SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation

Recent advancements in large-scale Vision Transformers have made significant strides in improving pre-trained models for medical image segmentation. However, these methods face a notable challenge in acquiring a substantial amount of pre-training data, particularly within the medical field. To address this limitation, we present Masked Multi-view with Swin Transformers (SwinMM), a novel multi-view pipeline for enabling accurate and data-efficient self-supervised medical image analysis. Our strategy harnesses the potential of multi-view information by incorporating two principal components. In the pre-training phase, we deploy a masked multi-view encoder devised to concurrently train masked multi-view observations through a range of diverse proxy tasks. These tasks span image reconstruction, rotation, contrastive learning, and a novel task that employs a mutual learning paradigm. This new task capitalizes on the consistency between predictions from various perspectives, enabling the extraction of hidden multi-view information from 3D medical data. In the fine-tuning stage, a cross-view decoder is developed to aggregate the multi-view information through a cross-attention block. Compared with the previous state-of-the-art self-supervised learning method Swin UNETR, SwinMM demonstrates a notable advantage on several medical image segmentation tasks. It allows for a smooth integration of multi-view information, significantly boosting both the accuracy and data-efficiency of the model. Code and models are available at https://github.com/UCSC-VLAA/SwinMM/.Comment: MICCAI 2023; project page: https://github.com/UCSC-VLAA/SwinMM

The novel prolyl hydroxylase-2 inhibitor caffeic acid upregulates hypoxia inducible factor and protects against hypoxia

Background & aims: Hypoxia inducible factor (HIF) is a hypoxia-associated transcription factor that has a protective role against hypoxia-induced damage. Prolyl hydroxylase-2 (PHD2) is a dioxygenase enzyme that specifically hydroxylates HIF targeting it for degradation, therefore, inhibition of the PHD2 enzyme activity acts to upregulate HIF function. This study was to identify novel PHD2 inhibitors. Methods: An established fluorescence-based PHD2 activity assay was used for inhibitors screening. Western blot and quantitative real-time PCR was used to detect the protein and mRNA levels respectively. Further animal experiment was carried out. Results: Caffeic acid was screened and identified as a novel PHD2 inhibitor. Caffeic acid treated PC12 and SH-SY5Y neuronal cell lines stabilized endogenous HIF-1α protein levels and consequently increased mRNA levels of its downstream regulated genes VEGF and EPO. Caffeic acid treatment reduced hypoxia-induced cell apoptosis and promoted HIF/BNIP3-mediated mitophagy. Moreover, animal studies indicated that caffeic acid increased the level of HIF-1α protein and mRNA levels of VEGF and EPO in the brain of mice exposed to hypoxia. Conventional brain injury markers including malondialdehyde, lactic acid and lactate dehydrogenase in the caffeic acid treated mice were shown to be reduced to the levels of the control group. Conclusions: This study suggests that caffeic acid inhibits PHD2 enzyme activity which then activates the hypoxia-associated transcription factor HIF leading to a neuroprotective effect against hypoxia

Abnormal Alterations of Regional Spontaneous Neuronal Activity in Inferior Frontal Orbital Gyrus and Corresponding Brain Circuit Alterations: A Resting-State fMRI Study in Somatic Depression

Background: Major depressive disorders often involve somatic symptoms and have been found to have fundamental differences from non-somatic depression (NSD). However, the neural basis of this type of somatic depression (SD) is unclear. The aim of this study is to use the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) analyses to examine the abnormal, regional, spontaneous, neuronal activity and the corresponding brain circuits in SD patients.Methods: 35 SD patients, 25 NSD patients, and 27 matched healthy controls were selected to complete this study. The ALFF and seed-based FC analyses were employed, and the Pearson correlation was determined to observe possible clinical relevance.Results: Compared with NSD, the SD group showed a significant ALFF increase in the right inferior temporal gyrus; a significant ALFF decrease in left hippocampus, right inferior frontal orbital gyrus and left thalamus; and a significant decrease in the FC value between the right inferior frontal orbital gyrus and the left inferior parietal cortex (p < 0.05, corrected). Within the SD group, the mean ALFF value of the right inferior frontal orbital gyrus was associated with the anxiety factor scores (r = –0.431, p = 0.010, corrected).Conclusions: Our findings suggest that abnormal differences in the regional spontaneous neuronal activity of the right inferior frontal orbital gyrus were associated with dysfunction patterns of the corresponding brain circuits during rest in SD patients, including the limbic-cortical systems and the default mode network. This may be an important aspect of the underlying mechanisms for pathogenesis of SD at the neural level

Safety and efficacy of non–vitamin K oral anticoagulant for atrial fibrillation patients after percutaneous coronary intervention::A bivariate analysis of the PIONEER AF-PCI and RE-DUAL PCI trial

Background: The tradeoff in safety versus efficacy in substituting a non-vitamin K antagonist oral anticoagulant for a vitamin K antagonist (VKA) in the stented atrial fibrillation patient has not been quantitatively evaluated. Methods: Based on summary data from the PIONEER AF-PCI and RE-DUAL PCI trials, 4 antithrombotic regimens were compared with VKA-based triple therapy: (1) rivaroxaban (riva) 15 mg daily + P2Y(12) inhibitor, (2) riva 2.5 mg twice daily + P2Y(12) inhibitor + aspirin, (3) dabigatran (dabi) 110 mg twice daily + P2Y(12) inhibitor, and (4) dabi 150 mg twice daily + P2Y(12) inhibitor. A bivariate model with a noninferiority margin of 1.38 was used to simultaneously assess safety and efficacy. The safety end point was major or clinically relevant nonmajor bleeding by International Society on Thrombosis and Haemostasis definitions. The efficacy end point was a thromboembolic event (myocardial infarction, stroke, or systemic embolism), death, or urgent revascularization. The bivariate outcome, a measure of risk difference in the net clinical outcome, was compared between antithrombotic regimens. Results: All 4 non-vitamin K antagonist oral anticoagulant regimens were superior in bleeding and noninferior in efficacy compared with triple therapy with VKA. Riva 15 mg daily and 2.5 mg twice daily were associated with bivariate combined risk reductions of 5.6% (2.3%-8.8%) and 5.5% (2.1%-8.7%), respectively, and dabi 110 mg twice daily and 150 mg twice daily reduced the bivariate risk by 3.8% (0.5%-7.0%) and 6.3% (2.4%-9.8%), respectively. Conclusions: A bivariate analysis that simultaneously characterizes both risk and benefit demonstrates that riva-and dabi-based regimens were both favorable over VKA plus dual antiplatelet therapy among patients with atrial fibrillation undergoing PCI. (C) 2018 Elsevier Inc. All rights reserved

Novel statistical methods for multi-stage designs in clinical trials with high placebo response

Placebo response occurs when a patient perceives an improvement from the psychological effect of receiving treatment rather than from the therapy itself. High placebo response reduces drug-placebo differences and makes it challenging to demonstrate a statistically significant benefit of an active drug over placebo. Two-way enriched design (TED) and sequential enriched design (SED) are two designs to estimate treatment effect with the existence of placebo response. They are extensions of sequential parallel comparison design (SPCD) and have multiple stages with enrichment strategies. This work aims to propose novel analysis methods and evaluate their performances in the framework of TED and SED. TED is a two-stage, randomized, placebo-controlled design with enrichment in 'placebo non-responders' and 'drug responders'. We first consider the placebo non-response as a measurable binary characteristic, either present or absent in an individual. We then discuss the placebo non-response as a characteristic that exists in every subject to a certain degree. We propose to include it in the model as a weight. In addition, we consider placebo non-response and drug non-response as latent characteristics and introduce stochastic components in the classification of the subjects in the setting of TED. SED, as the only three-stage design, aims to exclude subjects who are 'placebo responders' and those who never respond to either treatment. Considering the complexity of this design, we critically appraise the performance of SED from different perspectives. We first test the robustness of SED by varying values of parameters. We then calculate the actual sample size and the proportion of the target population in the sample. We also apply the first two analysis methods to SED. We evaluate these novel methods on a wide range of simulated data scenarios in terms of type I error, mean squared error, and power. From the appraisals above, SED does not benefit from the additional stage. Therefore, in terms of design, we suggest implementing TED rather than SED when placebo response is a critical issue. In terms of the proposed analysis methods, the approach with stochastic components performs the best based on our evaluations, especially when the definition of response is uncertain.2022-03-17T00:00:00

Predicting new-onset HF in patients undergoing coronary or peripheral angiography: results from the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) study

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