Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

Objective To systematically evaluate the efficacy and safety of immune checkpoint inhibitors (ICIs) as first-line treatment for advanced non-small cell lung cancer (NSCLC). Methods PubMed, The Cochrane Library, and EMbase databases were searched for clinical randomized controlled trials (RCTs) of ICIs as first-line treatment for NSCLC patients. The search period was from database inception to January 2023. Quality evaluation was conducted using the improved Jadad scale, and meta-analysis was performed using RevMan 5.4 software. Results Twelve RCTs were included, all of which were assessed as high-quality literature, involving a total of 7 121 patients. Meta-analysis results showed that, compared with chemotherapy, ICIs as first-line treatment for NSCLC patients significantly improved median overall survival (OS) [HR=0.72, 95%CI (0.64, 0.80), P<0.001] and median progression-free survival (PFS) [HR=0.65, 95%CI (0.53, 0.78), P<0.001], and improved objective response rate (ORR) [RR=1.52, 95%CI (1.28, 1.79), P<0.001]. Subgroup analysis showed that, compared with the ICIs monotherapy group, the ICIs combination therapy group significantly improved OS, PFS, and ORR in NSCLC patients. In terms of safety, the risk of any grade treatment-related adverse events (TRAEs) and grade 3-5 TRAEs in the ICIs group was lower than that in the chemotherapy group. The incidence of TRAEs leading to treatment discontinuation was higher in the ICIs group than in the chemotherapy group. Subgroup analysis showed that the incidence of any grade, grade 3-5, and TRAEs leading to treatment discontinuation was higher in the immune combination therapy group than in the immune monotherapy group. Conclusion ICIs as first-line treatment for NSCLC patients can significantly improve OS, PFS, and ORR compared with chemotherapy. Compared to immune monotherapy, immune combination therapy can significantly improve the efficacy in NSCLC patients, but patients have a higher risk of TRAEs.

Objective To investigate plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

Objective To investigate the diagnostic value of electromyographic(EMG)tremor indicators for Parkinson's disease(PD)using the Logistic regression model.Methods A total of 65 patients with PD(PD group)and 39 patients with essential tremor(ET)(ET group)were enrolled and underwent EMG tremor analysis.General information,disease-related data,and EMG tremor characteristics were compared between the two groups.Multivariate Logistic regression analysis was performed to screen for independent influencing factors of PD,and receiver operating characteristic(ROC)curves were plotted.The area under the curve(AUC)was used to evaluate the diagnostic value of EMG tremor indicators for PD.Results Compared with the ET group,the PD group had a higher proportion of patients with unilateral onset and those with tremor spectrum frequency≥2 times,and a lower proportion of patients with a family history of tremor(P＜0.05).The tremor peak frequencies in the resting,postural,and weight-bearing(1 000 g)states were lower in the PD group than in the ET group(P＜0.05).There were statistically significant differences in the tremor rhythm patterns between the two groups in the resting and weight-bearing states(P＜0.05),with the PD group dominated by alternating contraction patterns and the ET group by synchronous contraction pat-terns.Multivariate Logistic regression analysis revealed that the tremor peak frequency in the weight-bearing state,the tremor rhythm pattern in the resting state,and the frequency of tremor spectrum were independent influencing factors of PD(P＜0.05).The ROC curves showed that the AUCs of the tremor peak frequency in the weight-bearing state,the tremor rhythm pattern in the resting state,and the frequency of tremor spectrum for diagnosing PD were 0.886,0.750,and 0.779,respec-tively.The combination of these three indicators yielded the highest AUC(0.936)for diagnosing PD,with a sensitivity of 81.54％and a specificity of 94.87％.Conclusion The tremor peak fre-quency in the weight-bearing state,the tremor rhythm pattern in the resting state,and the frequency of tremor spectrum provided by EMG tremor analysis can serve as clinical indicators for early diagno-sis of PD,and their combined use offers higher diagnostic value,which can be used to differentiate PD from ET.

Objective:To apply data mining and bibliometric methods to collect and analyze literatures related to the uPMR 790 integrated positron emission tomography/magnetic resonance imaging(PET/MRI)of the United Imaging Healthcare(UIH)and assess its output effects in clinical research and application,continued research and development,performance improvement,technology assessment,healthcare technology management,and other aspects.Methods:To conduct literature searches on data platforms such as China National Knowledge Infrastructure(CNKI),WanFang Data Knowledge Service Platform(WANFANG DATA),Wanfang Medical Network(WANFANG MED ONLINE),Chinese Medical Association Journal Database(Yiigle),NIH/PubMed,etc.Based on literature review,to implement bibliometric analysis and evaluate from several technological output dimensions.Results:134 sample literatures were obtained.Among them,there are 121 journal articles,10 dissertations(1 doctoral dissertation and 9 master's theses),3 case reports from the Chinese Medical Case Repository,59 of foreign language journals,and 101 articles sourced from uPMR 790 users as the first author affiliation.Engineering and technical personnel from UIH participated in 58 journal articles;89 clinical research articles,accounting for 66.42%of the sample literatures,15 engineering research and artificial intelligence(AI)research articles,accounting for 11.19%,15 technology assessment articles,accounting for 11.19%,4 healthcare technology management articles,1 experimental research article,and 10 reviews.In addition,33 related patent technologies were retrieved from UIH and its cooperative institutions,as well as UIH PET/MRI equipment users,including 20 invention patents,13 utility model patents.Conclusion:The research results show that the innovative medical equipment,the uPMR 790 PET/MRI,has definite technological outputs in clinical research and application,providing important and widely data of evidence-based medicine for clinical application promotion.It also map out the effective support of this innovative medical equipment for multidisciplinary clinical research such as medical imaging,neurology,cardiovascular and cerebrovascular diseases,geriatrics,pediatrics,etc.Driven by the model of medical-engineering integration and synergy mechanism,display multidimensional output effects such as continuous research and development,quality improvement,technology assessment,configuration management,and healthcare technology management.UIH actively participates in researchs and follows up on innovative practices in medical-engineering integration,demonstrating a positive attitude as a leading medical equipment enterprise.Real world research will provide evidence support for the application demonstration and promotion for equipment manufactured by Chinese medical equipment enterprises.

Objective To investigate the relationship between sleep disorders and coronary heart disease through big data combined with Mendelian randomization analysis.Methods Data from 2005 to 2018 National Health and Nutrition Examination Survey in the United States were utilized.Logistic regression analysis was employed to evaluate the association between sleep disorders and coronary heart disease,while analyzing relevant influencing factors.A two-sample Mendelian randomization approach was implemented using Genome-Wide Association Studies to establish causal relationships.Results Logistic regression analysis demonstrated a significant association between sleep disorders and coronary heart disease(P＜0.001),with the neutrophil-to-lymphocyte ratio serving as a mediating factor in this relationship(P＜0.001).Mendelian randomization analysis revealed a positive correlation between sleep disorders and coronary heart disease(OR=1.030,95％CI:1.01-1.04).Conclusion Sleep disorders can increase the risk of coronary heart disease by activating inflammatory factors.

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.