Enhancing Information Maximization With Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning.

Existing Cross-Domain Few-Shot Learning (CDFSL) methods require access to source domain data to train a model in the pre-training phase. However, due to increasing concerns about data privacy and the desire to reduce data transmission and training costs, it is necessary to develop a CDFSL solution without accessing source data. For this reason, this paper explores a Source-Free CDFSL (SF-CDFSL) problem, in which CDFSL is addressed through the use of existing pretrained models instead of training a model with source data, avoiding accessing source data. However, due to the lack of source data, we face two key challenges: effectively tackling CDFSL with limited labeled target samples, and the impossibility of addressing domain disparities by aligning source and target domain distributions. This paper proposes an Enhanced Information Maximization with Distance-Aware Contrastive Learning (IM-DCL) method to address these challenges. Firstly, we introduce the transductive mechanism for learning the query set. Secondly, information maximization (IM) is explored to map target samples into both individual certainty and global diversity predictions, helping the source model better fit the target data distribution. However, IM fails to learn the decision boundary of the target task. This motivates us to introduce a novel approach called Distance-Aware Contrastive Learning (DCL), in which we consider the entire feature set as both positive and negative sets, akin to Schrödinger's concept of a dual state. Instead of a rigid separation between positive and negative sets, we employ a weighted distance calculation among features to establish a soft classification of the positive and negative sets for the entire feature set. We explore three types of negative weights to enhance the performance of CDFSL. Furthermore, we address issues related to IM by incorporating contrastive constraints between object features and their corresponding positive and negative sets. Evaluations of the 4 datasets in the BSCD-FSL benchmark indicate that the proposed IM-DCL, without accessing the source domain, demonstrates superiority over existing methods, especially in the distant domain task. Additionally, the ablation study and performance analysis confirmed the ability of IM-DCL to handle SF-CDFSL. The code will be made public at https://github.com/xuhuali-mxj/IM-DCL.

Microglia Caspase11 non-canonical inflammasome drives fever.

AIM: Animals exhibit physiological changes designed to eliminate the perceived danger, provoking similar symptoms of fever. However, a high-grade fever indicates poor clinical outcomes. Caspase11 (Casp11) is involved in many inflammatory diseases. Whether Casp11 leads to fever remains unclear. In this study, we investigate the role of the preoptic area of the hypothalamus (PO/AH) microglia Casp11 in fever. METHODS: We perform experiments using a rat model of LPS-induced fever. We measure body temperature and explore the functions of peripheral macrophages and PO/AH microglia in fever signaling by ELISA, immunohistochemistry, immunofluorescence, flow cytometry, macrophage depletion, protein blotting, and RNA-seq. Then, the effects of macrophages on microglia in a hyperthermic environment are observed in vitro. Finally, adeno-associated viruses are used to knockdown or overexpress microglia Casp11 in PO/AH to determine the role of Casp11 in fever. RESULTS: We find peripheral macrophages and PO/AH microglia play important roles in the process of fever, which is proved by macrophage and microglia depletion. By RNA-seq analysis, we find Casp11 expression in PO/AH is significantly increased during fever. Co-culture and conditioned-culture simulate the induction of microglia Casp11 activation by macrophages in a non-contact manner. Microglia Casp11 knockdown decreases body temperature, pyrogenic factors, and inflammasome, and vice versa. CONCLUSION: We report that Casp11 drives fever. Mechanistically, peripheral macrophages transmit immune signals via cytokines to microglia in PO/AH, which activate the Casp11 non-canonical inflammasome. Our findings identify a novel player, the microglia Casp11, in the control of fever, providing an explanation for the transmission and amplification of fever immune signaling.

Predicting long-term outcomes for acute ischemic stroke using multi-model MRI radiomics and clinical variables.

Purpose: The objective of this study was to create and validate a novel prediction model that incorporated both multi-modal radiomics features and multi-clinical features, with the aim of accurately identifying acute ischemic stroke (AIS) patients who faced a higher risk of poor outcomes. Methods: A cohort of 461 patients diagnosed with AIS from four centers was divided into a training cohort and a validation cohort. Radiomics features were extracted and selected from diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images to create a radiomic signature. Prediction models were developed using multi-clinical and selected radiomics features from DWI and ADC. Results: A total of 49 radiomics features were selected from DWI and ADC images by the least absolute shrinkage and selection operator (LASSO). Additionally, 20 variables were collected as multi-clinical features. In terms of predicting poor outcomes in validation set, the area under the curve (AUC) was 0.727 for the DWI radiomics model, 0.821 for the ADC radiomics model, 0.825 for the DWI + ADC radiomics model, and 0.808 for the multi-clinical model. Furthermore, a prediction model was built using all selected features, the AUC for predicting poor outcomes increased to 0.86. Conclusion: Radiomics features extracted from DWI and ADC images can serve as valuable biomarkers for predicting poor clinical outcomes in patients with AIS. Furthermore, when these radiomics features were combined with multi-clinical features, the predictive performance was enhanced. The prediction model has the potential to provide guidance for tailoring rehabilitation therapies based on individual patient risks for poor outcomes.

Associations between insomnia and large vessel occlusion acute ischemic stroke: An observational study

Abstract Objectives: This study explored the association between insomnia and the clinical outcome of large vessel occlusion Acute Ischemic Stroke (AIS) and attempted to explore its potential mechanisms from the perspectives of inflammation and oxidative stress. Methods: AIS patients who underwent endovascular treatment for large vessel occlusion at Binzhou Central Hospital from 2018 to 2022 (n = 508) were included. Patients were divided into an insomnia group and a non-insomnia group. Insomnia was judged by self-reported Athens Insomnia Scale score. Regression analysis was used to compare the differences in the 24-hour and 7-day National Institutes of Health Stroke Scale (NIHSS) score, Early Neurological Deterioration (END), early adverse event incidence, 90-day prognosis and mortality, and serum bio-markers levels. Results: The incidence of insomnia in the study population was 39.6% (n = 144, insomnia group; n = 364, non-insomnia group). Compared with the non-insomnia group, a worse prognosis outcome (63% vs. 49%, adjusted rate ratio: 1.8, 95% Confidence Interval: 1.2-3.7; p = 0.016), higher 24-h and 7-day NIHSS score (17 [9-36] vs. 13 [5-20]; p = 0.024, and 11 [4‒24) vs. 8 [2‒14]; p = 0.031, respectively), higher END (24% vs. 15%, p = 0.022), and higher incidence of adverse events were observed in the insomnia group (79% vs. 59%, p = 0.010). The 90-day mortality was higher in the insomnia group than that in the non-insomnia group (22% vs. 17%), however, such a difference was not statistically significant. Conclusion: Insomnia is closely related to the clinical outcome of AIS with large vessel occlusion, and inflammation and oxidative stress mechanisms may be involved.

Alprostadil attenuates myocardial ischemia/reperfusion injury by promoting antioxidant activity and eNOS activation in rats

Abstract Purpose: To investigate the effect of alprostadil on myocardial ischemia/reperfusion (I/R) in rats. Methods: Rats were subjected to myocardial ischemia for 30 min followed by 24h reperfusion. Alprostadil (4 or 8 μg/kg) was intravenously administered at the time of reperfusion and myocardial infarct size, levels of troponin T, and the activity of creatine kinase-MB (CK-MB) and lactate dehydrogenase (LDH) in the serum were measured. Antioxidative parameters, nitric oxide (NO) content and phosphorylated endothelial nitric oxide synthase 3 (p-eNOS) expression in the left ventricles were also measured. Histopathological examinations of the left ventricles were also performed. Results: Alprostadil treatment significantly reduced myocardial infarct size, serum troponin T levels, and CK-MB and LDH activity (P<0.05). Furthermore, treatment with alprostadil significantly decreased malondialdehyde (MDA) content (P<0.05) and markedly reduced myonecrosis, edema and infiltration of inflammatory cells. Superoxide dismutase and catalase activities (P<0.05), NO level (P<0.01) and p-eNOS (P<0.05) were significantly increased in rats treated with alprostadil compared with control rats. Conclusion: These results indicate that alprostadil protects against myocardial I/R injury and that these protective effects are achieved, at least in part, via the promotion of antioxidant activity and activation of eNOS.