Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

OBJECTIVES: To investigate the clinical features and prognosis of children with non-Down-syndrome-related acute megakaryoblastic leukemia (non-DS-AMKL). METHODS: A retrospective analysis was conducted on the medical data of 17 children with non-DS-AMKL who were admitted to Children's Hospital of The First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023, and their clinical features, treatment, and prognosis were summarized. RESULTS: Among the 17 children with non-DS-AMKL, there were 8 boys and 9 girls. Fourteen patients had an onset age of less than 36 months, with a median age of 21 months (range:13-145 months). Immunophenotyping results showed that 16 children were positive for CD61 and 13 were positive for CD41. The karyotype analysis was performed on 16 children, with normal karyotype in 6 children and abnormal karyotype in 9 children, among whom 5 had complex karyotype and 1 had no mitotic figure. Detected fusion genes included EVI1, NUP98-KDM5A, KDM5A-MIS18BP1, C22orf34-BRD1, WT1, and MLL-AF9. Genetic alterations included TET2, D7S486 deletion (suggesting 7q-), CSF1R deletion, and PIM1. All 17 children received chemotherapy, among whom 16 (94%) achieved complete remission after one course of induction therapy, and 1 child underwent hematopoietic stem cell transplantation (HSCT) and remained alive and disease-free. Of all children, 7 experienced recurrence, among whom 1 child received HSCT and died of graft-versus-host disease. At the last follow-up, six patients remained alive and disease-free. CONCLUSIONS Non-DS-AMKL primarily occurs in children between 1 and 3 years of age. The patients with this disorder have a high incidence rate of chromosomal abnormalities, with complex karyotypes in most patients. Some patients harbor fusion genes or gene mutations. Although the initial remission rate is high, the long-term survival rate remains low.
Humans ; Male ; Female ; Leukemia, Megakaryoblastic, Acute/etiology* ; Child, Preschool ; Infant ; Child ; Retrospective Studies ; Prognosis ; Down Syndrome/complications*

Acute lung injury(ALI) is a critical clinical condition primarily characterized by refractory hypoxemia and infiltration of inflammatory cells in lung tissue, which can progress into a more severe form known as acute respiratory distress syndrome(ARDS). Immune cells and inflammatory cytokines play important roles in the progression of the disease. Due to its unclear pathogenesis and the lack of effective clinical treatments, ALI is associated with a high mortality rate and severely affects patients' quality of life, making the search for effective therapeutic agents particularly urgent. Ginseng Radix et Rhizoma, the dried root of the perennial herb Panax ginseng from the Araliaceae family, contains active ingredients such as saponins and polysaccharides, which possess various pharmacological effects including anti-tumor activity, immune regulation, and metabolic modulation. In recent years, studies have shown that ginsenosides exhibit notable effects in reducing inflammation, ameliorating epithelial and endothelial cell injury, and providing anticoagulant action, indicating their comprehensive role in alleviating lung injury. This review summarizes the pathogenesis of ALI and the molecular mechanisms through which ginsenosides act at different stages of ALI development. The aim is to provide a scientific reference for the development of ginsenoside-based drugs targeting ALI, as well as a theoretical basis for the clinical application of Ginseng Radix et Rhizoma in the treatment of ALI.
Ginsenosides/pharmacology* ; Humans ; Acute Lung Injury/immunology* ; Animals ; Panax/chemistry* ; Drugs, Chinese Herbal

ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure （ACLF）， and to construct a risk scoring table that can accurately predict the prognosis of patients in the early stage. MethodsA retrospective analysis was performed for the clinical data of 502 patients with ACLF who were admitted to Tangdu Hospital， Air Force Medical University， from January 1， 2010 to December 31， 2020 （training set）， and the influencing factors for 28-day mortality rate were identified. The 69 ACLF patients who were admitted to Tangdu Hospital， Air Force Medical University， from January 1 to December 31， 2021 were enrolled as the validation set. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A univariate Cox regression analysis was used to obtain the early warning indicators associated with the 28-day prognosis of ACLF patients， and variance inflation factors were used to assess multicollinearity among predictors； a multivariate Cox regression analysis was used to construct a risk model for ACLF prognosis （mortality）. A risk scoring table for ACLF prognosis （mortality） was developed based on regression coefficients （β） from the model equation and weight assignments in the nomogram. Internal validation and comparison were performed for the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models （Child-Turcotte-Pugh ［CTP］ score， Model for End-Stage Liver Disease ［MELD］ score， MELD combined with serum sodium concentration ［MELD-Na］ score， and integrated MELD ［iMELD］ score） in the training set， while external validation and comprehensive evaluation of the scoring table and the other scoring models were performed in the validation set. The Nagelkerke’s R² test and the Hosmer-Lemeshow test were used to assess the degree of fitting of the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models， and fitting curves were plotted. C-index was used to assess the discriminatory ability of the scoring table for ACLF prognosis （mortality） and the other scoring models， and the Z-test was used for comparison of C-index between different models. The decision curve analysis was used to compare the clinical benefits of the scoring table for ACLF prognosis （mortality） and the other scoring models. ResultsThe multivariate Cox regression analysis showed that age （hazard ratio ［HR］=1.027， 95% confidence interval ［CI］： 1.015 — 1.039， P<0.001）， hepatic encephalopathy grade （grade 1： HR=2.928， 95%CI： 1.463 — 5.858， P=0.002； grade 2： HR=3.811， 95%CI： 2.078 — 6.988， P<0.001； grade 3： HR=3.916， 95%CI： 1.917 — 8.001， P<0.001； grade 4： HR=6.966， 95%CI： 4.559 — 10.644， P<0.001）， an increase in total bilirubin （TBil） by ≥17.1 μmol/L per day （HR=1.771， 95%CI： 1.248 — 2.513， P=0.001）， creatinine （HR=1.005， 95%CI： 1.004 — 1.006， P<0.001）， neutrophil count （HR=1.092， 95%CI： 1.060 — 1.126， P<0.001）， and international normalized ratio （HR=1.298， 95%CI： 1.187 — 1.418， P<0.001） were independent risk factors associated with the 28-day mortality rate of ACLF patients， and a risk scoring table was constructed for ACLF prognosis （mortality）. The Nagelkerke’s R² test showed that the risk scoring table for ACLF prognosis （mortality） had an R² value of 0.599 in the training set and 0.722 in the validation set， which were higher than the R² values of CTP， MELD， MELD-Na， and iMELD scores. The Hosmer-Lemeshow test showed that the risk scoring table for ACLF prognosis （mortality） had a P value of 0.280 in the training set and 0.788 in the validation set. The C-index analysis showed that the scoring table had a higher C-index than the other scoring models in the validation set （all P<0.001）， as well as a higher C-index than CTP score in the training set （P<0.001）. The decision curve analysis showed that the risk scoring table for ACLF prognosis （mortality） had higher clinical net benefits than the other scoring models. ConclusionCompared with other scoring models currently used in clinical practice， the novel risk scoring table for ACLF prognosis （mortality） constructed based on the six predictive factors of age， hepatic encephalopathy grade， an increase in TBil by ≥17.1 μmol/L per day， creatinine， neutrophil count， and international normalized ratio has a relatively high value in predicting the 28-day prognosis of ACLF patients.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

BACKGROUND:Ossification of the ligamentum flavum was previously considered to be rare in the population.As research has progressed,its incidence rate is increasing gradually,which has aroused the interest of a large number of researchers. OBJECTIVE:To visualize and analyze the research results on ossification of the ligamentum flavum from the Web of Science Core Collection since 1999 using bibliometric methods,and to review the research history of ossification of the ligamentum flavum,highlighting important literature,summarizing research hotspots,and providing ideas for researchers to find research directions. METHODS:Using the Web of Science Core Collection as the data source,relevant papers on ossification of the ligamentum flavum were searched and screened.VOSviewer 1.6.19 and CiteSpace 6.2.R6 were used to conduct the visual analysis of annual publication volume,research countries,institutions,citations,journals,authors,and keywords. RESULTS AND CONCLUSION:(1)A total of 347 papers were included.Since 1999,the number of published papers has increased in a spiral pattern.China's research started later than Japan's,but the number of publications has come up later,with Peking University being the institution with the most publications,and Prof.Chen Zhongqiang from Peking University being the scholar with the most publications.(2)Five of the 10 most frequently cited publications were related to the surgical treatment of the disease.(3)Excluding keywords directly related to the research topic and synthetically analyzing frequencies and betweenness centralities of key words,terms such as"thoracic myelopathy,""dural ossification,""minimally invasive surgery,"and"ossification of the posterior longitudinal ligament"occupied a central position in this field.(4)Keywords clustering analysis showed that clinical manifestations and surgical treatment of ossification of the ligamentum flavum accounted for a large proportion of study.(5)The timeline and burst analysis of keywords revealed that"minimally invasive surgery"appeared as a keyword around 2015,with the highest burst strength and the latest burst start time,and began to receive extensive attention from researchers in 2019.The burst of the keyword"dural ossification"has not yet ended.(6)Surgical treatment for ossification of the ligamentum flavum has been at the forefront of research.Development and research of minimally invasive surgery and research on dural ossification secondary to ossification of the ligamentum flavum are both current research hotspots and possible future research trends.

OBJECTIVE To systematically evaluate the efficacy and safety of tislelizumab in the treatment of advanced non- small cell lung cancer （NSCLC）. METHODS Computerized searches were conducted in PubMed， Embase， the Cochrane Library， CNKI， Wanfang and other Chinese and English databases to collect randomized controlled trials （RCTs） on tislelizumab for advanced NSCLC. The search period was from the establishment of the databases to December 2024. After strictly screening the literature， extracting data and conducting quality evaluations in accordance with the inclusion and exclusion criteria， a meta-analysis was performed using RevMan 5.3 and Stata 16.0 software. RESULTS A total of 18 RCTs involving 2 337 patients were included， with 1 283 in the experimental group and 1 054 in the control group. The meta-analysis results showed that the objective response rate [RR＝1.61， 95%CI （1.48， 1.75）， P＜0.000 01]， disease control rate [RR＝1.21， 95%CI （1.13， 1.29）， P＜0.000 01]， progression free survival [HR＝0.55， 95%CI （0.45， 0.66）， P＜0.000 01]， and overall survival [HR＝0.78， 95%CI（0.62， 0.97）， P＝0.03] were significantly better in the experimental group than in the control group. There was no statistically significant difference in the incidence of adverse reactions between the two groups [RR＝1.00， 95%CI （0.73， 1.37）， P＝1.00]； among the common adverse reactions， only the incidence of liver function impairment was significantly higher in the experimental group than in the control group [RR＝1.30， 95%CI （1.10， 1.54）， P＜0.01]. CONCLUSIONS Tislelizumab in combination with chemotherapy or targeted drugs significantly improves the efficacy in patients with advanced NSCLC without increasing the risk of adverse reactions overall. However， liver function should be closely monitored during treatment.

BACKGROUND:Adeno-associated virus(AAV)gene therapy has been proven to be reliable and safe for the treatment of osteoarthritis in recent years.However,given the complexity of osteoarthritis pathogenesis,single gene manipulation for the treatment of osteoarthritis may not produce satisfactory results.Previous studies have shown that nuclear factor κB could promote the inflammatory pathway in osteoarthritic chondrocytes,and bone morphogenetic protein 4(BMP4)could promote cartilage regeneration.OBJECTIVE:To test whether combined application of AAV-p65shRNA and AAV-BMP4 will yield the synergistic effect on chondrocytes regeneration and osteoarthritis treatment.METHODS:Viral particles containing AAV-p65-shRNA and AAV-BMP4 were prepared.Their efficacy in inhibiting inflammation in chondrocytes and promoting chondrogenesis was assessed in vitro and in vivo by transfecting AAV-p65-shRNA or AAV-BMP4 into cells.The experiments were divided into five groups:PBS group;osteoarthritis group;AAV-BMP4 group;AAV-p65shRNA group;and BMP4-p65shRNA 1:1 group.Samples were collected at 4,12,and 24 weeks postoperatively.Tissue staining,including safranin O and Alcian blue,was applied after collecting articular tissue.Then,the optimal ratio between the two types of transfected viral particles was further investigated to improve the chondrogenic potential of mixed cells in vivo.RESULTS AND CONCLUSION:The combined application of AAV-p65shRNA and AAV-BMP4 together showed a synergistic effect on cartilage regeneration and osteoarthritis treatment.Mixed cells transfected with AAV-p65shRNA and AAV-BMP4 at a 1:1 ratio produced the most extracellular matrix synthesis(P<0.05).In vivo results also revealed that the combination of the two viruses had the highest regenerative potential for osteoarthritic cartilage(P<0.05).In the present study,we also discovered that the combined therapy had the maximum effect when the two viruses were administered in equal proportions.Decreasing either p65shRNA or BMP4 transfected cells resulted in less collagen Ⅱ synthesis.This implies that inhibiting inflammation by p65shRNA and promoting regeneration by BMP4 are equally important for osteoarthritis treatment.These findings provide a new strategy for the treatment of early osteoarthritis by simultaneously inhibiting cartilage inflammation and promoting cartilage repair.