Liumotang comes from the Yuan dynasty's Effective Prescription Handed Down for Generations of Physicians. It is composed of six medicinal materials： Arecae Semen， Aquilariae Lignum Resinatum， Aucklandiae Radix， Linderae Radix， Rhei Radix et Rhizoma， and Aurantii Fructus. It is a classical formula for treating abdominal pain due to Qi stagnation and constipation accompanied by heat. This study systematically collated the records of Liumotang in ancient medical books and modern clinical literature and conducted in-depth analysis and textual research on its formula source， main diseases， composition， dosage， medical books， container capacity， processing， preparation method， usage， drug basis， formula meaning， and other key information， so as to provide a powerful reference for the development and clinical application of compound preparations of the classical formula Liumotang. The results show that Liumotang was first seen in Effective Prescription Handed Down for Generations of Physicians， and many medical books of the past dynasties have imitated this. In terms of drug basis， the dried and mature seeds of the palm plant Areca catechu， resin-containing wood of the Daphneaceae plant Aquilaria sinensis， the dried roots of the Asteraceae plant woody Aucklandia lappa， the dried tuber root of the Lauraceae plant Lindera aggregata， the dried roots and rhizomes of the knotweed plant， R. palmatum， R.tangutikum， and R. officinale， and the dried and unripe fruits of the citrus genus C. aurantium and its cultivated varieties from the family Rutaceae were selected. In terms of dosage， through the textual research on bowls in the Ming and Qing dynasties， combined with the conversion of medicines and bowl capacity in the Qing dynasty， it was estimated that the dosage of each drug in the Yuan dynasty was 10.86 g. In the Ming and Qing dynasties， the dosage of drugs was mostly equal， but the dosage of drugs was somewhat different. In terms of processing， preparation method， and usage， in the medical books of the past dynasties， the processing of drugs has slightly changed， but raw drugs are used in all preparations. The preparation method and usage did not change much during the Yuan， Ming， and Qing dynasties， except for certain differences in dosage. In terms of syndrome， Liumotang was first used to treat abdominal pain due to Qi stagnation and constipation accompanied by heat. Medical books of the past dynasties often omit the symptoms of heat. In modern clinical practice， Liumotang is mainly used in the digestive system and urinary system diseases and is mostly used to treat constipation-predominant irritable bowel syndrome， biliary reflux gastritis， functional constipation， slow transit constipation， and other diseases， with no adverse reactions found yet. The above results provide a reliable scientific basis for the development and clinical treatment of Liumotang compound preparations.

Lung cancer, a highly prevalent and deadly malignancy globally, poses a significant disease burden in China and is the leading cause of cancer death. Despite rapid advances in medicine, its incidence and mortality rates remain stubbornly high, making it a major challenge in public health. Against the backdrop of rapid progress in precision medicine, the paradigm of lung cancer treatment is shifting from single traditional therapy to multi-dimensional integration. This article comprehensively reviews the innovations and challenges in lung cancer surgery in 2024, aiming to explore the future development of surgical treatment with colleagues and to improve patients' quality of life and achieve the goal of "cure".
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Humans ; Lung Neoplasms/surgery*

Oral squamous cell carcinoma (OSCC) accounts for over 90% of oral malignancies, with more than 370 000 new cases and approximately 188 000 deaths annually worldwide. In China, there are roughly 65 000 new cases and 35 000 deaths each year, showing a significant upward trend compared with 2015 statistics. Despite continuous advancements in treatment modalities, the 5-year survival rate remains stagnant at 50%-60%, where tumor heterogeneity and therapy resistance persist as fundamental barriers to precision oncology. To address these critical challenges, this study established a standardized bioban-king protocol for OSCC patient-derived organoids (PDOs) (Patent: Method for constructing an oral squamous cell carcinoma organoid bank, ZL202311378598.3). Through groundbreaking optimization of culture media, enzymatic digestion kinetics, and stepwise cryopreservation, we achieved a biobanking success rate exceeding 95% and pioneered synchronous cultivation of matched primary tumors, lymph node metastases, and adjacent normal mucosa from individual patients, preserving spatial heterogeneity and stromal interactions. Leveraging this platform, we developed high-throughput drug screening: Quantified heterogeneity-driven differential chemoresponse using adenosine triphosphate (ATP)-based viability assays; We discovered resistance mechanisms: Identified sialylated cancer IgG (SIA-cIgG)-mediated cis-platin resistance (primary/secondary) through PTPN13 suppression, with anti-SIA-cIgG combination therapy demonstrating synergistic efficacy. Besides, we elucidated metastatic drivers: CRISPR-Cas9-edited organoids revealed WDR54 promoted metastasis via H3K4me3/H4K16ac epigenetic reprogramming, activating epithelial-mesenchymal plasticity (EMP) and inducing partial epithelial-mesenchymal transition (pEMT). This "holographic patient-mirroring" platform provided unprecedented resolution for OSCC precision therapy and had been formally incorporated into the Chinese Stomatological Association Technical Guidelines (Technical guideline for establishing patient-derived oral squamous cell carcinoma organoid banks, CHSA 2024-08). Future integration of immune-competent organoids, 3D-bioprinted vasculature, and multi-omics-AI systems will accelerate personalized oncology. These innovations will accelerate clinical translation of personalized therapeutic regimens, ultimately bridging the gap between bench research and bedside application.
Humans ; Organoids/pathology* ; Mouth Neoplasms/genetics* ; Carcinoma, Squamous Cell/pathology* ; Tissue Banks ; Biological Specimen Banks

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Objective To develop and compare prediction models for hyperuricemia(HUA)in perim-enopausal and postmenopausal women using Lasso regression,random forest,and multivariate logistic regres-sion.Methods A multi-stage,stratified cluster sampling method was used to select 12 790 subjects from An-ning City,Yunnan Province.Prediction models for HUA were constructed using Lasso regression,random for-est,and multivariate logistic regression.The efficacy of the model was evaluated by accuracy,sensitivity,speci-ficity,F1 score,and area under the curve(AUC).Results LASSO regression analysis screened 19 variables for inclusion in the model,such as age,waist circumference,diastolic blood pressure,BMI,HDL-C,fasting blood glucose(FBG),etc.The accuracy rate was 0.701,the sensitivity was 0.703,the specificity was 0.680,and the F1 score was 0.806.The AUC(95%CI)was 0.770(0.748-0.792).The results of the random forest model show that variables such as creatinine,triglyceride-glucose index(TyG),TG,BMI,TC,Urea nitrogen(Urea),and ALT were relatively important,with an accuracy rate of 0.663,a sensitivity of 0.653,a specificity of 0.738,and an F1 score of 0.774.The AUC(95%CI)was 0.763(0.741-0.785).Multivariate logistic re-gression results showed that 11 variables including creatinine(Cr),TyG,BMI,Urea,and ALT were included in the model,with an accuracy rate of 0.705,a sensitivity of 0.707,a specificity of 0.686,an F1 score of 0.809,and an AUC(95%CI)of 0.771(0.749-0.793).Conclusion The overall performance of LASSO re-gression and multivariate logistic regression models is better.The random forest model has a strong variable screening ability and high specificity,and can be used as a supplement to provide more accurate predictions.

Objective To investigate the causal relationship between gut microbiota and obstruc-tive sleep apnea syndrome(OSA)using a two-sample bidirectional Mendelian randomization(MR)approach.Methods Eligible single nucleotide polymorphisms(SNPs)were selected from genome-wide association study(GWAS)databases as instrumental variables.A bidirectional MR analysis was conducted to evaluate the causal effects between gut microbiota and OSA.Various statistical methods,including the inverse variance weighted(IVW)method,MR-Egger regression,the weighted model method,and the weighted median method,were employed for association assessment.The MR pleiot-ropy residual sum and outlier(MR-PRESSO)test,along with Cochran's Q test and the leave-one-out cross-validation method,were used to assess heterogeneity and pleiotropy.Results According to the IVW method analysis,an increased abundance of the genus Faecalibacterium(sp002397985)(OR=0.847,95％CI,0.719 to 0.997,P=0.046)was associated with a reduced risk of OSA.Conversely,increased abundances of the genera Bacteroides(OR=1.075,95％CI,1.016 to 1.138,P=0.012),Haemophilus(sp001679485)(OR=1.106,95％CI,1.016 to 1.203,P=0.021),Streptococcus(OR=1.168,95％CI,1.036 to 1.316,P=0.011),and Blautia(sp002159835)(OR=1.169,95％CI,1.035 to 1.319,P=0.012)were associated with an elevated risk of OSA.The reverse MR analysis revealed no significant association between the risk of OSA and the abundance of gut microbiota.The results of Cochran's Q test,MR-Egger test,and MR-PRESSO test indicated no het-erogeneity or horizontal pleiotropy(P＞0.05).Conclusion Causal relationships exist between the five genera(Faecalibacterium,Bacteroides,Haemophilus,Streptococcus,and Blautia)and the risk of OSA.

The performance appraisal of public hospitals is the most official and authoritative assessment and evaluation of tertiary public hospitals in China,and it is an important measure to guide hospitals to improve their internal management level and achieve high-quality development.In this study,a data monitoring management system based on the performance appraisal indicators of national tertiary public hospitals was developed and constructed through intelligent collection and reporting,report in-tegration,visual analysis,data drilling,etc.,which realized the one-stop dynamic management of indicators,optimized the data filling process of national examination indicators,improved the data quality and credibility,and promoted the integration of na-tional assessment and hospital assessment.the intelligent management level of the hospital has been improved,which provides strong support for the hospital's refined operation management and scientific decision-making.

Fetal structural anomalies and birth defects are primarily caused by genetic variants such as chromosomal number abnormalities, copy number variations (CNV), single nucleotide variants (SNV), and small insertions and deletions (indel). Whole-genome sequencing (WGS) based on next-generation sequencing (NGS) as an emerging technology for genetic disease diagnosis can detect the aforementioned types of variants. In recent years, high-depth WGS (> 30×) for prenatal diagnosis has also become available, and proved to be practical for unraveling the genetic etiology of fetal developmental abnormalities. To fascilitate clinical practice, test development and preliminary implementation of WGS for diagnosing fetal structural anomalies, we have formulated a consensus over the application of WGS in prenatal diagnosis by compiling previously published consensuses, guidelines, and research findings to provide a guidance on data analysis, reporting recommendations, and consultation of prenatal WGS results.

As a commonly used tool in obstetrics, fetal growth curves play an important role in screening for small for gestational age infants and predicting fetal growth restriction. However, a high-quality fetal growth standard curve based on the Chinese population has not yet been established. Compared to fetal growth reference values, fetal growth standards have higher requirements. This article discusses several key elements in establishing fetal growth standards in China, including the selection of research sites, the inclusion of low-risk pregnant women, the implementation of longitudinal study, the determination of sample size, the standardization of measurements, and quality control, aiming to ensure the scientific validity and accuracy of the fetal growth standards.

China prospective multicenter birth cohort (Prospective Omics Health Atlas birth cohort, POHA birth cohort) study was officially launched in 2022. This study, in collaboration with 12 participating units, aims to establish a high-quality, multidimensional cohort comprising 20 000 naturally conceived families and assisted reproductive families. The study involves long-term follow-up of parents and offspring, with corresponding biological samples collected at key time points. Through multi-omics testing and analysis, the study aims to conduct multi-omics big data research across the entire maternal and infant life cycle. The goal is to identify new biomarkers for maternal and infant diseases and provide scientific evidence for risk prediction related to maternal diseases and neonatal health.