OBJECTIVE To summarize the current status of position training for clinical pharmacists in China and provide references for the continuous optimization of such training programs. METHODS SinoMed， CNKI，VIP and Wanfang Data were electronically searched to collect position training of clinical pharmacists studies from the inception until November 5th 2024. After data extraction and quality evaluation， descriptive analysis was performed on the results of the included studies. RESULTS & A total of 68 pieces of relevant literature were included in the study. Among them， 50 studies reported on training content， 49 involved the allocation of teaching resources in the bases， 48 addressed training methods， and 39 focused on training evaluation； only 2 studies mentioned faculty development. There were notable variations in the clinical pharmacist training programs across different bases， particularly in the allocation of teaching resources， such as the composition of the teaching team and the utilization of auxiliary teaching tools. Additionally， differences existed in training approaches， such as those employing a single method versus a blended approach. Conversely， the core training content of each base generally revolved around clinical pharmacy practice， demonstrating a degree of consistency. Moreover， the overall emphasis on teacher training and assessment tended to be obviously insufficient. Each base can focus on enhancing the competence of clinical pharmacists by allocating teaching resources， selecting training methods， improving training content， and using evaluation tools， to further enhance the quality of clinical pharmacist training.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To explore the correlation of bilateral knee joint strength asymmetry with balance,walking ability,and motor function in hemiplegic stroke patients,providing a reference for clinical assessment of stroke patients.Methods A total of 46 hemiplegic stroke patients admitted to the Rehabilitation Medicine Department of People's Hospital of Shijiazhuang from February to December 2023 were selected.According to the Berg Balance Scale(BBS)scores,patients were divided into Group A(BBS score≤20,n=23)and Group B(BBS score>20,n=23).The peak torque and differences of bilateral knee flexors and extensors were compared between two groups.Isokinetic technology was used to assess the differences in peak torque of bilateral knee joints at 60°/s and 120°/s.BBS,Functional Ambulation Classification(FAC),and Fugl-Meyer Assessment of Lower Extremity(FMA-LE)were used to evaluate patients'balance,walking ability,and lower limb motor function.The correlation between bilateral knee joint peak torque and its difference with the scores of three functional scales was analyzed.Results The peak torque of knee flexors and extensors at 60°/s in group A was significantly lower than that in group B(P<0.05).At both 60°/s and 120°/s the differences in peak torque between the healthy and affected sides of knee flexors and extensors were greater than those in group B(P<0.05).At 60°/s,the difference in peak torque of bilateral knee extensors in hemiplegic stroke patients was negatively correlated with the scores of BBS,FAC,and FMA-LE(r=-0.569,-0.582,-0.606,P<0.01),as did the knee flexors(r=-0.534,-0.386,-0.458,P<0.05).At 120°/s,similar negative correlations were observed for both knee extensors(r=-0.304,-0.304,-0.443,P<0.05)and flexors(r=-0.337,-0.349,-0.370,P<0.05).Conclusions Bilateral knee joint strength asymmetry in hemiplegic stroke patients is negatively correlated with balance and walking ability.The difference in strength between the two sides of knee joint may be one of the clinical indicators for evaluating the motor function of stroke patients.

Objective To investigate the differences of characteristic of bone marrow plasma cells in patients of different plasma cell dyscrasias according to International Myeloma Working Group(IMWG)criteria.Methods We analyzed the serological and bone marrow flow cytometry results of patients with plasma cell dyscrasias diagnosed and treated in Department of Hematology,Zhongshan Hospital(Xiamen Branch),Fudan University from Jun 12,2019 to Sep 5,2023 retrospectively.Results A total of 102 patients,63 males and 39 females,aged 22 to 85 years,were included,including 46 patients with monoclonal gammaglobulinemia of unknown significance,39 patients with multiple myeloma,5 patients with smoldering multiple myeloma and 12 patients with light-chain amyloidosis.All patients had M proteinemia,including 58 patients with IgG type and 44 patients with non-IgG type.Plasma cells were detected in the bone marrow of all patients.Clonal plasma cells were detected in the bone marrow of 79 patients.Normal plasma cells were detected in the bone marrow of 63 patients.Both clonal and normal plasma cells were detected in the bone marrow of 40 patients.Clonal plasma cells from bone marrow of 52 patients expressed CD56 and 12 patients expressed CD117.There were no significant differences in gender,age among different disease groups.There were statistical differences in M protein type,the concentration of M protein,serum involved/uninvolved free light chain ratio,the proportion of plasma cells in bone marrow nucleated cells,the proportion of clonal plasma cells in bone marrow nucleated cells,the proportion of clonal plasma cells in all bone marrow plasma cells,and the proportion of normal plasma cells in all bone marrow plasma cells among different disease groups(P<0.05).There was statistical difference in the expression of CD56 in clonal plasma cells among different disease groups(P=0.009),but no statistical difference in the expression of CD117.Conclusion The proportion of clonal plasma cells to all nucleated cells,the proportion of clonal plasma cells to all plasma cells,and the proportion of CD56 expression in abnormal plasma cells in the bone marrow of patients with light amyloidosis were similar to those of monoclonal gammopathy of undetermined significance,but significantly different from those of patients with multiple myeloma.

Objective: This cross-sectional investigation aimed to determine the incidence, clinical characteristics, prognosis, and related risk factors of olfactory and gustatory dysfunctions related to infection with the SARS-CoV-2 Omicron strain in mainland China. Methods: Data of patients with SARS-CoV-2 from December 28, 2022, to February 21, 2023, were collected through online and offline questionnaires from 45 tertiary hospitals and one center for disease control and prevention in mainland China. The questionnaire included demographic information, previous health history, smoking and alcohol drinking, SARS-CoV-2 vaccination, olfactory and gustatory function before and after infection, other symptoms after infection, as well as the duration and improvement of olfactory and gustatory dysfunction. The self-reported olfactory and gustatory functions of patients were evaluated using the Olfactory VAS scale and Gustatory VAS scale. Results: A total of 35 566 valid questionnaires were obtained, revealing a high incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain (67.75%). Females(χ2=367.013, P<0.001) and young people(χ2=120.210, P<0.001) were more likely to develop these dysfunctions. Gender(OR=1.564, 95%CI: 1.487-1.645), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), oral health status (OR=0.881, 95%CI: 0.839-0.926), smoking history (OR=1.152, 95%CI=1.080-1.229), and drinking history (OR=0.854, 95%CI: 0.785-0.928) were correlated with the occurrence of olfactory and taste dysfunctions related to SARS-CoV-2(above P<0.001). 44.62% (4 391/9 840) of the patients who had not recovered their sense of smell and taste also suffered from nasal congestion, runny nose, and 32.62% (3 210/9 840) suffered from dry mouth and sore throat. The improvement of olfactory and taste functions was correlated with the persistence of accompanying symptoms(χ2=10.873, P=0.001). The average score of olfactory and taste VAS scale was 8.41 and 8.51 respectively before SARS-CoV-2 infection, but decreased to3.69 and 4.29 respectively after SARS-CoV-2 infection, and recovered to 5.83and 6.55 respectively at the time of the survey. The median duration of olfactory and gustatory dysfunctions was 15 days and 12 days, respectively, with 0.5% (121/24 096) of patients experiencing these dysfunctions for more than 28 days. The overall self-reported improvement rate of smell and taste dysfunctions was 59.16% (14 256/24 096). Gender(OR=0.893, 95%CI: 0.839-0.951), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), history of head and facial trauma(OR=1.180, 95%CI: 1.036-1.344, P=0.013), nose (OR=1.104, 95%CI: 1.042-1.171, P=0.001) and oral (OR=1.162, 95%CI: 1.096-1.233) health status, smoking history(OR=0.765, 95%CI: 0.709-0.825), and the persistence of accompanying symptoms (OR=0.359, 95%CI: 0.332-0.388) were correlated with the recovery of olfactory and taste dysfunctions related to SARS-CoV-2 (above P<0.001 except for the indicated values). Conclusion: The incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain is high in mainland China, with females and young people more likely to develop these dysfunctions. Active and effective intervention measures may be required for cases that persist for a long time. The recovery of olfactory and taste functions is influenced by several factors, including gender, SARS-CoV-2 vaccination status, history of head and facial trauma, nasal and oral health status, smoking history, and persistence of accompanying symptoms.
Female ; Humans ; Adolescent ; SARS-CoV-2 ; Smell ; COVID-19/complications* ; Cross-Sectional Studies ; COVID-19 Vaccines ; Incidence ; Olfaction Disorders/etiology* ; Taste Disorders/etiology* ; Prognosis

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is an autoimmune inflammatory disease of the central nervous system, and little is known about its immune mechanism at present. There is a lack of disease-related biomarkers in cerebrospinal fluid except anti-NMDAR antibody, which leads to delayed diagnosis and treatment in some patients. Therefore, there has been an increasing number of studies on related cytokines in recent years to assess whether they can be used as new biomarkers for evaluating disease conditions and assisting diagnosis and treatment. Current studies have shown that some cytokines may be associated with the progression of anti-NMDAR encephalitis, and this article reviews the research advances in such cytokines associated with anti-NMDAR encephalitis.
Humans ; Cytokines ; Anti-N-Methyl-D-Aspartate Receptor Encephalitis/therapy* ; Biomarkers

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

The global COVID-19 coronavirus pandemic has infected over 109 million people, leading to over 2 million deaths up to date and still lacking of effective drugs for patient treatment. Here, we screened about 1.8 million small molecules against the main protease (M^pro) and papain like protease (PL^pro), two major proteases in severe acute respiratory syndrome-coronavirus 2 genome, and identified 1851M^pro inhibitors and 205 PL^pro inhibitors with low nmol/l activity of the best hits. Among these inhibitors, eight small molecules showed dual inhibition effects on both M^pro and PL^pro, exhibiting potential as better candidates for COVID-19 treatment. The best inhibitors of each protease were tested in antiviral assay, with over 40% of M^pro inhibitors and over 20% of PL^pro inhibitors showing high potency in viral inhibition with low cytotoxicity. The X-ray crystal structure of SARS-CoV-2 M^pro in complex with its potent inhibitor 4a was determined at 1.8 Å resolution. Together with docking assays, our results provide a comprehensive resource for future research on anti-SARS-CoV-2 drug development.
Humans ; Antiviral Agents/chemistry* ; COVID-19 ; COVID-19 Drug Treatment ; High-Throughput Screening Assays ; Molecular Docking Simulation ; Protease Inhibitors/chemistry* ; SARS-CoV-2/enzymology* ; Viral Nonstructural Proteins

Humans ; Gemcitabine ; Neoplasms