Implementation science (IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. It provides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.

Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Allergic conjunctivitis is a common ocular inflammatory disease, with intense itching being the most typical and distressing symptom for patients. In recent years, with the in-depth study of the interaction between the nervous and immune systems, significant progress has been made in understanding the mechanism of itching in allergic conjunctivitis. This review elaborates on the neurobiological basis of itching in allergic conjunctivitis, with a focus on the complex dialogue between immune cells and sensory neurons, particularly the core role of the IL-33-ST2-CGRP signaling axis in mediating itching. Additionally, this article introduces new findings in genetic susceptibility research, including the identification of susceptibility genes for allergic conjunctivitis through transcriptome-wide association studies. The sensory nervous system not only transmits itch signals but also actively participates in the formation of antigen channels related to conjunctival goblet cells, thereby regulating the local uptake of allergens and the initiation of the immune response. Moreover, targeted novel therapeutic strategies offer hope for patients with refractory allergic conjunctivitis. Exploring the molecular and cellular mechanisms of itching in allergic conjunctivitis will provide a theoretical basis for the development of more effective treatment methods.

Objective:To investigate effect and mechanism of hydroxysafflor yellow A(HSYA)activating neuronal autophagy on cerebral ischemia-reperfusion injury through a combination of in vitro and in vivo experiments.Methods:SD rat MCAO/R model was established by improved suture method.Rats were randomly divided into sham surgery(Sham)group,MCAO/R group and MCAO/R+HSYA group,following indicators were detected to determine extent of cerebral ischemia-reperfusion nerve damage:Z-Longa neu-rological function score was detected,TTC staining to measure cerebral infarction area,and TUNEL staining to measure cell apopto-sis;Western blot was used to detect protein expressions of autophagy related markers LC3,Beclin1,P62 and SIRT1 in rat brain tis-sue;immunofluorescence staining was used to observe expression of LC3 co-localization with neurons.OGD/R injury model of SH-SY5Y cells was established and randomly divided into Normal group,OGD/R group,OGD/R+HSYA group,OGD/R+SIRT1 inhibitor(EX-527)group and OGD/R+EX-527+HSYA group.Western blot was used to detect protein expressions of LC3,Beclin1,P62 and SIRT1.Results:Compared with Sham group,model group rats showed impaired neurological function,significantly increased neu-robehavioral scores,widespread cerebral infarction,significantly increased neuronal cell apoptosis,significantly increased autophagy related protein Beclin1 expression and LC3-Ⅱ/LC3-Ⅰ,significantly decreased P62 expression,significantly increased LC3/NeuN co-stained cells,and decreased SIRT1 expression;compared with model group,HSYA intervention group showed a significant decrease in neurological functional scores,a significant reduction in cerebral infarction area,a significant decrease in neuronal cell apoptosis,a further increase in Beclin1 expression and LC3-Ⅱ/LC3-Ⅰ,a further decrease in P62 expression,number of LC3/NeuN and P62/NeuN co-stained cells also increased,and SIRT1 expression significantly increased.Expression trends of Beclin1,LC3-Ⅱ/LC3-Ⅰ,P62 and SIRT1 of cells between normal group,model group and HSYA intervention group were same as animal experiment;compared with model group,expressions of SIRT1,Beclin1 and LC3-Ⅱ/LC3-Ⅰ in OGD/R+EX-527 group were significantly reduced,while expression of P62 was significantly increased;compared with OGD/R+EX-527 group,there was no significant change in SIRT1 expression in OGD/R+EX-527+HSYA group,LC3-Ⅱ/LC3-Ⅰ and Beclin1 expression were significantly increased,and P62 expres-sion was significantly decreased.Conclusion:HSYA can significantly improve neurological deficits in rats after cerebral ischemia-reperfusion,reduce cerebral infarction area,and decrease neuronal cell apoptosis rate,whose neuroprotective effect may be related to its activation of SIRT1,which significantly enhances neuronal autophagy.

Objective To evaluate the application value of algal glycolipid nucleic acid-free extraction technology in human papillomaviruses(HPV)nucleic acid of cervical secretions.Methods From July 1 to September 30,2023,50 HPV samples were collected from the 903rd Hospital of PLA,and 12 quality control products of HPV nucleic acid were selected.Samples treated with algal glycolipid nucleic acid-free extraction technology were tested as the experimental group,samples treated with clinical routine detection kit were tested as the control group.The nucleic acid-free extraction technology for HPV detection was assessed for accuracy,sensitivity,precision and the correlation between the two methods.Results The HPV typing results of clinical samples(27 positive samples and 23 negative samples)and quality control products in the experimental group were consistent with those in the control group,with a 100%coincidence rate and high accuracy.The experimental group's detection limit reached 100 copies/ml,demonstrating great sensitivity.The intra-assay coefficient of variations were less than 5%,indicating good precision.The detection results(Ct values)of the two groups showed a strong correlation(P<0.05),and the linear regression equation was Y=2.524+0.901X,r=0.963.There was a good correlation between the Ct values of HPV nucleic acid testing between the experimental group and the control group.Conclusion Algal glycolipid nucleic acid-free extraction technology can be used in clinical cervical secretion HPV nucleic acid detection before treatment,which is suitable for clinical application and promotion.

Objective The mechanism of Huazhuo xingxue decoction(HZXXD)in the treatment of ischemic stroke was explored through network pharmacology,molecular docking and cell validation.Methods TCMSP,TCMID,BATMAN-TCM database and literature search were used to get the chemical components and related target proteins of Huazhuo Xingxue Decoction,and the targets of dementia,stroke and amnesia were obtained from Genecards database and OMIM database.The traditional Chinese medicine-active components-target-network and protein interaction map were constructed by using Cytoscape,and the target was enriched by KEGG pathway by David database.Western blot was used to investigate the effect of HZXXD on inflammation-related core targets expression using oxygen and glucose deprivation/reoxygenation cell model.Finally,Autodock was used for molecular docking of key active ingredients and important targets to evaluate their binding activity.Results 76 active molecules and 33 common targets of herb-disease were screened out.KEGG bioaccumulation results involve multiple inflammatory signal pathways such as TNF,chemical carcinogenesis-reactive oxygen species and HIF-1.TNF-α was found to be the core target of HZXXD by oxygen glucose deprivation/reoxygenation cell experiments.Five compounds with the strongest binding ability to TNF-α,kaempferol,apigenin,aloe-emodin,baicalein and stigasterol,were screened by traditional Chinese medicine-active ingredient-target network map and molecular docking.Conclusion Huazhuo Xingxue Decoction may down regulate the expression of core target TNF-α,kaempferol,apigenin,aloe emodin,baicalein and stigasterol may be the main active substances for TNF-α binding.

Objective To investigate the anti-hepatocellular carcinoma mechanism of Chloranthus fortunei(A.Gray)Solms-Laub.via network pharmacology,molecular docking techniques and in vitro experiments.Methods Chemical composition of Chloranthus fortunei(A.Gray)Solms-Laub.was searched by literature.Swiss Target Prediction was used to find corresponding targets.STRING was used to construct protein-protein interactions network(PPI).DAVID was used to enrich GO analysis and KEGG pathway.AutoDock Vina 1.1.2 and Pymol visualisation was used for docking and validation.Results Chloranthus fortunei(A.Gray)Solms-Laub.had 61 active components,685 targets,and 279 intersections with disease targets.The PPI showed that the main active components were Luteolin,Chloranthalactone C,Shizukanolide H,Esculetin,7-Hydroxycoumarin.The key targets were GAPDH,VEGFA,STAT3,JUN,HSP90AA1,AKT1,CTNNB1,CASP3,and ALB.Biological process(BP)involved protein phosphorylation,signal transduction,regulation of RNA polymerase II promoter transcription,cell proliferation,apoptosis.Cellular component(CC)involved cytoplasm,nucleus,cell membrane,cellular exosome.Molecular function(MF)involves protein binding,ATPase,threonine kinase,protein kinase activity.KEGG involved cancer pathway,metabolic pathway,PI3K-Akt signalling pathway,cancer proteoglycans,lipids and atherosclerosis,cytomegalovirus infection,microRNAs in cancer,human T-cell leukaemia virus type 1,Ras signalling pathway,MAPK signalling pathway.Molecular docking showed that silverweed lactone H had a strong affinity for each of the other target proteins,indicating that this component plays a key role.The results of RT-qPCR assay and WB assay showed that there were significant differences in gene and protein expression levels before and after drug administration.Conclusion The Chinese medicine in Chloranthus fortunei(A.Gray)Solms-Laub.can treat hepatocellular carcinoma through the MAPK pathway,and the main active ingredients have good docking effects with the core target proteins of the disease.

Objective To investigate the anti-hepatocellular carcinoma mechanism of Chloranthus fortunei(A.Gray)Solms-Laub.via network pharmacology,molecular docking techniques and in vitro experiments.Methods Chemical composition of Chloranthus fortunei(A.Gray)Solms-Laub.was searched by literature.Swiss Target Prediction was used to find corresponding targets.STRING was used to construct protein-protein interactions network(PPI).DAVID was used to enrich GO analysis and KEGG pathway.AutoDock Vina 1.1.2 and Pymol visualisation was used for docking and validation.Results Chloranthus fortunei(A.Gray)Solms-Laub.had 61 active components,685 targets,and 279 intersections with disease targets.The PPI showed that the main active components were Luteolin,Chloranthalactone C,Shizukanolide H,Esculetin,7-Hydroxycoumarin.The key targets were GAPDH,VEGFA,STAT3,JUN,HSP90AA1,AKT1,CTNNB1,CASP3,and ALB.Biological process(BP)involved protein phosphorylation,signal transduction,regulation of RNA polymerase II promoter transcription,cell proliferation,apoptosis.Cellular component(CC)involved cytoplasm,nucleus,cell membrane,cellular exosome.Molecular function(MF)involves protein binding,ATPase,threonine kinase,protein kinase activity.KEGG involved cancer pathway,metabolic pathway,PI3K-Akt signalling pathway,cancer proteoglycans,lipids and atherosclerosis,cytomegalovirus infection,microRNAs in cancer,human T-cell leukaemia virus type 1,Ras signalling pathway,MAPK signalling pathway.Molecular docking showed that silverweed lactone H had a strong affinity for each of the other target proteins,indicating that this component plays a key role.The results of RT-qPCR assay and WB assay showed that there were significant differences in gene and protein expression levels before and after drug administration.Conclusion The Chinese medicine in Chloranthus fortunei(A.Gray)Solms-Laub.can treat hepatocellular carcinoma through the MAPK pathway,and the main active ingredients have good docking effects with the core target proteins of the disease.