Objective: To explore the effects of personality and sleep quality with psychological distress of junior and senior high school stduents, so as to provide a reference basis for precise interventions of junior and senior high school students mental health. Methods: In October 2023, a convenience sampling method was used to select 9 034 students aged 12-17 from Shiyan City as the study subjects. The Pittsburgh Sleep Quality Index (PSQI) and Kessler Psychological Distress Scale (K10) were used to collect information on sleep quality and psychological distress of junior and senior high school stduents. Between group comparison was conducted by using t-test and Chi-square test. Generalized linear models were employed to analyze the interaction and joint effects of personality and sleep quality on psychological distress. Results: The generalized linear model analysis showed that the interaction between personality and sleep quality on psychological distress was statistically significant of junior and senior high school students(effect size=0.80, P <0.01). The general linear model analysis indicated that, after adjusting for variables such as age, gender, screen time, and daily sitting time with the extroverted and good sleep quality group as the reference, the introverted and poor sleep quality group had the largest mean difference in psychological distress scores (difference=0.51, P <0.05). When stratified by sleep quality, psychological distress scores were higher in the introverted and neutral personality groups with both poor and good sleep quality compared to the extroverted group (poor sleep quality: introverted difference=3.71, neutral difference=1.14; good sleep quality: introverted difference=2.23, neutral difference=0.57, all P < 0.05). When stratified by personality, psychological distress scores were higher in the poor sleep quality groups for introverted, neutral, and extroverted individuals compared to their good sleep quality counterparts (differences=8.66, 7.83, 7.34, all P < 0.05 ). Conclusions Personality and sleep quality have interactive and joint effects on psychological distress of junior and senior high school stduents. Personalized psychological interventions should be developed based on personality and sleep quality.

ObjectiveTo elucidate the potential mechanisms by which the classic prescription Anmeidan alleviates cognitive impairment in insomnia model rats through metabolic profiling. MethodsA total of 60 SD rats were randomly divided into six groups： blank group， model group， low-， medium-， and high-dose Anmeidan groups， and the Suvorexant group， with 10 rats in each group. Except for the blank group， the insomnia model was established in all other groups via intraperitoneal injection of para-chlorophenylalanine. The Suvorexant group was administered Suvorexant solution （30 mg·kg^-1·d^-1） by gavage， while the low-， medium-， and high-dose Anmeidan groups received Anmeidan decoction （4.55， 9.09， 18.18 g·kg^-1·d^-1） by gavage. The blank group received an equivalent volume of normal saline. The open field test was used to assess spatial exploration and anxiety/depressive-like behaviors in rats. Serum levels of epidermal growth factor （EGF）， brain-derived neurotrophic factor （BDNF）， and vasoactive intestinal peptide （VIP） were measured using enzyme-linked immunosorbent assay （ELISA）. Untargeted metabolomics was employed to identify differential metabolites in rat serum， and systematic biological methods were applied to analyze the potential targets and pathways of Anmeidan. ResultsCompared to the blank group， the model group exhibited significant reductions in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.01）， along with significant decreases in VIP， EGF， and BDNF levels （P<0.05，P<0.01）. A total of 100 differential metabolites were identified between the model and blank groups. Compared to the model group， the low-， medium-， and high-dose Anmeidan groups showed significant increases in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.05，P<0.01）， as well as a significant increase in VIP levels （P<0.05，P<0.01）. Anmeidan significantly reversed abnormal changes in 67 metabolites compared to the model group. A combined analysis identified 134 potential targets of Anmeidan， with network topology analysis suggesting that Caspase-3， B-cell lymphoma 2 （Bcl-2）， nuclear transcription factor-κB （NF-κB）， interleukin-1β （IL-1β）， interleukin-2 （IL-2）， matrix metalloproteinase-9 （MMP-9）， and Toll-like receptor 4 （TLR4）， among others， may serve as key targets of Anmeidan. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis revealed major enriched pathways， including the cyclic adenosine monophosphate （cAMP） signaling pathway， hypoxia inducible factor-1 （HIF-1） signaling pathway， and IL-17 signaling pathway. ConclusionThis study demonstrates that Anmeidan can recalibrate abnormal metabolic profiles in insomnia model rats to mitigate cognitive impairment， with its mechanisms of action potentially involving the regulation of immune-inflammatory responses， energy metabolism， and apoptosis-related pathways.

AIM: To investigate the relationship between Apelin and δ-like ligand 4(DLL4)expression levels and clinical stage and efficacy in patients with neovascular glaucoma(NVG).METHODS: A total of 96 NVG patients(96 eyes)who were admitted to our hospital from January 2022 to March 2024(NVG group)and 96 cataract patients(96 eyes)who underwent cataract surgery in our hospital during the same period(control group)were selected. NVG patients were divided into stage Ⅰ group(22 eyes), stage Ⅱ group(47 eyes)and stage Ⅲ group(27 eyes)according to the clinical stage; furthermore, patients were divided into ineffective group(20 eyes)and effective group(76 eyes)according to efficacy. Aqueous humor Apelin and DLL4 levels were detected by enzyme-linked immunosorbent assay. The influencing factors of the efficacy in NVG patients were analyzed by multivariate unconditional Logistic regression analysis, the evaluation efficiency of aqueous humor Apelin and DLL4 levels on the efficacy in NVG patients was analyzed by receiver operating characteristic(ROC)curve.RESULTS: Compared with the control group, aqueous humor Apelin and DLL4 levels in the NVG group were increased(all P<0.001). Aqueous humor Apelin and DLL4 levels in the stage Ⅰ, stage Ⅱ and stage Ⅲ groups increased in turn(all P<0.001). The effective rate of 96 NVG patients was 79.2%(76/96). Compared with the effective group, aqueous humor Apelin and DLL4 levels in the ineffective group increased(all P<0.001). Clinical stage III, high intraocular pressure, high Apelin and DLL4 were independent risk factors for ineffective treatment in NVG patients(all P<0.05). The area under the curve of the combined evaluation of aqueous humor Apelin and DLL4 levels in evaluating the efficacy of NVG patients was 0.874, which was greater than 0.790 and 0.786 of aqueous Apelin and DLL4 levels alone(all P<0.05).CONCLUSION: Aqueous humor Apelin and DLL4 levels in NVG patients increase, which relate to the increase of clinical stage and poor efficacy, and the combination of aqueous humor Apelin and DLL4 levels is more effective in evaluating the efficacy of NVG patients.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

This study aimed to explore the molecular mechanism of rubioncolin C(RuC) in inhibiting gastric cancer(GC). AGS and MGC803 cell lines were selected as cellular models. After treating the cells with RuC at different concentrations, the effects of RuC on the proliferation ability of GC cells were assessed using the CCK-8 method, real-time cellular analysis(RTCA), and colony formation assays. Transmission electron microscopy was used to observe subcellular structural changes. Immunofluorescence was applied to detect LC3 fluorescent foci. Acridine orange staining was used to evaluate the state of intracellular lysosomes. Western blot was employed to detect the expression of autophagy-related proteins LC3Ⅱ, P62, and lysosomal cathepsin D(CTSD). The SuperPred online tool was used to predict the target proteins that bound to RuC, and molecular docking analysis was conducted to identify the interaction sites between RuC and CTSD. The drug affinity responsive target stability(DARTS) assay was performed to detect the direct binding interaction between RuC and CTSD. The results showed that RuC significantly inhibited the proliferation and colony formation of GC cells at low concentrations, with 24-hour half-maximal inhibitory concentrations(IC_(50)) of 3.422 and 2.697 μmol·L~(-1) for AGS and MGC803 cells, respectively. After 24 hours of treatment with RuC at concentrations of 1, 2, and 3 μmol·L~(-1), the colony formation rates for AGS cells were 61.0%±1.5%, 28.0%±0.5%, and 18.2%±0.5%, respectively, while the rates for MGC803 cells were 56.0%±0.5%, 23.3%±1.0%, and 11.8%±1.0%, all of which were significantly reduced. Transmission electron microscopy revealed that RuC promoted an increase in autophagosome formation in GC cells. Immunofluorescence detection showed that LC3 fluorescent foci of GC cells increased with the increase in RuC dose. RuC up-regulated the expression of autophagy-related proteins LC3Ⅱ and P62 in GC cells. Acridine orange staining indicated that RuC altered the acidic environment of lysosomes. SuperPred online prediction identified CTSD as a potential target protein of RuC. Western blot analysis revealed that RuC induced the up-regulation of the inactive precursor of CTSD in GC cells. CTSD activity assays indicated that RuC reduced the activity of CTSD. Molecular docking simulations found that RuC bound to the substrate-binding region of CTSD, forming hydrogen bonds with the Tyr205 and Asp231 residues. Microscale thermophoresis and DARTS assays further confirmed that RuC directly bound to CTSD. In summary, RuC inhibits lysosomal activity by targeting and down-regulating the expression of CTSD, thereby inducing autophagosome accumulation in GC cells.
Humans ; Stomach Neoplasms/enzymology* ; Cathepsin D/chemistry* ; Cell Line, Tumor ; Molecular Docking Simulation ; Cell Proliferation/drug effects* ; Autophagosomes/metabolism* ; Autophagy/drug effects*

OBJECTIVE To estimate the quality markers of antioxidant activity for standard decoction of Schisandrae Chinensis Fructus.METHODS 15 batches of Schisandrae Chinensis Fructus standard decoctions were subjected to quality evaluation by ultra high-performance liquid chromatography(UPLC)based on single-marker(QAMS)method,before being summarized by chemometrics analysis.The antioxidant abilities of 15 batches of samples were determined by DPPH and ABTS methods,while gray correlation analy-sis(GRA)and the partial least squares regression(PLSR)methods were subsequently applied to investigating the relationship between the contents of 8 components and the antioxidant activity.Ultimately,molecule docking was utilized to explore the binding properties between candidate quality markers and the core targets of anti-oxidation,with the experimental verification being executed on the indi-vidual compound by in vitro anti-oxidation.RESULTS There was no remarkable difference between the results of QAMS and external standard method(ESM),with P valued greater than 0.05.And it was speculated that protocatechuic acid,gomisin A,schizantherin B and schisandrin B were the constituents of quality difference.Moreover,the 4 quality variation components were reckoned to be the al-ternative markers on antioxidant according to the results of GRA and PLSR.The molecule docking result also showed that 4 candidate quality markers presented good binding affinity with the antioxidant core targets.The antioxidant capacity was presumably originated from the collaborated effects by multi-components in the standard decoction of Schisandrae Chinensis Fructus.In the interim,protocate-chuic acid exhibited noteworthy antioxidant efficacy with dosage-depended manner in the results of single-compound verification,which was best conformed to the characteristics of quality markers and supposed to be the antioxidant quality marker for Schisandrae Chinensis Fructus standard decoction.CONCLUSION This research predicts the potential antioxidant substances on the basis of content deter-mination by UPLC and in vitro antioxidant assay,but also provides rational foundation for quality assessment on other preparations of Schisandrae Chinensis Fructus.

Objective To investigate the epidemiological characteristics and changing trend of malignant tumor death in Danjiangkou City, the water source area along the middle route of South-to-North Water Diversion Project. Methods The surveillance data of cancer death cases in Danjiangkou City from 2015 to 2022 were collected, and the mortality rate, gender mortality rate, age-specific mortality rate and the rank of cancer cause of death were calculated. Joinpoint regression model was used to analyze the trend of malignant tumor mortality and standardized mortality. Annual percentage change (APC) and average annual percentage change (AAPC) were calculated to analyze the trend changes. Results From 2015 to 2022, a total of 6 254 deaths from malignant tumors were reported in Danjiangkou City, with a crude mortality rate of 178.57/100 000 and a standardized mortality rate of 152.77/100 000. There were 4 366 male deaths, and the crude mortality and standardized mortality were 244.70/100 000 and 212.87/100 000 , respectively. There were 1 888 female deaths, and the crude mortality rate and the standardized mortality rate were 109.89/100 000 and 92.69/100 000, respectively. The crude death rate of malignant tumors in the whole population in Danjiangkou City showed an increasing trend from 2015 to 2022, and the difference was statistically significant (AAPC=5.18%, t=4.07, P<0.05). The crude mortality rates of malignant tumors in both men and women showed an upward trend, and the differences were statistically significant (AAPC =5.56% and 4.35%, both P<0.05). The standardized mortality rates of malignant tumors in the whole population, women and men remained stable, and the differences were not statistically significant (AAPC=0.68, 1.59 and -0.74, all P>0.05). The trend analysis of age-specific mortality of malignant tumors showed that the age-specific mortality of malignant tumors in the whole population, men and women showed an increasing trend with age, and the differences were statistically significant (AAPC =9.22%, 9.40% and 8.53%, P<0.05). The mortality rate of malignant tumors in 0-, 1-, 10-, 45- and 70- age groups decreased year by year (AAPC =-79.62%, -7.19%, -65.99%, -8.88%, and -5.83%, all P<0.05). The mortality rate in the age group of over 75 years old showed an increasing trend (AAPC =12.24%, P<0.05), and the differences were statistically significant. The top 10 malignant tumor deaths in the whole population were lung cancer, gastric cancer, liver cancer, esophageal cancer, colorectal cancer , leukemia , pancreatic cancer , breast cancer , brain malignant tumor and cervical cancer, accounting for 88.49% of all malignant tumor deaths. Mortality rates in lung cancer (AAPC =6.75%), esophageal cancer (AAPC=11.24%), colorectal cancer (AAPC =12.95%), leukemia (AAPC=8.10%), pancreatic cancer (AAPC=15.11%), breast cancer (AAPC=13.11%) and brain malignancies (AAPC=11.16%) showed an increasing trend, and the differences were statistical significant (P<0.05). Conclusion Malignant tumor is the main cause of death in Danjiangkou City. The death rate increases year by year and increases with age. Lung cancer, stomach cancer and liver cancer are the main causes of death. Men and the elderly are high-risk groups of malignant tumors. Early detection and treatment of malignant tumors should be strengthened to reduce the incidence and death.

Objective To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases. Methods A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.

Objective To analyze the prevalence, annual trends, and co-morbidity trends of common chronic diseases among workers in a large automotive industry from 2019 to 2021, and to provide a scientific basis for the health management of workers in the automotive industry. Methods The health examination data of workers in a large automotive industry from 2019-2021 were analyzed. Trends in the prevalence of chronic diseases and co-morbidities were analyzed using Join Point software and trend χ² test. Results The prevalence of metabolic syndrome, hyperuricemia, and fatty liver in the 2019 – 2021 health checkups of workers in this enterprise increased at an average rate of 9.27%, 11.35%, and 3.99% per year, respectively. The prevalence of metabolic syndrome, hyperuricemia, and fatty liver in male workers showed an increasing trend at an average rate of 7.05%, 9.25%, and 2.91% per year, respectively. The prevalence of metabolic syndrome in female workers showed an increasing trend at an average rate of 20.76% per year. The prevalence of metabolic syndrome, hyperuricemia and fatty liver was on the rise in the age groups ≤ 29 years old and 40 – 49 years old. The proportion of metabolic syndrome and its co-morbidity with one or two common chronic diseases showed an increasing trend. Conclusion The prevalence and co-morbidity of common chronic diseases in this enterprise are generally on the rise. The enterprise should focus on health education and preventive care for chronic diseases among workers aged ≤ 29 and 40 – 49 years old and male workers and control the annual increasing trend of metabolic syndrome among female workers and workers in the age group ≤ 29 years.

Objective:To explore the correlation between clinical classification and genotype and prognosis among Chinese children with Very-long chain acyl-CoA dehydrogenase deficiency (VLCADD).Methods:A Chinese pedigree affected with VLCADD admitted at the First People′s Hospital of Yunnan Province in February 2019 was selected as the study subject. The characteristics of disease onset, diagnosis and treatment and prognosis were retrospectively analyzed. Relevant literature was also systematically searched and reviewed.Results:The proband, a 1-year-old boy, had the clinical manifestations of frequently vomiting, hypoglycemia, abnormal liver function and myocardial enzymes. Tandem mass spectrometry screening showed significantly elevated C14, C14: 1, C16: 1, C16: 2, C18 and C14/C8. Genetic testing revealed that he has harbored compound heterozygous variants of the ACADVL gene, namely c. 664G>A (p.G222R) and c. 1345G>A (p.E449K), which were respectively derived from his father and mother. The child was diagnosed with VLCADD cardiomyopathy type and deceased 2 weeks later. Literature review has identified 60 Chinese children with VLCADD. The clinical classifications were mainly cardiomyopathy type and liver disease type, which accounted for 73.3% (43/60). The combination of ACADVL gene variants were correlated with the clinical classifications of VLCAD. Children with one or two loss-of-function (LOF) mutations showed more severe clinical manifestation and a higher mortality. Cardiomyopathy type had the poorest prognosis, with a mortality rate of 76.9% (20/26). C14: 1 may be used as an indicator for the diagnosis of VLCADD, but cannot be used for clinical subtyping and prognosis evaluation. The c. 1349G>A (p.R450H) variant had the highest frequency among the Chinese patients, accounting for 10.8% (13/120). Conclusion:The clinical classifications of VLCADD are strongly correlated with the prognosis, and LOF mutations are more common in those with severe clinical manifestations. c. 1349G>A (p.R450H) may be the most common variant among the Chinese patients, and early screening and diagnosis can greatly improve the prognosis of patients.