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Recent research has indicated that the cerebellum is responsible for social judgments, such as making trait attributions. The present study investigated the function of the posterior cerebellum in supporting sequence learning linked to trait inferences about persons. We conducted a memory paradigm that required participants to learn a given temporal order of six behavioral sentences that all implied the same personality trait of the protagonist. We then asked participants to infer the trait of the person and to recall the correct order of the sentences and to rate their confidence in their trait judgments and retrieval accuracy. Two control conditions were created a nonsocial comparison control, involving six nonsocial sentences implying a feature of an object, and a nonsocial nonsequential reading baseline condition. NSC 644468 datasheet While learning the specific sequence of the sentences, the posterior cerebellum (Crus 2) was more activated for social trait-related sequencing than nonsocial object-related sequencing. Also, given a longer duration to learn the sequences, the precuneus and posterior cingulate cortex were more activated when participants attempted to retrieve the sequences linked to social traits. In addition, confidence in retrieving the correct order of the social sequences modulated the posterior cerebellum (Crus 1) given a longer duration to learn. Our findings highlight the important function of the posterior cerebellum in supporting an active process of sequencing trait-implying actions.Background Recent studies have observed an association between immune-related adverse events (irAE) and favorable clinical outcomes in the setting of cancer treatment with immune checkpoint inhibitors (ICI). However, results have been variable and inconclusive. Therefore, we have conducted a pan-cancer meta-analysis evaluating the relationship between irAEs and clinical outcomes. Materials and methods The search included studies published in PubMed, Embase, and Web of Science from conception to 12.28.2019 as well as abstracts published in the ASCO and ESMO meetings from 2015 to 2019. Studies were included if ICI was used in advanced or metastatic cancer settings and excluded if data contained only combination therapy regimens or contained anti-CTLA-4. Raw data for overall response rate (ORR), hazard ratios (HR), number of patients (n), and p values for overall survival (OS) and progression-free survival (PFS) were extracted. Pooled sensitivity (SN), specificity (SP), positive (PPV) and negative predictive valS were 0.47 [95% CI 0.37-0.60] and 0.46 [95% CI 0.37-0.56], respectively. Between-study publication bias was present for ORR, OS, and PFS; however, results remained significant after trim-fill analysis. Conclusion irAEs predict OR, OS, and PFS across different types of cancer and may represent useful biomarkers in the clinical setting.Accurate diagnosis of schizophrenia is of great importance to patients and clinicians. Recent studies have found that different frequency bands contain complementary information for diagnosis and prognosis. However, conventional multiple frequency functional connectivity (FC) networks using Pearson’s correlation coefficient (PCC) are usually based on pairwise correlations among different brain regions on single frequency band, while ignoring the interactions between regions in different frequency bands, the relationship among different networks, and the nonlinear properties of blood-oxygen-level-dependent (BOLD) signal. To take into account these relationships, we propose in this study a multiple networks fusion method for schizophrenia diagnosis. Specifically, we first construct FC networks within the same and across frequency from the resting-state functional magnetic resonance imaging (rs-fMRI) time series by using extended maximal information coefficient (eMIC) based on four frequency bands slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz), and slow-2 (0.198-0.25 Hz). Then, these networks are combined nonlinearly through network fusion, which generates a unified network for each subject. Features extracted from the unified network are used for final classification. Experimental results demonstrated that the interaction between distinct brain regions across different frequency bands can significantly improve the classification performance, comparing with conventional FC analysis based on specific or entire low-frequency band. The promising results suggest that our proposed framework would be a useful tool in computer-aided diagnosis of schizophrenia. Graphical abstract The flowchart of proposed classification framework.Skin picking is highly prevalent in people with Prader-Willi syndrome (PWS). This study addressed the temporal (frequency, duration) and wider characteristics (e.g. type of skin picked, apparent motivations, or management strategies) of skin picking to inform intervention strategies. Nineteen parents/carers who observe skin picking shown by the person they care for completed a semi-structured interview. Results were consistent with previous research but advanced the field by finding that most participants picked skin with an imperfection and that parents/carers most commonly use distraction as a management strategy. Interventions that are behavioural, support emotion regulation and/ or are used in the typically developing population are therefore likely to be beneficial for future research.Wall shear stress (WSS) plays a key role in maintaining glycocalyx function, gene expression, and structure. Experimental studies have discussed the relationship between the shedding of the endothelial glycocalyx (EG) and WSS. However, rare literature about how WSS affects the EG during cardiopulmonary bypass (CPB) was mentioned. This study aimed to investigate the correlation between the WSS of carotid arteries and shedding of the EG during CPB in humans. The WSS level was calculated in accordance with an equation. The plasma concentrations of heparan sulfate, syndecan-1, and nitric oxide were measured to reflect shedding of the EG at six time points. A negative correlation was observed between the peak wall shear stress (PWSS) and syndecan-1 (R = – 0.5, p less then 0.01) and heparan sulfate (R = – 0.461, p less then 0.01) during CPB. The WSS is closely associated with the components of glycocalyx shedding during CPB. The WSS produced by non-pulsatile flow during CPB may contribute to the degradation of EG.