaction were analyzed with multiple linear regression analysis. Results: The overall prevalence rate of OAB was 4.9% (244/5018).Multivariate logistic regression analysis showed that the history of urinary tract infection (OR=0.177), constipation (OR=0.636), smoking (OR=0.582), alcohol consumption (OR=0.685), coffee/strong tea drinking (OR=0.387), carbonated beverage drinking (OR=0.631), redundant prepuce (OR=0.673), phimosis (OR=0.311), urine holding (OR=0.593), and chronic insomnia (OR=0.256) were influencing factors for the occurrence of OAB (P＜0.05).The OAB group had higher SAS score [(41.18±6.54) vs. (38.61±6.36)], QoL score [(3.65±1.20) vs. (2.79±0.95)], social avoidance score [(6.25±1.86) vs. (5.86±1.51)], social distress score [(6.27±1.59) vs. (5.97±1.32)], and total SADS score [(12.51±2.35) vs. (11.84±2.01)] than the non-OAB group (P＜0.05).The results of multiple linear regression analysis showed that OAB could independently affect the scores of QoL, SAS, and SADS.The OAB group had higher scores of QoL, SAS, and SADS compared with the non-OAB group (P＜0.001). Conclusion: History of urinary tract infection, constipation, smoking, alcohol consumption, coffee/strong tea drinking, carbonated beverage drinking, redundant prepuce, phimosis, urine holding, and chronic insomnia are influencing factors for the occurrence of OAB in male college students.Moreover, OAB has negative impacts on their mental health, quality of life, and social interaction.

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

BACKGROUND: Ferroptosis-related genes play a crucial role in regulating intracellular iron homeostasis and lipid peroxidation, and they are involved in the regulation of tumor growth and drug resistance. The expression of ferroptosis-related genes in tumor tissues can be used to predict patients' future survival times, aiding doctors and patients in anticipating disease progression. Based on the sequencing data of lung adenocarcinoma (LUAD) patients from The Cancer Genome Atlas (TCGA) database, this study identified genes involved in the regulation of ferroptosis, constructed a prognostic model, and evaluated the predictive performance of the model. METHODS: A total of 1467 ferroptosis-related genes were obtained from the GeneCards database. Gene expression profiles and clinical data from 541 LUAD patients were collected from the TCGA database. The expression data of all ferroptosis-related genes were extracted, and differentially expressed genes were identified using R software. Survival analysis was performed on these genes to screen for those with prognostic value. Subsequently, a prognostic risk scoring model for ferroptosis-related genes was constructed using LASSO regression model. Each LUAD patient sample was scored, and the patients were divided into high-risk and low-risk groups based on the median score. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. Kaplan-Meier survival curves were generated to assess model performance, followed by validation in an external dataset. Finally, univariate and multivariate Cox regression analyses were conducted to evaluate the independent prognostic value and clinical relevance of the model. RESULTS: Through survival analysis, 121 ferroptosis-related genes associated with prognosis were initially identified. Based on this, a LUAD prognostic risk scoring model was constructed using 12 ferroptosis-related genes (ALG3, C1QTNF6, CCT6A, GLS2, KRT6A, LDHA, NUPR1, OGFRP1, PCSK9, TRIM6, IGF2BP1 and MIR31HG). The results indicated that patients in the high-risk group had significantly shorter survival time than those in the low-risk group (P<0.001), and the model demonstrated good predictive performance in both the training set (1-yr AUC=0.721) and the external validation set (1-yr AUC=0.768). Risk scores were significantly associated with the prognosis of LUAD patients in both univariate and multivariate Cox regression analyses (P<0.001), suggesting that this score is an important prognostic factor for LUAD patients. CONCLUSIONS This study successfully established a LUAD risk scoring model composed of 12 ferroptosis-related genes. In the future, this model is expected to be used in conjunction with the tumor-node-metastasis (TNM) staging system for prognostic predictions in LUAD patients.
Humans ; Ferroptosis/genetics* ; Prognosis ; Adenocarcinoma of Lung/pathology* ; Lung Neoplasms/pathology* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Middle Aged ; ROC Curve

OBJECTIVES: To investigate the role of activating transcription factor 3 (ATF3) in atherosclerotic plaques for regulating inflammatory responses during atherosclerosis (AS) progression. METHODS: Human coronary artery specimens from autopsy cases were examined for ATF3 protein expression and localization using immunofluorescence staining and Western blotting. Apolipoprotein E-deficient (ApoE^-/-) mouse models of AS induced by high-fat diet (HFD) feeding for 12 weeks were subjected to tail vein injection of adeno-associated virus serotype 9 (AAV9) to knock down ATF3 expression. After an additional 5 weeks of HFD feeding, the mice were euthanized for analyzing structural changes of the aortic plaques, and the expression levels of ATF3, inflammatory factors (CD45, CD68, IL-1β, and TNF-α), and NF-κB pathway proteins (P-IKKα/β and P-NF-κB p65) were detected. In the cell experiment, THP-1-derived foam cells were transfected with an ATF3-overexpressing plasmid or an ATF3-specific siRNA to validate the relationship between ATF3 and NF‑κB signaling. RESULTS: In human atherosclerotic plaques, ATF3 expression was significantly elevated and partially co-localized with CD68. ATF3 knockout in ApoE^-/- mice significantly increased aortic plaque volume, upregulated the inflammatory factors, enhanced phosphorylation of the NF‑κB pathway proteins, and increased the expressions of VCAM1, MMP9, and MMP2 in the plaques. In THP-1-derived foam cells, ATF3 silencing caused activation of the NF‑κB pathway, while ATF3 overexpression suppressed the activity of the NF-κB pathway. CONCLUSIONS AS promotes ATF3 expression, and ATF3 deficiency exacerbates AS progression by enhancing plaque inflammation via activating the NF-κB pathway, suggesting the potential of ATF3 as a therapeutic target for AS.
Animals ; Activating Transcription Factor 3/metabolism* ; Signal Transduction ; NF-kappa B/metabolism* ; Humans ; Mice ; Plaque, Atherosclerotic/metabolism* ; Inflammation/metabolism* ; Apolipoproteins E ; Atherosclerosis/metabolism* ; Diet, High-Fat

Cardiovascular disease(CVD)is currently one of the most severe diseases endangering human health,encompassing myocardial ischemia syndrome,myocardial fibrosis,atrial fibrillation,and other conditions.MicroRNAs(miRNAs/miR)are a class of small non-coding RNAs that can bind to specific se-quences and subsequently regulate post-transcriptional processing,translation,or epigenetic modifications,thereby modulating gene expression.Studies have found that miR-223 is associated with the occurrence and de-velopment of CVD and represents a potential specific therapeutic target.This article summarizes the relevant re-search on miR-223 in CVD,focusing on myocardial ischemia syndrome,myocardial fibrosis,and atrial fibrilla-tion,and discusses its application prospects and challenges as a specific therapeutic target,providing new ideas for the diagnosis and treatment of CVD.

Objective:To study the changes of patient-related costs and the use of stents and other consumables before and after the centralized procurement of coronary stents.Methods:The inpatient medical insurance settlement case data of 1,973 patients with coronary stent implantation admitted to Daping Hospital of Army Medical University from December 2019 to October 2021 were selected.Among them,the data of 1,317 cases of percutaneous cardiovascular surgery and coronary stent implantation with serious or complications and accompanying disease group were slected according to disease diagnosis related groups(DRG),which were divided into the pre-centralized procurement group(667 cases)and the post-centralized procurement group(650 cases)according to the centralized procurement of coronary stents before and after.The costs of patients'medical consumables with the consumption of patients'medical consumables and the impact of the use of consumables such as coronary stents on the costs of medical consumables were compared.Results:There was no significant statistical difference in the hospitalization days and the average number of stents used in patients undergoing percutaneous cardiovascular procedures and coronary stent implantation with centralized procurement of coronary stents.There was a statistically significant difference in the total diagnosis and treatment cost,medical consumables cost,medicines and consumables cost and medicines cost between the pre-centralized procurement group and the post-centralized procurement group(Z=-22.316,-23.546,-22.917,-5.724,P<0.05).The cost of stents[16 260(13 300,32 272)yuan],the number of catheter guidewire balloon sheaths consumables[5(4,8)sets(pieces)],and the cost of catheter guidewire balloon sheaths consumables[8 719(5 805,15 372)yuan]in the pre-collection group were collected.There were statistically significant differences in the stent cost[1 059(590,1 770)yuan],the number of catheter guidewire balloon sheaths consumables[8(7,12)sets(pieces)],and the cost of catheter guidewire balloon sheaths consumables[5 708(3 392,12 871)yuan]between the two groups(Z=-30.452,16.582,-7.670,P<0.05).There was a statistical correlation between the cost of coronary stents and the cost of catheter guidewire balloon sheaths before and after centralized volume procurement on the cost of medical consumables for patients(r=0.903,0.473,0.785,0.953,P<0.05).The correlation coefficient between the cost of coronary stents and the cost of medical consumables for patients in the post-centralized procurement group decreased compared to the pre-centralized procurement group,the correlation coefficient between the cost of catheter guidewire balloon sheath and the cost of medical consumables for patients increased.Conclusion:The centralized procurement of coronary stents has a significant cost control effect on patients in the disease groups,and affects the cost structure of medical consumables.Combined with DRG reform,it can continuously improve the standardization and scientificity of clinical use of medical consumables.

BACKGROUND:Rapid developments in the field of bioinformatics have provided new methods for the diagnosis of osteoarthritis.Artificial neural networks have powerful data computing and classification capabilities,which have shown better performance in disease diagnosis. OBJECTIVE:To establish a new diagnostic predictive model of osteoarthritis based on artificial neural network and to verify the diagnostic value of the model in osteoarthritis with an external dataset. METHODS:The eligible osteoarthritis-related data sets were downloaded through GEO database search and divided into Train group and Test group.The gene expression matrix of the Train group was analyzed to screen the differentially expressed genes.GO and KEGG enrichment analyses were performed on the differentially expressed genes.Through Lasso regression model,support vector machine model and random forest tree model,the key genes of osteoarthritis were further identified from the differentially expressed genes.The R software"Neuralnet"package was then used to construct the osteoarthritis diagnosis model based on artificial neural network,and the model performance was evaluated by the five-fold cross-validation.Two independent data sets in the Test group were used to verify their diagnostic results. RESULTS AND CONCLUSION:A total of 90 differentially expressed genes related to osteoarthritis were obtained by differential analysis,of which 33 were down-regulated and 57 were up-regulated.GO enrichment analysis showed that the differentially expressed genes were mainly involved in the following biological processes,including leukocyte-mediated immunity,leukocyte migration in bone marrow and chemokine production.KEGG enrichment analysis showed that these genes were mainly enriched in rheumatoid arthritis,interleukin-17 signaling pathway and osteoclast differentiation pathway.Five key genes for the diagnosis of osteoarthritis,HMGB2,GADD45A,SLC19A2,TPPP3 and FOLR2,were identified by three machine learning methods.The artificial neural network model of five key genes in the Train group showed that the accuracy was 96.36%and the area under the curve was 0.997.The five-fold cross validation of the neural network model showed that the average area under the curve was greater than 0.9 and the model was of robustness.Two independent data sets in the Test group showed its area under the curve was 0.814 and 0.788 respectively.Therefore,the establishment of an artificial neural network model for the diagnosis of osteoarthritis has a certain diagnostic value.