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 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.

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

Objective: To investigate the value of uterine morphological parameters and endometrial T₂ signal intensity (T₂-SI) in evaluating the degree of the fibrotic repair secondary to endometrial injury. Methods: From Sep. 2018 to Feb. 2023, this study prospectively enrolled 29 patients with fibrotic repair secondary to severe endometrial injury (severe group), 17 patients with fibrotic repair secondary to mild to moderate endometrial injury (mild to moderate group), and 40 healthy women of reproductive age (control group) in Nanjing Drum Tower Hospital. The length of uterine cavity (LUC), length of cervix and isthmus (LCI), width of upper uterine cavity (WUUC) and width of lower uterine cavity (WLUC) were measured using magnetic resonance imaging. T₂-SI of endometrium and subcutaneous fat of buttocks were measured, and endometrial normalized T₂-SI (nT₂-SI; T₂-SI of endometrium/T₂-SI of subcutaneous fat of buttocks) was calculated. Statistical analyses of data were performed using one-way analysis of variance, Mann-Whitney U test, intraclass correlation coefficient, Spearman rho test, area under the receiver operating characteristic curve (AUC). Results: LUC, WUUC, WLUC and endometrial nT₂-SI of severe group [(19.7±3.5) mm, (26.9±6.4) mm, (7.9±1.4) mm, 0.73±0.11, respectively] were significantly lower than those of the control group (all P<0.01), while LCI and WUUC/LUC [(51.3±7.3) mm and 1.38±0.34] were significantly higher than those of the control group (all P<0.001). LUC and WLUC of severe group were significantly lower than those of mild to moderate group [(32.4±5.1) mm and (8.8±1.2) mm; all P<0.05], while LCI and WUUC/LUC were significantly higher than those of mild to moderate group [(41.8±8.6) mm and 0.94±0.16; all P<0.001]. LUC and endometrial nT₂-SI of mild to moderate group were significantly lower than those of the control group [ (32.4±5.1) vs (35.3±3.5) mm, 0.68±0.13 vs 0.80±0.12; all P<0.01]. LUC, WUUC, WLUC and endometrial nT₂-SI were significantly negatively correlated to the degree of the fibrotic repair secondary to endometrial injury (Spearman rho:-0.794, -0.441, -0.471 and -0.316, respectively; all P<0.05), while LCI and WUUC/LUC were significantly positively correlated to the degree of the fibrotic repair secondary to endometrial injury (Spearman rho: 0.481 and 0.674, respectively; all P<0.05). LUC and WUUC/LUC showed high value in distinguishing severe group from the control group or mild to moderate group (all AUC>0.9, all P<0.001). Conclusion: As noninvasive and quantitative biomarkers, uterine morphological parameters and endometrial nT₂-SI could evaluate the degree of the fibrotic repair secondary to endometrial injury.
Humans ; Female ; Uterus ; Endometrium ; Health Status ; Hospitals ; ROC Curve

Objective:To explore the clinical characteristics and influencing factors intracranial hemorrhagic lesions in patients with intracranial venous sinus thrombosis (CVST).Methods:The 108 patients with CVST from January 2013 to December 2020 in the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed. Among them, 46 patients had intracranial hemorrhagic lesions (hemorrhagic lesion group), and 62 patients did not have intracranial hemorrhagic lesions (non hemorrhagic lesion group). The general medical history data, laboratory examination results, imaging examination results, National Institutes of Health stroke scale (NIHSS) score within 24 hours of admission and modified Rankin scale (mRS) score (2 to 6 scores indicating poor prognosis) at discharge (or on the 30th day of hospitalization) were recorded. Multivariate Logistic regression analysis was used to analyze the independent risk factors of intracranial hemorrhagic lesions in patients with CVST and the independent risk factors of prognosis in patients CVST combined with intracranial hemorrhagic lesions.Results:The NIHSS score, neutrophil to lymphocyte ratio (NLR), high sensitivity C-reactive protein (hs-CRP) and the proportions of changes in consciousness, epileptic seizures, poor prognosis, oral contraceptives, congenital protein C or S deficiency in hemorrhagic lesion group were significantly higher than those in non hemorrhagic lesion group: 4 (0, 10) scores vs. 0 (0, 5) scores, 4.62 (2.50, 8.58) vs. 3.46 (2.01, 5.00), 13.1 (5.6, 56.7) mg/L vs. 7.5 (2.8, 18.0) mg/L, 47.8% (22/46) vs. 29.0% (18/62), 39.1% (18/46) vs. 21.0% (13/62), 39.1% (18/46) vs. 21.0% (13/62), 32.6% (15/46) vs. 8.1% (5/62), 30.4% (14/46) vs. 12.9% (8/62), and there were statistical differences ( P<0.01 or <0.05). The incidences of straight sinus and multiple venous sinus thrombosis in hemorrhagic lesion group were significantly higher than those in non hemorrhagic lesion group: 43.5% (20/46) vs. 24.2% (15/62) and 82.6% (38/46) vs. 58.1% (36/62), and there were statistical differences ( P<0.05 or <0.01). Multivariate Logistic regression analysis result showed that the oral contraceptives, multiple venous sinus thrombosis and the elevated hs-CRP, NLR were independent risk factors of intracranial hemorrhagic lesions in patients with CVST ( OR = 6.950, 5.182, 1.026 and 1.137; 95% CI 1.453 to 33.243, 1.076 to 24.960, 1.007 to 1.046 and 1.004 to 1.287; P<0.05 or <0.01). Among 46 patients with CVST combined with intracranial hemorrhagic lesions, 28 patients had a good prognosis, and 18 patients had a poor prognosis. The NIHSS score, NLR, hs-CRP and the proportions of oral contraceptives, congenital protein C or S deficiency, changes in consciousness and epileptic seizures in patients with poor prognosis were significantly higher than those in patients with good prognosis: 9 (4, 28) scores vs. 0 (0, 6) scores, 7.43 (3.86, 12.99) vs. 3.3 (1.97, 6.77), 127.0 (96.5, 168.0) mg/L vs. 11.5 (3.3, 33.5) mg/L, 10/18 vs. 17.9% (5/28), 10/18 vs. 14.3% (4/28), 12/18 vs. 35.7% (10/28) and 11/18 vs. 25.0% (7/28), and there were statistical difference ( P<0.01 or <0.05). Multivariate Logistic regression analysis result showed that the elevated hs-CRP was the independent risk factor of prognosis in patients CVST combined with intracranial hemorrhagic lesions ( OR = 1.046, 95% CI 1.007 to 1.086, P<0.05). Conclusions:The patients with CVST combined with intracranial hemorrhagic lesions have more severe clinical symptoms, and the changes in consciousness, epileptic seizures, poor short-term prognosis are more common. The oral contraceptives, multiple venous sinus involvement and elevated NLR, hs-CRP are independent risk factors in patients with CVST combined with intracranial hemorrhagic lesions; moreover, the elevated hs-CRP is an independent risk factor for poor short-term prognosis in patients with CVST combined with intracranial hemorrhagic lesions.

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*

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

ObjectiveTo reveal the differences of the related pathogenicity gene mutations between sebaceous adenocarcinoma （SC） of scalp and sebaceous adenoma （SA） of scalp on whole exome level. MethodsWhole exome sequencing was performed on a SC sample and a SA sample by Illumina Hiseq 2500 platform. Suspicious single nucleotide variation sites were selected for mutation conservation and functional analysis. SciClone was used to track subclone evolution and clonal map information was obtained for each tumor sample. The high-frequency significant gene mutations in the tumor sample were screened by MutSigCV software， and compared with the known driver genes. ResultsTwo driver genes TFDP1 and ACVR1B harboring mutations in scalp SC compared to SA were found. ConclusionsThe finding of mutation in driver genes TFDP1 and ACVR1B should be confirmed in a large cohort， which might reveal the mechanism of scalp SC development and find a therapeutic target for SC.