The Prediction Analysis of Autistic and Schizotypal Traits in Attentional Networks

Objective@#Empirical findings confirmed that autistic and schizotypal traits are associated with attentional function as well as include various dimensions. So far, no study has reported which dimension of these traits relates to attentional networks. This study aimed to find out whether there are associations between attentional networks and autistic traits; and between attentional networks and schizotypal traits. @*Methods@#A total of 449 volunteers was included in this study, and autism-spectrum quotient (AQ), schizotypal personality questionnaire (SPQ), and attention network test (ANT) were used to measure autistic traits and schizotypal traits. The three independent attentional networks, including alerting network, orienting network, and executive control network, were also measured. @*Results@#Autistic traits were associated with the orienting network, whereas schizotypal traits were associated with the orienting network and executive control network. Furthermore, attentional networks could be predicted by specific dimensions of autistic and schizotypal traits. AQ-attention switching [0.104 (-1.175– -0.025), p=0.041] and AQ-attention to detail [-0.097 (-0.798– -0.001), p=0.049] were significant predictors of orienting network and gender were significant predictor of executive network (Beta=0.107; 95% CI=-0.476–10.139; p=0.031). Whereas, schizotypal dimension “interpersonal” was a significant predictor of all three attentional networks [Alerting: 0.147 (-0.010–0.861), p=0.045; Orienting: 0.147 (0.018–0.733), p=0.040; Executive: 0.198 (0.215–1.309), p=0.006]. @*Conclusion@#This study demonstrated that autistic and schizotypal traits were associated with attentional networks. The specific dimensions of autistic and schizotypal traits could predict attentional networks. Nevertheless, the attentional networks predicted with these two traits were different.

The Prediction Analysis of Autistic and Schizotypal Traits in Attentional Networks

Objective@#Empirical findings confirmed that autistic and schizotypal traits are associated with attentional function as well as include various dimensions. So far, no study has reported which dimension of these traits relates to attentional networks. This study aimed to find out whether there are associations between attentional networks and autistic traits; and between attentional networks and schizotypal traits. @*Methods@#A total of 449 volunteers was included in this study, and autism-spectrum quotient (AQ), schizotypal personality questionnaire (SPQ), and attention network test (ANT) were used to measure autistic traits and schizotypal traits. The three independent attentional networks, including alerting network, orienting network, and executive control network, were also measured. @*Results@#Autistic traits were associated with the orienting network, whereas schizotypal traits were associated with the orienting network and executive control network. Furthermore, attentional networks could be predicted by specific dimensions of autistic and schizotypal traits. AQ-attention switching [0.104 (-1.175– -0.025), p=0.041] and AQ-attention to detail [-0.097 (-0.798– -0.001), p=0.049] were significant predictors of orienting network and gender were significant predictor of executive network (Beta=0.107; 95% CI=-0.476–10.139; p=0.031). Whereas, schizotypal dimension “interpersonal” was a significant predictor of all three attentional networks [Alerting: 0.147 (-0.010–0.861), p=0.045; Orienting: 0.147 (0.018–0.733), p=0.040; Executive: 0.198 (0.215–1.309), p=0.006]. @*Conclusion@#This study demonstrated that autistic and schizotypal traits were associated with attentional networks. The specific dimensions of autistic and schizotypal traits could predict attentional networks. Nevertheless, the attentional networks predicted with these two traits were different.

Multi-organ Proteomic Landscape of COVID-19 Autopsies

The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report an in-depth multi-organ proteomic landscape of COVID-19 patient autopsy samples. By integrative analysis of proteomes of seven organs, namely lung, spleen, liver, heart, kidney, thyroid and testis, we characterized 11,394 proteins, in which 5336 were perturbed in COVID-19 patients compared to controls. Our data showed that CTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients. Dysregulation of protein translation, glucose metabolism, fatty acid metabolism was detected in multiple organs. Our data suggested upon SARS-CoV-2 infection, hyperinflammation might be triggered which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart and thyroid. Evidence for testicular injuries included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility. In summary, this study depicts the multi-organ proteomic landscape of COVID-19 autopsies, and uncovered dysregulated proteins and biological processes, offering novel therapeutic clues. HIGHLIGHTSO_LICharacterization of 5336 regulated proteins out of 11,394 quantified proteins in the lung, spleen, liver, kidney, heart, thyroid and testis autopsies from 19 patients died from COVID-19. C_LIO_LICTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients. C_LIO_LIEvidence for suppression of glucose metabolism in the spleen, liver and kidney; suppression of fatty acid metabolism in the kidney; enhanced fatty acid metabolism in the lung, spleen, liver, heart and thyroid from COVID-19 patients; enhanced protein translation initiation in the lung, liver, renal medulla and thyroid. C_LIO_LITentative model for multi-organ injuries in patients died from COVID-19: SARS-CoV-2 infection triggers hyperinflammatory which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart, kidney and thyroid. C_LIO_LITesticular injuries in COVID-19 patients included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility. C_LI

Eleven Routine Clinical Features Predict COVID-19 Severity

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort consisting of training, validation, and internal test sets, longitudinally recorded 124 routine clinical and laboratory parameters, and built a machine learning model to predict the disease progression based on measurements from the first 12 days since the disease onset when no patient became severe. A panel of 11 routine clinical factors, including oxygenation index, basophil counts, aspartate aminotransferase, gender, magnesium, gamma glutamyl transpeptidase, platelet counts, activated partial thromboplastin time, oxygen saturation, body temperature and days after symptom onset, constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 94%. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, PPV and NPV were 0.70, 0.99, 0.93 and 0.93, respectively. Our model captured predictive dynamics of LDH and CK while their levels were in the normal range. This study presents a practical model for timely severity prediction and surveillance for COVID-19, which is freely available at webserver https://guomics.shinyapps.io/covidAI/.

Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.

Summary of research methods for drug intestinal absorption / 药物评价研究

At present,the study of intestinal absorption of oral drugs mainly includes in vitro,in vivo and in situ methods.In view of the advantages of in situ intestinal perfusion such as simple operation,mature technology,controllable,ensure the neuroendocrine regulation and blood supply,and so on,which could better reflect the true situation of drug absorption.In this study,the research methods and characteristics of intestinal absorption of oral drugs were systematically introduced.The recirculating perfusion method and single-pass perfusion method were compared,and several volume correction methods were also introduced.In order to ensure the operability and accuracy of experimental results,proper experiment method of intestinal absorption will be adopt according to the factors such as drug characters,experiment requirements,experimental conditions,and so on.The article provides a scientific basis for the development of pharmaceutical dosage and clinical rational drug use.

The event-related potentials study on empathy for pain in the subjects with autistic traits / 中华行为医学与脑科学杂志

Objective To study the features and neural mechanism of pain empathy in autistic individuals.MethodsTotally 21 subjects with high level autistic traits and 22 subjects with low level autism traits completed the pain empathy task,recording RT and accuracy automatically.The event-related potentials(ERPs) were recorded by Neuroscan system simultaneously.Results(1)From the behavioral results,the IRI scores of the two groups had significant differences in the factors of perspective taking ((23.71±4.16) vs (26.95±3.24)),empathy concerning ((24.10±4.04) vs (26.36±2.82)) and personal distress ((24.19±3.59) vs (19.82±3.96)) (t=-2.86,P0.05).(2) According to the behavioral result of pain empathy test,the main effect of task type in reaction time and accuracy of the two groups had significant difference (F(1,41)=24.21,P0.05,F(1,41)=0.29,P>0.05;F(1,41)=3.20,P>0.05,F(1,41)=0.14,P>0.05).(3)From the results of ERP,the main effect of emotion type,task type and group didn't reach the significant level in the N2 amplitude of the two groups(F(1,41)=0.04,P>0.05;F(1,41)=0.08,P>0.05;F(1,41)=3.86,P>0.05).The main effect of emotion type had significant difference in the P3 amplitude of the two groups(F(1,41)=8.27,P0.05,F(1,41)=0.25,P>0.05).It had significant difference in LPP amplitude in the main effect of emotion type,task type and group(F(1,41)=32.07,P<0.01;F(1,41)=8.63,P<0.01;F(1,41)=4.73,P<0.05).ConclusionsThere are differences in the abilities of empathy between the high and low level autistic traits groups,especially in the late processing of pain empathy.

Efficacy of RNA interference mediated by cationic liposomes / 生物工程学报

To investigate the cytotoxicity of the homemade peptide cationic liposome CDO14 and its efficacy of RNA interference (RNAi). MTT method was used to determine the cytotoxicity of the liposome to a human lung cancer cell line Luc-A549 that can express luciferase stably. Luciferase siRNA (Luc-siRNA) was transfected into Luc-A549 cells by CDO14. Contents of luciferase in the transfected cells were detected by luminous instrument and contents of total protein in these cells were detected by BCA method. Nude mice were inoculated with Luc-A549 cells in axilla to establish xenograft tumor model. Complexes of Luc-siRNA and the cationic liposomes were injected into the modeling mice via tail vein. Contents of luciferase in the transfected mice were detected by the whole body imaging system. The cytotoxicity of the homemade cationic liposome was similar to that of commercial liposome DOTAP, and lower than that of Lipo2000. The siRNA transfection efficacy mediated by CDO14 was higher than that mediated by DOTAP. The homemade peptide cationic liposome CDO14 is expected to serve as delivery vector in gene therapy because of its low cytotoxicity and high transfection efficiency.