38 research outputs found

    Application of Zebrafish Models in Inflammatory Bowel Disease

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    Inflammatory bowel disease (IBD) is a chronic, recurrent, and remitting inflammatory disease with unclear etiology. As a clinically frequent disease, it can affect individuals throughout their lives, with multiple complications. Unfortunately, traditional murine models are not efficient for the further study of IBD. Thus, effective and convenient animal models are needed. Zebrafish have been used as model organisms to investigate IBD because of their suggested highly genetic similarity to humans and their superiority as laboratory models. The zebrafish model has been used to study the composition of intestinal microbiota, novel genes, and therapeutic approaches. The pathogenesis of IBD is still unclear and many risk factors remain unidentified. In this review, we compare traditional murine models and zebrafish models in terms of advantages, pathogenesis, and drug discovery screening for IBD. We also review the progress and deficiencies of the zebrafish model for scientific applications

    Augmenting Buried In Treasures With In-Home Uncluttering Practice: Pilot Study In Hoarding Disorder

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    Hoarding disorder is characterized by difficulty parting with possessions and by clutter that impairs the functionality of living spaces. Cognitive behavioral therapy conducted by a therapist (individual or in a group) for hoarding symptoms has shown promise. For those who cannot afford or access the services of a therapist, one alternative is an evidence-based, highly structured, short-term, skills-based group using CBT principles but led by non-professional facilitators (the Buried in Treasures [BIT] Workshop). BIT has achieved improvement rates similar to those of psychologist-led CBT. Regardless of modality, however, clinically relevant symptoms remain after treatment, and new approaches to augment existing treatments are needed. Based on two recent studies - one reporting that personalized care and accountability made treatments more acceptable to individuals with hoarding disorder and another reporting that greater number of home sessions were associated with better clinical outcomes, we tested the feasibility and effectiveness of adding personalized, in-home uncluttering sessions to the final weeks of BIT. Participants (n = 5) had 15 sessions of BIT and up to 20 hours of in-home uncluttering. Reductions in hoarding symptoms, clutter, and impairment of daily activities were observed. Treatment response rate was comparable to rates in other BIT studies, with continued improvement in clutter level after in-home uncluttering sessions. This small study suggests that adding in-home uncluttering sessions to BIT is feasible and effective

    Correction to: Robust Findings From 25 Years of PTSD Genetics Research

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    Temporal Shift Module with Pretrained Representations for Speech Emotion Recognition

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    Recent advances in self-supervised models have led to effective pretrained speech representations in downstream speech emotion recognition tasks. However, previous research has primarily focused on exploiting pretrained representations by simply adding a linear head on top of the pretrained model, while overlooking the design of the downstream network. In this paper, we propose a temporal shift module with pretrained representations to integrate channel-wise information without introducing additional parameters or floating-point operations per second. By incorporating the temporal shift module, we developed corresponding shift variants for 3 baseline building blocks: ShiftCNN, ShiftLSTM, and Shiftformer. Furthermore, we propose 2 technical strategies, placement and proportion of shift, to balance the trade-off between mingling and misalignment. Our family of temporal shift models outperforms state-of-the-art methods on the benchmark Interactive Emotional Dyadic Motion Capture dataset in fine-tuning and feature-extraction scenarios. In addition, through comprehensive experiments using wav2vec 2.0 and Hidden-Unit Bidirectional Encoder Representations from Transformers representations, we identified the behavior of the temporal shift module in downstream models, which may serve as an empirical guideline for future exploration of channel-wise shift and downstream network design
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