Objective To summarize the clinical and genetic characteristics of end-stage renal disease caused by PLCE1 gene mutations.Methods A retrospective analysis of the clinical and genetic features of three children from a family with PLCE1 gene mutations was conducted,along with a literature review of hereditary kidney disease cases caused by PLCE1 gene mutations.Results The proband was an 8-year-old male presenting with nephrotic syndrome stage 4 chronic kidney disease.Renal biopsy showed focal segmental glomerulosclerosis.Two years and five months after kidney transplantation,the patient had persistent negative proteinuria and normal renal function.Whole-exome sequencing identified two pathogenic heterozygous variants:c.961C>T and c.3255_3256delinsT,with c.3255_3256delinsT being a novel mutation.Family screening revealed no renal involvement in the parents,but among five siblings,one brother died at age of 4 years from end-stage renal disease.A 7-year-old sister presented with proteinuria and bilateral medullary sponge kidney,with proteinuria resolving after one year of follow-up.A 3-year-old brother died after kidney transplantation due to severe pneumonia.The literature review included 45 patients with hereditary kidney disease caused by PLCE1 gene mutations.The main clinical phenotype was nephrotic syndrome(87%,39/45),and renal pathology predominantly showed focal segmental glomerulosclerosis(57%,16/28).No mutation hotspots were identified.Conclusions Compound heterozygous mutations in the PLCE1 gene can lead to rapid progression of the disease to end-stage renal disease,with favorable outcomes following kidney transplantation.Family screening is crucial for early diagnosis,and medullary sponge kidney may be a novel phenotype associated with these gene mutations.Citaion:[Chinese Journal of Contemporary Pediatrics,2025,27(5):580-587]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.

Objective To analyze the correlation between lesion volume,lesion mass,and maximum lesion diameter in the assessment of advanced hepatocarcinoma with lung metastasis,and to evaluate the application value of total volume response and total mass response of lung metastatic lesions in efficacy assessment.Methods A retrospective analysis was conducted on the CT imaging data of 20 patients clinically confirmed with hepatocarcinoma and lung metastases,followed by subsequent follow-up to monitor their survival outcomes.Volume measurement software was used to measure the volume of lesions before and after treatment.We recored lesion diameter,volume measurements and CT values,calculated the mass of the lesions.The correlation between lesion volume,mass and diameter was analyzed,as well as the correlation between the change rates of volume,mass and lesion diameter.Additionally,the total volume and total mass of all lesions were calculated.The correlation between the change rates of total volume/total mass and the change rate of pulmonary lesion diameter under the RECIST 1.1 criteria,as well as the correlation with changes in patients'tumor markers,were analyzed.Furthermore,the overall volume response and overall mass response of lesions were evaluated based on changes in total volume and total mass,and their consistencies with the RECIST 1.1 criteria for efficacy evaluation were analyzed.Finally,univariate Cox regression analysis was performed to explore the association between these variables and patient survival outcomes.Results There was strong correlation between lesion volume,mass and tumor diameter(r=0.771,0.775),between the rate of change in mass and the rate of change in lesion diameter(r=0.846),and between the rates of change in total volume/total mass and the rate of change in pulmonary lesion diameter under the RECIST 1.1 criteria(r=0.800,0.896).The correlation between the rates of change in total volume/total mass and patients'tumor markers was not statistically significant.There was moderate correlation between the rate of change in volume and the rate of change in lesion diameter(r=0.692).The evaluation results of total volume response and total mass response for pulmonary lesions in advanced hepatocarcinoma with lung metastasis were generally consistent with the RECIST 1.1 criteria(Kappa=0.486,0.426).Univariate Cox regression analysis revealed that total lesion volume(P=0.047)and total lesion mass(P=0.049)were independent prognostic factors for survival outcomes.Conclusion Lesion volume,mass,and diameter,as well as their respective change rates,were found to be interrelated.Furthermore,total lesion volume and total lesion mass were identified as independent prognostic factors for survival outcomes.The total volume response and total mass response are promising evaluation methods in evaluating the efficacy of lung metastasis of hepatocarcinoma,which are different from the RECIST 1.1 evaluation criteria.

Objective To explore the effects of dodecanoylcarnitine(DA)and myristoleic acid(MA)on the function of mouse alveolar epithelial cell line MLE-12 and their underlying mechanisms.Methods An inflammatory model was established by stimulating MLE-12 cells with IL-4.The expression levels of DA,MA,and sphingosine-1-phosphate(S1P)in the cell supernatant were detected by ELISA.MLE-12 cells were separately intervened with DA and MA.RT-PCR and flow cytometry were used to detect the expression changes of inflammatory factors IL-6 and tumor necrosis factor-α(TNF-α)and the level of intracellular reactive oxygen species(ROS).Additionally,Western blot was performed to detect the expression of key proteins such as p38 mitogen-activated protein kinase(p-38 MAPK)and src homology 2 domain-containing phosphatase 1(SHP-1).To explore the role of S1PR2 in the effects of DA and MA,MLE-12 cells were pretreated with the S1PR2 inhibitor JTE-013,and the above experiments were repeated.Results IL-4 stimulation significantly upregulated the levels of DA,MA,and S1P in MLE-12 cells(P<0.05).DA/MA treatment groups exhibited significantly increased expression of IL-6 and TNF-α compared with the control group(P<0.05),along with elevated ROS levels(P<0.05).Western blot analysis revealed that DA/MA promoted SHP-1 dephosphorylation and phosphorylated p38 MAPK activation in MLE-12 cells.Notably,JTE-013 pre-treatment completely reversed these effects(P<0.05).Conclusion Asthma-related metabolites DA and MA exacerbate the inflammatory and oxidative stress responses of MLE-12 cells by activating the S1PR2 receptor,promoting the dephosphorylation of SHP-1 and the activation of the p-p38 MAPK pathway.This study reveals the core regulatory role of S1PR2 in this pathway as well.

The aim of this study was to establish a rapid,highly sensitive,and specific nucleic acid detection method for the H5N6 and H9N2 avian influenza virus(AIV)subtypes by using reverse transcription-recombinase polymerase amplification(RT-RPA)combined with clustered regularly interspaced short palindromic repeats(CRISPR)-Cas13a proteins.The conserved regions were selected to design specific RT-RPA primers and crRNA sequences of H5,H6,H9,and N2 genes.RT-RPA tech-nology combined with CRISPR-Cas13a detection was used to evaluate the sensitivity and specificity of AIV nucleic acid detec-tion.The detection was performed on avian influenza environmental samples and compared with the results of fluorescence quantitative RT-PCR,to evaluate the effectiveness of the RT-RPA technology combined with CRISPR-Cas13a.AIV H5,H9,and N2 subtypes were detected with a sensitivity as high as 1 copy/μL,and AIV N6 subtypes were detected with a sensitivity of 10 copies/μL.Plasmid samples with differing copy numbers showed fluorescence under blue LED transillumination.The four AIV subtypes showed high specificity and did not cross-react with the other AIV subtypes.The detection of avian influenza ex-ternal environmental samples containing AIV H5,N6,and H9 subtypes was consistent with the results of fluorescence quanti-tative RT-PCR,with 100％accuracy.For AIV N2 subtypes,one additional negative sample was detected with 97.9％accuracy.The established RT-RPA technology combined with CRISPR-Cas13a detection enabled sensitive,specific visual detection of AIV H5N6 and H9N2 subtypes.This study provides a new nucleic acid detection method for AIV surveillance and subtype clas-sification.

Monoamine neurotransmitters mainly include serotonin,dopamine,epinephrine,and norepinephrine.They play an indispensable regulatory role in key physiological activities such as emotion,sleep,and memory within the central nervous system.Precise detection of these neurotransmitters holds great significance in the field of neuroscience research.Detection methods for monoamine neurotransmitters encompass high-performance liquid chromatography,mass spectrometry,capillary electrophoresis,fluorescence spectroscopy,and electrochemical methods,etc.Compared with other methods,electrochemical methods offer advantages such as high sensitivity,good selectivity,low cost,strong portability,convenient operation,and capability for in vivo real-time detection.This article reviewed recent research progress in electrochemical detection of monoamine neurotransmitters,focusing on a retrospective and summary from three aspects:sensor electrode materials,detection of various monoamine neurotransmitters,and in vivo real-time analysis.Furthermore,the future development of electrochemical sensors for monoamine neurotransmitters was prospected.

Food,drug and environment related cases are becoming more and more frequent,and the demand for on-site rapid detection is also increasing.Nanozymes are nanomaterials with enzyme-like catalytic activity,which have the advantages of high catalytic efficiency,good stability,economy,adjustability,multifunctionality and large-scale preparation.The colorimetric sensing technology based on nanozymes combined with smart phones has wide range of applications in the field of food,drugs and environment detection,and is expected to become an important means for relevant departments to combat crime.This paper summarized the progresses of nanozymes in the field of environmental,food and drug crime(EFDC)detection,focusing on the detection mechanism of different types of nanozymes and the current status of research on the detection of EFDC,and prospected the future development of nanozymes.The possible future prospects of machine learning(ML)in the field of nanozymes colorimetric sensing technology and the challenges in detection of EFDC were also discussed.

Objectives:To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods:Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation.Results:A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions:The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.Objectives To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation. Results A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.

AIM To evaluate the quality consistency of Tongmai Granules,Tongmai Tablets,Tongmai Capsules and Tongmai Oral Liquid.METHODS The HPLC fingerprints were established,after which the contents of danshensu,protocatechuic aldehyde,3'-hydroxy puerarin,puerarin,puerarin apioside,daidzin,ferulic acid,salvianolic acid B and salvianolic acid A were determined,and cluster analysis and principal component analysis were adopted in the quality analysis from the perspective of daily intake.RESULTS There were 21 common peaks in the fingerprints for 39 batches of samples with the similarities of 0.765-0.997.Various batches of samples were clustered into 5 categories,2 principal components demonstrated the accumulative variance contribution rate of 83.53％ .The daily intakes of various constituents in different dosage forms exhibited obvious differences,especially for that of salvianolic acid B,which were low in tablets and capsules,and their heterogeneities existed among the same dosage forms.CONCLUSION This simple and accurate method can provide a reference for the quality evaluation of Tongmai preparations from different manufacturers.