ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

Medical ultrasound technology is widely used for diagnosis and therapy in clinical practice.Ultrasound probes,which are directly contact with patients,pose a potential risk of pathogen transmission.This expert consen-sus was developed by a multidisciplinary team based on international guidelines,standards in China,and the results of a national survey,aiming to reduce the risk of healthcare-associated infection through standardizing reprocessing of medical ultrasound probes,and formulating consensus recommendations with the Delphi method.The consensus clarifies the reprocessing principles for three types of ultrasound probes of different infection risks:external-use ul-trasound probes,interventional percutaneous ultrasound probes,and internal-use ultrasound probes,puts forward systematic suggestions on the reprocessing standards and disinfection levels of ultrasound probe isolation covers and coupling agents,the reprocessing procedures and methods of ultrasound probes,as well as architectural layout and management of reprocessing,so as to provide a scientific prevention and control framework for ensuring ultrasound diagnosis and therapy safety.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

ObjectiveTo investigate the influence of entecavir （ETV） versus tenofovir alafenamide fumarate （TAF） on renal function in previously untreated patients with chronic hepatitis B （CHB）. MethodsA retrospective analysis was performed for the clinical data of 167 previously untreated CHB patients who received ETV or TAF treatment for at least 48 weeks at the outpatient service of Department of Infectious Diseases in The First Affiliated Hospital of Nanchang University from September 2019 to November 2023， and according to the antiviral drug used， they were divided into ETV group with 117 patients and TAF group with 50 patients. In order to balance baseline clinical data， propensity score matching （PSM） was used for matching and analysis at a ratio of 2∶1， and the two groups were compared in terms of estimated glomerular filtration rate （eGFR） and the incidence rate of abnormal renal function at week 48. According to eGFR at week 48， the patients were divided into normal renal function group and abnormal renal function group. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The multivariate Logistic regression analysis was used to investigate the influencing factors for abnormal renal function， and the receiver operating characteristic （ROC） curve was used to assess the performance of each indicator in predicting abnormal renal function. The Kaplan-Meier method was used to analyze the cumulative incidence rate of abnormal renal function， and the log-rank test was used for comparison. The analysis of variance with repeated measures was used to compare the dynamic changes of eGFR during antiviral therapy in CHB patients. ResultsAfter PSM matching， there were 100 patients in the ETV group and 50 patients in the TAF group. There were no significant differences in baseline clinical data between the ETV group and the TAF group （all P>0.05）， with an eGFR level of 112.29±9.92 mL/min/1.73 m² in the ETV group and 114.72±12.15 mL/min/1.73 m² in the TAF group. There was a reduction in eGFR from baseline to week 48 in both groups， and compared with the TAF group at week 48， the ETV group had a significantly lower eGFR （106.42±14.12 mL/min/1.73 m² vs 112.25±13.44 mL/min/1.73 m²， t=-2.422， P=0.017） and a significantly higher incidence rate of abnormal renal function （17.00% vs 4.00%， χ²=5.092， P=0.024）. After the patients were divided into normal renal function group with 131 patients and abnormal renal function group with 19 patients， the univariate analysis showed that there were significant differences between the two groups in age （Z=-2.039， P=0.041）， treatment drug （ETV/TAF） （χ²=5.092， P=0.024）， and baseline eGFR level （t=4.023， P<0.001）， and the multivariate Logistic regression analysis showed that baseline eGFR （odds ratio ［OR］=0.896， 95% confidence interval ［CI］： 0.841 — 0.955， P<0.001） and treatment drug （OR=5.589， 95%CI： 1.136 — 27.492， P=0.034） were independent influencing factors for abnormal renal function. Baseline eGFR had an area under the ROC curve of 0.781 in predicting abnormal renal function in CHB patients， with a cut-off value of 105.24 mL/min/1.73 m²， a sensitivity of 73.68%， and a specificity of 82.44%. The Kaplan-Meier curve analysis showed that the patients with baseline eGFR≤105.24 mL/min/1.73 m² had a significantly higher cumulative incidence rate of abnormal renal function than those with baseline eGFR>105.24 mL/min/1.73 m² （χ²=22.330， P<0.001）， and the ETV group had a significantly higher cumulative incidence rate of abnormal renal function than the TAF group （χ²=4.961， P=0.026）. With the initiation of antiviral therapy， both the ETV group and the TAF group had a significant reduction in eGFR （F=5.259， P<0.001）， but the ETV group only had a significant lower level of eGFR than the TAF group at week 48 （t=-2.422， P=0.017）； both the baseline eGFR≤105.24 mL/min/1.73 m² group and the baseline eGFR>105.24 mL/min/1.73 m² group had a significant reduction in eGFR （F=5.712， P<0.001）， and there was a significant difference in eGFR between the two groups at baseline and weeks 12， 24， 36， and 48 （t=-13.927， -9.780， -8.835， -9.489， and -8.953， all P<0.001）. ConclusionFor CHB patients initially treated with ETV or TAF， ETV antiviral therapy has a higher risk of renal injury than TAF therapy at week 48.

Objective To investigate the correlation between serum levels of macrophage inflammatory protein-1α(MIP-1α),apolipoprotein C1(APOC1),cysteine leukotrienes(CysLTs)and prognosis in children with severe Mycoplasma pneumoniae pneumonia.Methods The children with severe M.pneumoniae pneumonia admitted to the Second Hospital of Handan City from January 2022 to December 2023 were included as case group.The children in case group were assigned to a good prognosis group(n=69)or poor prognosis group(n=24)according to patient outcome.Additionally,93 healthy children who underwent physical examination were included as control group.Enzyme linked immunosorbent assay(ELISA)was applied to determine the serum levels of MIP-1α,APOC1,and CysLTs.Pearson correlation was used to analyze the correlation between serum levels of MIP-1α,APOC1,CysLTs and other biomarkers.Receiver operating characteristic(ROC)curve was plotted to analyze the value of MIP-1α,APOC1,and CysLTs levels for predicting the outcome of children with severe M.pneumoniae pneumonia.Results The serum levels of MIP-1α,APOC1,and CysLTs in case group were higher than those in the control group(P＜0.05).The serum levels of MIP-1α,APOC1,and CysLTs were higher in poor prognosis group compared with good prognosis group(P＜0.05).The levels of MIP-1α,APOC1,and CysLTs in the serum of case group were positively correlated with platelet count,mean platelet volume,white blood cell,neutrophil count,lactate dehydrogenase,erythrocyte sedimentation rate,C-reactive protein,and D-dimer(P＜0.05),and negatively correlated with AT-Ⅲ(P＜0.05).ROC analyses showed that the area under the curve(AUC)of MIP-1α,APOC1,and CysLTs combined was 0.881 in predicting prognosis,significantly higher than MIP-1α(Z=2.096,P=0.036),APOC1(Z=2.236,P=0.025),and CysLTs(Z=2.058,P=0.040)alone,with a sensitivity of 70.80％and specificity of 89.90％.Conclusions The levels of serum MIP-1α,APOC1,and CysLTs are elevated in children with severe M.pneumoniae pneumonia.Serum MIP-1α,APOC1,and CysLTs combined can provide higher value for predicting the prognosis of children with severe M.pneumoniae pneumonia.

Objective To study the effects of Hedysarum polysaccharides polysaccharide(HPS)on the farnesoid X receptor(FXR)-fibroblast growth factor-19(FGF19)signaling pathway of diabetes rats.Methods Twelve Wistar male rats were randomly selected as the normal group,and the other rats were fed with a single intraperitoneal injection of streptozotocin(50 mg·kg-1 STZ)and a high sugar and high-fat diet to replicate the diabetes rat model.Model rats were randomly divided into model group,positive control group(given 400 mg·kg-1·d-1 suspension of Bifidobacterium quadruplex live bacterial tablets by gavage),experimental-H,-M,-L groups(given 200,100,and 50 mg·kg-1·d-1 doses of HPS suspension by gavage);normal group,and model group were given equal volume of purified water by gavage once a day for 8 consecutive weeks.Glucose(Glu)was detected by a blood glucose meter;and serum total glyceride(TG)and total cholesterol(TC)were detected by enzyme-linked immunosorbent assay reagent kit;the expressions of FXR、fibroblast growth factor receptors 4(FGFR4)relative mRNA expression level and protein were detected by real-time fluorescence quantitative polymerase chain reaction method and Western blot.Results The Glu concentrations in the normal group,model group,positive control group,and experimental-H groups were(7.66±0.61),(29.25±1.64),(23.31±3.02)and(19.31±5.13)mmol·L-1,respectively;the TG content were(957.00±113.73),(1 345.00±246.44),(958.00±96.53)and(964.00±130.22)μmol·L-1,respectively;the TC content were(161.65±4.53),(302.19±5.35),(236.09±5.14)and(165.58±2.58)μmol·L-1,respectively;the expression of FXR relative mRNA expression level were 1.00±0.06,0.48±0.02,0.67±0.04 and 0.92±0.04,respectively;the expression of FGFR4 relative mRNA expression level were 1.00±0.04,0.17±0.01,0.48±0.04 and 0.41±0.03;respectively.The above indexes of the model group were compared with the control group,and the above indexes of the control group and the experimental-H group were compared with the model group,and the differences were statistically significant(all P＜0.01).Conclusion HPS improves blood sugar,lowers blood lipids,and protects liver and intestinal tissues,possibly by regulating the FXR-FGF19 signaling pathway in intestinal tissue,and regulating bile acid synthesis.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective:To investigate clinical characteristics, treatment approaches, and prognosis of drug-induced hypersensitivity syndrome (DIHS) in children.Methods:A retrospective analysis was performed on clinical data from pediatric inpatients with DIHS in Department of Dermatology, Beijing Children's Hospital from 2009 to 2023. The clinical data included demographic characteristics, clinical manifestations, laboratory findings, treatment regimens, and outcomes.Results:A total of 103 children with DIHS were included, comprising 54 males (52.4%) and 49 females (47.6%), with ages ( M [ Q1, Q3]) of 2.3 (1.2, 4.5) years. Primary causative drugs were antibiotics (52 cases, 45.2%), antiepileptic drugs (41 cases, 35.7%), and nonsteroidal anti-inflammatory drugs (19 cases, 16.5%), with a median latency period of 12 days. All patients presented with rashes, including 72 (69.9%) with maculopapular rashes, 69 (67.0%) with edema (including 46 with facial edema). Lip involvement occurred in 25 cases (24.3%), and mucosal involvement was noted in 11 cases (10.7%). Additionally, 102 (99.0%) patients had fever, and 79 (76.7%) presented with lymphadenectasis. Eosinophilia was present in 64 cases (62.1%). Among 84 patients tested for atypical lymphocytes, 51 (60.7%) showed elevated percentages of atypical lymphocytes. Liver involvement was noted in 94 cases (91.3%), followed by pulmonary involvement in 31 (30.1%), gastrointestinal symptoms in 25 (24.3%), cardiac involvement in 14 (13.6%), renal involvement in 10 (9.7%), and pancreatic involvement in 7 cases (6.8%). Among 82 patients tested for blood immunocytes, 49 (59.8%) showed decreased percentages of B lymphocytes, and 69 (84.1%) showed decreased percentages of natural killer cells. Of 88 patients tested for serum immunoglobulins, 40 (45.5%) showed decreased IgA levels. Among 20 patients tested for serum cytokines, 15 (75.0%), 15 (75.0%), 13 (65.0%), and 12 (60.0%) showed elevated levels of interleukin (IL) -5, IL-6, IL-10, and interferon-γ, respectively. All patients received systemic glucocorticoid therapy, among whom 86 additionally received intravenous immunoglobulin therapy, 4 received Janus kinase inhibitors, and 3 received dupilumab. Five patients died, 9 developed hemophagocytic lymphohistiocytosis, 6 developed bronchiolitis obliterans, and 5 experienced long-term immune-related sequelae. Conclusions:Among these children with DIHS, antibiotics were the most common causative drugs, and the latency period could be shorter than 2 weeks. In addition to the common involvement of the liver and lungs, gastrointestinal and cardiac impairments were relatively frequent, while renal involvement was rare. Immunological features included decreased percentages of B lymphocytes and natural killer cells, reduced IgA levels, and elevated levels of cytokines such as IL-5, IL-6, IL-10, and interferon-γ.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.