Children， as a special group， frequently experience of off-label drug use worldwide. Common reasons for off-label drug use in children include the lack of data on pediatric patients during the clinical trial stage of drug development， delayed updates to drug instructions， and the non-standard professional behavior of some doctors. Off-label drug use in children is a double-edged sword. It could save lives and provide a way to explore additional functions of drugs， while it may also lead to the phenomenon of hyper-indication abuse， increasing the risk of adverse drug events. Regulating off-label drug use in children can safeguard the best treatment rights and interests of children. It is recommended to encourage pharmaceutical enterprises to conduct research and development of pediatric new drugs， simplify the approval process for drug instructions amendments， accumulate evidence-based medical evidence for off-label drug use in children， standardize the process of off-label drug use in children in medical institutions， continuously improve the standardized diagnosis and treatment capabilities of pediatricians， and actively cooperate with the families of pediatric patients in diagnosis and treatment， so as to comprehensively safeguard the rights and interests of both doctors and patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Objective: To investigate the predictive value of EZH2 expression for malignant transformation in oral leukoplakia (OLK) and to provide a reference for clinical practice. Methods: This study was approved by the institutional ethics committee, and informed consent was obtained from all participants. A total of 114 patients diagnosed with OLK by pathological examination and treated at our hospital between November 2020 and July 2022 were initially enrolled. After excluding those with incomplete data or follow-up, 105 participants were included in the final analysis, comprising 14 in the high EZH2 expression group and 91 in the low EZH2 expression group. Histopathological examination of oral mucosa and immunohistochemical detection of EZH2 protein expression were performed. The follow-up period was 30 months; participants were followed until malignant transformation occurred or until the end of follow-up, at which point they were withdrawn from the study. The exposure factor was the level of EZH2 protein expression, and the outcome was the malignant transformation rate of OLK. Differences in EZH2 expression levels and transformation outcomes were analyzed. Results: There were no statistically significant differences between the high and low EZH2 expression groups in terms of age, sex, history of systemic disease, lifestyle habits, psychological status, diet, and sleep conditions (P > 0.05). Lesions in the high EZH2 expression group were mainly located on the ventral tongue, while in the low EZH2 expression group, they were more commonly found on the dorsal tongue and buccal mucosa. The malignant transformation rate was 28.6% (4/14) in the high expression group and 8.8% (8/91) in the low expression group; these differences were not statistically significant (P=0.053). In univariate Cox regression analysis, the risk of malignant transformation in the high EZH2 expression group was 3.647 times that of the low EZH2 expression group (HR = 3.647, 95% CI: 1.097-12.120, P<0.05). Kaplan-Meier survival analysis showed that over the 30-month follow-up period, the cancer-free survival rate in the high EZH2 expression group was 19.8% lower than in the low expression group, and the difference was statistically significant (P<0.05). In multivariate Cox regression analysis, only moderate and severe epithelial dysplasia were identified as independent risk factors for malignant transformation. The risk of malignant transformation in the moderate and severe dysplasia groups was 10.695 and 13.623 times higher, respectively, than in the mild dysplasia group (HR = 10.695, 95% CI: 2.270-50.396, P<0.05; HR=13.623, 95% CI: 1.918-96.774, P<0.05). EZH2 high expression was not an independent risk factor in the multivariate model (HR= 2.528, 95% CI: 0.752-8.500, P = 0.134). Conclusion High EZH2 protein expression is a risk factor for the malignant transformation of OLK but does not have independent predictive value.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

Cognitive impairment is a common clinical complication in type 2 diabetes (T2DM). T2DM-related cognitive impairment has complex and multifactorial pathogenesis. Cerebral microvascular dysfunction is an important pathological change in patients with T2DM and pre-T2DM, and it can induce blood-brain barrier injury and impaired blood perfusion regulation, with disturbed neurovascular coupling and cerebral autoregulation, leading cognitive impairment. This article reviews the epidemiology and pathophysiological mechanisms related to T2DM cerebral microvascular lesions and cognitive impairment, and how to monitor changes of cerebral microvascular structure and function so as to provide new approach for diagnosis and treatment of T2DM-related cognitive impairment.

Objective To evaluate the potential risk of transmission of angiostrongyliasis by common freshwater snails in Dali Bai Autonomous Prefecture, Yunnan Province, so as to provide insights into local surveillance of angiostrongyliasis. Methods Common freshwater snails were collected from Dali Bai Autonomous Prefecture, Yunnan Province from March to April, 2020, and identified and bred in laboratory. SD rats were infected with third-stage larvae of Angiostrongylus cantonensis that were isolated from commercially available Pomacea canaliculata snails in Dali Bai Autonomous Prefecture, and freshwater snails were infected with the first-stage larvae of A. cantonensis that were isolated from the feces of SD rats 39 days post-infection at room temperature. The developmental process and morphological characteristics of worms in hosts were observed, and the percentages of A. cantonensis infections in different species of freshwater snails were calculated. Then, SD rats were infected with the third-stage larvae of A. cantonensis that were isolated from A. cantonensis-infected freshwater snails, and the larval development and reproduction was observed. Results More than 3 000 freshwater snail samples were collected from farmlands, ditches and wetlands around Erhai Lake in Dali Bai Autonomous Prefecture, and Cipangopaludina chinensis, P. canaliculata, Parafossarulus striatulus, Oncomelania hupensis robertsoni, Galba pervia, Physa acuta, Radix swinhoei, Assiminea spp., Tricula spp. and Bellamya spp. were morphologically identified. A total of 105 commercially available P. canaliculata snails were tested for A. cantonensis infections, and 2 P. canaliculata snails were found to be infected with A. cantonensis, in which the third-stage larvae of A. cantonensis were isolated. Ten species of freshwater snails were artificially infected with the third-stage larvae of A. cantonensis, and all 10 species of freshwater snails were found to be infected with A. cantonensis, with the highest positive rate of A. cantonensis infections in Bellamya spp. (62.3%, 137/204), and the lowest in C. chinensis (35.5%, 11/31). After SD rats were infected with the third-stage larvae of A. cantonensis isolated from different species of freshwater snails, mature adult worms of A. cantonensis were yielded. Conclusions Multiple species of freshwater snails may serve as intermediate hosts of A. cantonensis under laboratory conditions in Dali Bai Autonomous Prefecture of Yunnan Province. Further investigations on natural infection of A. cantonensis in wild snails in Dali Bai Autonomous Prefecture seem justified.

ObjectiveUltra-performance liquid chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS/MS） was used to investigate the metabolism and distribution of nardosinone in rats， then metabolic pathways were speculated. MethodRats were administered with 30 mg·kg^-1 of nardosinone suspension by gavage for 3 consecutive days， and plasma， urine， feces， and tissues of heart， liver， spleen， lung， kidney， brain， stomach， and intestine were collected at predetermined time points. After treatment， the samples were processed for UPLC-Q-Exactive Orbitrap MS/MS， and the MS data were analyzed using Xcalibur 2.2 software. The metabolites were searched by comparing the base peak chromatogram and extracted ion chromatogram between the treated group and blank group， and based on the relative retention time（t_R）， quasi-molecular ion peak， precise molecular mass， and fragment ions of MS/MS， the elemental composition were searched using databases such as SciFinder and PubChem， as well as referring to relevant literature， the possible metabolites were identified and the metabolic pathways were inferred. ResultA total of 30 metabolites of nardosinone were identified， including 15， 19， 12， 7， 4， 11， 8， 13， 13， 8 and 12 metabolites in urine， feces， plasma， brain， heart， liver， spleen， lung， kidney， stomach and intestine， respectively. The main metabolic pathways of nardosinone in rats were hydroxylation， dehydroxylation， reduction， dehydrogenation， hydration， dehydration， carboxylation， glucuronidation， and dehydroxy-isopropyl. ConclusionNardosinone can be metabolized by phase Ⅰ and phase Ⅱ metabolism in rats， and the metabolites are widely distributed in the major organs. The results of this study can provide a basis for further research on the pharmacodynamic material basis， pharmacological mechanism and clinical application of nardosinone.