Objective: To investigate the prevalence of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District, Beijing Municipality, so as to provide the evidence for \prevention and control of comorbidity. Methods: In September from 2020 to 2024, a stratified cluster sampling method was adopted annually to select primary, junior high school, senior high school, and vocational high school students in Yanqing District as survey subjects. Myopia was screened based on Screening Protocol for Myopia in Children and Adolescents. Height an weight were measured, and overweight and obesity were determined using the Screening for overweight and Obesity in School-Age Children and Adolescents. Results: A total of 9 883 individuals were surveyed, including 5 219 primary school students (52.81%), 2 486 junior high school students (25.15%), and 2 178 senior high school / vocational high school students (22.04%). There were 5 154 boys (52.15%) and 4 729 girls (47.85%). From 2020 to 2024, the numbers of primary and middle school students in Yanqing District with myopia, overweight, and obesity were 4 426, 1 897, and 3 164, respectively, with detection rates of 44.78%, 19.19%, and 32.01%. The detection rates of myopia, overweight, and obesity showed an increasing trend with the elevation of school stage (all P<0.05). The detection rate of myopia was higher in girls than in boys, while the detection rate of obesity was lower in girls than in boys (all P<0.05). There were 2 588 individuals with both myopia and overweight/obesity, representing a detection rate of 26.19%, which showed an increasing trend (P<0.05), rising from 25.04% in 2020 to 34.41% in 2024. The detection rates of comorbidity of myopia, and overweight and obesity among primary school, junior high school, and senior high school / vocational high school students were 13.22%, 36.93%, and 45.00%, respectively, showing an increasing trend with the elevation of school stage (P<0.05). The difference between genders was not statistically significant (P>0.05). Conclusions The detection rates of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District is relatively high and shows an upward trend, with students in higher school stage being the key target group for prevention and control. It is recommended to strengthen health education on the co-prevention of multiple health issues and implement differentiated interventions based on school stages.

Objective To examine the impact of extreme temperature and drought stress on the survival of Bulinus globosus, so as to provide the theoretical evidence for the genomic research of Bulinus in absence of reference genes. Methods B. globosus snail samples were collected from Kiwani Shehia in Pemba Island, Zanzibar, Tanzania, and offspring snails were obtained through laboratory breeding and reproduction. A total of 120 10-week-old B. globosus snails from the same generation were selected and randomly assigned into four groups, including the high-temperature drought (HD) group, normal temperature drought (D) group, low-temperature drought (LD) group, and the control (C) group, of 30 snails in each group. Snails in HD, D, and LD groups were placed in beakers containing dry soil at the bottom and subsequently housed in climate chambers at 35, 26 ℃, and 10 ℃, respectively, while snails in Group C were maintained in 500 mL petri dishes containing dechlorinated tap water at 26 ℃. Following 3 days of breeding, living snails in each group were collected, and soft tissues were dissected and isolated. Total RNA was extracted from snail soft tissues for library construction, followed by high-throughput sequencing on the Illumina HiSeq 4000 sequencing system. De novo transcriptome assembly was performed using the Trinity software, and the longest transcripts were selected as unigenes. Gene functional annotations of unigenes were conducted using the Diamond software against Gene Ontology (GO) knowledgebase, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, NCBI non-redundant (NR) protein sequences database, Protein Family (Pfam) database, and UniProtKB/Swiss-Prot (Swiss-Prot) knowledgebase. GO and KEGG enrichment analyses of differentially expressed genes (DEGs) were performed using the topGO and clusterProfiler software, respectively. In addition, four relevant genes were selected for validation using a real-time quantitative PCR (qRT-PCR) assay to verify the reliability of transcriptome sequencing results. Results Following 3 days of breeding, there were 7, 20, 28, and 30 survival B. globosus snails in HD, LD, D, and C groups, with corresponding survival rates of 23.33% (7/30), 66.67% (20/30), 93.33% (28/30), and 100.00% (30/30), respectively (χ² = 52.72, P < 0.001). De novo transcriptome assembly generated 176 942 unigenes, with annotation rates of 0.98%, 13.49%, 26.46%, 12.48%, and 14.39% against GO knowledgebase, KEGG pathway database, NR protein sequences database, Pfam database, and Swiss-Prot knowledgebase, respectively. There were 33 up-regulated and 72 down-regulated genes in Group D, 483 up-regulated and 815 down-regulated genes in Group HD, and 245 up-regulated and 172 down-regulated genes in Group LD relative to in Group C. Following removal of overlapping genes across groups and unmatched genes, 11 candidate genes were identified. GO and KEGG analyses revealed 3 heat shock protein (HSP)-related DEGs in these 11 candidate genes, which were annotated as HSP12.2, HSP70, and HSP20 genes and were all significantly up-regulated in each treatment group. Three immune and nervous system-related DEGs were identified, and were all significantly down-regulated in each treatment group, which were involved in the neural cell adhesion molecule L1-like protein pathway, fibrinogen binding protein pathway, and leukocyte elastase inhibitor-like protein pathway. qRT-PCR assay quantified that the expression trends of four genes related to temperature and drought stress across different treatment groups were highly consistent with transcriptome sequencing data. Conclusion The survival rate of B. globosus significantly reduces under combined stresses of extreme temperature and drought, possibly due to an imbalance in its cellular homeostasis regulatory system.

Objective To explore factors associated with early postoperative hormonal remission in patients with prolactinoma and to develop prediction models based on clinical and radiological features. Methods Data from 107 patients with prolactinoma who underwent transsphenoidal surgery at The First People’s Hospital of Huai’an, Nanjing Medical University between January 2020 and December 2024 was collected, included general clinical characteristics, preoperative laboratory indicators, and imaging features. Based on whether early postoperative prolactin (PRL) levels normalized, patients were divided into a remission group (n=76) and a non-remission group (n=31). Univariate logistic regression was used for preliminary evaluation of candidate variables, followed by LASSO regression for feature selection. Multiple machine learning models were constructed, including logistic regression, random forest, support vector machine, K-nearest neighbors, naive Bayes, decision tree, neural network, and gradient boosting decision tree (GBDT). All models were trained and evaluated using ten-fold cross-validation, with comprehensive assessment of model performance based on the area under the ROC curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score. Results The maximum diameter of tumors in the non remission group was larger than that in the remission group (P=0.019), and the incidence of tumor stroke and preoperative PRL levels were significantly higher than those in the remission group (P＜0.001). Univariate analysis showed that sex, maximum tumor diameter, tumor stroke, and preoperative PRL levels were influencing factors for early postoperative hormone response in patients with prolactinoma (P＜0.05). The comparison results of machine learning models show that the neural network model performs the best (AUC=0.921) and has good clinical application value, followed by the GBDT model (AUC=0.893) and the support vector machine model (AUC=0.884). Other models also show certain predictive ability. Conclusions Sex, preoperative PRL levels, maximum tumor diameter, Hounsfield unit value, and tumor stroke are important factors affecting early hormone response after prolactinoma surgery. The machine learning model constructed based on the above variables has good predictive performance, and performs the best and has good clinical application value.

AIM To investigate the ameliorative effects of Compound Fufangteng Mixture(CFM)on cyclophosphamide(CTX)-induced immunosuppression in mice.METHODS Forty-eight male C57BL/6J mice were randomly divided into the blank control group,the model group,the levamisole hydrochloride group(40 mg/kg)and the low-dose,medium-dose and high-dose CFM groups(3.75,7.5,10 g/kg),with 8 mice in each group,and given respective intervention orally once daily for 14 days.On the 5th to 7th day of administration,with the blank control group given normal saline intraperitoneally,the other groups underwent intraperitoneal CTX injections(80 mg/kg).24 hours after the last administration,organ indices of thymus and spleen were calculated;splenic histopathological alterations were assessed by HE staining;serum levels of IL-2,IL-6 and IgG were quantified using ELISA;splenic CD4+,CD8+T lymphocytes,alongside CD86+and CD206+macrophages populations were analyzed by flow cytometry;and splenic expression of CD4,CD8 and F4/80 was evaluated by immunohistochemical staining.RESULTS In CTX-treated mice,CFM administration mitigated body weight loss;enhanced thymus weight and thymic index;ameliorated splenic immune cell populations,elevated serum levels of cytokines IL-2,IL-6 and IgG in serum;and upregulated splenic levels of CD45+CD3+T lymphocytes and F4/80+CD11b+macrophages,alongside increasing the expression of CD4,CD8 and F4/80 surface markers.CONCLUSION CFM alleviates CTX-induced immunosuppression state in mice by modulating immune cells,restoring immune function and enhancing anti-inflammatory and tissue repair capabilities.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

N6-methyladenosine (m6A) modification, as a widespread and high-profile type of epigenetic modification, can dynamically and reversibly regulate the whole process of RNA metabolism. This modification governs RNA stability, splicing, and translation via m6A regulators, which are categorized as Writers, Erasers, and Readers. m6A modification also plays a critical role in the development of tumors. Disruptions in the homeostasis of m6A modification levels lead to dysregulation of m6A regulators. Consequently, these dysregulated regulators modulate the proliferation, migration, and invasion of tumor cells and interfere with the normal functions of suppressor genes and oncogenes. This article aims to comprehensively elucidate the specific regulatory impacts of m6A modification on tumor-related gene expression. It focuses on the regulatory mechanisms of m6A modification on mRNA stability. Additionally, it explores the influence of m6A on the molecular translation of key signaling pathways. Moreover, it investigates the indirect regulatory effects mediated by non-coding RNAs (ncRNAs), etc. The intention is to offer a novel analysis of the pathogenesis of cancer at a new level, and also provide a theoretical basis for finding new effective treatment methods.

AIM To establish an HPLC-MS/MS method for the simultaneous content determination of dehydrodiisoeugenol,eugenol,costiolactone,dehydrocostiolactone,quercetin,isorhamnetin,luteolin,caffeic acid,gallic acid,protocatechuic acid,ellagic acid and kaempferol in Anshen Buxin Liuwei Pills,and to make chemical pattern recognition.METHODS The analysis was performed on a 35 ℃ thermostatic Shim-pack GST-HP C18 column(2.1 mm × 100 mm,3 μm),with the mobile phase comprising of methanol-water(containing 0.1％formic acid)flowing at 0.25 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.Subsequently,cluster analysis,principal component analysis and orthogonal partial least square-discriminant analysis were performed.RESULTS Twelve constituents showed good linear relationships within their own ranges(r≥0.999 0),whose average recoveries were 95.38％-105.00％with the RSDs of 1.91％-5.14％.Thirteen batches of samples were clustered into 3 types,ellagic acid,dehydrocodenolactone,dehydrodiisoeugenol,protocatechuic acid,gallic acid,quercetin and kaempferol were taken as potential quality differential markers.CONCLUSION This accurate,sensitive,stable and reproducible method can be used for the quality control and evaluation of Anshen Buxin Liuwei Pills.

An 85-year-old male patient received immunotherapy with toripalimab (240 mg by intravenous infusion on day 1, 21 days as one treatment cycle). After one week of the first medication, the patient experienced fatigue, poor appetite, weight loss, gradually developed mild ptosis of the right eyelid, shortness of breath and palpitations after activity, which were progressively aggravated. The patient also developed unclear speech, choking on water, and difficulty breathing. Laboratory tests showed alanine aminotransferase (ALT) 93 U/L, aspartate aminotransferase (AST) 171 U/L, creatine kinase (CK) 2 982 U/L, creatine kinase isoenzyme (CK-MB) 110 U/L, lactate dehydrogenase (LDH) 603 U/L, and high-sensitivity troponin T (hs-cTnT) 243 ng/L. All indicators of thyroid function were abnormal. Based on results of the laboratory tests, neurophysiological examination, and electrocardiogram examination, combined with the patient′s clinical symptoms, immune-mediated hepatitis of grade 2, immune-mediated myocarditis of grade 3, myasthenia gravis of grade 3, immune-mediated myositis of grade 2, and thyroid dysfunction of grade 1 were diagnosed, which was considered to be induced by toripalimab. Toripalimab was stopped. After treatments with glucocorticoids, liver-protective drugs, and symptomatic treatments, above-mentioned indicators showed a downward trend. After 27 days of treatments, the patient′s clinical symptoms were improved significantly. Laboratory tests showed ALT 123 U/L, AST 68 U/L, CK 116 U/L, CK-MB 42 U/L, LDH 305 U/L. The thyroid function indicators were all normal. After 57 days of treatments, above symptoms in the patient basically disappeared, and laboratory indicators tended to be normal.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To explore the mediating effects of self-management and medication adherence between type D personality and viral load in HIV-infected individuals.Methods:HIV patients who were newly diagnosed and undergoing antiretroviral therapy (ART) at the Heilongjiang AIDS Treatment Center of the Fourth Hospital of Harbin Medical University from October 2023 to March 2024 were enrolled by convenience sampling. Data were collected using the Type D Personality Scale-14 (DS-14), HIV Self-Management Scale (HIVSMS), and 8-item Morisky Medication Adherence Scale (MMAS-8). HIV-1 viral load was also measured. Pearson correlation analysis explored the relationships among type D personality, self-management, medication adherence, and viral load. The SPSS Process V4.0 macro was used to test the mediating effects.Results:A total of 318 questionnaires were distributed and 313 valid responses were collected (effective response rate: 98.43%). The mean scores for the 313 HIV-infected individuals were as follows: DS-14 (33.39±4.98), HIVSMS (29.84±4.41), and MMAS-8 (6.11±1.29). The mean viral load was (1 803.19±870.81) copies/ml. Pearson correlation analysis showed that type D personality was negatively correlated with self-management and medication adherence ( r=-0.307, -0.208, respectively; P<0.01) and positively correlated with viral load ( r=0.213; P<0.01). Medication adherence was negatively correlated with viral load ( r=-0.232; P<0.01), while self-management was positively correlated with medication adherence ( r=0.353; P<0.01). The mediation analysis revealed that self-management and medication adherence played a chain mediating role between type D personality and viral load, with a mediation effect value of 0.016, accounting for 8.08% of the total effect. Conclusions:Type D personality directly influences the viral load of HIV-infected individuals and indirectly affects it through the mediating effects of self-management and medication adherence.