Mitochondrial dysfunction in chondrocytes is a key pathogenic factor in osteoarthritis (OA), but directly modulating mitochondria in vivo remains a significant challenge. This study is the first to verify a correlation between mitochondrial dysfunction and the downregulation of the FOXO3 gene in the cartilage of OA patients, highlighting the potential for regulating mitophagy via FOXO3 gene modulation to alleviate OA. Consequently, we developed a chondrocyte-targeting CRISPR/Cas9-based FOXO3 gene-editing tool (FoxO3) and integrated it within a nanoengineered 'truck' (NETT, FoxO3-NETT). This was further encapsulated in injectable hydrogel microspheres (FoxO3-NETT@SMs) to harness the antioxidant properties of sodium alginate and the enhanced lubrication of hybrid exosomes. Collectively, these FoxO3-NETT@SMs successfully activate mitophagy and rebalance mitochondrial function in OA chondrocytes through the Foxo3 gene-modulated PINK1/Parkin pathway. As a result, FoxO3-NETT@SMs stimulate chondrocytes proliferation, migration, and ECM production in vitro, and effectively alleviate OA progression in vivo, demonstrating significant potential for clinical applications.

Transcranial temporal interference stimulation (tTIS) is a novel non-invasive neuromodulation technique with the potential to precisely target deep brain structures. This study explores the neural and behavioral effects of tTIS on the superior colliculus (SC), a region involved in eye movement control, in mice. Computational modeling revealed that tTIS delivers more focused stimulation to the SC than traditional transcranial alternating current stimulation. In vivo experiments, including Ca²⁺ signal recordings and eye movement tracking, showed that tTIS effectively modulates SC neural activity and induces eye movements. A significant correlation was found between stimulation frequency and saccade frequency, suggesting direct tTIS-induced modulation of SC activity. These results demonstrate the precision of tTIS in targeting deep brain regions and regulating eye movements, highlighting its potential for neuroscientific research and therapeutic applications.
Animals ; Superior Colliculi/physiology* ; Transcranial Direct Current Stimulation/methods* ; Eye Movements/physiology* ; Male ; Mice ; Mice, Inbred C57BL

Objective To understand the genotyping of human immunodeficiency virus (HIV) co-infected hepatitis C virus (HCV) patients in Yunnan Province, and to analyze the differences in viral load, biochemical indicators, and blood routine indicators among different genotypes, in order to provide a laboratory basis for the diagnosis and clinical treatment of HIV/HCV co-infected patients. Methods From November 2022 to June 2023, the serum samples and basic information of patients diagnosed with HIV/HCV co-infection were collected in the antiviral outpatient clinic of Yunnan Provincial Hospital of Infectious Diseases. The HCV viral load was detected by one-step qRT-PCR amplification, the positive samples were sequenced, and genotyping was determined based on NS5 gene sequence. The differences in biochemical and blood routine indexes between HIV patients co-infected with different HCV genotypes and low/high viral loads were analyzed. Results A total of 126 HIV/HCV co-infected patients were collected, including 20 HCV genotype 1 (15.9%), 91 HCV genotype 3 (72.2%), and 15 HCV genotype 6 (11.9%). The maximum and minimum viral load of the three HCV genotypes were as follows: HCV type 1 (1.0×108, 4.8×104 IU/mL), HCV type 3 (2.2×108, 2.9×102 IU/mL), and HCV type 6 (8.1×107, 6.8×104 IU/mL). The results showed that there was no significant difference between HIV co-infection with different genotypes of HCV and three HIV treatment schemes, including nucleoside reverse transcriptase inhibitors+integrase strand transfer inhibitors (NRTIs+INSTIs), nucleoside reverse transcriptase inhibitors+non-nucleoside reverse transcriptase inhibitors (NRTIs+NNRTIs) and nucleoside reverse transcriptase inhibitors+protease inhibitor (NRTIs+PLs), and the viral load of patients (P>0.05). The analysis of biochemical indexes such as total bilirubin (TBIL), direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CREA), and blood routine indexes such as white blood cell (WBC), red blood cell (RBC), hemoglobin (HGB), platelet (PLT), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) among different HCV genotypes and low/high viral loads showed that there was no significant difference in biochemical indexes and blood routine indexes between low/high viral loads of HIV co-infected HCV patients (P>0.05); however, the biochemical indicators TBIL, IBIL and MCHC were significantly different statistically between patients with genotype 3 HCV infection and those with genotype 1 HCV infection (P<0.05), while other biochemical and blood routine indexes were not statistically different among different HCV genotypes (P>0.05). Conclusions There are six subtypes of HCV co-infection in HIV patients in Kunming, Yunnan Province, including three genes of genotype 1, 3, and 6. Among them, genotype 3 HCV is the main prevalent genetic virus among HIV co-infected populations. The TBIL, IBIL and MCHC values of HIV patients co-infected with HCV type 3 are different from those infected with HCV type 1.

ObjectiveTo investigate the genotyping and drug resistance trends of 461 strains of diarrheagenic Escherichia coli (DEC) isolated and identified in Suzhou, Jiangsu Province from 2019 to 2023. MethodsDEC detected in Suzhou in the past 5 years was used as the research subject, and the virulence genotyping was tested by real-time fluorescence quantitative polymerase chain reaction (PCR). The microbroth dilution method was used to perform drug susceptibility test, and the corresponding susceptibility (S), intermediate (I) and resistance (R) results were obtained based on the minimum inhibitory concentration (MIC) values, according to the criteria of United States Clinical and Laboratory Standardization Committee (CLSI) 2017. Differences of DEC drug resistance among different virulence genotypes were compared by χ² test or Fisher exact probability method. ResultsA total of 461 DEC strains were detected in Suzhou from 2019 to 2023, of which the highest proportion was enterotoxigenic Escherichia coli (ETEC) accounting for 45.77% (211/461), followed by enteropathogenic Escherichia coli (EPEC) accounting for 32.32% (149/461) and enteroaggregative Escherichia coli (EAEC) accounting for 20.39% (94/461), while enterohemor-rhagic Escherichia coli (EHEC) and enteroinvasive Escherichia coli (EIEC) were individually distributed. The antimicrobial drug with the highest resistance rate was ampicillin (61.61%), followed by cefazolin (49.89%) and nalidixic acid (44.47%). There were statistically significant differences in drug resistence rates of the three major virulence genotypes of DEC (ETEC, EPEC and EAEC) to ampicillin (AMP), ampicillin/sulbactam (AMS), amoxicillin/clavulanic acid (AMC), cefoxetine (CFX), gentamicin (GEN), streptomycin (STR), tetracycline (TET), nalidixic acid (NAL), and chloramphenicol (CHL), and methotrexate/sulfamethoxazole (SXT). The multi-drug resistance (MDR) rate of DEC was 59.87% (276/461), and the MDR rate of each genotype, from high to low, was EIEC (75.00%), EAEC (71.28%), EHEC (66.66%), EPEC (61.74%) and ETEC (52.86%). ConclusionETEC, EPEC and EAEC are the main genotypes prevalent in DEC in Suzhou in recent years. The drug resistance strains and MDR are still serious, which should arouse wide public health concern and take targeted prevention and control measures.

Objective To develop and validate a fatigue risk nomogram model in Chronic Obstructive Pulmonary Disease(COPD)patients.Methods A prospective study design was adopted,and 430 COPD patients recruited from a tertiary A hospital in Huzhou City from January to December 2022 were conveniently selected for model construction,and 129 patients were recruited from the same hospital from January to June 2023 for external validation of the model.The general information questionnaire,Pittsburgh Sleep Quality Index,2-item Generalized Anxiety Disorder Scale,2-item Patient Health Questionnaire,modified British Medical Research Council Dyspnea Index,International Physical Activity Questionnaire,and Fatigue Severity Scale were used for questionnaire survey.The risk prediction model and nomograms model were constructed using Logistic regression analysis and R 4.3.2 software,and the area under the receiver operating characteristic(ROC)curve was used to test the prediction effect of the model.Results Univariate and binary logistic regression analysis results showed that age(OR=1.095),gender(OR=2.077),dyspnea(OR=3.309),sleep quality(OR=1.979),anemia(OR=3.289),the number of acute exacerbation(OR=2.991)were independent influencing factors for fatigue in COPD patients.The internal evaluation and external validation results of the model showed that the areas under the curve are 0.912 and 0.844 respectively,and the Hosmer-Lemeshow goodness of fit test P values were 0.806 and 0.526 respectively.The average absolute errors were 0.013 and 0.019 respectively.Conclusion The COPD fatigue risk prediction model constructed in this study has good prediction effect.The visual nomogram is intuitive,convenient and easy to operate.It can provide a tool for early screening of fatigue in COPD patients.

Objective:To explore the mediating effect of psychological resilience between structural empowerment and work engagement of clinical nurses.Methods:This study was a cross-sectional study. Using the convenient sampling method, a total of 1 723 nurses from three Class Ⅲ Grade A hospitals in Henan Province were selected as the research objects from March to May 2023. The survey was conducted using general information questionnaire, Conditions of Work Effectiveness Questionnaire-Ⅱ (CWEQ-Ⅱ), Nurses Psychological Resilience Scale and Utrecht Work Engagement Scale (UWES). Pearson correlation analysis was used to explore the correlation between structural empowerment, psychological resilience and job engagement. AMOS 24.0 software was used to establish the structural equation model and analyze the mediating effect.Results:A total of 1 723 questionnaires were sent out in this study, and 1 590 were effectively collected, with an effective recovery rate of 92.28%. The total scores of structural empowerment, psychological resilience and job engagement of 1 590 clinical nurses were (70.42±15.61), (96.84±13.15) and (62.24±11.02), respectively. Pearson correlation analysis showed that job engagement was positively correlated with structural empowerment and psychological resilience ( r=0.637, 0.670, P<0.01). The results of structural equation model showed that psychological resilience had a partial mediating effect between structural empowerment and job engagement. The mediating effect value was 0.321, accounting for 48.86% of the total effect. Conclusions:In this study, the structural empowerment, psychological resilience and job engagement of clinical nurses are above the medium level, and psychological resilience has a partial mediating effect between structural empowerment and job engagement. Nursing managers should fully empower nurses at the organizational level, take targeted measures to improve their psychological resilience and enhance their level of work engagement.

Objective:To develop the Clinical Nurse Extra Task Load Scale and test its reliability and validity.Methods:Based on the job demand-control model, a primary scale was formed through literature search and qualitative interviews, as well as Delphi consultation and pre-survey. In September 2023, 813 clinical nurses from First Affiliated Hospital of Xinxiang Medical University and Xinxiang Central Hospital were selected for reliability and validity testing. In October 2023, 1 050 clinical nurses from First Affiliated Hospital of Xinxiang Medical University and Xinxiang Central Hospital were selected for investigation, and the reliability and validity of the scale were tested.Results:The final Clinical Nurse Extra Task Load Scale included two dimensions and a total of 12 items. The item-level content validity index was 0.86 to 1.00, and the scale-level content validity index was 0.84. Exploratory factor analysis extracted two common factors, with a cumulative variance contribution rate of 74.55%. Confirmatory factor analysis showed that χ 2/ df was 1.613, GFI was 0.928, CFI was 0.971, NFI was 0.928, IFI was 0.971, and RMSEA was 0.024. Cronbach's α coefficient of the work environment demand dimension was 0.897, Cronbach's α coefficient of individual behavior restriction was 0.955, Cronbach's α coefficient of the total scale was 0.950, and the split-half reliability was 0.850. Conclusions:The Clinical Nurse Extra Task Load Scale developed has a good reliability and validity, and can be used to evaluate and quantify the extra task load for clinical nurses.

Objective:To construct a hypoglycemia random forest prediction model for older adults with type 2 diabetes, and assess the model′s prognostication performance through internal and external verification.Methods:From August 2022 to January 2023, 300 older adults with type 2 diabetes in Beijing Hospital were selected. The demographic characteristics, medical history, laboratory tests, and other data of the patients were collected, and the data set was randomly divided into the training set and verification set in a ratio of 7∶3. The hypoglycemia prediction model for older adults with type 2 diabetes was constructed and optimized based on the random forest algorithm. The calibration curve was used to evaluate the model′s calibration, and the ROC was used to evaluate the model′s discrimination. The clinical applicability of the model was assessed by the decision curve analysis. The risk factors for hypoglycemia in the older adults were explored by prioritizing the contributions of variables in prediction. The Bootstrap method was used for internal validation, and the validation set was used for external validation.Results:Among the 300 older adults with type 2 diabetes, 128 cases (42.67%) experienced hypoglycemia within one week. The predictive contributions of risk factors in the model were ranked as follows: the number of episodes of hypoglycemia in one month, HDL-C, heart disease, diabetes knowledge and education, combination therapy, age, duration of diabetes, staple food restriction, glycosylated hemoglobin, and gender. The internal and external calibration curves of the hypoglycemia random forest model for the older adults with type 2 diabetes fluctuated around the diagonal, indicating that the calibration degree of the predictive model is good. The AUROC of internal verification was 0.823 (95% CI 0.752-0.894), the sensitivity and specificity were 0.867 and 0.698, respectively. The external verification was 0.859 (95% CI 0.817 - 0.902), and sensitivity and specificity were 0.789 and 0.804, respectively, showing that the overall discrimination of the prediction model was good. The DCA curves were far from the all-positive line and all-negative line, which indicated that the prediction model had good clinical applicability. Conclusions:The predictive effect of this model is good, and it is suitable for predicting the risk of hypoglycemia in older adults with type 2 diabetes, and it provides a reference for early hypoglycemia screening and predictive intervention for this kind of patients.

AIM: To investigate the changes of bile acid metabolism in healthy adults after taking acetaminophen. METHODS: Ten healthy subjects were enrolled and the serum samples of subjects before and after multiple administration of acetaminophen were collected. They were divided into pre-dose group (PD), fifth-dose gro-up (FD) and eighth-dose group (ED). A high performance liquid chromatography-tandem mass spectrometric method (HPLC-MS/MS) was used to quantify 15 target-edbile acid metabolites in human plasma, combined with principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA)to investigate the changes of bile acid metabolism profile in healthy adults after taking acetaminophen. And the biochemical indicators of each group were detected. RESULTS: There was a change in the bile acid spectrum of human serum after taking acetaminophen. Compared with group PD, the taurochenodeoxycholicacid (TCDCA), glycocholicacid (GCA), glycochenodeoxycholic acid (GCDCA) and tauroursodeoxycholic acid (TUDCA) levels were significantly increased (P<0.05). There was no obvious changes in biochemical indicators. GCA and GCDCA were the most sen-sitive indicators of bile acid. CONCLUSION: GCA and GCDCA can be used as potential biomarkers of early liver injury caused by acetaminophen.

Objective: To explore the expression of KIF20A (kinesin family member 20A) in colorectal cancer (CRC) tissues and adjacent normal tissues, and to analyze the relationship between KIF20A expression level and clinicopathological factors in CRC patients. Meth-ods: Data from The Cancer Genome Atlas (TCGA) database were used to analyze KIF20A mRNA expression in CRC tissues and adjacent normal tissues. A total of 105 paraffin samples were obtained from CRC patients who had undergone surgery at Huai He Hospital of Henan University, from January 2011 to December 2012. Immunohistochemical staining (IHC) was performed to examine KIF20A pro-tein expression in tumor samples for which complete clinical and pathological data were available. Statistical analyses were applied to analyze the association between KIF20A expression and the clinical data, as well as with survival outcomes. Results: Bioinformatics analysis showed that the mRNA expression level of KIF20A was upregulated in CRC tissues and normal tissues (P<0.001). IHC revealed significantly higher expression of KIF20A in CRC tissues from 67 patients (64%) and lower or undetectable expression in 38 patients (36%). The difference was statistically significant (P<0.05). Overexpression of KIF20A in CRC tissues was significantly associated with depth of invasion, lymphatic node metastasis, distant metastasis, and TNM stage (all P<0.05). Kaplan-Meier survival analysis showed that patients with high levels of KIF20A expression had poor prognosis compared to patients with low levels of KIF20A expression. Cox proportional hazard regression analysis revealed that KIF20A was an independent prognostic factor in patients with CRC. Conclusions:KIF20A is upregulated in CRC tissues and could serve as a novel prognostic biomarker for CRC patients.