Background Fatigue among distribution network live-line workers in complex operational environments has become increasingly severe and requires widespread attention. Objective To investigate the positive rates of fatigue and associated influencing factors of live-line power distribution workers, and to make a reasonable strategy to reduce the fatigue of front-line workers. Methods Power supply companies in Guangdong, Guangxi, and Yunnan provinces were selected by cluster sampling in 2023, and all front-line live-line workers in the selected companies were recruited. The questionnaire used in this study consisted of two parts: one was the Fatigue Scale-14 (FS-14) for investigating fatigue status and the other was for associated influencing factors. A FS-14 score greater than 3 points was defined as fatigue. \begin{document}$ {\chi }^{2} $\end{document} test and logistic regression were employed to analyze the factors affecting fatigue. Results A total of 1341 questionnaires were distributed, and 1217 valid questionnaires were recovered, with a valid response rate of 90.75%. The average fatigue score of the participants was (6.84±3.79) points, and a total of 1054 participants scored over 3, resulting a fatigue positive rate of 86.6%. The logistic regression model showed that working under extreme weather (OR=2.03, 95%CI: 1.38, 2.98), overtime 2-3 times a week (OR=5.24, 95%CI: 1.28, 21.40), overtime everyday (OR=6.95, 95%CI: 1.71, 28.27), frequent wrist rotation (OR=1.95, 95%CI: 1.08, 3.51), and leaning back slightly (OR=2.94, 95%CI: 1.19, 7.28) associated with higher positive rates of fatigue. Conclusion The high positive rate of fatigue among live-line power distribution workers suggests severe fatigue issues. Extreme weather conditions, working overtime frequency, and maintaining wrist rotation and backward bending postures during work are main factors affecting their fatigue.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Acute pancreatitis （AP） often has an acute onset， and although most cases are self-limiting， there is still a risk of rapid deterioration， posing a serious threat to the lives of patients. Currently， traditional assessment tools such as clinical scoring systems and serum biomarkers are widely used to determine disease severity and prognosis. To enhance the accuracy of assessment， combined detection strategies integrating different scores and biomarkers are often used in clinical practice； however， there are still certain limitations such as insufficient specificity， limited early sensitivity， and a lack of consistent cut-off values. Therefore， current studies are actively exploring novel biomarkers with superior specificity and sensitivity and continuously optimizing their combined application strategies. This article summarizes the current application status of traditional assessment tools and reviews the research advances in novel biomarkers.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

OBJECTIVE: To explore the genetic basis for a boy affected with Cohen syndrome. METHODS: A boy admitted to Children's Hospital of Nanjing Medical University in January 2021 was selected as the study subject. Genome DNA was extracted from peripheral blood samples from the child and his parents. Whole exome sequencing (WES) was carried out. And candidate variants were verified by Sanger sequencing. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 202106060-1). RESULTS: WES revealed that the child has harbored compound heterozygous variants of the VPS13B gene, namely c.1563+1G>A and c.3007insC (p.A1003Afs*13), which were inherited from his mother and father, respectively. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were rates as pathogenic. The c.3007insC (p.A1003Afs*13) was unreported previously. CONCLUSION The compound heterozygous variants c.1563+1G>A and c.3007insC (p.A1003Afs*13) of the VPS13B gene probably underlay the pathogenesis of Cohen syndrome in this child. Above finding has enriched the mutational spectrum of VPS13B gene.
Humans ; Male ; Vesicular Transport Proteins/genetics* ; Intellectual Disability/genetics* ; Muscle Hypotonia/genetics* ; Microcephaly/genetics* ; Fingers/abnormalities* ; Myopia/genetics* ; Obesity/genetics* ; Developmental Disabilities/genetics* ; Mutation ; Exome Sequencing ; Child ; Heterozygote ; Retinal Degeneration

Objective To explore the correlation between visceral fat area(VFA)and triglyceride-glucose(TyG)index in people with normal body mass index(BMI)based on quantitative CT(QCT).Methods Totally 1 358 healthy adults with normal BMI who underwent QCT body composition measurement were retrospectively enrolled and divided into normal visceral fat group(normal group,VFA＜100 cm2,n=509),mild visceral fat accumulation group(mild group,100 cmn2≤VFA＜150 cm2,n=431)and severe visceral fat accumulation group(severe group,VFA≥150 cm2,n=418)according to VFA measured with QCT.Pearson and Spearman correlation analysis were performed to observe correlations of TyG index with general data and body composition in 20-40,41-60,61-90 years old men and women with normal BMI,respectively.Multiple linear regression analysis was performed to screen the independent impact factors of TyG index in normal BMI people.Results Low density lipoprotein cholesterol(LDL-C),total cholesterol(TC),glutamic-pyruvic transaminase(GPT),VFA and subcutaneous fat area(SFA)of men with normal BMI at different age stages were weakly-lowly positively correlated with TyG index(r=0.143-0.459,all P＜0.05),while high-density lipoprotein cholesterol(HDL-C)were weakly-lowly negatively correlated with TyG index(r=-0.410--0.222,all P＜0.05).LDL-C,VFA and SFA of women with normal BMI at different age stages were weakly-lowly positively correlated with TyG index(r=0.206-0.495,all P＜0.05).GPT,TC,VFA and liver fat content(LFC)were all independent risk factors,while HDL-C was independent protective factor for TyG index in people with normal BMI(all P＜0.05).Conclusion VFA was positively correlated with TyG index in people with normal BMI.Measurement of abdominal body composition based on QCT combined with lipid indexes had certain potential for predicting insulin resistance and relative metabolic diseases in abdominal obese people.

Ureaplasma urealyticum (UU) is one of the most commonly occurring pathogens associated with genital tract infections in infertile males, but the impact of seminal UU infection in semen on intrauterine insemination (IUI) outcomes is poorly understood. We collected data from 245 infertile couples who underwent IUI at The First Affiliated Hospital of USTC (Hefei, China) between January 2021 and January 2023. The subjects were classified into two groups according to their UU infection status: the UU-positive group and the UU-negative group. We compared semen parameters, pregnancy outcomes, and neonatal birth outcomes to investigate the impact of UU infection on IUI outcomes. There were no significantly statistical differences in various semen parameters, including semen volume, sperm concentration, total and progressive motility, sperm morphology, leukocyte count, the presence of anti-sperm antibody, and sperm DNA fragmentation index (DFI), between the UU-positive and UU-negative groups of male infertile patients (all P > 0.05). However, the high DNA stainability (HDS) status of sperm differed between the UU-positive and UU-negative groups, suggesting that seminal UU infection may affect sperm nuclear maturation ( P = 0.04). Additionally, there were no significant differences in pregnancy or neonatal birth outcomes between the two groups (all P > 0.05). These results suggest that IUI remains a viable and cost-effective option for infertile couples with UU infection who are facing infertility issues.
Humans ; Male ; Ureaplasma Infections/complications* ; Female ; Infertility, Male/therapy* ; Ureaplasma urealyticum/isolation & purification* ; Pregnancy ; Adult ; Pregnancy Outcome ; Semen Analysis ; Insemination, Artificial ; Semen/microbiology* ; China

Patients with Noonan syndrome (NS) are born with normal or slightly lower body length and weight compared to the normal ranges. However, their height gradually falls behind that of the general population, leading to growth retardation and delayed puberty. In China, the incidence of short stature in patients with NS is approximately 65%. Short stature in these patients arises from multiple causes, including feeding difficulties in infancy, comorbidities such as congenital heart disease, genetic heterogeneity, and disorders of the growth hormone/insulin-like growth factor-1 axis. Growth hormone is commonly used to alleviate symptoms of short stature. This article reviews the growth and development patterns at different stages of NS, analyzes the causes of short stature, and summarizes the latest advances in treatment to provide new insights for the diagnosis and management of short stature in patients with NS.
Noonan Syndrome/complications* ; Humans ; Body Height ; Growth Disorders/therapy*

Objective:To analyze the genetic characteristics of hemagglutinin（HA）and neuraminidase（NA）of influenza A（H1N1）pdm09 viruses in Kunming during the 2022-2023 influenza season.Methods:A total of 15 strains of A（H1N1）pdm09 influenza virus isolated from sentinel hospital surveillance and from outbreaks from April 2022 to March 2023 in Kunming were chosen for sequencing. The genetic analysis，which included sequence alignment，homology analysis，construction of phylogenetic tree and amino-acid mutations analysis，was carried out using MAFFT version 7，MegAlign and MEGA 11.Results:Fourteen strains isolated during the 2022-2023 influenza season in Kunming belong to clade 6B.1A.5a.2a，and A/Kunming/284/2023 belonged to clade 6B.1A.5a.2a.1. They all diverged from the northern hemisphere vaccine strain A/Wisconsin/588/2019 in clade 6B.1A.5a.2 recommended by WHO during the 2022-2023 influenza season. Comparing with the HA of the vaccine strain：A186T and Q189E，which might cause the reduction of vaccine protection，were identified in Sb of 14 strains；P137S，K142R in Ca and A186T，Q189E in Sb were identified in A/Kunming/284/2023 and two strains isolated from Thailand. The four mutations at tow antigenic sites identified immune escape at the molecular level. Q189E in the 190-helix and E224A in the 220-loop，which might change the pathogenicity of A（H1N1）pdm09 viruses，were identified in 15 strains. Comparing with NA of the vaccine strain：S200N in 14 strains and S339L in 1 strain were identified in antigenic sites. The two mutations might reduce the protection of antibodies induced by NA.Conclusion:Strengthening influenza surveillance and timely detecting new variants in Kunming contributes to preventing the importation of foreign strains and issuing early warnings for influenza outbreaks.