Eight new diterpenoids, Isodons A-H (1-8), comprising seco-abietane and abietane-type structures, together with 13 known analogues (9-21), were isolated from Isodon lophanthoides (Buch.-Ham. ex D. Don) Hara. The compounds (+)-3/(-)-3, (+)-4/(-)-4, and (+)-5/(-)-5 were identified as three enantiomeric pairs. The planar structures and absolute configurations of 1-8 were determined through high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), 1D & 2D nuclear magnetic resonance (NMR) spectroscopy, electronic circular dichroism (ECD) calculations, and X-ray diffraction crystallography. A cholesterol 7α-hydroxylase (Cyp7a1) luciferase reporter assay revealed significant anti-cholestatic activities for compounds 1, (+)-4, 6, 7, 12-14, and 16. Additionally, compound 6 demonstrated anti-cholestatic effects through the farnesoid X receptor (FXR)-associated signaling pathways in vitro and in vivo. These findings suggest potential applications for I. Lophanthoides in pharmaceutical development.
Abietanes/pharmacology* ; Molecular Structure ; Animals ; Isodon/chemistry* ; Humans ; Diterpenes/pharmacology* ; Plant Extracts/chemistry*

Objective: To evaluate the preventive effect of implementing the free influenza vaccination policy on school absence among primary and secondary school students, so as to provide a reference for formulating and adjusting vaccination strategies. Methods: Among primary and secondary school students aged 6 to 18 in Longgang District, Shenzhen, they were divided into a vaccinated group (265 996 students) and an unvaccinated group (122 513 students) according to their influenza vaccination history during November 2023. Propensity score matching was used to conduct a 1∶1 match between the two groups to balance covariates. The number of absences per month was set as the dependent variable to construct a difference in differences model, and Poisson regression was employed to analyze the overall and multi time point effects. Results: Vaccination against influenza was associated with low rate of absenteeism among primary and secondary school students, with an overall preventive effect of 26.52% (95% CI = 23.47% -29.45%). The preventive effects in November (the month of vaccination) and December 2023, January and March 2024 were 42.12%, 40.12%, 30.33% and 20.91%, respectively. The preventive effect of the influenza vaccine on absenteeism among primary school students (26.39%) was not significantly different from that among secondary school students ( 27.97% ) ( P >0.05). The regression coefficient for class vaccination rates ranged from 0.998 to 0.999 ( P <0.01), indicating that for every 10% increase in influenza vaccination rates, absenteeism could be reduced by 1.5% to 2.2%. Conclusion Implementing free influenza vaccination for primary and secondary school students might help to reduce the risk of absenteeism, yielding significant socioeconomic benefits.

Objective:To understand the infection status and molecular types of rhinovirus (RV) among cases of Acute Respiratory Infections (ARIs) in Luohe City, Henan Province, from 2017 to 2022.Methods:From October 2017 to June 2022, clinical and epidemiological data were collected from 2 270 cases of ARIs at Luohe Central Hospital in Henan Province. Throat swab specimens were obtained from these cases. Real-time quantitative polymerase chain reaction (qPCR) was used to screen for RV-positive specimens. Subsequently, the positive samples were subjected to nested reverse transcription polymerase chain reaction (nested RT-PCR) to amplify the full-length VP1 region. Using the MEGA software, along with 169 RV reference strains recommended by the International Committee on Taxonomy of Viruses, a phylogenetic tree was constructed to determine RV types.Results:Among the 2 270 cases of ARIs, there were 1 283 male cases (56.52%). The median age ( Q 1, Q 3) was 3 (1, 6) years, with the population under 5 years old accounting for 68.59% (1 557/2 270). RV was detected in 137 cases (6.04%), of which 68 cases (49.64%) showed co-detection with other viruses, with the most common being co-detection with enterovirus, accounting for 14.60% (20/137). The RV detection rates in the age groups of 0-4 years, 5-14 years, 15-59 years, and≥60 years were 6.42% (100/1 557), 4.69% (21/448), 3.80% (6/158), and 9.35% (10/107), respectively, with no statistically significant differences ( χ2=5.310, P=0.150). The overall detection rates of RV before (2017-2019) and during (2020-2022) the COVID-19 pandemic showed no statistically significant difference ( χ2=1.823, P=0.177). A total of 109 VP1 sequences were obtained, including 62 types. Among them, RV-A, RV-B, and RV-C had 42, 3, and 17 types respectively. Conclusion:RV is one of the predominant pathogens in ARIs cases in Luohe City, Henan Province, from 2017 to 2022. Multiple types of RV co-circulate without any apparent dominant type.

Objective:To compare the differences in prefrontal activation patterns between major depressive disorder and schizophrenia during the eye basic emotion discrimination task (EBEDT).Methods:Using functional near infrared spectroscopy (fNIRS) technology and block design, the changes of prefrontal lobe oxyhemoglobin (Oxy-Hb) concentrations under EBEDT in 40 patients with major depressive disorder, 47 patients with schizophrenia and 55 normal controls were compared. Subsequently, employing years of education as a covariate, an analysis of covariance was performed on the EBEDT behavioral results and the changes in prefrontal Oxy-Hb concentrations in the three groups.The statistical software was SPSS 25.0.Results:(1)The correct number of EBEDT in schizophrenia group (13.93±7.67) was significantly lower than that in major depressive disorder group (19.26±8.07) and normal control group (21.79±6.36)(both P<0.05), and the EBEDT reaction time in schizophrenia group ((3.97±1.77) s) was significantly longer than those in major depressive disorder group ((3.21±1.27) s) and normal control group ((2.63±0.62) s)(both P<0.05).(2)During the EBEDT task block, the normal control group showed increased activation levels in the frontal polar region, Broca's area, anterior motor cortex and supplementary motor area (SMA) compared with the control block( t=2.02-3.18, all P<0.05); and the schizophrenia group showed increased activation levels in the frontal eye field compared with the control block( t=2.26, P=0.03); while the major depressive disorder group exhibited decreased activation levels in the entire prefrontal lobe compared with the control block( t=-3.47--2.34, all P<0.05). (3)During the emotion recognition task of EBEDT, the activation levels of the frontal polar area (ch37), dorsolateral prefrontal cortex (ch31), Broca's area (ch49, ch51, ch53), and SMA (ch1, ch47, ch52) were significantly different among the major depressive disorder, schizophrenia and normal controls( F=3.23-5.53, all P<0.05). Further pairwise comparisons showed that the activation levels in all the above pathways were lower in the major depressive disorder group than those in the normal control group, and the activation levels in Broca's area (ch53) and SMA area (ch52) were lower in the schizophrenia group than those in the normal control group, while the activation levels in the frontal polar area (ch37) and Broca's area (ch49) were lower in the major depressive disorder group than those in the schizophrenia group(all P<0.05). Conclusions:In EBEDT, the activation patterns of the prefrontal cortex are different between patients with major depressive disorder and patients with schizophrenia. Patients with major depressive disorder have a decrease in prefrontal cortex activation, while patients with schizophrenia have an increase in the frontal eye field activation.The activation levels in prefrontal cortex of both patients group are lower than that of normal controls. Meanwhile, the prefrontal cortex activation level of patients with major depressive disorder is lower than that of patients with schizophrenia.

Objective:To understand the infection status and molecular types of rhinovirus (RV) among cases of Acute Respiratory Infections (ARIs) in Luohe City, Henan Province, from 2017 to 2022.Methods:From October 2017 to June 2022, clinical and epidemiological data were collected from 2 270 cases of ARIs at Luohe Central Hospital in Henan Province. Throat swab specimens were obtained from these cases. Real-time quantitative polymerase chain reaction (qPCR) was used to screen for RV-positive specimens. Subsequently, the positive samples were subjected to nested reverse transcription polymerase chain reaction (nested RT-PCR) to amplify the full-length VP1 region. Using the MEGA software, along with 169 RV reference strains recommended by the International Committee on Taxonomy of Viruses, a phylogenetic tree was constructed to determine RV types.Results:Among the 2 270 cases of ARIs, there were 1 283 male cases (56.52%). The median age ( Q 1, Q 3) was 3 (1, 6) years, with the population under 5 years old accounting for 68.59% (1 557/2 270). RV was detected in 137 cases (6.04%), of which 68 cases (49.64%) showed co-detection with other viruses, with the most common being co-detection with enterovirus, accounting for 14.60% (20/137). The RV detection rates in the age groups of 0-4 years, 5-14 years, 15-59 years, and≥60 years were 6.42% (100/1 557), 4.69% (21/448), 3.80% (6/158), and 9.35% (10/107), respectively, with no statistically significant differences ( χ2=5.310, P=0.150). The overall detection rates of RV before (2017-2019) and during (2020-2022) the COVID-19 pandemic showed no statistically significant difference ( χ2=1.823, P=0.177). A total of 109 VP1 sequences were obtained, including 62 types. Among them, RV-A, RV-B, and RV-C had 42, 3, and 17 types respectively. Conclusion:RV is one of the predominant pathogens in ARIs cases in Luohe City, Henan Province, from 2017 to 2022. Multiple types of RV co-circulate without any apparent dominant type.

Objective To establish an ultra-high liquid chromatography(UPLC)characteristic spectrum of Rheum tanguticum Maxim.ex Balf.water decoction and conduct chemical pattern recognition analysis,and to identify the medicinal materials of different origins and different processed products.Methods:UPLC was adopted to establish the characteristic spectra of 15 batches of Rheum tanguticum Maxim.ex Balf.Cluster analysis combined with principal component analysis was used to analyze their quality.Rhei Radix et Rhizoma from different origins and different processed products of Rheum tanguticum Maxim.ex Balf.were identified.Results:The characteristic spectrum of Rheum tanguticum Maxim.ex Balf.water decoction was established,18 common peaks were identi-fied,and 15 batches of Rheum tanguticum Maxim.ex Balf.were divided into 2 categories according to their origins by cluster analysis.The similarity between 15 batches of samples from different origins and the control spectrum was greater than 0.900.According to OPLS-DA analysis,a total of 6 markers(rhein-8-O-β-D-glu-cosid,resveratrol-4'-O-β-D-(6''-O-D-gallyl)glucopyranside,isolindleyin,rhein,epicatechin-3-O-D-gallate,and catechin)affecting the quality of Rheum tanguticum Maxim.ex Balf.water decoction samples were found.Rhei Radix et Rhizoma from different origins and different processed products of Rheum tanguticum Maxim.ex Balf.can be effectively distinguished.Conclusion:The established characteristic spectrum method is easy to operate and has good repeatability.It can be used for the quality control of Rheum tanguticum Maxim.ex Balf.water decoction,and can provide reference for the formulation of quality standard of formula granules of Rhei Radix et Rhizoma.

Objective:To investigate the predictive value of clinical factor model, deep learning model based on baseline plain CT images, and combination of both for predicting hematoma expansion in cerebral hemorrhage.Methods:The study was cross-sectional. Totally 471 cerebral hemorrhage patients who were firstly diagnosed in the Second Affiliated Hospital of Soochow University from January 2017 to December 2021 were collected retrospectively. These patients were randomly divided into a training dataset ( n=330) and a validation dataset ( n=141) at a ratio of 7∶3 by using the random function. All patients underwent two noncontrast CT examinations within 24 h and an increase in hematoma volume of >33% or an absolute increase in hematoma volume of >6 ml was considered hematoma enlargement. According to the presence or absence of hematoma enlargement, all patients were divided into hematoma enlargement group and hematoma non-enlargement group.Two-sample t test, Mann-Whitney U test or χ2 test were used for univariate analysis. The factors with statistically significant differences were included in multivariate logistic regression analysis, and independent influences related to hematoma enlargement were screened out to establish a clinical factor model. ITK-SNAP software was applied to manually label and segment the cerebral hemorrhage lesions on plain CT images to train and build a deep learning model based on ResNet50 architecture. A combination model for predicting hematoma expansion in cerebral hemorrhage was established by combining independent clinical influences with deep learning scores. The value of the clinical factor model, the deep learning model, and the combination model for predicting hematoma expansion in cerebral hemorrhage was evaluated using receiver operating characteristic (ROC) curves and decision curves in the training and validation datasets. Results:Among 471 cerebral hemorrhage patients, 136 cases were in the hematoma enlargement group and 335 cases were in the hematoma non-enlargement group. Regression analyses showed that male ( OR=1.790, 95% CI 1.136-2.819, P=0.012), time of occurrence ( OR=0.812, 95% CI 0.702-0.939, P=0.005), history of oral anticoagulants ( OR=2.157, 95% CI 1.100-4.229, P=0.025), admission Glasgow Coma Scale score ( OR=0.866, 95% CI 0.807-0.929, P<0.001) and red blood cell distribution width ( OR=1.045, 95% CI 1.010-1.081, P=0.011) were the independent factors for predicting hematoma expansion in cerebral hemorrhage. ROC curve analysis showed that in the training dataset, the area under the curve (AUC) of clinical factor model, deep learning model and combination model were 0.688 (95% CI 0.635-0.738), 0.695 (95% CI 0.642-0.744) and 0.747 (95% CI 0.697-0.793) respectively. The AUC of the combination model was better than that of the clinical model ( Z=0.54, P=0.011) and the deep learning model ( Z=2.44, P=0.015). In the validation dataset, the AUC of clinical factor model, deep learning model and combination model were 0.687 (95% CI 0.604-0.763), 0.683 (95% CI 0.599-0.759) and 0.736 (95% CI 0.655-0.806) respectively, with no statistical significance. Decision curves showed that the combination model had the highest net benefit rate and strong clinical practicability. Conclusions:Both the deep learning model and the clinical factor model established in this study have some predictive value for hematoma expansion in cerebral hemorrhage; the combination model established by the two together has the highest predictive value and can be applied to predict hematoma expansion.

Objective This study aimed to investigate the physical activity status of liver transplant patients,explore the relevant influencing factors,and provide a basis for developing a physical activity management program for this population.Methods A convenience sampling method was used from January to May 2023 to investigate 250 liver transplant patients in a tertiary hospital in Guangzhou,using a general situation questionnaire,international physical activity questionnaire,exercise fear scale,and organ transplant patient symptom and happiness scale.Ordinal logistic regression analysis was used to analyze the relevant influencing factors of physical activity in liver transplant patients.Results 240 valid questionnaires were collected,and the median total metabolic equivalent of physical activity in liver transplant patients was 2 433(506,30263)MET-min/week patients.Ordinal logistic regression analysis revealed that body mass index(BMI),time to transplantation,postoperative follow-up,fear of exercise,and quality of life were significant factors influencing physical activity in liver transplant patients(P＜0.05).Conclusion Liver transplant patients have lower levels of physical activity,mainly with light activity intensity such as walking.Medical staff need to pay attention to the management of physical activity in liver transplant patients,especially for obese and low-quality of life patients.Postoperative follow-up should be strengthened to improve their fear of exercise and promote early and regular exercise.

Objective:To study the distribution of drug resistance genes and virulence genes in multidrug-resistant Salmonella typhimurium strains.Methods:A total of 96 strains of Salmonella typhimurium were collected，and drug sensitivity tests were performed to evaluate the drug resistance and multidrug-resistance of Salmonella typhimurium.Multidrug-resistant Salmonella typhimurium strains were selected to conducted whole genome sequencing，and the distribution of drug resistance genes and virulence genes in the strain were analyzed.Results:Salmonella typhimurium strains had the highest resistance rates to ampicillin and ampicillin/sulbactam，with 89.58% and 76.04%，respectively.Followed by trimethoprim/sulfamethoxazole，ceftriaxone，and aztreonam，with 47.92%，38.54% and 33.33%，respectively，and low resistance rates to ciprofloxacin and levofloxacin，with 8.33% and 4.17%，respectively.Ninety-six strains were all sensitive to carbapenem antibiotics and piperacillin/tazobactam.Fifty-seven strains（59.38%）of Salmonella typhimurium showed multidrug-resistance.Resistance genes were detected in all 57 multidrug-resistant Salmonella typhimurium strains,with higher carrier rates of 98.25%,77.19%,and 59.65% for aac(6')-Iaa,aadA22,and blaTEM-1B,respectively.The multidrug-resistant Salmonella typhimurium strains had the highest carrier rates for invA，sipA，sseL，and sopB.Conclusion:Multidrug-resistant Salmonella typhimurium strains have a high incidence and a high carrier rate for multiple drug resistance genes and virulence genes.The monitoring and prevention of Salmonella typhimurium should be strengthened in the clinic in order to reduce the spreading epidemic of multidrug-resistant strains.

Objective:To summarize the content and effects of exercise interventions for stroke survivors, providing references for medical and nursing personnel in formulating exercise intervention plans for these patients.Methods:Literature on exercise interventions for stroke survivors was searched in databases such as China National Knowledge Infrastructure, Wanfang, VIP, China Biology Medicine disc, Cochrane Library, PubMed, Embase, and Web of Science up to May 1, 2023. Data extraction and summarization were conducted on the included literature.Results:Twenty-two articles were included in the review. The exercise types for stroke survivors primarily involved aerobic and resistance training; the intensity was mainly moderate to high; the frequency was mostly 3-5 times per week, with each session lasting 30-60 minutes; and the duration of interventions ranged from as short as two weeks to as long as one year. Exercise interventions improved stroke survivors' functional mobility, quality of life, cardiopulmonary function, mental state, cognitive function, fatigue, sleep, and compliance to varying degrees.Conclusions:Exercise interventions have achieved positive outcomes in stroke survivors. In the future, medical and nursing personnel can incorporate patient preferences into exercise intervention plans while ensuring patient safety to promote rehabilitation.