ObjectiveTo investigate the possible mechanism of Jishe Qushi Capsule （脊蛇祛湿胶囊， JQC） in treating rheumatoid arthritis （RA） from the perspective of macrophage polarization mediated by neutrophil extracellular traps （NETs）. MethodsTwenty-four female SD rats were randomly divided into four groups， blank control group， model group， JQC group， and peptidylarginine deiminase 4 （PAD4） inhibitor group with 6 rats in each group. All groups but the blank control group were subjected to the induction of collagen-induced arthritis （CIA）. After successful model establishment， rats in the JQC group received intragastric administration of JQC 1.47 g/kg daily； rats in the PAD4 inhibitor group received intraperitoneal injections of the PAD4 inhibitor 4 mg/kg weekly. Rats in the blank， model， and PAD4 inhibitor groups received 2 ml of pure water daily by gavage. All treatments lasted 4 weeks. Joint lesions of each group were assessed on day 7， 14， 21， 28， and 35 after model establishment， and arthritis index （AI） scores were recorded. At 24 h after the final administration， histopathology of knee joints， including HE staining， safranin O-fast green staining， and TRAP staining， was performed. Flow cytometry was used to detect the counts of M1 and M2 macrophages in peripheral blood. ELISA was used to determine serum levels of TRACP， NETs， TNF-α， IL-1β， and iNOS. Western Blotting and qRT-PCR were used to measure MPO， NE， RANKL， OPG， and p65 protein and mRNA expression in knee cartilage tissue. ResultsCompared with the blank control group， the model group showed increased AI scores （P＜0.05）， marked synovial inflammatory infiltration， angiogenesis， and bone-cartilage destruction， increased TRAP-positive osteoclasts， increased M1 macrophages and decreased M2 macrophages， elevated serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， elevated MPO， NE， RANKL， and p65 protein/mRNA expression and decreased OPG protein/mRNA expression in knee cartilage tissue （P＜0.05）. Compared with the model group， the JQC group exhibited improved synovial inflammation， angiogenesis， and bone-cartilage damage， reduced AI scores on day 21， 28， and 35， decreased osteoclast counts， decreased M1 macrophages and increased M2 macrophages， reduced serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， decreased MPO， NE， RANKL， and p65 protein/mRNA expression and increased OPG expression （P＜0.05）. Compared with the PAD4 inhibitor group， the JQC group showed significantly lower AI scores， reduced M1 macrophages， increased M2 macrophages （P＜0.05）， reduced serum TRACP， TNF-α， IL-1β， and iNOS， decreased MPO， RANKL， and p65 expression， and increased OPG levels （P＜0.05）. ConclusionThe therapeutic mechanism of JQC for RA may involve inhibition of NETs formation， downregulation of the RANKL/NF-κB signaling pathway， and regulation of macrophage M1/M2 polarization imbalance， thereby suppressing osteoclastogenesis and inflammatory bone destruction.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Here, we report a previously unrecognized syndromic neurodevelopmental disorder associated with biallelic loss-of-function variants in the RBM42 gene. The patient is a 2-year-old female with severe central nervous system (CNS) abnormalities, hypotonia, hearing loss, congenital heart defects, and dysmorphic facial features. Familial whole-exome sequencing (WES) reveals that the patient has two compound heterozygous variants, c.304C>T (p.R102*) and c.1312G>A (p.A438T), in the RBM42 gene which encodes an integral component of splicing complex in the RNA-binding motif protein family. The p.A438T variant is in the RRM domain which impairs RBM42 protein stability in vivo. Additionally, p.A438T disrupts the interaction of RBM42 with hnRNP K, which is the causative gene for Au-Kline syndrome with overlapping disease characteristics seen in the index patient. The human R102* or A438T mutant protein failed to fully rescue the growth defects of RBM42 ortholog knockout ΔFgRbp1 in Fusarium while it was rescued by the wild-type (WT) human RBM42. A mouse model carrying Rbm42 compound heterozygous variants, c.280C>T (p.Q94*) and c.1306_1308delinsACA (p.A436T), demonstrated gross fetal developmental defects and most of the double mutant animals died by E13.5. RNA-seq data confirmed that Rbm42 was involved in neurological and myocardial functions with an essential role in alternative splicing (AS). Overall, we present clinical, genetic, and functional data to demonstrate that defects in RBM42 constitute the underlying etiology of a new neurodevelopmental disease which links the dysregulation of global AS to abnormal embryonic development.
Female ; Animals ; Mice ; Humans ; Child, Preschool ; Intellectual Disability/genetics* ; Heart Defects, Congenital/genetics* ; Facies ; Cleft Palate ; Muscle Hypotonia

[This corrects the article DOI: 10.1016/j.apsb.2022.02.031.].

Objective:To understand the identification value of pointing gestures in children with autism spectrum disorder(ASD) and its relationship with functional development.Methods:From December 2020 to November 2021, 1 099 children from Children’s Health Care Center of Beijing Children’s Hospital were tested by pointing gestures test, including 942 ASD children and 157 typical developed children.And the data of children's neuropsychological development scale from 800 children aged 1.0-5.9 were collected.SPSS 20.0 was used for statistical analysis. Trend test was used to analyze the distribution of pointing gestures test sensitivity in autistic children, and ANOVA was used to analyze the relationship between pointing gestures test scores and functional development fields.Results:The sensitivity of pointing gestures was 83.5% in children aged 1.0-10.0 years, 76.3%-93.1% in children aged 1.0-4.9 years, and 93.1%-95.1% in children aged 1.0-2.9.With the increase of age, the sensitivity of pointing gestures in autistic children (linear-by-linear association =164.889, P<0.001) and the Yoden index had a decreasing trend. The positive predictive value (91.53%-100.00%) and negative predictive value (75.36%-91.84%) were found in the children aged 1.0-10.0 years.The sensitivity of pointing gestures test was 44.9% in children with mild autism aged 1.0-10.0 years and 46.5%-65.9% in children with mild autism aged from 1.0-3.9 years. The sensitivity of pointing gestures test was 81.5% in children with moderate autism aged from 1.0-10.0 years and 87.3%-97.8% in children with moderate autism aged 1.0-3.9 years. The sensitivity of the pointing gestures test was 97.2% in children with severe autism aged 1.0-10.0 years, and 100.0% in children with severe autism aged 1.0-3.9 years. The sensitivity of the pointing gestures in mild, moderate and severe autism children decreased with age (linear-by-linear association values were 16.725, 64.232, 66.732 respectively, all P<0.001). The children with severe autism mainly scored 2 points (80.3%, 419/522) on the pointing gestures test , and children with moderate autism mainly scored 1 point(64.2%, 170/265) on the pointing gestures test. There were significant differences in functional development among different pointing gestures test groups.Functional development score in the autism children with 0 score of pointing gestures test was significantly higher than those with 1 score and 2 scores of pointing gestures test (all P<0.05). Conclusion:Pointing gestures has good sensitivity in children with autism (especially 1.0-4.9 years of age), and may serve as an objectively observable screening method. The better children with autism score on the pointing gestures, the better their functional development.

PD-1 and PD-L1 antibodies have brought about extraordinary clinical benefits for cancer patients, and their indications are expanding incessantly. Currently, most PD-1/PD-L1 agents are administered intravenously, which may be uncomfortable for some cancer patients. Herein, we develop a novel oral-delivered small molecular, YPD-29B, which specifically targets human PD-L1. Our data suggested that YPD-29B could potently and selectively block the interaction between PD-L1 and PD-1, but did not inhibit any other immune checkpoints. Mechanistically, YPD-29B induced human PD-L1 dimerization and internalization, which subsequently activated T lymphocytes and therefore overcomes immunity tolerance in vitro. YDP-29B was modified as the YPD-30 prodrug to improve druggability. Using humanized mice with human PD-1 xenografts of human PD-L1 knock-in mouse MC38 cancer cells, we demonstrated that YPD-30 exhibited significant antitumor activity and was well tolerated in vivo. Taken together, our results indicate that YPD-30 serves as a promising therapeutic candidate for anti-human PD-L1 cancer immunotherapy.

Objective:To explore whether the introduction of the O-PIRTAS (objective, preparation, instructive vedio, review, test, activity, summary) teaching model can help in curriculum learning and improve students' medical humanities literacy.Methods:Taking 118 sophomores of clinical medicine and nursing majors from Xiamen Medical College as control group, and 122 students as experimental group and as control group, the research lasting 8 weeks was carried out around five modules. The control group adopted the traditional teaching mode, while the experimental group used the O-PIRTAS model. After teaching, by comparing the exam results and issuing questionnaires, the teaching effects of the two methods on students' caring ability, empathy, emotional intelligence and supportive communication ability were compared. SPSS 22.0 was used for t test and chi-square test. Results:The average score of the experimental group [(83.61±2.13) points] was higher than that of the control group [(78.03±2.02) points], with significant differences ( t=3.60, P<0.001). As for the statistical analysis of the questionnaire, the students in experimental group scored higher in empathy, emotional intelligence and supportive communication skills than those in control group ( t=-3.20, P=0.002; t=-3.93, P<0.001; t=-4.00, P<0.001). Conclusion:Applying O-PIRTAS flipped classroom teaching model to medical humanities English courses helps to improve students' curriculum learning and medical humanities literacy, improve the effectiveness of the classroom and better play the educational role of the curriculum.

Objective To seek differentially expressed proteins for human epithelial growth factorreceptor-2 (HER-2)negative and positive breast carcinoma through establishing proteins profiles,and to providenew prognostic markers and therapeutic targets for patients with breast cancer.Methods HER-2 positiveand negative breast cancer protein expression profiles were established using proteomic isobaric tags for relativeand absolute quantitation (iTRAQ)technology.Differences of protein expression were identified and parts ofdifferential expression proteins were analyzed by bio-informatics,including protein function annotation and GOclassification analysis and Kyoto Encyclopedia of Gene and Genome (KEGG)pathway analysis.Results Proteomicanalysis of breast cancer tissue with identified HER-2 positive and negative groups showed 4 999 differentiallyexpressed proteins by iTRAQ.Based on the criteria of the ratio of HER-2(+)/HER-2(-)≥3,119up-regulated proteins were identified in HER-2 positive group.Based on the criteria of the ratio of HER-2(+)/HER-2(-)≤0.5,47 down-regulated proteins were identified in HER-2 positive group.The results ofGO analysis showed that the molecular function,biological process and cellular composition of differentiallyexpressed proteins were complex between HER-2 positive and negative breast cancer.There were differences inthe distribution of up-regulated proteins and down-regulation of proteins.KEGG pathway analysis showed thatdifferentially expressed proteins involved in 168 signal pathways.Conclusion There are differentiallyexpressed proteins between HER-2 positive and negative breast cancer,which involve complex molecular func-tion,biological process and signaling pathway.

Objective To investigate the distribution and drug resistance of pathogens in intensive care unit (ICU) so as to provide scientific basis for antibiotic adoption and the prevention and control of nosocomial infections. Methods The various specimens collected from the patients admitted into ICU in the First People's Hospital of Shunde Affiliated to the South Medical University from January 2007 to December 2014 were used to isolate the pathogens that might cause nosocomial infections and retrospectively analyze their clinical distribution and drug resistance. Kirby-Bauer paper diffusion and minimal inhibitory concentration (MIC) methods were applied to test the drug sensitivity, and according to National Committee for Clinical Laboratory Standards/Clinical and Laboratory Standards Institute (NCCLS/CLSI) standard, the results were identified.Results The sputum was the major specimen source in ICU, accounting for 68.8%, followed by urine (12.4%) and blood (6.8%). All together 557 pathogens in ICU causing nosocomial infections were isolated of which there were 377 gram-negative (G-) bacilli (67.7%), 103 gram-positive (G+) cocci (18.5%), and 77 fungi (13.8%). Among G- bacilli, the top three wereAcinetobacter baumannii (34.5%), Klebsiella pneumonia (17.8%), andPseudomonas aeruginosa (13.0%). Beside carbapenem, the drug resistance rates of Acinetobacterbaumannii to other antibiotics were more than 40%. The main G+ coccus causing nosocomial infection wasSaphylococcus aureus (36.9%) in ICU. The drug resistance rates ofSaphylococcus aureus to penicillin, gentamicin and erythromycin were higher than 50%. In 77 fungus strains,Candida albicans was ranked the first, accounting for 41.6%.Conclusion The main infection site in ICU is primarily respiratory tract, the G- bacilli are the predominate pathogens, and the drug resistance to antibiotics found in this report is serious, so clinically, the antibiotics should be properly used to avoid the occurrence of pathogenic strain with drug tolerance.