Objective To explore an artificial intelligence (AI)-based method for automated hand hygiene monitoring and to compare the effectiveness of three algorithms (UniFormerV2, TDN, C3D) in recognizing hand hygiene steps in surgical settings, thereby aiding hospital infection control. Methods From April to October 2024, we non-invasively collected 641 video recordings of healthcare staff performing hand hygiene at four-bay scrub sinks in two tertiary hospitals using overhead HD cameras. The dataset was annotated by five trained experts for model training and validation. Results Following training on 385 samples, internal validation (n=119) showed the C3D model achieved 81% accuracy, 87% recall, and an 83% F1-score. The TDN model achieved 93%, 91%, and 92% for the same metrics. The UniFormerV2 model outperformed both, with an accuracy, recall, and F1-score of 93%—an improvement of over 10 percentage points compared to traditional CNNs (TDN, C3D). It also achieved an 84% accuracy in external validation, demonstrating strong generalization. Conclusion The UniFormerV2 model is more accurate than CNN-based models for hand hygiene step recognition and shows robust performance in external validation. It presents a viable tool for healthcare facilities to enhance hand hygiene management, ultimately improving medical quality and patient safety.

By consulting ancient and modern literature， this article systematically reviews and verifies the historical evolution of the herbal medicine known as Baijiang across various dimensions， including name， origin， scientific name verification， medicinal parts， production area， quality， harvesting and processing， as well as its nature， taste， and therapeutic effects， in order to provide a reference for the development and utilization of famous classical formulas containing Patriniae Herba. Patriniae Herba has a long history of use. It derives its name from the distinctive musty odor of its roots， which resembles spoiled soy sauce. However， due to its alias Kucai， there has been much confusion with other plants. Since the Ming dynasty， various plants have been used interchangeably as Baijiang. Herbal textual research showed that Patriniae Herba was first recorded in Shennong Bencaojing， and throughout history， Baijiang has been recognized as its standard name， though it has also been known by alternative names such as Luchang， Lujiang， and Suanyi. The main sources used throughout the ages were Patrinia scabiosaefolia or P. villosa， which is consistent with the 1977 edition of the Pharmacopoeia of the People's Republic of China. However， while the roots were traditionally used medicinally， the whole plant is now more commonly used in modern practice. In addition， the whole plants of Thlaspi arvense from the Cruciferae family and Sonchus brachyotus from the Compositae family are commonly used as regional substitutes for Baijiang. According to ancient records， Patriniae Herba was primarily found in Jiangxia（present-day eastern Hubei province） and Jiangdong（the region south of the lower reaches of the Yangtze River）， but modern literature shows that it is distributed throughout the country without a distinct geographical origin. In ancient times， the roots were harvested in August and sun-dried， today， the whole plant is typically dug up in summer or autumn and sun-dried. In recent times， the quality has been summarized as being best when the roots are long， the leaves are abundant and green， and the aroma is strong. Regarding the processing， ancient methods often involved baking（drying over fire）， while modern methods typically involve removing impurities， washing， and then cutting and drying the segments. The effects of Patriniae Herba are to clear heat and detoxify， eliminate blood stasis and drain pus. During the Han and Northern and Southern dynasties， it was used to treat skin diseases caused by heat， abscesses， postpartum diseases， and rheumatism， during the Five dynasties period， its therapeutic applications expanded to include diseases of the five senses， and by the modern era， conditions such as neurasthenia and insomnia were added. Regarding its properties and taste， it was recorded as bitter and neutral during the Han dynasty. By the Tang dynasty， it was slightly cold， with a taste of acrid and bitter. During the Yuan and Ming dynasties， it was mostly slightly cold and neutral， with a bitter and salty taste. In the Qing dynasty and modern times， it was mostly bitter and neutral， and in contemporary times， it has evolved to a taste of acrid， bitter， and cool. Based on the results of this study， it is recommended that when developing and utilizing famous classical formulas containing Patriniae Herba， one should select the entire herb of the historically mainstream sources， P. scabiosaefolia or P. villosa from the Valerianaceae family， and choose the processing method according to the prescription requirements. It is recommended to use raw products without specific requirements.

By consulting ancient and modern literature， this article systematically reviews and verifies the historical evolution of the herbal medicine known as Baijiang across various dimensions， including name， origin， scientific name verification， medicinal parts， production area， quality， harvesting and processing， as well as its nature， taste， and therapeutic effects， in order to provide a reference for the development and utilization of famous classical formulas containing Patriniae Herba. Patriniae Herba has a long history of use. It derives its name from the distinctive musty odor of its roots， which resembles spoiled soy sauce. However， due to its alias Kucai， there has been much confusion with other plants. Since the Ming dynasty， various plants have been used interchangeably as Baijiang. Herbal textual research showed that Patriniae Herba was first recorded in Shennong Bencaojing， and throughout history， Baijiang has been recognized as its standard name， though it has also been known by alternative names such as Luchang， Lujiang， and Suanyi. The main sources used throughout the ages were Patrinia scabiosaefolia or P. villosa， which is consistent with the 1977 edition of the Pharmacopoeia of the People's Republic of China. However， while the roots were traditionally used medicinally， the whole plant is now more commonly used in modern practice. In addition， the whole plants of Thlaspi arvense from the Cruciferae family and Sonchus brachyotus from the Compositae family are commonly used as regional substitutes for Baijiang. According to ancient records， Patriniae Herba was primarily found in Jiangxia（present-day eastern Hubei province） and Jiangdong（the region south of the lower reaches of the Yangtze River）， but modern literature shows that it is distributed throughout the country without a distinct geographical origin. In ancient times， the roots were harvested in August and sun-dried， today， the whole plant is typically dug up in summer or autumn and sun-dried. In recent times， the quality has been summarized as being best when the roots are long， the leaves are abundant and green， and the aroma is strong. Regarding the processing， ancient methods often involved baking（drying over fire）， while modern methods typically involve removing impurities， washing， and then cutting and drying the segments. The effects of Patriniae Herba are to clear heat and detoxify， eliminate blood stasis and drain pus. During the Han and Northern and Southern dynasties， it was used to treat skin diseases caused by heat， abscesses， postpartum diseases， and rheumatism， during the Five dynasties period， its therapeutic applications expanded to include diseases of the five senses， and by the modern era， conditions such as neurasthenia and insomnia were added. Regarding its properties and taste， it was recorded as bitter and neutral during the Han dynasty. By the Tang dynasty， it was slightly cold， with a taste of acrid and bitter. During the Yuan and Ming dynasties， it was mostly slightly cold and neutral， with a bitter and salty taste. In the Qing dynasty and modern times， it was mostly bitter and neutral， and in contemporary times， it has evolved to a taste of acrid， bitter， and cool. Based on the results of this study， it is recommended that when developing and utilizing famous classical formulas containing Patriniae Herba， one should select the entire herb of the historically mainstream sources， P. scabiosaefolia or P. villosa from the Valerianaceae family， and choose the processing method according to the prescription requirements. It is recommended to use raw products without specific requirements.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

Urinary system tumors are very common nowadays，including prostate cancer，renal cancer，bladder cancer，and urothelial carcinoma.In recent years，the incidence of these tumors has been on the rise.This paper briefly summarizes the emerging technologies explored by West China Hospital in recent years for urinary system tumors，such as gene sequencing analysis，radiomics and big data，liquid chromatography-mass spectrometry，multi-modal intelligent fusion diagnostic technology，surgical decision-making tools built with artificial intelligence and big data，mRNA vaccines，combination of targeted and immune therapies，and irreversible electroporation technology.These technologies provide strong support and point out the ways for the prevention，early diagnosis，and individualized treatment of urinary system tumors.

ObjectiveTo construct an intelligent model for literature screening， retrieval， and data extraction with a systematic review of coronary heart disease syndromes as an example， so as to improve the efficiency of evidence-based Chinese medicine research. MethodsBased on China National Knowledge Infrastructure （CNKI）， VIP and Wanfang Data Resource System， the articles related to coronary heart disease syndrome research published from January 1， 2000 to December 31， 2023 were retrieved. Automated tools were used to batch retrieve paper metadata. Using text similarity algorithms， papers were merged， deduplicated， and subjected to preliminary screening based on titles and abstracts. Further screening was performed using object detection and image processing technologies on the full texts and statistical tables. Natural language processing （NLP） techniques and pre-trained models were applied to extract information. ResultsThe initial search retrieved 56 255 coronary heart disease syndrome-related articles. By artificial intelligence-assisted preliminary and secondary screening， the manual verification scope was narrowed to 1075 articles. Ultimately， 646 coronary heart disease syndrome related studies were included manually. With accuracy verification showing over 90% consistency in semantic recognition and element decomposition processes， we achieved data extraction and standardization processing for both basic literature information and 38 syndrome element statistics. ConclusionBy incorporating natural language processing， pre-trained models， artificial intelligence image processing and other technologies， this study enabled efficient retrieval， screening and standardized data extraction of Chinese medicine research literature.

ObjectiveTo analyze the epidemiological characteristics of influenza virus in severe acute respiratory tract infection (SARI) cases in Jingzhou City, so as to provide a scientific basis for the formulation of influenza prevention and control policies in Jingzhou City. MethodsSARI surveillance was carried out in two sentinel hospitals in Jingzhou City from 2018 to 2023. Respiratory tract samples were collected from cases and influenza virus nucleic acid was measured using real-time fluorescent polymerase chain reaction (RT-PCR). ResultsA total of 2 603 SARI samples were tested from 2018 to 2023, and 338 samples were positive for influenza virus nucleic acid, with a detection rate of 12.99%. The highest positive detection rate was 20.22% in 2019, followed by 14.29% in 2022, and the lowest detection rate was 7.75% in 2020. There were significant differences for the positive detection rates of influenza in each monitoring year (χ²=30.386, P<0.001). There were epidemic peaks in the five surveillance years from 2018 to 2023 except 2020. There were winter epidemic peaks during 2018‒2019 and 2021‒2022, and an obvious summer epidemic peak was also observed from 2019 to 2022. H1N1, H3N2, B-Victoria and B-Yamagata were alternately prevalent in the six surveillance years. In 2019, H1N1, H3N2 and B-Victoria were alternately prevalent with time progress, in 2021 only B-Victoria was prevalent, and in 2022 H3N2 and B-Victoria were prevalent. There was no statistically significant difference for the positive detection rates of influenza virus between different genders (χ²=0.178, P=0.673). Among the four age groups, the positive rate of influenza virus in the age group of 15‒<25 years old was the highest (40.91%), followed by the age group of 25‒<60 years old (21.31%). There were statistically significant differences for the positive rates of influenza virus among different age groups (χ²=24.496, P<0.001). ConclusionThe surveillance of SARI cases in Jingzhou City could serve as an effective supplement to the surveillance of ILI in sentinel hospitals. It is suggested to expand the surveillance scope, strengthen public education and outreach on the prevention and control of respiratory diseases, thereby providing a scientific basis for influenza prevention and control.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

OBJECTIVE To analyze the influencing factors of voriconazole trough concentration and adverse drug reactions （ADR） in renal transplant recipients. METHODS Data from inpatients who received voriconazole and therapeutic drug monitoring in our hospital between January 2022 and August 2023 were retrospectively analyzed. Patients were divided into renal transplant group and non-renal transplant group based on transplantation status. A 1∶1 propensity score matching （PSM） method was used to balance differences in baselines between the two groups. Voriconazole trough concentrations， target attainment rate， clinical efficacy， and ADR were compared between the two groups. Multiple linear regression （backward） was used to analyze the factors influencing voriconazole trough concentrations in the renal transplant group. Univariate analysis and binary Logistic regression were used to identify independent risk factors for ADR in the renal transplant group. RESULTS After PSM， 48 patients were included in each group. There were no statistically significant differences in the mean voriconazole trough concentration， target attainment rate or efficacy rate between the two groups （P＞0.05）. The total incidence of ADR was significantly higher in the renal transplant group than in the non-renal transplant group （P＜0.05）. Multiple linear regression analysis showed that age， average daily dose， pulmonary infection， total bilirubin during medication， day-1 loading dose， use of the original drug， concomitant immunosuppressant use， and the occurrence of ADR were factors influencing voriconazole trough concentration in renal transplant patients （P＜0.05）. Binary Logistic regression analysis showed that abnormal direct bilirubin during medication [OR＝7.747， 95%CI （1.334， 45.005）， P＝0.023] was an independent risk factor for ADR in renal transplant patients receiving voriconazole. CONCLUSIONS Age， average daily dose， pulmonary infection， use of the original drug， day-1 loading dose， total bilirubin during medication， concomitant immunosuppressant use， and the occurrence of ADR are the factors influencing voriconazole trough concentration in renal transplant patients. Furthermore， patients with abnormal direct bilirubin during medication are more susceptible to ADR.

Aim To explore the possible regulatory effect of leptin on acyl-CoA synthetase long chain fami-ly member ACSL5 and their effect on migration and in-vasion of breast cancer cell,and to explore the underly-ing mechanism.Methods The expression of leptin receptor was detected by immunofluorescence assay.The migration and invasion ability of MCF-7 cells were detected by wound healing assay and Transwell assay respectively.The downstream target gene of leptin was analyzed by PCR microarray data.The expression of ACSL5 in breast cancer and its correlation with the staging and prognosis of breast cancer patients were as-sessed uing bioinformatics methods.The expression of ACSL5 in MCF-7 cells treated with different concentra-tions of leptin was detected using real time fluorescence quantitative polymerase chain reaction(RT-qPCR).Overexpressing ACSL5 was constructed by lentiviral transfection;the expressions of EMT related proteins,AMPK-α and p-AMPK-α were detected by Western blot.Results Leptin promoted breast cancer cell mi-gration and invasion and EMT.ACSL5 was significant-ly low expressed in breast cancer and related to progno-sis.Leptin downregulated the expression of ACSL5 through OBR.Leptin activated AMPK pathway to downregulate ACSL5 and promote migration,invasion and EMT of breast cancer cells.Conclusions Leptin may promote the migration,invasion and EMT of breast cancer by downregulating ACSL5 through activating AMPK pathway.