OBJECTIVE To provide reference for improving the pre-prescription review system and reducing the occurrence of medication error by analyzing the drug-related problems （DRPs） in the pre-prescription review orders of pediatric outpatient clinics using the Pharmaceutical Care Network Europe （PCNE） classification system. METHODS The data of pre-prescription review orders were retrospectively collected from outpatient department of Shanghai Children’s Medical Center， Shanghai Jiao Tong University School of Medicine from July 2022 to June 2023； DRPs in the pre-prescription review orders were classified and summarized by using the PCNE classification system （version 9.1）， and then analyzed in terms of types and causes of issues， and the acceptance of interventions. RESULTS A total of 66 017 DRPs orders were included， involving 41 165 patients. The proportion of DRPs orders in children aged ≤5 years old was the highest （58.25%）， followed by children aged 6-12 years old （33.52%）； the department with the highest proportion of DRPs was internal medicine of pediatrics department （71.41%）； the department with the highest incidence of DRPs was thoracic surgery department （9.73%）； top three drug categories of DRPs orders were systemic anti- infective drugs （25.26%）， Chinese patent medicines （24.74%） and respiratory drugs （22.38%）. Referring to PCNE classification system， the types of DRPs mainly focused on treatment safety （64.86%）； the reasons of DRPs orders mainly focused on dose selection （82.09%）， of which 41.26% were due to excessive drug dosage； 92.13% of interventions could be accepted and fully executed by doctors. CONCLUSIONS DRPs orders identified by the pre-prescription review system can be effectively analyzed by using PCNE classification system. Pharmacists should focus on medication use in children aged ≤5 years old， update and develop personalized prescription review rules timely， and meet the rational needs of clinical medication for children.

Abstract The physical and mental health issues of children and adolescents in China are becoming increasingly prominent. Integrating physical education deeply into the educational system and maximizing its role in fostering personal development, preventing common illnesses among students, and promoting mental health has emerged as the intersection of school health and sports. The article systematically arranges the development history and patterns of physical education in Chinese schools, summarizes the existing difficulties in the integration of physical education and educational system, and presents improvement suggestions to provide a basis for enhancing the integration system and promote the comprehensive development of children and adolescents.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

Dental pulp-dentin complex defects remain a major unresolved problem in oral medicines. Clinical therapeutic methods including root canal therapy and vital pulp therapy are both considered as conservative strategies, which are incapable of repairing the pulp-dentin complex defects. Although biomaterial-based strategies show remarkable progress in antibacterial, anti-inflammatory, and pulp regeneration, the important modulatory effects of nerves within pulp cavity have been greatly overlooked, making it challenging to achieve functional pulp-dentin complex regeneration. In this study, we propose an injectable bioceramics-containing composite hydrogel in combination of Li-Ca-Si (LCS) bioceramics and gelatin methacrylate matrix with photo-crosslinking properties. Due to the sustained release of bioactive Li, Ca and Si ions from LCS, the composite hydrogels possess multiple functions of promoting the neurogenic differentiation of Schwann cells, odontogenic differentiation of dental pulp stem cells, and neurogenesis-odontogenesis couples in vitro. In addition, the in vivo results showed that LCS-containing composite hydrogel can significantly promote the pulp-dentin complex repair. More importantly, LCS bioceramics-containing composite hydrogel can induce the growth of nerve fibers, leading to the re-innervation of pulp tissues. Taken together, the study suggests that LCS bioceramics can induce the innervation of pulp-dentin complex repair, offering a referable strategy of designing multifunctional filling materials for functional periodontal tissue regeneration.
Dental Pulp/drug effects* ; Hydrogels/pharmacology* ; Animals ; Ceramics/pharmacology* ; Dentin/drug effects* ; Biocompatible Materials/pharmacology* ; Rats ; Gelatin ; Regeneration/drug effects* ; Cell Differentiation/drug effects* ; Injections ; Humans ; Odontogenesis/drug effects*

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.