Background Due to the unique working environment and numerous occupational disease hazards, workers in mining industry are particularly susceptible to psychological problems such as occupational stress. Objective To understand the current status of occupational stress, depressive symptoms, anxiety symptoms and sleep quality of workers in ferrous and non-ferrous metal mining industry in Gansu Province, and to explore the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep. Methods From April to December 2022, the workers of 25 large, medium, and small and micro enterprises were selected by stratified cluster random sampling and surveyed in ferrous and non-ferrous metal mining industry in Gansu Province. The Occupational Health Literacy Questionnaire of National Key Population, Core Occupational Stress Scale, Patient Health Questionnaire-q, Generalized Anxiety Disorder, and Self-administer Sleep Questionnaire were used to collect basic information, occupational stress, depressive symptoms, anxiety symptoms, and sleep quality of the workers. Chi-square test was used to compare occupational stress, depressive symptoms, anxiety symptoms and sleep disorders among different categories. Logistic regression model was used to study the effects of occupational stress on depressive symptoms, anxiety symptoms, and sleep quality. Results In this study, 2192 workers in mining industry were surveyed, of which 2087 returned valid questionnaires, and the recovery rate of valid questionnaires was 95.2%. Among them, 728 (38.4%) reported occupational stress. There were statistically significant differences in the positive rate of occupational stress among workers by gender, age, marital status, education level, average monthly income, length of service, enterprise size, and night shifts (P<0.001). The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders in the mining industry workers were 85.6%, 49.8%, and 47.3%, respectively. The positive rates of depressive symptoms, anxiety symptoms, and sleep disorders among workers with higher occupational stress were higher than those among workers without occupational stress (P<0.001). The logistic regression analysis showed that occupational stress was a common risk factor for depressive symptoms (OR=3.29, 95%CI: 2.26, 4.79), anxiety symptoms (OR=2.87, 95%CI: 2.33, 3.53), and sleep disorder (OR=1.78, 95%CI: 1.46, 2.16). In addition, length of service and enterprise-scale were also risk factors for depressive symptoms, anxiety symptoms, and sleep disorders. In the 5−<10 and 10−<20 years of service groups, the risks of reporting depressive symptoms were 1.80 (95%CI: 1.18, 2.74) and 1.73 (95%CI: 1.10, 2.71) times higher than that of workers with less than 1 year of service, respectively; the risks of reporting anxiety symptoms were 1.98 (95%CI: 1.42, 2.76) and 2.11 (95%CI: 1.48, 3.01) times higher than that with less than 1 year of service, respectively; the risks of reporting sleep disorders were 1.58 (95%CI: 1.15, 2.16) and 1.78 (95%CI: 1.29, 2.45) times higher than that with less than 1 year of service, respectively. Workers in large enterprises were inclined to report more depressive symptoms, anxiety symptoms, and sleep disturbances than those in micro and small enterprises (OR=3.53, 95%CI: 2.41, 5.16; OR=2.49, 95%CI: 1.98, 3.13; OR=2.10, 95%CI: 1.67, 2.62). Conclusion The occupational stress level of mining industry workers in Gansu Province is high, and reporting occupational stress, 5−<10 and 10−<20 working age groups, and large enterprises are important risk factors affecting workers' mental health and sleep. It is necessary to increase the attention and develop intervention programs for mental health of miners in the working age group of 5−20 years old and in large enterprises.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Kounis syndrome is an acute coronary syndrome triggered by an allergic reaction, which is clinically rare and frequently subject to misdiagnosis or missed diagnosis. This article presents a case report of a 70-year-old male patient who developed a rash, pruritus, and chest pain following colon polyp resection. Coronary angiography revealed occlusion of the left anterior descending artery, and blood flow was restored after stent implantation. However, the patient experienced recurrent symptoms accompanied by loss of consciousness. Drug skin tests confirmed positive reactions to chlorhexidine and fondaparinux sodium, leading to a diagnosis of type Ⅱ Kounis syndrome. By avoiding allergenic drugs and combining antihistamines with symptomatic treatment to correct myocardial ischemia, the patient′s clinical symptoms significantly improved, and he eventually recovered and was discharged from the hospital. This case underscores the importance of maintaining vigilance for this syndrome in patients with allergies accompanied by chest pain and promptly identifying and avoiding allergens.

Objective: To investigate the expression and functional role of FK506 binding protein 10 (FKBP10) in oral squamous cell carcinoma (OSCC), and to provide a research basis for the estimated prognosis and targeted therapy of OSCC. Methods: A total of 284 OSCC samples and 19 normal samples were selected from the Cancer Genome Atlas (TCGA) database, and diagnostic analysis was performed to determine mRNA expression. Survival analysis for FKBP10 and OSCC was conducted on a gene expression profile interaction analysis website. Real-time fluorescence quantitative PCR and Western Blot were used to detect the mRNA and protein expression of FKBP10 in four OSCC cell lines and SAS and SCC9 cells transfected with siRNA. The cell proliferation ability of FKBP10-silenced cells was detected using the CCK8 method, and the cell cycle distribution and apoptosis were detected by flow cytometry. Cell migration and invasion ability were detected through wound healing and invasion experiments. The expression changes of total protein and phosphatidylinositol 3-kinase (PI3K)-serine/threonine kinase (AKT) after FKBP10 silencing were analyzed by proteomics and Western Blot. Results: According to the analysis of gene expression levels, the mRNA expression level of FKBP10 in OSCC was significantly higher than that in normal tissues (P < 0.001). In terms of diagnosis, the expression level of FKBP10 has unique diagnostic value for OSCC (P < 0.05). The survival analysis of FKBP10 and OSCC showed that a high expression of FKBP10 led to a decrease in patient survival and poor prognosis (P < 0.05). The expression of FKBP10 mRNA and protein in OSCC cell lines was higher than that in normal oral keratinocytes (P < 0.001). Silencing FKBP10 can reduce the proliferation, invasion, and migration ability of SAS and SCC9 (P < 0.001), and also block their cell cycle in the G0/G1 phase (P < 0.001), with a significant increase in apoptosis (P < 0.05). Protein mass spectrometry and Western blot analysis revealed that FKBP10 silencing significantly downregulated the expression of multiple proteins in the RAP1 signaling pathway, mainly RAP guanine nucleotide exchange factor 1 (RAPGEF1) (P < 0.05) and the phosphorylation of PI3K-AKT proteins (P < 0.05). Conclusion FKBP10 is highly expressed in OSCC, leading to poor prognosis for patients. Downregulated FKBP10 expression can inhibit the proliferation, migration, and invasion ability of OSCC cells, hinder cell cycle progression, and promote apoptosis via the RAP1-PI3K-AKT axis. FKBP10 is a potential therapeutic target and prognostic biomarker for OSCC.

Objective: To establish an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method based on solid-phase extraction column purification for simultaneous determination of cyromazine and melamine in poultry eggs and meat. Methods: Eggs, quail eggs, and chicken were collected from markets. After homogenization, the sample was extracted with 0.5% formic acid in acetonitrile, subjected to solid-phase extraction using an MCX cartridge, and eluted with 5% ammonia in methanol. The eluate was collected, evaporated to near dryness under nitrogen, and reconstituted in a 10% aqueous methanol solution. Separated using TSK gel Amide-80 column (2.0 mm×150 mm, 5 μm), cyromazine and melamine were simultaneously detected in positive ion multiple reaction monitoring mode via tandem mass spectrometry, with quantification achieved by isotope dilution internal standard methods. Efficiency was enhanced and matrix interference minimized by optimizing conditions such as sample extraction, solid-phase extraction cartridge selection, and instrumental parameters. Calibration curves were constructed, and detection limits, quantification limits, spiked recoveries, and relative standard deviations for (RSD) of cyromazine and melamine were calculated. Results: After method optimization, matrix effects for cyromazine and melamine ranged from 0.97 to 1.04, indicating no significant matrix suppression or enhancement. Both cyromazine and melamine exhibited excellent linearity within the concentration range of 1.0-200.0 ng/mL, with correlation coefficients ≥0.999 5. The limits of detection were 0.3 μg/kg for cyromazine and 0.5 μg/kg for melamine, the quantification limits were 1.0 and 1.5 μg/kg, respectively. At spiked levels of 1.0, 20.0, and 150.0 μg/kg, the average recoveries ranged from 78.6% to 103.1%, with RSD between 3.5% and 6.3%. Among 95 samples tested, cyromazine was detected in 6 samples and melamine in 5 samples; neither cyromazine nor melamine was detected in chicken samples. Conclusion The UPLC-MS/MS method established in this study enables simultaneous detection and accurate quantification of cyromazine and melamine in poultry eggs and meat.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

To explore the variation laws of volatile oil during the extraction process of Artemisiae Argyi Folium and its impact on the quality of the medicinal solution, as well as to achieve precise control of the extraction process, this study employed headspace solid phase microextraction gas chromatography-mass spectrometry(HS-SPME-GC-MS) in combination with multiple light scattering techniques to conduct a comprehensive analysis, identification, and characterization of the changes in volatile components and the physical properties of the medicinal solution during the extraction process. A total of 82 volatile compounds were identified using the HS-SPME-GC-MS technique, including 21 alcohols, 15 alkenes, 14 ketones, 9 acids, 6 aldehydes, 5 phenols, 3 esters, and 9 other types of compounds. At different extraction time points(15, 30, 45, and 60 min), 71, 72, 64, and 44 compounds were identified in the medicinal solution, respectively. It was observed that the content of volatile components gradually decreased with the extension of extraction time. Through multivariate statistical analysis, four compounds with significant differences during different extraction time intervals were identified, namely 1,8-cineole, terpinen-4-ol, 3-octanone, and camphor. RESULTS:: from multiple light scattering techniques indicated that at 15 minutes of extraction, the transmittance of the medicinal solution was the lowest(25%), the particle size was the largest(0.325-0.350 nm), and the stability index(turbiscan stability index, TSI) was the highest(0-2.5). With the extension of extraction time, the light transmittance of the medicinal solution improved, stability was enhanced, and the particle size decreased. These laws of physicochemical property changes provide important basis for the control of Artemisiae Argyi Folium extraction process. In addition, the changes in the bioactivity of Artemisiae Argyi Folium extracts during the extraction process were investigated through mouse writhing tests and antimicrobial assays. The results indicated that the analgesic and antimicrobial effects of the medicinal solution were strongest at the 15-minute extracting point. In summary, the findings of this study demonstrate that the content of volatile oil in Artemisiae Argyi Folium extracts gradually decreases with the extension of extraction time, and the variation in volatile oil content directly influences the physicochemical properties and pharmacological efficacy of the medicinal solution. This discovery provides important scientific reference for the optimization of Artemisiae Argyi Folium extraction processes and the development and application of process analytical technologies.
Oils, Volatile/pharmacology* ; Artemisia/chemistry* ; Gas Chromatography-Mass Spectrometry ; Drugs, Chinese Herbal/pharmacology* ; Chlorogenic Acid/pharmacology* ; Solid Phase Microextraction ; Quality Control

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

OBJECTIVE: To investigate the clinical features and prognosis of central nervous system (CNS) invasion in peripheral T-cell lymphoma (PTCL) and construct a risk prediction model for CNS invasion. METHODS: Clinical data of 395 patients with PTCL diagnosed and treated in the First Affiliated Hospital of Zhengzhou University from 1st January 2013 to 31st December 2022 were analyzed retrospectively. RESULTS: The median follow-up time of 395 PTCL patients was 24(1-143) months. There were 13 patients diagnosed CNS invasion, and the incidence was 3.3%. The risk of CNS invasion varied according to pathological subtype. The incidence of CNS invasion in patients with anaplastic large cell lymphoma (ALCL) was significantly higher than in patients with angioimmunoblastic T-cell lymphoma (AITL) (P <0.05). The median overall survival was significantly shorter in patients with CNS invasion than in those without CNS involvement, with a median survival time of 2.4(0.6-127) months after diagnosis of CNS invasion. The results of univariate and multivariate analysis showed that more than 1 extranodal involvement (HR=4.486, 95%CI : 1.166-17.264, P =0.029), ALCL subtype (HR=9.022, 95%CI : 2.289-35.557, P =0.002) and ECOG PS >1 (HR=15.890, 95%CI : 4.409-57.262, P <0.001) were independent risk factors for CNS invasion in PTCL patients. Each of these risk factors was assigned a value of 1 point and a new prediction model was constructed. It could stratify the patients into three distinct groups: low-risk group (0-1 point), intermediate-risk group (2 points) and high-risk group (3 points). The 1-year cumulative incidence of CNS invasion in the high-risk group was as high as 50.0%. Further evaluation of the model showed good discrimination and accuracy, and the consistency index was 0.913 (95%CI : 0.843-0.984). CONCLUSION The new model shows a precise risk assessment for CNS invasion prediction, while its specificity and sensitivity need further data validation.
Humans ; Lymphoma, T-Cell, Peripheral/pathology* ; Prognosis ; Retrospective Studies ; Central Nervous System Neoplasms/pathology* ; Neoplasm Invasiveness ; Male ; Female ; Central Nervous System/pathology* ; Middle Aged ; Adult