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.

Most cancers are currently incurable, partly due to abnormal post-translational modifications (PTMs). In this study, we initially used multiple myeloma (MM) as a working model and found that SUMOylation activating enzyme subunit 1 (SAE1) promotes the malignancy of MM. Through proteome microarray analysis, SAE1 was identified as a potential target for bioactive colcemid or its derivative colchicine. Elevated levels of SAE1 were associated with poor clinical survival and increased MM proliferation in vitro and in vivo. Additionally, SAE1 directly SUMOylated and upregulated the total protein expression of p27, leading to LLPS-mediated nuclear export of p27. Our study also demonstrated the involvement of SAE1 in other types of cancer cells, and provided the first monomer crystal structure of SAE1 and its key binding model with colchicine. Colchicine also showed promising results in the Patient-Derived Tumor Xenograft (PDX) model. Furthermore, a controlled clinical trial with 56 MM patients demonstrated the clinical efficacy of colchicine. Our findings reveal a novel mechanism by which tumor cells evade p27-induced cellular growth arrest through p27 SUMOylation-mediated nuclear export. SAE1 may serve as a promising therapeutic target, and colchicine may be a potential treatment option for multiple types of cancer in clinical settings.

OBJECTIVE: To investigate the effect of relaxing needling at the contracted sites of meridian-muscle regions in the patients with post-stroke shoulder-hand syndrome (SHS) at acute stage. METHODS: Eighty patients with post-stroke SHS at acute stage were randomized into an observation group (40 cases, 1 case dropped out) and a control group (40 cases, 1 case was eliminated). In the control group, the routine medication, basic rehabilitation training, and hyperbaric oxygen therapy were administered. In the observation group, besides the treatment as the control group, relaxing needling was delivered at the contracted sites of meridian-muscle regions. These contracted sites were distributed along three yin meridians of hand and three yang meridians of hand on the affected upper limbs. The intervention was given once daily, 5 times a week and for 4 weeks. Before and after treatment, the scores of visual analogue scale (VAS) for pain, edema degree, modified Barthel index (MBI), and Fugl-Meyer assessment (FMA) for motor function, and the integrated electromyography (iEMG) of surface electromyogram (sEMG) were observed in the two groups. The curative effect was evaluated after treatment and in follow-up of 2 months after treatment in the two groups. RESULTS: After treatment, VAS scores and the scores of edema degree were reduced when compared with those before treatment in the two groups (P<0.05), and the scores in the observation group were lower than those in the control group (P<0.05). MBI and FMA scores increased after treatment compared with those before treatment in the two groups (P<0.05), and the scores in the observation group were higher than those in the control group (P<0.05) after treatment. The iEMG values of the biceps brachii, triceps brachii, and wrist extensors were elevated after treatment in comparison with those before treatment (P<0.05) in the two groups, and the values in the observation group were larger than those in the control group after treatment (P<0.05). The total clinical effective rate in the observation group was 92.3% (36/39), which was better than that of the control group (74.4%, 29/39, P<0.05) after treatment; and that of the observation group was 97.4% (38/39), which was better than 82.1% (32/39) in the control group (P<0.05) in follow-up. CONCLUSION Relaxing needling at the contracted sites of meridian-muscle regions in treatment of post-stroke SHS at acute stage can attenuate the symptoms such as upper limb pain, swelling and spasm, improve motor function and the activity of daily living of patients.
Humans ; Male ; Female ; Middle Aged ; Acupuncture Therapy ; Aged ; Meridians ; Stroke/complications* ; Reflex Sympathetic Dystrophy/etiology* ; Adult ; Acupuncture Points

Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To compare the performance of 4 mainstream convolutional neural network models in one-step automatic di-agnosis of cervical vertebra maturation(CVM)and sagittal skeletal type on lateral cephalogram.Methods:600 lateral cephalograms were collected.2 orthodontists were included to determine the stage of CVM and semi-automatic measurement of sagittal skeletal type.After the data set was enhanced,80％was used as the training set and 20％as the test set.The same training method was used to compare the performance of convolutional neural network models of InceptionV3,ResNet50,ShuffleNetV2 and VGG16).Results:The accuracy of InceptionV3,ResNet50,ShuffleNetV2 and VGG16 in distinguishing CVM stage was 98.44％,89.85％,60.55％and 67.97％,and the accuracy of sagittal bone surface classification 96.56％,92.19％,80.00％and 88.13％,respec-tively.Conclusion:Among the 4 convolutional neural network models,InceptionV3 has the best overall learning performance for CVM stage and sagittal skeletal type classification.

Objective:To compare the performance of 4 mainstream convolutional neural network models in one-step automatic di-agnosis of cervical vertebra maturation(CVM)and sagittal skeletal type on lateral cephalogram.Methods:600 lateral cephalograms were collected.2 orthodontists were included to determine the stage of CVM and semi-automatic measurement of sagittal skeletal type.After the data set was enhanced,80％was used as the training set and 20％as the test set.The same training method was used to compare the performance of convolutional neural network models of InceptionV3,ResNet50,ShuffleNetV2 and VGG16).Results:The accuracy of InceptionV3,ResNet50,ShuffleNetV2 and VGG16 in distinguishing CVM stage was 98.44％,89.85％,60.55％and 67.97％,and the accuracy of sagittal bone surface classification 96.56％,92.19％,80.00％and 88.13％,respec-tively.Conclusion:Among the 4 convolutional neural network models,InceptionV3 has the best overall learning performance for CVM stage and sagittal skeletal type classification.

Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

In the aftermath of the pandemic,the government is accelerating the development of top-tier medical resources to broaden the supply and deliver superior healthcare services.However,during this transitional phase,hospitals are experiencing operational challenges due to concurrent construction activities.Notably,a shortage of parking facilities and increased traffic con-gestion continue to impactmedial consultation experience of patients.This paper tries to explore strategies and methods for dynam-ic parking management during hospital campus expansions,offering insights for other medical institutions into grappling with pa-tient parking issues.