Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

Objective:To provide novel genetic biomarkers for the diagnosis and treatment of sepsis,bioinformatics analysis was used to screen differentially expressed genes and identify Hub genes in sepsis.Methods:Gene Expression Omnibus(GEO)database was used to retrieve gene expression datasets of sepsis and screen for differentially expressed genes(DEGs).Protein-protein interaction(PPI)network analysis,Gene Ontology(GO)analysis,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were used to clarify the molecular mechanism of DEGs,and Hub genes were screened.Results:A total of 361 DEGs were identified,including 163 up-regulated genes and 198 down-regulated genes.Enrichment analysis revealed that these DEGs were primarily involved in antigen processing and presentation,T cell biology,cell adhesion molecules,and T cell receptor signaling pathways.CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1 were determined as optimal diagnostic biomarkers for sepsis.Conclusions:This study elucidated 10 Hub genes(CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1)as potential biomarkers for the diagnosis and treatment of sepsis.However,since the the generalizability of these Hub genes in patients with sepsis remains unvalidated,further experimental verification is still needed in the future.

Depression is a prevalent mental and emotional disor-der that often results in significant emotional disturbances,cog-nitive dysfunction,and memory impairments.It is characterized by a high incidence rate,a substantial disability burden,and limited therapeutic efficacy.Currently,the long-term use of medications for the treatment of depression can result in a range of adverse reactions,highlighting the urgent need to explore no-vel approaches that can effectively alleviate depressive symptoms while minimizing side effects.Curcumin,a natural polyphenolic compound derived from the rhizome of turmeric,demonstrates considerable potential in the prevention and treatment of depres-sion,owing to its diverse array of biological activities.In recent years,numerous studies have investigated the use of curcumin for the treatment of depression.This article aims to provide a comprehensive review of the mechanisms of action underlying curcumin's efficacy in treating depression.Specifically,it focu-ses on its ability to improve neurotransmitter imbalances,restore neural plasticity,alleviate neural damage,mitigate dysfunction of the hypothalamic-pituitary-adrenal(HPA)axis,regulate in-flammatory factors and neuroinflammatory signaling pathways,and inhibit oxidative stress.This review is intended to offer in-sights and methodological references for basic research on curcu-min,as well as for the development of novel therapeutic agents for the treatment of depression.

AIM To evaluate the quality of Rubi Fructus.METHODS UPLC-Q-TOF-MS/MS was adopted in the component identification,after which the HPLC fingerprints were established,cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition.and the contents of chlorogenic acid,ferulic acid,ellagic acid,isoquercitrin,kaempferol-3-O-rutinoside,astragalin,tiliroside quercetin,kaempferol were determined.RESULTS Total 34 constituents were identified.There were 19 common peaks in the fingerprints for 31 batches of medicinal materials with the similarities of more than 0.8.Wild varieties and cultivated varieties,and medicinal materials from different producing areas could be distinguished;4 principal components demonstrated the accumulative variance contribution rate of 84.142％;8 differential components were screened,2 of which were ellagic acid and astragalin.Ellagic acid and astragalin displayed higher contents in the wild varieties than those in the cultivated varieties(P＜0.05,P＜0.01).CONCLUSION UPLC-Q-TOF-MS/MS,HPLC fingerprints combined with content determination can be used for the quality control of Rubi Fructus.

Objective To investigate the current status of operational management in tertiary maternal and child health(MCH)hospitals in Guizhou Province and propose recommendations for refining their operational management practices.Meth-ods A self-designed electronic questionnaire was distributed to seven tertiary MCH hospitals in Guizhou Province.The survey fo-cused on fundamental dimensions of operational management,particularly the implementation of refined management practices,with results analyzed using descriptive statistics.Results Among the seven hospitals,five had independently established opera-tional management departments,with three staffing 3-4 personnel.Sixty percent of the hospitals engaged in data statistics,strate-gic management,and process optimization.Only two hospitals had implemented operational management information systems(HRP),but these systems featured incomplete modules and lacked interconnectivity between subsystems,failing to meet opera-tional needs.Additionally,while total expenditures increased year-over-year across all hospitals,insufficient government compen-sation has heightened operational pressures.Conclusions Operational management in Guizhou's tertiary MCH hospitals faces multiple challenges,including incomplete organizational structures and systems,inadequate execution of core functions,subopti-mal information systems for refined management,and limited fiscal support.Recommendations include establishing a multi-tiered operational management framework,implementing comprehensive long-term safeguards,and developing an integrated data man-agement platform.Simultaneously,improving government compensation mechanisms through increased fiscal investment and sup-portive policies is critical to enhancing operational capabilities and achieving high-quality development.

Objective To explore the pharmacokinetic(PK)characteristics of desloratadine tablets and reference drugs in healthy subjects,and evaluate their bioequivalence and safety.Methods The random,open,two-period,cross-over pharmacokinetic study method was adopted,each subject received a single oral dose of desloratadine tablets test drug(T)or reference drug(R)for 5 mg.The concentrations of desloratadine and 3-hydroxy desloratadine in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS);and the PK parameters were calculated by WinNonlin 8.1 software to evaluate the bioequivalence.Results The main PK parameters of T and R of desloratadine were as follows:the fasting condition Cmax were respectively(3 809.82±1 016.54)and(3 642.36±777.07)pg·mL-1;AUC0-120h were respectively(5.75 ×104±5.03 ×104)and(5.51 × 104±4.00 × 104)pg·h·mL-1;AUC0-∞ were respectively(6.85× 104±1.03× 104)and(6.37 × 104±7.92 × 104)pg·h·mL-1.The fed condition Cmax were respectively(4 398.98±1 191.22)and(4 744.4±1 511.97)pg·mL-1;AUC0-120h were respectively(5.25 × 104±1.82 × 104)and(5.55 × 104±1.98 × 104)pg·h·mL-1;AUC0-∞ were respectively(5.37 × 104±1.86 × 104)and(5.68 × 104±2.04 × 104)pg·h·mL-1.The 90％confidence interval of Cmax,AUC0-t and AUC0-∞ of desloratadine were all within 80.00％～125.00％.Conclusion There was no significant difference in the main PK parameters between T tablets and R under fasting or high-fat postprandial conditions,and desloratadine tablets were bioequivalent,safe and well tolerated.

Objective To analyze the caregiver presence needs and their influencing factors among hospitalized elderly non-surgical patients and provide a basis for formulating relevant policies.Methods A descriptive qualitative study method was adopted.Through purposive sampling,semi-structured interviews were conducted on elderly non-surgical patients and their families and medical staff in Peking Union Medical College Hospital from September to October 2023.MAXQDA 2020 and the 7-step phenomenological analysis method of Colaizzi were used to classify and code the interview contents and identify themes.Results The categories of caregiver presence needs of elderly non-surgical patients included basic living assistance needs,disease monitoring needs,psychological support needs,as well as the needs for family members to provide economic support and participate in treatment decision-making.The influencing factors included advanced age,frailty,the lack of self-care ability in patients with comorbidities,the susceptibility of patients to sudden situations during the disease exacerbation period,the increased risk of unexpected events in patients with psychological distress,and patients' concerns about social support and medical decision-making.Conclusion The caregiver presence needs of elderly non-surgical patients during hospitalization are high and influenced by multiple factors.
Humans ; Caregivers/psychology* ; Aged ; Hospitalization ; Social Support ; Male ; Qualitative Research ; Female

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

The objective of this study is to map the global scientific competitive landscape in the field of artificial intelligence (AI) medical devices using scientific data. A bibliometric analysis was conducted using the Web of Science Core Collection to examine global research trends in AI-based medical devices. As of the end of 2023, a total of 55 147 relevant publications were identified worldwide, with 76.6% published between 2018 and 2024. Research in this field has primarily focused on AI-assisted medical image and physiological signal analysis. At the national level, China (17 991 publications) and the United States (14 032 publications) lead in output. China has shown a rapid increase in publication volume, with its 2023 output exceeding twice that of the U.S.; however, the U.S. maintains a higher average citation per paper (China: 16.29; U.S.: 35.99). At the institutional level, seven Chinese institutions and three U.S. institutions rank among the global top ten in terms of publication volume. At the researcher level, prominent contributors include Acharya U Rajendra, Rueckert Daniel and Tian Jie, who have extensively explored AI-assisted medical imaging. Some researchers have specialized in specific imaging applications, such as Yang Xiaofeng (AI-assisted precision radiotherapy for tumors) and Shen Dinggang (brain imaging analysis). Others, including Gao Xiaorong and Ming Dong, focus on AI-assisted physiological signal analysis. The results confirm the rapid global development of AI in the medical device field, with "AI + imaging" emerging as the most mature direction. China and the U.S. maintain absolute leadership in this area-China slightly leads in publication volume, while the U.S., having started earlier, demonstrates higher research quality. Both countries host a large number of active research teams in this domain.
Artificial Intelligence ; Bibliometrics ; Humans ; China ; Equipment and Supplies ; United States ; Biomedical Research

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors