Background: Recurrent pregnancy loss undermines the physical and mental health of women. Recent randomized controlled trials have reported some effects of traditional Chinese medicine (TCM); however, whether various TCM methods have different effectiveness remains unclear. Objective: To comprehensively evaluate the efficacy and adverse events of TCM for patients with RPL and to explore whether various TCM methods have different effectiveness. Methods: Ten databases were searched up to May 27, 2024. The risk of bias was assessed using the RoB2 tool. The certainty of the evidence was evaluated using the grading of Recommendations, Assessment, Development, and Evaluation tool. Pairwise and network analyses were conducted using Stata 18.0. Results: A total of 47 randomized controlled trials enrolling 6678 women with RPL were included. Pairwise analysis showed that use of TCM had a significantly lower miscarriage rate (RR 0.50 [95% CI 0.45, 0.55]), lower preterm birth rate (RR 0.81 [95% CI 0.67, 0.98), and lower adverse event rate (RR 0.46 [95% CI 0.37, 0.58]). Moreover, use of TCM was associated with a higher alive-fetus rate (RR 1.21 [95% CI 1.15, 1.26]), live-birth rate (RR 1.20 [95% CI 1.15, 1.25]), and full-term rate (RR 1.37 [95% CI 1.23, 1.53]) compared with nonuse of TCM. Network analysis demonstrated that Bushenshugan combined with conventional Western medicine was ranked the best for the reduction of miscarriage rate. Discussion: Use of TCM is more likely to improve pregnancy outcomes and reduce adverse events compared with nonuse of TCM in patients with RPL. Different TCM methods have differences in reducing the miscarriage rate. The Bushenshugan method might be a potential optimal TCM therapy, but more high-quality evidence is needed to further validate and evaluate the efficacy and safety.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Objective To addresses the challenges arising from the rapid expansion of pharmaceutical clinical trials and the growing demands for quality management,this paper investigates the application of low-code technology in project management.Its goals are to enhance the operational efficiency and execution capabilities of clinical trial institutions,ensure trial quality and safety,and accelerate the translation of pharmaceutical scientific achievements.Methods A brainstorming session was conducted to analyze the technical and functional requirements for managing pharmaceutical clinical trial projects.Utilizing the ＂template design＂ and ＂decision analysis＂ functionalities of low-code technology,the study adopted a modular and visually driven data management approach to develop a system compliant with Good Clinical Practice(GCP)standards.This system integrates key functionalities,including project progress management,funding management,drug inventory management,and quality control.Its effectiveness was evaluated through real-world operation and performance validation.Results The system had demonstrated stable operation with substantial improvements in practical application.Compared with conventional management approaches,it significantly enhanced project management efficiency:the time required for project schedule management was reduced by 80%,the efficiency of financial processing increased by 95%,drug inventory management efficiency improved by 75%,and the time spent on quality control was shortened by 60%.Conclusion The pharmaceutical clinical trial project management system developed using low-code technology offers substantial advantages and promising application potential.It represents a critical practice in applying digital and intelligent tools to advance pharmaceutical productivity in the medical and healthcare sectors.

Aim To evaluate the bioequivalence of two oral preparations of rivaroxaban tablets(test preparation T and refe-rence preparation R)in fasting/postprandibular state in healthy Chinese subjects.Methods A randomized,open,single-dose,four-cycle,completely repeated crossover experiment was used in this study.A total of 70 healthy male and female subjects were enrolled,including 38 subjects in the fasting group and 32 sub-jects in the postprandial group.Rivaroxaban tablets(2.5 mg/tablet)were taken orally once per cycle and their reference preparations were tested.The plasma rivaroxaban concentration was determined by LC-MS/MS method.The pharmacokinetic parameters of rivaroxaban tablets were calculated by WinNonlin software,and the parameters were analyzed and processed.Re-sults The PK parameters of rivaroxaban tablets and reference preparations in fasting group were as follows:Cmax was(72.48±17.08)and(66.36±15.64)μg·L-1,respectively.AUC0-t were(383.49±101.06)and(370.43±102.16)h·ng·mL-1,and AUC0-inr were(389.58±102.28)and(375.84±103.01)h·μg·L-,respectively.Main PK parameters of subjects taking rivaroxaban tablets orally after meals:Cmax were(66.48±15.64 and 60.87±13.44)μg·L-1,AUC0-t were(404.44±72.58)and(381.80±79.93)h·μg·L-1,re-spectively.AUC0_inf was(410.88±73.55)and(393.64±69.71)h·μg·L-1,respectively.Under fasting and postmeal conditions,subjects took rivaroxaban test and reference prepara-tion orally,one tablet(2.5 mg/tablet)each time.The geometric mean of the main pharmacokinetic parameters of rivaroxaban in plasma(Cmax,AUC0-t,AUC0-inf)and their corresponding values had a 90％confidence interval ranging from 80.00％to 125.00％.No serious adverse events or unexpected adverse e-vents occurred in both groups.Conclusion Rivaroxaban tablets are bioequivalent and safe in vivo under fasting and postprandial conditions.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

Objective:To explore the progress and trend in research of target trial emulation (TTE) and provide reference for research in this field.Methods:A literature retrival of research papers in this field published as of November 30, 2024 was conducted based on three databases (i.e. PubMed, Web of Science, and Scopus). The papers which were highly cited were analyzed by Bibliometrix package in R 4.3.2. The co-occurrence network of keywords were analyzed by using software VOSviewer. The keyword burst test was carried out with software CiteSpace.Results:A total of 685 papers from 314 journals were included. The annual number of the papers published showed a significant growth in recent three years. JAMA Network Open had the highest publication mumber related to TTE (34 papers), Annals of Internal Medicine had the highest H-index and American Journal of Epidemiology had the highest total citations. In the 2 997 authors, Hernán MA made a greatest contribution. In the 2 046 institutions, Harvard Medical School was at leading position. The analysis on highly cited papers and keyword co-occurrence showed that TTE was mainly used in the studies of COVID-19 vaccine, cancer and the treatment efficacy and safety of chronic diseases. The analysis on the co-occurence of keyword burst test showed that keywords frequently used until 2024 were COVID-19 vaccine, cardiovascular disease and breast cancer. Conclusions:TTE is mainly used in the studies of public health emergency (such as COVID-19), patients with cancer and chronic diseases. TTE will play a crucial role when randomized controlled trial is difficult to conduct or current evidence requirement can not be met.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the progress and trend in research of target trial emulation (TTE) and provide reference for research in this field.Methods:A literature retrival of research papers in this field published as of November 30, 2024 was conducted based on three databases (i.e. PubMed, Web of Science, and Scopus). The papers which were highly cited were analyzed by Bibliometrix package in R 4.3.2. The co-occurrence network of keywords were analyzed by using software VOSviewer. The keyword burst test was carried out with software CiteSpace.Results:A total of 685 papers from 314 journals were included. The annual number of the papers published showed a significant growth in recent three years. JAMA Network Open had the highest publication mumber related to TTE (34 papers), Annals of Internal Medicine had the highest H-index and American Journal of Epidemiology had the highest total citations. In the 2 997 authors, Hernán MA made a greatest contribution. In the 2 046 institutions, Harvard Medical School was at leading position. The analysis on highly cited papers and keyword co-occurrence showed that TTE was mainly used in the studies of COVID-19 vaccine, cancer and the treatment efficacy and safety of chronic diseases. The analysis on the co-occurence of keyword burst test showed that keywords frequently used until 2024 were COVID-19 vaccine, cardiovascular disease and breast cancer. Conclusions:TTE is mainly used in the studies of public health emergency (such as COVID-19), patients with cancer and chronic diseases. TTE will play a crucial role when randomized controlled trial is difficult to conduct or current evidence requirement can not be met.

Objective To explore the functional mechanism of spinal cord fragile X mental retardation protein(FMRP)involved in neuropathic pain(NP)by using the sciatic nerve model of chronic compression injury(CCI).Methods First,to investigate the changes of spinal cord FMRP and β-catenin following the development of NP,this study compared the 50%mechanical withdrawal threshold(MWT)and thermal withdrawal latency(TWL)in CCI rats,as well as changes of FMRP and β-catenin in the spinal dorsal horn post-surgery,through random grouping.Immunofluorescence staining was performed on spinal cord tissue sections from CCI rats.Second,to further validate the alterations in pain behavior when the FMRP function was lost,we measured the 50%MWT,TWL,and FMRP and β-catenin in the spinal dorsal horn after FMRP knockdown in CCI rats.Finally,we measured the 50%MWT,TWL,and FMRP and β-catenin in the case of FMRP hyperfunction for validation.Results Compared with the baseline CCI group and the naive and sham groups after modeling,the CCI group after modeling showed decreases in 50%MWT and TWL(all P<0.001).After modeling,compared with the naive group and the sham group,the CCI group presented up-regulated expression of FMRP(P=0.027,P=0.022)and β-catenin(P<0.001,P=0.001)in the spinal dorsal horn.No co-localization of FMRP with astrocytes and microglia was observed in the spinal cord,while the co-localization with neurons was observed.Compared with the baseline,the CCI+FMRP knockdown group showed decreases in 50%MWT(P=0.015)and TWL(P=0.001)after modeling.After intrathecal injection of small interfering RNA(siRNA),the 50%MWT(P=0.020)and TWL(P=0.009)of the CCI+FMRP knockdown group were increased.Moreover,compared with the CCI group and the CCI+solvent group,the CCI+FMRP knockdown group showed increases in 50%MWT(both P<0.001)and TWL(P=0.005,P=0.006).After intrathecal injection of siRNA,the expression levels of FMRP(P=0.012,P=0.007)and β-catenin(both P<0.001)in the spinal dorsal horn of the CCI+FMRP knockdown group were lower than those of the CCI group and the CCI+solvent group.Compared with the baseline FMRP overexpression group and the naive and negative control groups after adeno-associated virus(AAV)injection,the FMRP overexpression group after AAV injection showed decreases in 50%MWT and TWL(all P<0.001).After AAV injection,compared with the naive group and the negative control group,the FMRP overexpression group demonstrated up-regulated expression of FMRP(both P<0.001)and β-catenin(P=0.006,P=0.008)in the spinal cord.Conclusions This study confirms that spinal cord FMRP and β-catenin are involved in NP induced by CCI.Spinal cord FMRP may be one of the potential therapeutic targets for NP.
Animals ; beta Catenin/metabolism* ; Neuralgia/metabolism* ; Fragile X Mental Retardation Protein/physiology* ; Spinal Cord/metabolism* ; Rats ; Rats, Sprague-Dawley ; Male