ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Mytilus is one of bivalves with great economic and ecological values.The innate immune de-fense of Mytilus shows great significance in the study of marine biological immunology.Hemolymph is the main immune tissue for Mytilus.The Nanopore full-length transcriptome of Mytilus coruscus hemocytes,and the serum differential proteomics based on SDS-PAGE analysis were performed to identify key pro-teins involving in the immune response of Mytilus hemolymph in response of different bacteria and fungi stresses.A total of 44 proteins were identified in the serum induced by different microorganisms.Among them,26 proteins showed significant differential expression level in response to different microbial stres-ses,and their functions were involved in protein folding protection,cell autophagy and apoptosis regula-tion,reactive oxygen species production,energy metabolism regulation,cell detoxification,and immune regulation.The changes in expression levels of these proteins varied in response to different bacterial and fungal stresses,suggesting that Mytilus has different immune response strategies to different bacterial and fungal stresses.The results provide a new scientific basis for understanding the differential immune mech-anism of Mytilus innate immune system in response to different types of microbial invasion,as well as the screening of specific biomarker proteins for microbial infection,and provide ideas for the healthy develop-ment and disease prevention of shellfish aquaculture.

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
Male ; Humans ; Prostate/pathology* ; Prostate-Specific Antigen/analysis* ; Prostatic Neoplasms/diagnostic imaging* ; Biopsy ; Nomograms ; Retrospective Studies

Objective:A mouse model of pancreatitis induced by coxsackievirus B3 (CVB3) was established. The pathological change of pancreas and the infiltration of Th17/Treg cells were observed.Methods:The BALB/c mice were inoculated intraperitoneally with CVB3 to induce acute viral pancreatitis model. Then the pathological changes of pancreas were observed by HE staining; the viral RNA load and relative expression of cytokines (IFN-γ, IL-6 and IL-17) mRNA were detected by q-PCR; the proportion of infiltrated CD45 + CD3 + T cells, CD4 + and CD8 + T cells, Th17 and Treg cells in the pancreas was determined by flow cytometry. Results:Three days after CVB3 infection, the viral RNA load in pancreas was the highest (0.96±0.18) and gradually decreased with prolongation of infection. Compared with the 3 dpi group, the viral RNA load in pancreas was decreased (0.96±0.18 vs. 0.62±0.14) at 7 dpi, but there was no statistically significant difference. In addition, the infiltration of immune cell in pancreas increased significantly after 7dpi and the pathological score >2. The percent of infiltrated Th17 cells (1.05±0.21 vs. 22.13±5.79) and Treg cells (3.11±0.78 vs. 8.25±1.30) among CD4 + T cells significantly increased after infection (P<0.05), and the Th17/Treg also increased (P<0.01). Compared with the control group, the relative mRNA expression of IFN-γ (1.05±0.23 vs. 672.6±47.67), IL-6 (1.00±0.38 vs. 68.28±4.57), and IL-17 (1.01±0.11 vs. 54.15±7.94) in pancreas increased at 7 days after CVB3 infection ( P<0.01). Conclusions:The infiltration of Th17/Treg cells and the expression of related cytokines related cytokines IL-6 and IL-17 mRNA were upregulated in pancreas, which promoted the process of CVB3-induced pancreatitis.

This study aims to evaluate the methodological and reporting quality of diagnosis and treatment guidelines for hyperuricemia as well as the expert consensuses and promote the understanding and application of the diagnosis and treatment guidelines for hyperuricemia. With "hyperuricemia" "guidelines" "consensus" "recommendations" as the key words in titles, the authors searched for the published clinical guidelines on hyperuricemia in Chinese against CNKI, Wanfang, VIP, Medlive and the official website of the industry association. The retrieval time limit was until May 31, 2021. The appraisal of guidelines for research and evaluation Ⅱ(AGREEⅡ) and the reporting items for practice guidelines in health care(RIGHT) were employed to evaluate the methodological quality and reporting quality of 14 guidelines/consensuses included. The average scores of the guidelines/consensuses were 80.85%(48.61%-98.61%) for the domain of scope and purpose, 34.52%(0-69.44%) for the domain of stakeholder involvement, 35.53%(6.25%-92.19%) for the domain of rigor of development, 55.85%(23.61%-86.11%) for the domain of clarity of presentation, 26.19%(0-76.04%) for the domain of applicability, and 21.42%(0-50.00%) for the domain of editorial independence. Nine guidelines/consensuses were of medium overall quality with grade B recommendation, and five guidelines/consensuses were of poor quality with grade C recommendation. The RIGHT classified the fourteen guidelines/consensuses into one of high reporting quality, three of medium reporting quality, and ten of low reporting quality. The results of this study indicate that the standardization and rigor of the methodological quality and the reporting quality of the clinical guidelines/consensuses for hyperuricemia in China remain to be strengthened.
China ; Consensus ; Humans ; Hyperuricemia/drug therapy* ; Publications ; Reference Standards

Objective:To analyze the epidemiological characteristics and genotypes of human rhinovirus (HRV) in patients with upper respiratory tract infection in Qingdao in the winter of 2020.Methods:Throat swab samples were collected from 101 patients with upper respiratory tract infection in Qingdao from November 2020 to January 2021. Quantitative PCR was used to detect 15 common respiratory viruses in the samples. HRV-positive samples were further analyzed with RT-PCR to amplify and sequence HRV VP4/VP2 gene. A phylogenetic tree was constructed based on the sequencing results and homology analysis was conducted.Results:Six common respiratory viruses were detected in the 101 patients. Thirty-four cases (34/101, 33.66%) were single pathogen infection and two cases were multiple infection (2/101, 1.98%). The positive rate of HRV was the highest (21.78%, 22/101). Twenty HRV VP4/VP2 sequences were successfully amplified. Phylogenetic analysis showed that there were 16 strains of HRV-A subtype and four strains of HRV-C subtype and 14 serotypes were involved.Conclusions:HRV was one of the leading viral pathogens causing upper respiratory tract infection in Qingdao in the winter of 2020 and the predominant subtype was HRV-A.