ObjectiveTo explore the relationship between acne vulgaris and gut microbiota. MethodsA total of 29 clinical cases diagnosed with moderate-to-severe acne vulgaris and 26 healthy individuals as control subjects were recruited. Fecal specimens were collected from all participants， and further analysis of gut microbial communities was performed by leveraging high-throughput sequencing techniques that target the hypervariable regions of 16S rRNA genes. ResultsAssociations between acne vulgaris and alterations in gut microbiota were identified. At the phylum level， the relative abundance of Bacteroidota exhibited a statistically significant elevation in the acne vulgaris cohort when compared with the healthy control group （P<0.01）， while Cyanobacteria was significantly lower in the acne group （P<0.01）. At the genus level， the top five different bacterial taxa in both groups were Bacteroides， Escherichia⁃Shigella， Klebsiella， Roseburia， and Parabacteroides. Among them， Bacteroides， Roseburia， and Parabacteroides were more abundant in acne patients. Linear discriminant analysis identified five biomarkers all belonging to the Bacteroidota phylum in the acne and control groups. These biomarkers belong to the phylum Bacteroidetes. ConclusionThere are significant differences in the composition of intestinal microbiota between acne patients and healthy people. Changes in the richness of specific bacterial genera may become new targets for the diagnosis and treatment of acne.

Background China is a major coal producer and consumer country in the world. Coal workers' pneumoconiosis (CWP) is a primary factor endangering the occupational health of coal miners. Research on the disease burden of CWP and its changing trend is significant for disease prevention & control and associated policies. Objective To analyze the disease burden of CWP in China from 1990 to 2021 and its changing trend, and predict the disease burden from 2022 to 2035. Methods Using the Global Burden of Disease Study (GBD) database of 2021, numbers ofincident cases, prevalent cases, deaths, and disability-adjusted life years (DALYs) as well as crude and age-standardized rates of CWP in China were retrieved. Linear regression model was used to calculate the estimated annual percentage change (EAPC) of the age-standardized rates. Joinpoint regression model was used to analyze the temporal trend of disease burden and the disease burden of different sexes and age groups, and Bayesian age-period-cohort (BAPC) model was used to forecast the trend of CWP disease burden. Results In 1990, the incident, prevalent, and deaths cases of CWP in China were 3266, 18872, and 1561, respectively, and the DALYs of CWP were 44614.718 person-years. In 2021, the incident, prevalent, and deaths cases of CWP were 3446, 23975, and 1229, respectively, and the DALYs of CWP were 29610.754 person-years. From 1990 to 2021, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP in China all showed a downward trend, with the EAPCs of −3.121%, −2.532%, −4.018%, and −4.268%, respectively. The disease burden of CWP in China was mainly concentrated in the male population. The annual average percent change analysis indicated that each standardized rate showed a fluctuating downward trend in different periods. The BAPC model showed that from 2022 to 2035, the age-standardized rates of CWP in China would continue to decline steadily. In 2035, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP would be reduced to 0.10 per 100000, 0.74 per 100000, 0.03 per 100000, and 0.74 per 100000, respectively. Conclusion The disease burden contributed by CWP in China generally show a downward trend from 1990 to 2021, and it is expected that the age-standardized rates will continue to decline steadily from 2022 to 2035.

INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency department (ED) physicians on a binomial classification task. METHODS: A total of 1,314 paediatric elbow lateral radiographs (patient mean age 8.2 years) were retrospectively retrieved and classified based on annotation as normal or abnormal (with pathology). They were then randomly partitioned to a development set (993 images); first and second tuning (validation) sets (109 and 100 images, respectively); and a test set (112 images). An artificial intelligence (AI) model was trained on the development set using the EfficientNet B1 network architecture. Its performance on the test set was compared to that of five physicians (inter-rater agreement: fair). Performance of the AI model and the physician group was tested using McNemar test. RESULTS: The accuracy of the AI model on the test set was 80.4% (95% confidence interval [CI] 71.8%-87.3%), and the area under the receiver operating characteristic curve (AUROC) was 0.872 (95% CI 0.831-0.947). The performance of the AI model vs. the physician group on the test set was: sensitivity 79.0% (95% CI: 68.4%-89.5%) vs. 64.9% (95% CI: 52.5%-77.3%; P = 0.088); and specificity 81.8% (95% CI: 71.6%-92.0%) vs. 87.3% (95% CI: 78.5%-96.1%; P = 0.439). CONCLUSION The AI model showed good AUROC values and higher sensitivity, with the P-value at nominal significance when compared to the clinician group.
Humans ; Deep Learning ; Child ; Retrospective Studies ; Male ; Female ; Radiography/methods* ; ROC Curve ; Elbow/diagnostic imaging* ; Neural Networks, Computer ; Child, Preschool ; Elbow Joint/diagnostic imaging* ; Emergency Service, Hospital ; Adolescent ; Infant ; Artificial Intelligence

OBJECTIVE: To construct a predictive model for the reduction in methadone maintenance treatment (MMT) and evaluate the effects of different interventions and other clinical factors on methadone reduction using Shapley additive explanations (SHAP). METHODS: Two clinical trials of acupuncture for methadone reduction in MMT patients were analyzed, and the baseline data, MMT related information, intervention measures, the data related to dose-reduction outcomes were collected. The predictive model was constructed by means of 6 machine learning algorithms including support vector machine (SVM), K-nearest neighbors (KNN), logistic regression (LR), Naive Bayes (NB), random forest (RF) and categorical-boosting (CatBoost), and 2 integration methods, blending-ensemble method (Blending) and Stacking-ensemble method (Stacking). SHAP was employed for the interpretability analysis of the optimal model. RESULTS: A total of 251 MMT patients were included, 128 cases in the acupuncture group and 123 cases in the non-acupuncture group. CatBoost and Stacking performed optimally in the test set. CatBoost obtained an accuracy of 0.780 0±0.060 8, a precision of 0.500 0±0.120 0, a recall of 0.818 2±0.140 2, F1 score of 0.620 7±0.114 0, and receiver operating characteristic-area under curve (ROC-AUC) of 0.857 8±0.140 2 for the subjects. In MMT patients with acupuncture as an adjunctive therapy, the top 5 important features for methadone reduction, included intervention measures, body mass index (BMI), the duration of MMT, the history of opioid use and occupation; and SHAP values were 1.25, 0.36, 0.21, 0.19 and 0.12, respectively. The SHAP feature dependence plot showed that BMI, MMT duration and the history of opioid use presented a nonlinear negative correlation with the reduction effect. CONCLUSION In acupuncture as adjunctive therapy for methadone reduction, the clinical factors should be considered comprehensively; and the interpretable predictive model provides a scientific basis for it, which is conducive to the improvement of clinical strategy of acupuncture for methadone reduction and the development of personalized reduction scheme.
Humans ; Methadone/therapeutic use* ; Acupuncture Therapy ; Adult ; Female ; Male ; Machine Learning ; Middle Aged ; Opiate Substitution Treatment ; Young Adult

Study on the mechanism of Fangxia Dihuang Formula(FXDH) in treating breast cancer complicated with depression through the regulation of M1/M2 microglial polarization via the PERK/eIF2α axis. In addition to control group and 4T1 group, a mouse model of breast cancer complicated with depression was established using 4T1 cells combined with corticosterone. The mice were divided into model group, PERK/eIF2α signaling axis agonist(CCT020312, 2 mg·kg~(-1)·d~(-1)) group, CCT020312(2 mg·kg~(-1)·d~(-1)) + FXDH(13.65 g·kg~(-1)·d~(-1)) group, FXDH(13.65 g·kg~(-1)·d~(-1)) group, FXDH(13.65 g·kg~(-1)·d~(-1)) + Capecitabine Tablets(CAP, 390 mg·kg~(-1)·d~(-1)) group, and Fluoxetine Hydrochloride Capsules(FXT, 2.6 mg·kg~(-1)·d~(-1)) + CAP(390 mg·kg~(-1)·d~(-1)) group, with continuous intervention for 21 d. Depression-like behaviors in mice were assessed through sugar preference test and open field test. Hematoxylin-eosin(HE) staining was used to evaluate the morphology of tumor and hippocampal DG region neurons. Nissl staining was employed to detect changes in Nissl bodies in the hippocampal CA3 region. Immunofluorescence was used to observe cluster of differentiation 86(CD86)/ionized calcium-binding adapter molecule 1(Iba-1) and cluster of differentiation 206(CD206)/Iba-1 in hippocampal tissue. Real-time fluorescence quantitative polymerase chain reaction(RT-qPCR) was used to detect the mRNA expression of M1-type microglia [interleukin-6(IL-6), tumor necrosis factor-α(TNF-α)] and M2-type [arginase-1(Arg-1), IL-10] in hippocampal tissue. Western blot was used to detect the protein expression of key factors in the PERK/eIF2α axis, including PERK, eIF2α, activating transcription factor 4(ATF4), and C/EBP homologous protein(CHOP) in hippocampal tissue. The results showed that compared to model group/CCT020312 + FXDH group, FXDH group increased sugar preference index, total movement distance, central zone distance, and central zone entries; reduced tumor mass and volume; tumor cells were sparsely arranged, with a smaller nuclear-to-cytoplasmic ratio and reduced nuclear division figures, increased Nissl body count, and alleviated neuronal nuclear pyknosis; increased CD206-positive M2-type microglia expression, decreased CD86/Iba-1-positive M1-type microglia expression; reduced IL-6 and TNF-α mRNA expression, and increased Arg-1 and IL-10 mRNA expression; downregulated PERK, eIF2α, ATF4, and CHOP protein expression levels. The results indicate that the mechanism of FXDH in treating breast cancer complicated with depression may be related to inhibiting the activity of the PERK/eIF2α axis, reducing the proportion of M1-type microglia, increasing the proportion of M2-type microglia, thereby suppressing neuronal immune inflammation, improving depressive symptoms, and subsequently delaying the progression of breast cancer.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Microglia/cytology* ; Mice ; Depression/complications* ; eIF-2 Kinase/genetics* ; Humans ; Breast Neoplasms/psychology* ; Eukaryotic Initiation Factor-2/genetics* ; Mice, Inbred BALB C ; Signal Transduction/drug effects* ; Cell Line, Tumor

As a common clinical treatment technique, nasogastric tube insertion plays an important role in assisting in disease diagnosis and treatment, and promoting patient recovery. Nasogastric tubes currently used in clinical practice are packaged individually without accompanying sterile materials, hence additional materials need to be prepared before operation, which is complicated and prone to omission, consumes clinical manpower, and increases the proportion of departmental consumption. The operator needs to hold the nasogastric tube with one hand and place it with the other hand during operation, the lack of auxiliary tool for uniformly controlling the placement of gastric tubes may easily lead to tube failure due to patient intolerance, agitation, or uneven force exerted by the operator, and improper force may even result in violent tube placement, leading to adverse outcomes such as mucosal bleeding and aspiration into the airway. Medical staff of intensive care unit of department of infectious diseases of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology have designed a nasogastric tube auxiliary pushing device and an intubation kit to overcome the above problems, and obtaining National Utility Model Patent of China (patent number: ZL 2024 2 0300856.X). The device consists of two parts: a nasogastric tube auxiliary pushing device and a nasogastric tube insertion kit. Nasogastric tube auxiliary pushing device mainly consists of a nasogastric tube with guide wire, a circular wire harness, and a booster base with a pushing element. The tube insertion kit includes sterile treatment trays, main placement slots, and other operational accessory slots. The new nasogastric tube auxiliary pushing device and tube insertion kit integrates packaging and portable design, providing stable and uniform assistance for safe insertion of nasogastric tubes by a single person, which is able to reduce the occurrence of complications, ensure patient safety, improve patient comfort, and reduce occupational exposure risks, making it suitable for clinical promotion.
Intubation, Gastrointestinal/methods* ; Equipment Design ; Humans

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

OBJECTIVE: To reveal the effects and potential mechanisms by which synaptic vesicle glycoprotein 2A (SV2A) influences the distribution of amyloid precursor protein (APP) in the trans-Golgi network (TGN), endolysosomal system, and cell membranes and to reveal the effects of SV2A on APP amyloid degradation. METHODS: Colocalization analysis of APP with specific tagged proteins in the TGN, ensolysosomal system, and cell membrane was performed to explore the effects of SV2A on the intracellular transport of APP. APP, β-site amyloid precursor protein cleaving enzyme 1 (BACE1) expressions, and APP cleavage products levels were investigated to observe the effects of SV2A on APP amyloidogenic processing. RESULTS: APP localization was reduced in the TGN, early endosomes, late endosomes, and lysosomes, whereas it was increased in the recycling endosomes and cell membrane of SV2A-overexpressed neurons. Moreover, Arl5b (ADP-ribosylation factor 5b), a protein responsible for transporting APP from the TGN to early endosomes, was upregulated by SV2A. SV2A overexpression also decreased APP transport from the cell membrane to early endosomes by downregulating APP endocytosis. In addition, products of APP amyloid degradation, including sAPPβ, Aβ _1-42, and Aβ _1-40, were decreased in SV2A-overexpressed cells. CONCLUSION These results demonstrated that SV2A promotes APP transport from the TGN to early endosomes by upregulating Arl5b and promoting APP transport from early endosomes to recycling endosomes-cell membrane pathway, which slows APP amyloid degradation.
Amyloid beta-Protein Precursor/genetics* ; Membrane Glycoproteins/genetics* ; Animals ; Protein Transport ; Nerve Tissue Proteins/genetics* ; Humans ; Mice ; Endosomes/metabolism* ; trans-Golgi Network/metabolism*

To explore the regulatory mechanism of drought stress on the synthesis of chlorogenic acid and luteoloside in Lonicera japonica, we designed five drought gradients (soil water contents of 30%, 24%, 17%, 14%, and 10%) and screened and verified the differentially expressed genes (DEGs) by RNA sequencing (RNA-seq) and reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, we employed HPLC to systematically measure the content changes of chlorogenic acid and luteoloside. The results revealed that drought significantly reduced the accumulation of secondary metabolites, and severe drought led to more obvious reductions. Under extreme drought (soil water content of 10%), the content of chlorogenic acid and luteoloside decreased significantly to 25.73 mg/g and 11.33 mg/g (with the decrease rates of 37.85% and 9.58%, respectively). A total of 77 454 genes were identified via transcriptome analysis, among which the number of DEGs reached 1 128 under the extraordinary drought. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses revealed that the DEGs were mainly involved in flavonoid synthesis, secondary metabolite biosynthesis, plant hormone signal transduction and the plant-pathogen interaction pathways, and the expression of key genes regulating the synthesis of chlorogenic acid and luteoloside was significantly downregulated. RT-qPCR verified the accuracy of the RNA-seq data. This study revealed that drought stress reduced the content of chlorogenic acid and luteoloside, the main secondary metabolites, by inhibiting the expression of key genes in the secondary metabolism pathways. The findings provide candidate gene resources for molecular breeding of drought-tolerant Lonicera japonica.
Lonicera/physiology* ; Chlorogenic Acid/metabolism* ; Droughts ; Stress, Physiological ; Gene Expression Regulation, Plant ; Glucosides/metabolism* ; Luteolin