BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.

Objective To understand the sleep status in patients with Parkinson's disease (PD), and to explore its relationship with dyskinesia and negative emotions. Methods A total of 308 patients with PD who met the inclusion and exclusion criteria in the hospital from September 2022 to May 2024 were selected as the research subjects. The scores of sleep status [Pittsburgh Sleep Quality Index (PSQI)], dyskinesia [Simplified Fugl-Meyer Motor Assessment (FMA)] and negative emotions [Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II)] were analyzed, and the PSQI score was compared among patients with different demographic characteristics. Pearson correlation analysis was performed to analyze the correlation of sleep with dyskinesia and negative emotions in patients with PD. Results The total score of PSQI scale was (6.16±0.97) points in 308 PD patients, of which 208 cases (67.53%) were complicated with sleep disorders. The proportions of female, 61-75 years old, technical secondary school or below, disease course of 4 years and above, Hoehn-Yahr stage IV and unmarried status in the sleep disorder group were higher than those in the non-sleep disorder group (P<0.05). Compared with the non-sleep disorder group, the FMA score in the sleep disorder group was lower (P<0.05) while the BAI score and BDI-II score were higher (P<0.05). Pearson correlation analysis revealed that PSQI was negatively correlated with FMA (r=-0.489, P<0.05), and was positively correlated with BAI and BDI-II (r=0.476, 0.502, P<0.05). Conclusion The incidence rate of sleep disorders in PD patients is high. PSQI is negatively correlated with FMA, and is positively correlated with BAI and BDI-II.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

Human NAD(P)H: quinone oxidoreductase 1 (NQO1) is a flavoenzyme expressed at high levels in multiple solid tumors, making it an attractive target for anticancer drugs. Bioactivatable drugs targeting NQO1, such as β-lapachone (β-lap), are currently in clinical trials for the treatment of cancer. β-Lap selectively kills NQO1-positive (NQO1⁺) cancer cells by inducing reactive oxygen species (ROS) via catalytic activation of NQO1. In this study, we demonstrated that cryptotanshinone (CTS), a naturally occurring compound, induces NQO1-dependent necrosis without affecting NQO1 activity. CTS selectively kills NQO1⁺ cancer cells by inducing NQO1-dependent necrosis. Interestingly, CTS directly binds to NQO1 but does not activate its catalytic activity. In addition, CTS enables activation of JNK1/2 and PARP, accumulation of iron and Ca²⁺, and depletion of ATP and NAD⁺. Furthermore, CTS selectively suppressed tumor growth in the NQO1⁺ xenograft models, which was reversed by NQO1 inhibitor and NQO1 shRNA. In conclusion, CTS induces NQO1-dependent necrosis via the JNK1/2/iron/PARP/NAD⁺/Ca²⁺ signaling pathway. This study demonstrates the non-enzymatic function of NQO1 in inducing cell death and provides new avenues for the design and development of NQO1-targeted anticancer drugs.

Objective:To identify the types of fear of progression in patients after percutaneous coronary intervention (PCI) based on latent profile analysis, and to explore the influencing factors of different types.Methods:Cross-sectional survey method was used to select the patients with coronary heart disease and underwent PCI in Anhui Public Health Clinical Center from April to December 2023 as the research object. The general information questionnaire, Fear of Progression Questionnaire-Short Form, Ruminative Response Scale and Brief Illness Perception Questionnaire were used to investigate them. Mplus8.3 software was used to construct the latent profile model.Results:A total of 240 patients with complete data were enrolled, including 176 males and 64 females, aged 28-84 (62.94 ± 11.20) years. The results of latent profile analysis showed that the fear of progression of patients after PCI could be divided into three latent categories: There were 59 cases (24.6%) in the low fear group, 111 cases (46.3%) in the medium fear group, and 70 cases (29.1%) in the high fear-worried family group. The results of multiple logistic regression analysis showed that compared with the low fear group, the probability of having primary school education or below was higher in the medium fear group ( OR=4.054, 95% CI 1.370-11.996) and the high fear-worry family group ( OR=5.996, 95% CI 1.562-23.014), secondary school was more likely in the moderate fear group ( OR=3.096, 95% CI 1.104-8.682, all P<0.05);Living in rural areas were more likely to be in the moderate fear group ( OR=2.587, 95% CI 1.187-5.637) and the high few-worry family group ( OR=6.958, 95% CI 2.567-18.856, all P<0.05); The probability of the first interventional therapy was higher in the moderate fear group ( OR=2.496, 95% CI 1.107-5.630) and the high fear-worry family group ( OR=4.924, 95% CI=1.809-13.402, all P<0.05). In addition, compared with the low fear group, patients with higher rumination were more likely to belong to the high few-worry family working group ( OR=1.130, 95% CI 1.055-1.210, P<0.05);Moderate fear group ( OR=1.181, 95% CI 1.046-1.334) and high fear family working group ( OR=1.349, 95% CI 1.164-1.562, all P<0.05) had a higher level of illness perception. Conclusions:There is significant heterogeneity in the fear of progression among patients after PCI. Medical staff can implement precise intervention according to the potential category characteristics of patients′ fear of progression, so as to reduce the level of fear of disease progression.

Norovirus is the global leading cause of epidemic and endemic acute gastroenteritis in people of all ages.To inves-tigate the genetic diversity of GⅡ genogroup noroviruses linked to clustered infections in northeast Chongqing,we collected anal swabs or environmental smears from 11 norovirus outbreaks during 2021-2022.Norovirus RNA was detected by quantitative real-time PCR(qRT-PCR),and partial viral RdRp/capsid genes were amplified by reverse transcription PCR(RT-PCR)and sequenced.Among samples from 11 outbreaks in 4 districts and counties,55 strains of GⅡ genogroup norovirus were detected.Six genotypes were identified with an online norovirus genotyping tool(http://www.rivm.nl/mpf/norovirus/typingtool).Genotype GⅡ.17[P17]was associated with four outbreaks;the co-circulating GⅡ.17[P17]and GⅡ.1[P16]caused another out-break;GⅡ.6[P7]and GⅡ.8[P8]respectively were linked to two outbreaks;and GⅡ.3[P12]and GⅡ.2[P16]respectively ac-counted for one outbreak.Phylogenetic analysis also indicated that 55 GⅡ genogroup strains formed five clusters,with norovir-uses of identical genotypes from diverse events belonging to the same cluster,and that genetically distinct genotypes from di-verse events belonged to different clusters.Therefore,our results revealed that multiple genotypes associated with norovirus outbreaks were circulating in northeast Chongqing,and GⅡ.17[P17]was the predominant genotype linked to these out-breaks during 2021-2022.Most norovirus outbreak events were caused by single sources,and genetic relationships were demonstrated among noroviruses of identical genotypes from diverse events.

The current treatment of glioma is facing drug resistance,which limits the efficacy of traditional chemotherapy drugs.This study aims to explore the potential mechanisms of the trifluoromethylquinazoline compound(KZL204)against glioma.Through the Cell Counting Kit-8(CCK-8)assay,we found that KZL204 significantly inhibits the growth of drug-resistant cancer cells,with a 48-hour half-maximal inhibitory concentration(IC50)of 3.63±0.38 μmol/L,which is significantly better than the positive control drug temozolomide(TMZ)(IC50 value of 81.67±5.49 μmol/L).Additionally,flow cytometry analysis showed that KZL204 treatment significantly increased the apoptosis rate of drug-resistant tumor cells and arrested the cell cycle at the G2/M phase.At the same time,the Transwell assay confirmed the inhibitory effect of KZL204 on the migration and invasion of drug-resistant cancer cells.Transcriptome analysis revealed 2 435 differentially expressed genes in drug-resistant cancer cells treated with KZL204,of which 1 320 were upregulated,and 1 115 were downregulated.KEGG and GO enrichment analysis showed that these differential genes were significantly enriched in apoptosis-related signaling pathways.Further bioinformatics prediction and Venn diagram analysis identified 35 potential core targets,with the PI3K-AKT signaling pathway being the most significant among the differentially expressed genes.Quantitative real-time PCR(RT-qPCR)experiments confirmed the downregulating effects of KZL204 on genes such as CREB3L1,CSF1,CXCL5,BCL3,and the upregulating effects on genes like FOS,LT A,PTGS2,MAP2K3.Immunoblotting experiments at the protein level also confirmed the impact of KZL204 on the expression of apoptotic proteins,including the upregulation of Bax,cleaved Caspase-3 protein,and the downregulation ofAKT,Bcl-2,Caspase-3,and Caspase-8 protein expression.In summary,KZL204 significantly inhibits the growth and metastasis of drug-resistant glioblastoma and induces apoptosis and cell cycle arrest by regulating the PI3K-AKT and apoptosis-related signaling pathways,demonstrating its potential as a candidate drug against drug-resistant glioma.

Objective To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE-/-mice.Methods The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE-/-mice.Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers.Results Proteomic analysis showed that there were 43 significantly up-regulated and 58 sig-nificantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group.Among them,GBP2,TAOK3,TFR1 and UCP1 were biomarkers with great diagnostic potential.KEGG pathway enrichment analysis indicated that fer-roptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model.The mmu_circ_0001567/miR-7a/Tfr-1 and mmu_circ_0001042/miR-7a/Tfr-1 might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model.Conclusion Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferrop-tosis.Four potential biomarkers are selected for myocardial injury diagnosis,providing a new direction for sudden cardiac death(SCD)caused by hyperlipidemia combined with the restraint stress.

Objective To investigate the effect and mechanism of proteasome inhibitor MG132 on memory impairment induced by chronic hypoxia in mice.Methods(1)A hypoxic model of the mouse midbrain dopaminergic neuron cell line MN9D was established using a hypoxia workstation.To observe the effects of hypoxia on the expression of TH,Ub-K48 and Ub-K63,MN9D cells were divided into normoxia group and hypoxia(12 h,24 h and 48 h)groups.To observe the effects of MG132 on the expression of the above-mentioned proteins,MN9D cells were divided into normoxia group,hypoxia group and hypoxia + MG132(25,50,100,200 μmol/L)group.(2)A mouse model of memory impairment was established using a hypobaric chamber.To observe the effects of hypobaric hypoxia on the expression of TH,Ub-K48 and Ub-K63 in the substantia nigra compacta(SNc)of mice,thirty C57BL/6 mice were randomly and equally divided into normoxia group and hypobaric hypoxia(3 d and 21 d)groups,10 in each group.To observe the effects of MG132 on spatial memory impairment induced by hypobaric hypoxia,twenty-four C57BL/6 mice were randomly and equally divided into normoxia group,hypobaric hypoxia 21 d group and hypobaric hypoxia 21 d+MG132 group,8 in each group.(3)The protein expression levels of TH,Ub-K48,and Ub-K63 in MN9D cells which were either subjected to different durations of hypoxia treatment or pre-treated with MG132 prior to hypoxia treatment were detected using Western blotting(WB).The novel object recognition test was used to detect the memory function of mice.Immunofluorescence was used to detect the proportion of positive immunoreactive area of TH response in the SNc region.The expression levels of TH,Ub-K48,and Ub-K63 in the SNc region were detected by WB.Results(1)Compared with normoxia group,MN9D cells in hypoxia 24 h group showed increasing expression of Ub-K48 and Ub-K63(P<0.05),and decreasing expression of TH(P<0.05),and MN9D cells in all hypoxia groups showed increasing expression of Ub-K48/TH and Ub-K63/TH(P<0.05).Compared with hypoxia group,MN9D cells showed decreasing expression of Ub-K48/TH and Ub-K63/TH in hypoxia + MG132 100 umol/L group and hypoxia + MG132 200 umol/L group(P<0.05).(2)Compared with the mice in normoxia group,mice in 3 d and 21 d hypobaric hypoxia groups showed decreasing expression of TH(P<0.001),and increasing expression of Ub-K48/TH and Ub-K63/TH(P<0.05)in the SNc region.Compared with normoxia group,the mice in 21 d hypobaric hypoxia group showed a lower new object recognition index(P<0.01),and the proportion of positive immunoreactive area of TH response in the SNc region(P<0.05).Compared with 21 d hypobaric hypoxia group,the mice in hypobaric hypoxia 21 d+MG132 group showed a higher new object recognition index(P<0.01).Conclusion The proteasome inhibitor MG132 could alleviate the memory impairment induced by chronic hypoxia in mice,and its mechanism may be related to the inhibition of Ub-K63 and Ub-K48,which in turn upregulates expression of TH in dopaminergic neurons.