ObjectiveMaxing Shigan Tang， as a traditional prescription for treating pneumonia， has a remarkable clinical effect. This study aims to systematically investigate the molecular mechanisms of Maxing Shigan Tang in treating pneumonia by integrating its structural and transcriptomic data at the target level. MethodsNP-TCMtarget， a developed systematic network pharmacological model focusing on drug targets， was used to mine the effect targets of Maxing Shigan Tang for treating pneumonia based on the transcriptome data. The structural targets of chemical components in Maxing Shigan Tang were predicted based on the structural information. The intersection of effect targets and structural targets was taken as the direct targets of Maxing Shigan Tang for treating pneumonia， and the remaining effect targets except direct targets were taken as indirect targets. Finally， functional enrichment analysis was performed on these targets to explore the molecular mechanism of Maxing Shigan Tang in treating pneumonia. ResultsA total of 1 604 effect targets and 816 structural targets of Maxing Shigan Tang for treating pneumonia were identified. Maxing Shigan Tang exerted its therapeutic effects through 164 direct targets and 1 440 indirect targets. The functional analysis of 1 604 effect targets predicted 19 significantly enriched pathways. Comprehensive analysis of these pathways showed that these targets were mainly linked to immune and inflammatory responses， such as cytokine-cytokine receptor interaction， necrosis factor （NF）-κB signaling pathway， and helper T cell 17 differentiation. ConclusionFocusing on the hierarchical feature of drug targets and the structural and transcriptomic data， this study systematically reveals the path of herbal component-direct target-indirect target-biological effects of Maxing Shigan Tang in treating pneumonia.

ObjectiveMaxing Shigan Tang， as a traditional prescription for treating pneumonia， has a remarkable clinical effect. This study aims to systematically investigate the molecular mechanisms of Maxing Shigan Tang in treating pneumonia by integrating its structural and transcriptomic data at the target level. MethodsNP-TCMtarget， a developed systematic network pharmacological model focusing on drug targets， was used to mine the effect targets of Maxing Shigan Tang for treating pneumonia based on the transcriptome data. The structural targets of chemical components in Maxing Shigan Tang were predicted based on the structural information. The intersection of effect targets and structural targets was taken as the direct targets of Maxing Shigan Tang for treating pneumonia， and the remaining effect targets except direct targets were taken as indirect targets. Finally， functional enrichment analysis was performed on these targets to explore the molecular mechanism of Maxing Shigan Tang in treating pneumonia. ResultsA total of 1 604 effect targets and 816 structural targets of Maxing Shigan Tang for treating pneumonia were identified. Maxing Shigan Tang exerted its therapeutic effects through 164 direct targets and 1 440 indirect targets. The functional analysis of 1 604 effect targets predicted 19 significantly enriched pathways. Comprehensive analysis of these pathways showed that these targets were mainly linked to immune and inflammatory responses， such as cytokine-cytokine receptor interaction， necrosis factor （NF）-κB signaling pathway， and helper T cell 17 differentiation. ConclusionFocusing on the hierarchical feature of drug targets and the structural and transcriptomic data， this study systematically reveals the path of herbal component-direct target-indirect target-biological effects of Maxing Shigan Tang in treating pneumonia.

Epimedin B(EB)is one of the main flavonoid ingredients present in Epimedium brevicornum Maxim.,a traditional herb widely used in China.Our previous study showed that EB was a stronger inducer of melanogenesis and an activator of tyrosinase(TYR).However,the role of EB in melanogenesis and the mechanism underlying the regulation remain unclear.Herein,as an extension to our previous investi-gation,we provide comprehensive evidence of EB-induced pigmentation in vivo and in vitro and eluci-date the melanogenesis mechanism by assessing its effects on the TYR family of proteins(TYRs)in terms of expression,activity,and stability.The results showed that EB increased TYRs expression through microphthalmia-associated transcription factor-mediated p-Akt(referred to as protein kinase B(PKB))/glycogen synthase kinase 3β(GSK3β)/β-catenin,p-p70 S6 kinase cascades,and protein 38(p38)/mitogen-activated protein(MAP)kinase(MAPK)and extracellular regulated protein kinases(ERK)/MAPK pathways,after which EB increased the number of melanosomes and promoted their maturation for melanogenesis in melanoma cells and human primary melanocytes/skin tissues.Furthermore,EB exerted repigmentation by stimulating TYR activity in hydroquinone-and N-phenylthiourea-induced TYR inhibitive models,including melanoma cells,zebrafish,and mice.Finally,EB ameliorated monobenzone-induced depigmentation in vitro and in vivo through the enhancement of TYRs stability by inhibiting TYR misfolding,TYR-related protein 1 formation,and retention in the endoplasmic reticulum and then by downregulating the ubiquitination and proteolysis processes.These data conclude that EB can target TYRs and alter their expression,activity,and stability,thus stimulating their pigmentation function,which might provide a novel rational strategy for hypopigmentation treatment in the pharmaceutical and cosmetic industries.

Objective To explore the effectiveness of Failure Modes and Effects Analysis(FMEA)in emergency man-agement of sudden incidents involving outpatient and emergency patients in general hospitals,to provide references for the optimi-zation of emergency response process for such incidents.Methods Based on FMEA,we identified and evaluated risks in the e-mergency response procedures for sudden incidents involving outpatient and emergency patients in general hospitals.Potential fail-ure modes were analyzed to identify key risks with a Risk Priority Number(RPN)greater than 125.Continuous quality improve-ment measures were implemented to control these risks,and the effectiveness of these controls was evaluated using chi-square tests for statistical analysis.Results A total of 16 risk points in 4 major areas were identified.After implementing continuous quality improvement measures,the RPNs of these high-risk points decreased to below 125,effectively controlling the potential risks.This intervention significantly improved the utilization rate of emergency equipment,the timely reporting rate of sudden in-cidents,the timely feedback rate of emergency response,with statistically significant differences(P＜0.01).Conclusion The application of FMEA to outpatient and emergency management of sudden incidents helps optimize the emergency response process,thus enhancing the emergency response capability of general hospitals and ensuring effective handling of such incidents.

Objective:To implement a scoping review on prediction models for the outcome of the trial of labor after cesarean (TOLAC), providing a reference for the clinical application of the model.Methods:Literature on TOLAC outcome prediction models was searched in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang Data, VIP, and China Biology Medicine disc. The search period was from database establishment to May 1, 2023. Two researchers independently screened literature and extracted data, and used the prediction model risk of bias assessment tool (PROBAST) to analyze the risk of bias and applicability of the included studies.Results:A total of 24 articles were included. The research design was mainly retrospective, with diverse model fitting methods and good predictive performance. The predictive factors of the TOLAC outcome prediction model especially included Bishop score, body mass index, mode of delivery, age, pregnancy days or weeks, and vaginal delivery history.Conclusions:In the future, research on the construction of TOLAC outcome prediction models may lean towards prospective research design, further improving research design, model fitting methods, model evaluation, and validation.

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.

Objective To explore the lipid-lowering effect of Qige Decoction before and after compatibility through the combination of pharmacodynamics and liver metabolomics,and to provide new research strategies for exploring the scientific notation of traditional Chinese medicine compatibility.Methods According to the pharmacodynamic strategy,three groups of drug administration were set up as Qige Decoction group,Astragali Radix-Puerariae Radix group,and Pericarpium Citri Tangerinae group.Four indices of blood lipids,serum biochemical indicators,and liver morphology and pathology were used to evaluate the intervention effect of Qige Decoction on hyperlipidemic rats.Liver metabolomics technology was used to analyze the effects of Qige Decoction on metabolites before and after compatibility,and multivariate statistical analysis was used to evaluate the differences between groups in terms of differential metabolites and metabolic pathways.Results Compared with the model group,the callback abilities of four indices of blood lipid in the Qige Decoction group were higher than those in Astragali Radix-Puerariae Radix group and Pericarpium Citri Tangerinae group,among which the total cholesterol(TC)and triglyceride(TG)levels in the Qige Decoction group decreased(P＜0.05).A total of 86 potential biomarkers were identified by liver metabolomics,with 23,13,and 7 metabolites being significantly different in the Qige Decoction group,Astragali Radix-Puerariae Radix group,and Pericarpium Citri Tangerinae group,respectively(P＜0.05).Metabolic pathway analysis of 29 specific biomarkers with significant callback effects showed that they were related to glycerophospholipid metabolism,linoleic acid metabolism,α-linolenic acid metabolism,sphingolipid metabolism,arachidonic acid metabolism,and unsaturated fatty acid biosynthesis.Qige Decoction mainly regulates glycerophospholipid and linoleic acid metabolism,and uniquely acts on sphingolipid metabolism.Conclusion Qige Decoction has more lipid-lowering targets after compatibility,with better lipid-lowering effects than the Astragali Radix-Puerariae Radix group and Pericarpium Citri Tangerinae group.This study provides experimental evidence and research strategies for further revealing the scientific notation of traditional Chinese medicine compatibility.

OBJECTIVE: To investigate the early effectiveness of transiliac-transsacral screws internal fixation assisted by augmented reality navigation system HoloSight (hereinafter referred to as "computer navigation system") in the treatment of posterior pelvic ring injuries. METHODS: A retrospective analysis was made in the 41 patients with posterior pelvic ring injuries who had been treated surgically with transiliac-transsacral screws between June 2022 and June 2023. The patients were divided into navigation group (18 cases, using computer navigation system to assist screw implantation) and freehand group (23 cases, using C-arm X-ray fluoroscopy to guide screw implantation) according to the different methods of transiliac-transsacral screws placement. There was no significant difference in gender, age, body mass index, causes of injuries, Tile classification of pelvic fracture, days from injury to operation, usage of unlocking closed reduction technique between the two groups ( P>0.05). The time of screw implantation, the fluoroscopy times, the guide wire adjustment times of each screw, and the incidence of complications were recorded and compared between the two groups. The position of the transiliac-transsacral screw was scanned by CT within 2 days after operation, and the position of the screw was classified according to Gras standard. RESULTS: The operation was successfully completed in both groups. The time of screw implantation, the fluoroscopy times, and the guide wire adjustment times of each screw in the navigation group were significantly less than those in the freehand group ( P<0.05). There were 2 cases of incision infection in the freehand group, and the incision healed by first intention after active dressing change; there was no screw-related complication in the navigation group during operation and early period after operation; the difference in incidence of complications between the two groups (8.7% vs. 0) was not significant ( P=0.495). According to the Gras standard, the screw position of the navigation group was significantly better than that of the freehand group ( P<0.05). CONCLUSION Compared with the traditional freehand method, the computer navigation system assisted transiliac-transsacral screws internal fixation in the treatment of posterior pelvic ring injuries has advantages of improving the accuracy of screw implantation and reducing radiation damage and the time of screw implantation.
Humans ; Retrospective Studies ; Surgical Wound Infection ; Replantation ; Body Mass Index

Objective:To deeply explore the pain experience of patients with rheumatoid arthritis, so as to provide a basis for the practical interventions in the next step.Methods:Using the phenomenological research method, 18 patients with rheumatoid arthritis who experienced pain in the First Hospital of Soochow University from September 2020 to January 2021 were selected for semi-structured interviews, and the Colaizzi 7-step analysis method was used for data analysis.Results:The pain experience of patients with rheumatoid arthritis were summarized into six themes. Pain was complex and erratic, pain relief strategies were ineffective, pain negatively affected daily life, expected more pain relief, seeking help selectively when pain occurs, and experienced pain brings positive change.Conclusions:Medical staff must pay attention to the real experiences and demands of pain in rheumatoid arthritis patients, use information technology and multidisciplinary collaboration to provide patients with effective pain management strategies and encourage patients to make more positive changes to relieve pain symptoms.

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts.To fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico pre-diction of TSSs solely based on genomic sequences.Most of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome scale.Here,we present DeeReCT-TSS,a deep learning-based method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data.We show that by effectively incorporating these two sources of information,DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types.Furthermore,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific TSSs.Finally,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states.The source code for DeeReCT-TSS is available at https://github.-com/JoshuaChou2018/DeeReCT-TSS_release and https://ngdc.cncb.ac.cn/biocode/tools/BT007316.