This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Objective To develop the Children's Screen Interaction Quality Questionnaire(CSIQ)suit-able for measuring Chinese children aged 0 to 4 years,and to test its reliability and validity.Methods The purposive sampling method was used,and the guardians of 30 normal children aged 0 to 4 years undergoing physical examinations in the Department of Child Health Care of Guiyang Maternal and Child Health Care Hospital from February to April 2023 were selected as the interview objects.25 initial items were constructed through literature review,semi-structured interviews,and the Delphi expert consultation method.With the convenience sampling method,2 242 guardians of children aged 0 to 4 years old in the small and middle classes of 9 kindergartens in Guiyang City,Zunyi City,and Renhuai City were surveyed for item analysis,exploratory factor analysis,confirmatory factor analysis,and reliability and validity analysis.Results Exploratory factor a-nalysis extracted three factors,namely screen content interaction,reality interaction,and media interaction,with a total of 12 items.The cumulative variance explained rate of the 3-factor model was 69.829％.Confirma-tory factor analysis supported the three-factor model of CSIQ:x2/df=4.424,root mean square error of ap-proximation(RMSEA)=0.066,normed fit index(NFI)=0.955,comparative fit index(CFI)=0.965,incre-mental fit index(IFI)=0.965,Tucker-Lewis index(TLI)=0.955,goodness-of-fit index(GFI)=0.955,and the CSIQ had good convergent validity and discriminant validity.Conclusion The CSIQ has good reliability and validity.

OBJECTIVE: To investigate the relationship between angiotensin Ⅱ type 1 receptor autoantibody (AT1-AA) and semen parameters. Methods： The semen samples of 820 male patients who were treated in the Reproductive Medicine Center of Taiyuan Central Hospital from August 2022 to August 2023 were retrospectively analyzed. The levels of AT1-AA and Ang Ⅱ of semen were detected by ELISA, and the function of AT1-AA was detected by cardiomyocyte beating assay in suckling rats. The patients were divided into low group, median group and high group according to the OD values of AT1-AA. The differences in general data and semen parameters between different groups were analyzed. And the correlation between AT1-AA level and semen parameters in semen of all study subjects was analyzed by the method of Spearman analysis. And the relationships between AT1-AA OD value, Ang Ⅱ level and semen parameters in the AT1-AA high value group were analyzed as well. RESULTS: AT1-AA was present in semen with good function. There was no significant difference in the general data of patients in different AT1-AA levels (P>0.05). In the comparison of semen parameters among the groups with different levels of AT1-AA, there were differences in sperm concentration, PR concentration, NP％, and ALH among the three groups (P<0.05). And AT1-AA OD value was positively correlated with total sperm count, sperm concentration, PR concentration, and NP％, and negatively correlated with semen volume (P<0.05). In the AT1-AA high value group, the OD value of AT1-AA in semen was negatively correlated with inactive sperm, and positively correlated with total motility (［PR+NP］％), curve rate, mean path rate, and ALH. However, there was no correlation between the level of Ang Ⅱ in semen and semen parameters (P>0.05). CONCLUSION The presence of AT1-AA in semen may be associated with the promotion of sperm motility.
Male ; Humans ; Autoantibodies ; Sperm Motility ; Semen ; Retrospective Studies ; Receptor, Angiotensin, Type 1/immunology* ; Animals ; Rats ; Angiotensin II ; Adult ; Sperm Count ; Semen Analysis ; Receptor, Angiotensin, Type 2/immunology*

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.

OBJECTIVE T o carry out the health economics evaluation and cost-benefit analysis of the type b Hae-mophilus influenzae(Hib)vaccination for the children who were hospitalized due to Hib infection so as to provide evidence for public health policies.METHODS The children who were diagnosed with Hib-related respiratory tract infections or meningitis and were hospitalized in respiratory medicine department,infection management depart-ment,emergency rooms and neurology department of Jiangxi Provincial Children's Hospital from Jan.1,2021 to Dec.31,2023 were recruited as the research subjects.Based on a 1∶1 matching condition,the matching variables included four items such as the same age for the admission to the hospital,same gender,same department and same grade of disease severity.The children for whom the primary immunization of Hib vaccination(including Hib monovalent vaccine and Hib-containing combination vaccine)were completed and the integrity of vaccination infor-mation could be checked out were assigned as the intervention group,while the children for whom the primary im-munization of Hib vaccination was not completed were chosen as the control group.The clinical data,vaccination data and the data such as length of hospital stay and hospitalization cost were collected from the children.The cost-benefit of the Hib vaccination among the children with Hib infection was observed.RESULTS A total of 622 hospi-talized children who were detected with Hib-positive respiratory tract infections or meningitis were enrolled in the study,and 73 children(20 children from infection management department,27 children from respiratory medi-cine department,26 children from emergency rooms)were finally included in the intervention group after matc-hing and multiple rounds of screening,73 children were chosen as the control group based on a 1∶1 matching con-dition.The male children accounted for 57.53％(42 cases)in both groups,and the female children accounted for 42.47％(31 cases)in both groups.With the respect to the length of hospital stay,it was 7.00(5.00,8.00)days in the intervention group,7.00(6.00,8.00)days in the control group(Z=-0.341,P=0.733).In terms of the hospitalization cost,it was 7 756.17(6 617.92,10 617.69)yuan in the intervention group,9 040.65(8 033.76,10 935.84)yuan in the control group(Z=-2.795,P=0.005).The cost of Hib vaccination was 343.03 yuan per capita in the intervention group,and the benefit-cost ratio(BCR)was 1∶3.74(343.03 yuan/1 284.48 yuan).CONCLUSIONS The Hib vaccination can save the hospitalization cost and has high cost effectiveness.It is sugges-ted that the Hib vaccination should be promoted and the coverage rate of Hib vaccination should be raised among the age-eligible children.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Objective:To investigate the curative effect and possible mechanism of rifaximin treatment on monocrotaline-induced hepatic sinusoidal obstruction syndrome (HSOS) in mice.Methods:Twenty-four male C57BL/6J mice were divided into three groups and treated with solvent control, monocrotaline, and rifaximin, respectively. The histopathological changes of the liver and intestine were observed by hematoxylin-eosin staining. The differences were compared in liver parameters, serum liver enzymes, inflammatory factors, apoptotic factors, gut microbiota, and gut tight junction proteins among three groups of mice. The inter-group comparison was conducted using a t-test and one-way analysis of variance.Results:The rifaximin-treated group had significantly improved liver histopathology. The serological levels of alanine aminotransferase and aspartate aminotransferase were (559.04±89.42) U/L and (676.90±106.25) U/L, respectively, which were significantly lower than those in the PA-HSOS model group [(846.05±148.46) U/L and (953.87±58.10) U/L, P<0.05], and were accompanied by lower levels of apoptotic cells and inflammatory factors. Additionally, the rifaximin-treated mice group gut microbiota had higher diversity compared with the PA-HSOS group ( P<0.05), and the Shannon index was 7.77±0.10 and 7.16±0.07, respectively, indicating apparent differences in microbiota among different groups. The abundance of Firmicutes in the rifaximin group was 39.58%±0.56%, which was significantly higher than that in the model group (24.25%±0.64%, P<0.05), while the abundance of Bacteroidetes was 54.7%±0.41%, which was significantly lower than that in the model group (70.92%±0.49%, P<0.05). Simultaneously, the expressions of gut tight junction proteins ZO-1 and Occludin showed an upward trend and validated transcription levels compared to the model group following rifaximin intervention ( P<0.05). Conclusion:Rifaximin can alleviate monocrotaline-induced hepatic sinusoidal obstruction syndrome in mice, and its mechanism may be via gut microbiota regulation, which in turn plays a role in improving intestinal barrier function.

Processing for deodorization is widely used in the production of animal-derived Chinese medicinal materials. In this study, Heracles Neo ultra-fast gas-phase electronic nose combined with chemometrics was employed to analyze the overall odor difference of Cervi Cornu Pantotrichum(focusing on that derived from Cervus nippon Temminck in this study) before and after processing. The results showed that the electronic nose effectively distinguished between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. HS-GC-MS was used to identify and quantify the volatile components in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum, and 35 and 37 volatile components were detected in the medicinal materials and decoction pieces, respectively. The medicinal materials and decoction pieces contained 28 common volatile components contributing to the odor of Cervi Cornu Pantotrichum. The odor activity value(OAV) of each volatile component was calculated based on the olfactory threshold and relative content. The results showed that there were 17 key odor substances such as isovaleraldehyde, 2-methylbutanal, isobutyraldehyde, hexanal, and methanethiol in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. All of them had bad odor and were the main source of the odor of Cervi Cornu Pantotrichum. The results of principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) showed that there were significant differences in volatile components between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. Based on the thresholds of P<0.05 and Variable Importance in Projection(VIP)>1, 21 differential volatile odor components were screened out. Among them, isopentanol, isovaleraldehyde, 2-methylbutanal, n-nonanal, and dimethylamine were the key differential odor compounds between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. The odor compounds and their relative content reduced, and some flavor substances such as esters were produced after processing with wine, which was the main reason for the reduction of the odor after processing of Cervi Cornu Pantotrichum.
Odorants/analysis* ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods* ; Animals ; Volatile Organic Compounds/analysis* ; Deer ; Drugs, Chinese Herbal/chemistry*

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.