Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in an Alzheimer's disease model

Amyloid-β plaques and neurofibrillary tau tangles are the neuropathologic hallmarks of Alzheimer's disease (AD), but the spatiotemporal cellular responses and molecular mechanisms underlying AD pathophysiology remain poorly understood. Here we introduce STARmap PLUS to simultaneously map single-cell transcriptional states and disease marker proteins in brain tissues of AD mouse models at subcellular resolution (200 nm). This high-resolution spatial transcriptomics map revealed a core-shell structure where disease-associated microglia (DAM) closely contact amyloid-β plaques, whereas disease-associated astrocytes (DAA) and oligodendrocyte precursor cells (OPC) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerged mainly in excitatory neurons in the CA1 region accompanied by the infiltration of oligodendrocyte subtypes into the axon bundles of hippocampal alveus. The integrative STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing an unprecedented roadmap to pinpoint the molecular and cellular mechanisms of AD pathology and neurodegeneration.

Evaluation of anti-inflammatory and antioxidant for chrysanthemum stem and leaf in zebrafish inflammatory bowel disease model and identification of the bioactive compositions by UPLC-TQ/MS

Background Modern studies have shown that chrysanthemum has anti-inflammatory, regulating intestinal function and other effects, chrysanthemum stem and leaf as a nonmedicinal part of chrysanthemum, has similar chemical components with chrysanthemum, so it is speculated that chrysanthemum stem and leaf also has the effect of regulating intestinal inflammation. The purpose of this study was to evaluate the antiinflammatory and antioxidant effect of chrysanthemum stem and leaf extract through zebrafish inflammatory bowel disease model, and to detect flavonoids, phenolic acids and polysaccharides in chrysanthemum stem and leaf extract. Methods DSS induced inflammatory bowel disease model of zebrafish was used. Aliciin blue staining was used to observe the secretion of intestinal acid mucin, and H&E staining was used to detect the inflammatory cell infiltration. Superoxide dismutase activity was determined by kit, and the expression levels of key inflammatory cytokines IL-1 β , IL8 and MMP9 were detected by quantitative polymerase chain reaction. Furthermore, UPLC-TQ /MS method was used to detect the contents of flavonoids and phenolic acids in chrysanthemum stem and leaf extracts. Neutral and acidic polysaccharides were determined by the phenol-sulfuric acid method and the carbazol-sulfuric acid method. Results H&E staining showed that extracts from chrysanthemum stem and leaf inhibited inflammatory cell infiltration to varying degrees. The expressions of inflammatory cytokines IL-1 β , IL8 and MMP9 were significantly increased in DSS induced zebrafish. The extracts inhibited the expression of IL-1 β , IL8 and MMP9 in DSS induced zebrafish. The water extract 0.2mg/ mL and alcohol extract 0.04mg/ mL had the most significant inhibition. Superoxide dismutase activity in extract treatment group was also up-regulated compared with model group. The results showed that the contents of total flavonoids and phenolic acids in the alcohol extract of chrysanthemum stem and leaf were significantly higher than those in the water extract of chrysanthemum stem and leaf, but the water-soluble polysaccharides were significantly more in the water extract of chrysanthemum stem and leaf. Conclusions In conclusion, this study suggests that chrysanthemum stem and leaf extract can improve inflammatory bowel disease of zebrafish through antiinflammatory and antioxidant activities.

Cognitive behaviour therapy for adolescents with eating disorders: An effective alternative to the disease-based treatments

Several clinical services offer eclectic multidisciplinary treatments with no evidence of efficacy and effectiveness for adolescents with eating disorders. These treatments are usually based on the ‘disease model’ of eating disorders. The model postulates that eating disorders are the result of a specific disease (i.e., anorexia nervosa, bulimia nervosa or other eating disorders), and patients are considered not to have control of their illness. Therefore, they need the external control of parents and/or health professionals. In this model, the patients adopt a passive role in the treatment. On the contrary, enhanced cognitive behaviour therapy (CBT-E) for adolescents is based on a ‘psychological model’ of eating disorders. Patients are helped to understand the psychological mechanisms that maintain their eating disorder and are ‘actively’ involved in the recovery process. Clinical studies showed that more than 60% of adolescent patients who complete the treatment achieve a full response at 12-month follow-up. The treatment is well accepted by young people and their parents, and its collaborative nature is well suited to ambivalent young patients who may be particularly concerned about control issues and for parents who cannot participate in all treatment sessions.

Solving an Infectious Disease Model considering Its Anatomical Variables with Stochastic Numerical Procedures

The aim of the current work is to perform the numerical investigation of the infectious disease based on the nonlinear fractional order prey-predator model using the Levenberg–Marquardt backpropagation (LMB) based on the artificial neuron networks (ANNs), i.e., LMBNNs. The fractional prey-predator model is classified into three categories, the densities of the susceptible, infected prey, and predator populations. The statistics proportions for solving three different variations of the infectious disease based on the fractional prey-predator model are designated for training 80% and 10% for both validation and testing. The numerical actions are performed using the LMBNNs to solve the infectious disease based on the fractional prey-predator model, and comparison is performed using the database Adams–Bashforth–Moulton approach. The infectious disease based on the fractional prey-predator model is solved using the LMBNNs to reduce the mean square error (M.S.E). In order to validate the exactness, capability, consistency, and competence of the proposed LMBNNs, the numerical procedures using the correlation, M.S.E, regression, and error histograms are drawn.

Advantages and Limitations of Clinical Scores for Donation After Circulatory Death Liver Transplantation

Background: Scoring systems have been proposed to select donation after circulatory death (DCD) donors and recipients for liver transplantation (LT). We hypothesized that complex scoring systems derived in large datasets might not predict outcomes locally.Methods: Based on 1-year DCD-LT graft survival predictors in multivariate logistic regression models, we designed, validated, and compared a simple index using the University of California, San Francisco (UCSF) cohort (n = 136) and a universal-comprehensive (UC)-DCD score using the United Network for Organ Sharing (UNOS) cohort (n = 5,792) to previously published DCD scoring systems.Results: The total warm ischemia time (WIT)-index included donor WIT (dWIT) and hepatectomy time (dHep). The UC-DCD score included dWIT, dHep, recipient on mechanical ventilation, transjugular-intrahepatic-portosystemic-shunt, cause of liver disease, model for end-stage liver disease, body mass index, donor/recipient age, and cold ischemia time. In the UNOS cohort, the UC-score outperformed all previously published scores in predicting DCD-LT graft survival (AUC: 0.635 vs. ≤0.562). In the UCSF cohort, the total WIT index successfully stratified survival and biliary complications, whereas other scores did not.Conclusion: DCD risk scores generated in large cohorts provide general guidance for safe recipient/donor selection, but they must be tailored based on non-/partially-modifiable local circumstances to expand DCD utilization.