Objective To establish a fluorescent recombinase-aided amplification (RAA) assay for detection of Strongyloides stercoralis nucleic acid and to preliminarily evaluate its performance. Methods Six sets of specific primers targeting S. stercoralis 18S ribosomal RNA (18S rRNA) gene and one fluorescent probe were designed and synthesized. The optimal primer-probe set was determined through systematic screening and optimization to establish the fluorescent RAA assay. The assay was evaluated using S. stercoralis genomic DNA at concentrations of 100, 10, and 1 pg/μL, and 100, 10, and 1 fg/μL, as well as recombinant pUC57 plasmids containing the target gene fragments at 1 × 10⁵, 1 × 10⁴, 1 × 10³, 1 × 10², 1 × 10¹, 1 × 10⁰ copies/reaction, to determine the analytical sensitivity. Genomic DNA from Ascaris lumbricoides, Ancylostoma duodenale, Enterobius vermicularis, Angiostrongylus cantonensis, Trichinella spiralis, Clonorchis sinensis, Schistosoma japonicum, and Taenia saginata was used to assess assay specificity. A total of 25 stool samples from patients suspected of S. stercoralis infection were tested by the modified Baermann funnel technique, PCR, and the established fluorescent RAA assay. The sensitivity, specificity, concordance rate and their 95% confidence intervals (CI) of these three techniques were estimated, and agreement between methods was evaluated using the Kappa coefficient. Results Exo-4 was identified as the optimal primer set screened from the six primer sets, and the best amplification performance was achieved when the final concentrations of the forward and reverse primers were 0.44 μmol/L and a probe concentration was 0.20 μmol/L. The limit of detection of the fluorescent RAA assay was 100 fg/μL for genomic DNA of S. stercoralis and 1 × 10⁰ copies/reaction for recombinant plasmids. Specific fluorescence signals were detected within 5 min, with no cross-reactivity observed with A. lumbricoides, A. duodenale, E. vermicularis, A. cantonensis, T. spiralis, C. sinensis, S. japonicum, or T. saginata. Among the 25 clinical stool samples from patients suspected of S. stercoralis infections, the modified Baermann funnel technique and fluorescent RAA assay detected 19 positives and 6 negatives, whereas PCR detected 18 positives and 7 negatives. The fluorescent RAA assay showed a sensitivity of 100.00% [95% CI: (82.35%, 100.00%)], specificity of 100.00% [95% CI: (54.07%, 100.00%)], concordance rate of 100.00% [95% CI: (86.28%, 100.00%)], and a Kappa coefficient of 1.00 [95% CI: (1.00, 1.00)] (P < 0.001) relative to the modified Baermann funnel technique, and a sensitivity of 100.00% [95% CI: (81.47%, 100.00%)], specificity of 85.71% [95% CI: (42.13%, 99.64%)], concordance rate of 96.00% [95% CI: (79.65%, 99.90%)], and a Kappa coefficient of 0.90 [95% CI: (0.70, 1.00)] (P < 0.001). Positive amplification products emitted green fluorescence under a portable blue-light device, enabling visual interpretation of results. Conclusions The fluorescent RAA assay established in this study is rapid, highly sensitive, and highly specific. It enables detection of S. stercoralis nucleic acid under isothermal conditions and allows visual interpretation of results, providing a novel tool for rapid clinical diagnosis and field screening of S. stercoralis infections.

Delirium is a common cause and complication of hospitalization in the elderly and is associated with higher risk of future dementia and progression of existing dementia, of which 70% is Alzheimer's disease (AD). AD and delirium, which are known to be aggravated by one another, represent significant societal challenges, especially in light of the absence of effective treatments. The intricate biological mechanisms have led to numerous clinical trial setbacks and likely contribute to the limited efficacy of existing therapeutics. Artificial intelligence (AI) presents a promising avenue for overcoming these hurdles by deploying algorithms to uncover hidden patterns across diverse data types. This review explores the pivotal role of AI in revolutionizing drug discovery for AD and delirium from target identification to the development of small molecule and protein-based therapies. Recent advances in deep learning, particularly in accurate protein structure prediction, are facilitating novel approaches to drug design and expediting the discovery pipeline for biological and small molecule therapeutics. This review concludes with an appraisal of current achievements and limitations, and touches on prospects for the use of AI in advancing drug discovery in AD and delirium, emphasizing its transformative potential in addressing these two and possibly other neurodegenerative conditions.

OBJECTIVE: To explore the pathogenic mechanism of a child with Waardenburg syndrome type 4C due to a c.661_664dup (p.P222Lfs*60) variant of SOX10 gene through in vitro experiments. METHODS: A child diagnosed at the Handan First Hospital was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples were collected from the child and his parents. Following extraction of genomic DNA, trio-whole exome sequencing was carried out. Pathogenicity of candidate variant was determined by bioinformatic analysis and reference to the guidelines from the American College of Medical Genetics and Genomics (ACMG). Candidate variant was verified by Sanger sequencing. Expression plasmids of wild-type SOX10 and the c.661_664dup (p.P222Lfs*60) variant were constructed and transiently transfected into 293T cells to determine the expression at the RNA and protein levels. The 293T cells transiently transfected with the wild-type/mutant SOX10 were treated with 10 ug/mL cycloheximide (CHX) for 0, 4, 8, 24 h, respectively, and the degradation rate of target protein was detected by Western blotting assay. This study has been approved by the Ethics Committee of Handan First Hospital (Ethics No. HDYY-LW-25053). RESULTS: The child was found to harbor a heterozygous c.661_664dup (p.P222Lfs*60) variant of the SOX10 gene, which was unreported previously. The variant did not significantly alter the expression of SOX10 at the mRNA level but the protein level. After the CHX treatment, the degradation of mutant SOX10 protein had slowed down. CONCLUSION The mutant SOX10 may affect the expression of downstream genes by affecting the degradation rate of its protein product.
Humans ; HEK293 Cells ; Mutation ; SOXE Transcription Factors/metabolism* ; Waardenburg Syndrome/genetics* ; Child

In drug clinical trials,the protection of subjects'privacy should take precedence over scientific exploration and societal benefits.This paper compared the differences in legal systems for the protection of subjects'privacy in China and abroad by employing methods such as literature review,case analysis,and comparison of domestic and foreign situations.It also elucidated the current ethical challenges faced by the protection of subjects'privacy,which primarily included imperfect laws and regulations,insufficient protection awareness among relevant personnel,risks of privacy breaches in critical links,and increased difficulty in data confidentiality under emerging technologies.From the perspective of responsible innovation,specific paths were proposed to protect subjects'privacy by using the four-dimensional structure of"prediction-reflection-negotiation-feedback,"maintaining a balance between ethical principles and technological innovation,ensuring the ethical and compliant nature of drug clinical trials,and thus better contributing to the cause of human health.

Objective:To explore the pathogenic mechanism of a child with Waardenburg syndrome type 4C due to a c. 661_664dup (p.P222Lfs*60) variant of SOX10 gene through in vitro experiments. Methods:A child diagnosed at the Handan First Hospital was selected as the study subject. Clinical data of the child was collected. Peripheral blood samples were collected from the child and his parents. Following extraction of genomic DNA, trio-whole exome sequencing was carried out. Pathogenicity of candidate variant was determined by bioinformatic analysis and reference to the guidelines from the American College of Medical Genetics and Genomics (ACMG). Candidate variant was verified by Sanger sequencing. Expression plasmids of wild-type SOX10 and the c. 661_664dup (p.P222Lfs*60) variant were constructed and transiently transfected into 293T cells to determine the expression at the RNA and protein levels. The 293T cells transiently transfected with the wild-type/mutant SOX10 were treated with 10 μg/mL cycloheximide (CHX) for 0, 4, 8, 24 h, respectively, and the degradation rate of target protein was detected by Western blotting assay. This study has been approved by the Ethics Committe of Handan First Hospital(Ethics No.HDYY-LW-25053). Results:The child was found to harbor a heterozygous c. 661_664dup (p.P222Lfs*60) variant of the SOX10 gene, which was unreported previously. The variant did not significantly alter the expression of SOX10 at the mRNA level but the protein level. After the CHX treatment, the degradation of mutant SOX10 protein had slowed down. Conclusion:The mutant SOX10 may affect the expression of downstream genes by affecting the degradation rate of its protein product.

Objective To explore the association of working hours and shift work with occupational stress, fatigue accumulation, and depressive symptoms among primary community medical workers. Methods A total of 516 medical workers from five community medical service centers in Pudong New Area, Shanghai City, were selected as the research subjects using the convenience sampling method. The Core Scale of Occupational Stress Measurement, the Workers' Fatigue Accumulation Self-diagnosis Questionnaire, and the Patient Health Questionnaire were used to assess research subjects' occupational stress, fatigue accumulation, and depressive symptoms, respectively. Results Long working hours (>40 hours/week) were reported by 50.4% of workers among the research subjects, while shift works were reported by 16.9% of the workers. The detection rates of occupational stress, fatigue accumulation, and depressive symptoms were 26.6%, 41.7%, and 30.8%, respectively. Multivariate logistic regression analysis result revealed that, after adjusting for confounders such as age, sex, and education level, longer working hours were associated with higher risks of occupational stress, fatigue accumulation, and depressive symptoms (all P<0.05). Shift workers in community medical centers had higher risks of occupational stress, fatigue accumulation, and depressive symptoms compared with non-shift workers (all P<0.05). Conclusion Long working hours and shift work could increase the risks of occupational stress, fatigue accumulation, and depressive symptoms among community medical workers.

ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

Objective To investigate the regulatory role of the programmed cell death protein 1 (PD-1) and its ligand programmed cell death protein ligand 1 (PD-L1) signaling on the subtypes and functions of natural killer (NK) cells at the maternal-fetal interface during the second trimester in mice following Toxoplasma gondii infection during the first trimester. Methods Twelve 6- to 8-week-old female mice of the C57BL/6J strain were divided into a control group and an infection group, of 6 mice in each group. On the 6.5th day of pregnancy (Gd6.5), each pregnant mouse in the infection group was intraperitoneally injected with 150 tachyzoites of the Toxoplasma gondii PRU strain, while mice in the control group were injected with an equal volume of physiological saline. On the 12.5th day of pregnancy (Gd12.5), uterus and placenta tissues were sampled from pregnant mice for pathological observations, and the mRNA expression levels of PD-1, PD-L1, and tumor necrosis factor-α (TNF-α) were quantified in uterus and placenta tissues. The PD-1 and DX5 expression was measured on NK cells at the maternal-fetal interface using flow cytometry. In addition, the in vitro JEG-3 trophoblast cells and NK-92MI cells co-culture system was established as the control group, and the addition of T. gondii tachyzoites in the co-culture system served as the infection group. The PD-1, PD-L1, and DX5 mRNA expression was quantified in cells using real-time fluorescence quantitative reverse transcription PCR (RT-qPCR) assay, and the TNF-α concentration was measured in the cell culture supernatant using enzyme-linked immunosorbent assay (ELISA). Results On Gd12.5, clear and intact cellular structures of placental decidual tissues were seen in pregnant mice in the control group, with no remarkable abnormal changes found in the uterine columnar epithelial cells, and inflammatory cell infiltration and blood stasis at varying degrees were found in uterine and placental tissues from pregnant mice in the infection group. The relative PD-1, PD-L1, and TNF-α mRNA expression was (1.004 ± 0.004), (1.001 ± 0.001), and (1.001 ± 0.001) in uterine tissues from pregnant mice in the control group and (2.480 ± 0.720), (3.355 ± 0.920), and (2.391 ± 0.073) in the infection group, respectively. The relative PD-1, PD-L1, and TNF-α mRNA expression was (1.007 ± 0.010), (1.006 ± 0.006), and (1.001 ± 0.001) in the uterine tissues in the control group and (6.948 ± 1.918), (3.225 ± 1.034), and (1.536 ± 0.150) in the infection group, respectively. The relative PD-1, PD-L1, and TNF-α mRNA expression was higher in both the uterine (t = 3.55, 4.43 and 33.02, all P values < 0.05) and placental tissues (t = 5.36, 3.72 and 6.18, all P values < 0.05) in the infection group than in the control group. Flow cytometry showed that the proportions of PD-1⁺ NK cells, PD-1⁺ DX5⁺ NK cells, and DX5⁺ NK cells were (12.200 ± 1.082)%, (9.373 ± 7.728)%, and (44.000 ± 4.095)% in uterine tissues from pregnant mice in the control group, and (21.733 ± 1.630)%, (18.767 ± 1.242)%, and (73.367 ± 0.611)% in the infection group, respectively. The proportions of PD-1⁺ NK cells, PD-1⁺ DX5⁺ NK cells, and DX5⁺ NK cells were (1.100 ± 0.510)%, (2.277 ± 1.337)%, and (96.167 ± 2.831)% in placental tissues from mice in the control group, and (26.867 ± 9.722)%, (23.433 ± 6.983)%, and (82.467 ± 2.248)% in the infection group, respectively. The proportions of PD-1⁺ NK cells (t = 8.45, P < 0.05) and DX5⁺ NK cells (t = 12.29, P < 0.05) were higher in uterine tissues from pregnant mice in the infection group than in the control group, and no significant difference was seen in the proportion of PD-1⁺ DX5⁺ NK cells (Z = -1.09, P > 0.05). The proportions of PD-1⁺ NK cells (t = 4.58, P < 0.05) and PD-1⁺ DX5⁺ NK cells (t = 5.15, P < 0.05) were higher in placental tissues from pregnant mice in the infection group than in the control group, while the proportion of DX5⁺ NK cells was lower in the infection group than in the control group (t = -6.56, P < 0.05). RT-qPCR assay revealed that the relative PD-1, PD-L1, and DX5 mRNA expression was (1.010 ± 0.005), (1.002 ± 0.003), and (1.001 ± 0.001) in the JEG-3 cells and NK92MI cells co-culture system and (3.638 ± 1.258), (0.397 ± 0.158), and (4.267 ± 1.750) in the control group, and ELISA measured that the TNF-α concentration was higher in the cell culture supernatant in the infection group [(22.056 ± 3.205) pg/mL] than in the control group [(12.441 ± 0.001) pg/mL] (t = 5.20, P < 0.05). The PD-1(t = 3.62, P < 0.05) and DX5 mRNA expression (t = 3.23, P < 0.05) was higher in the infection group than in the control group, and the PD-L1 mRNA expression was lower in the infection group than in the control group (t = -6.63, P < 0.05). Conclusions Following T. gondii infection, both PD-L1 expression and PD-1 expression on DX5⁺ NK cells at the maternal-fetal interface are upregulated in mice during the second trimester; however, the proportion of DX5⁺ NK cells decreases. These findings suggest that PD-1/PD-L1 signaling may suppress NK cell functions by modulating DX5⁺ NK cell subsets.

This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

Objective:To construct and validate a predictive model and application program for stone recurrence after endoscopic retrograde cholangiopancreatography (ERCP) based on machine learning algorithms in patients with common bile duct stones (CBDS).Methods:A multicenter retrospective cohort study was conducted, 862 CBDS patients underwent ERCP from June 2020 to September 2023 in Changshu First People′s Hospital (data set 1, 759 cases, including a training set of 588 cases and a validation set of 171 cases) and Changshu Hospital of Traditional Chinese Medicine (data set 2, 103 cases, used as a test set). The demographics, medical history, ERCP procedural records and laboratory indices were collected. All patients were followed up for 1 year, and the stone recurrence was recorded. In training set, the feature selection was conducted by the least absolute shrinkage and selection operator (LASSO) algorithm, and a conventional Logistic regression model was constructed based on selected features. The 3 machine learning algorithms (gradient boosting machine model, extreme gradient boosting model and random forest model) and a conventional Logistic regression model (LASSO model) were trained to fit predictive models. The model performance was assessed by area under curve (AUC) of receiver operating characteristic curve. The model interpretability was analyzed by feature importance evaluation, Shapley additive explanations (SHAP) and force plots. The best-performing model was deployed as an online application by Streamlit framework (V1.36.0).Results:Among the 862 patients, 158 patients (18.33%) developed stone recurrence after ERCP. There were no statistical difference in demographics, medical history, ERCP procedural records and laboratory indices between training set and a validation set ( P>0.05). LASSO regression analysis result showed that 6 key variables (in descending order of significance: endoscopic sphincterotomy, common bile duct angulation, stone diameter, stone count, common bile duct diameter, and periampullary diverticulum) influencing stone recurrence. ROC curve analysis result showed that the random forest model exhibited the highest predictive performance (it had the largest AUC of 0.900). SHAP analysis result showed that common bile duct angulation, common bile duct diameter, stone diameter, endoscopic sphincterotomy and stone count were the top 5 contributing factors in the random forest model. Using Python, the random forest model was implemented into a Streamlit-based application with a user-friendly visual interface, providing predictive outcomes, confidence levels, SHAP force diagram and health recommendations. In the test set, the application program achieved an accuracy of 84.5% (87/103), sensitivity of 82.6% (19/23), and specificity of 85.0% (68/80). SHAP plots and force diagram intuitively illustrated the impact of key features on stone recurrence prediction, offering a clear visualization of each variable′s role within the model. Conclusions:The predictive model and application program based on the random forest machine learning algorithms demonstrate excellent predictive performance and practical usability in predicting stone recurrence after ERCP in patients with CBDS.