R\'{e}nyi Divergence Deep Mutual Learning

This paper revisits Deep Mutual Learning (DML), a simple yet effective computing paradigm. We propose using R\'{e}nyi divergence instead of the KL divergence, which is more flexible and tunable, to improve vanilla DML. This modification is able to consistently improve performance over vanilla DML with limited additional complexity. The convergence properties of the proposed paradigm are analyzed theoretically, and Stochastic Gradient Descent with a constant learning rate is shown to converge with $\mathcal{O}(1)$-bias in the worst case scenario for nonconvex optimization tasks. That is, learning will reach nearby local optima but continue searching within a bounded scope, which may help mitigate overfitting. Finally, our extensive empirical results demonstrate the advantage of combining DML and R\'{e}nyi divergence, which further improves generalized models

Lack of correlation between the levels of soluble cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and the CT-60 genotypes

BACKGROUND: Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) plays a critical role in downregulation of antigen-activated immune response and polymorphisms at the CTLA-4 gene have been shown to be associated with several autoimmune diseases including type-1 diabetes (T1D). The etiological mutation was mapped to the CT60-A/G single nucleotide polymorphism (SNP) that is believed to control the processing and production of soluble CTLA-4 (sCTLA-4). METHODS: We therefore determined sCTLA-4 protein levels in the sera from 82 T1D patients and 19 autoantibody positive (AbP) subjects and 117 autoantibody negative (AbN) controls using ELISA. The CT-60 SNP was genotyped for these samples by using PCR and restriction enzyme digestion of a 268 bp DNA segment containing the SNP. Genotyping of CT-60 SNP was confirmed by dye terminating sequencing reaction. RESULTS: Higher levels of sCTLA-4 were observed in T1D (2.24 ng/ml) and AbP (mean = 2.17 ng/ml) subjects compared to AbN controls (mean = 1.69 ng/ml) with the differences between these subjects becoming significant with age (p = 0.02). However, we found no correlation between sCTLA-4 levels and the CTLA-4 CT-60 SNP genotypes. CONCLUSION: Consistent with the higher serum sCTLA-4 levels observed in other autoimmune diseases, our results suggest that sCTLA-4 may be a risk factor for T1D. However, our results do not support the conclusion that the CT-60 SNP controls the expression of sCTLA-4

The role of Tyro 3 subfamily receptors in the regulation of hemostasis and megakaryocytopoiesis

Background and Objectives The molecular mechanisms regulating megakaryocytopoiesis and hemostasis remain largely unknown. The Tyro 3 subfamily of receptor tyrosine kinases (RTK), which is composed of three members (Tyro 3, Axl and Mer), plays important roles in various tissues, such as those in the nervous, immune and reproductive systems. Here, we investigate the roles of the Tyro 3 RTK subfamily in regulating megakaryocytopoiesis and hemostasis.Design and Methods Single, double, and triple knock-out mice for the three Tyro 3 RTK were used in the study. Bleeding time, platelet count, megakaryocyte count, megakaryocyte ploidy, rate of proplatelet formation, platelet aggregation and ATP release were used as criteria to evaluate hemostasis, megakaryocytopoiesis and platelet function.Results Mice lacking all three receptors had impaired hemostasis and mild thrombocytopenia, which may be due to platelet dysfunction and defective megakaryocytopoiesis. Mice lacking different combinations of two receptors of the Tyro 3 RTK subfamily had normal platelet counts in peripheral blood, but exhibited impaired hemostasis and platelet function. Although knock-out mice for any single receptor had normal hemostasis and megakaryocytopoiesis, they exhibited a mild platelet dysfunction.Interpretation and Conclusions The Tyro 3 RTK subfamily plays important roles in regulating hemostasis, megakaryocytopoiesis and platelet function

Effect of magnesium sulfate on cerebral vasospasm in the treatment of aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis

IntroductionThe use of magnesium sulfate for treating aneurysmal subarachnoid hemorrhage (aSAH) has shown inconsistent results across studies. To assess the impact of magnesium sulfate on outcomes after aSAH, we conducted a systematic review and meta-analysis of relevant randomized controlled trials.MethodsPubMed, Embase, and the Cochrane Library were searched for relevant literature on magnesium sulfate for aSAH from database inception to March 20, 2023. The primary outcome was cerebral vasospasm (CV), and secondary outcomes included delayed cerebral ischemia (DCI), secondary cerebral infarction, rebleeding, neurological dysfunction, and mortality.ResultsOf the 558 identified studies, 16 comprising 3,503 patients were eligible and included in the analysis. Compared with control groups (saline or standard treatment), significant differences were reported in outcomes of CV [odds ratio (OR) = 0.61, p = 0.04, 95% confidence interval (CI) (0.37–0.99)], DCI [OR = 0.57, p = 0.01, 95% CI (0.37–0.88)], secondary cerebral infarction [OR = 0.49, p = 0.01, 95% CI (0.27–0.87)] and neurological dysfunction [OR = 0.55, p = 0.04, 95% CI (0.32–0.96)] after magnesium sulfate administration, with no significant differences detected in mortality [OR = 0.92, p = 0.47, 95% CI (0.73–1.15)] and rebleeding [OR = 0.68, p = 0.55, 95% CI (0.19–2.40)] between the two groups.ConclusionThe superiority of magnesium sulfate over standard treatments for CV, DCI, secondary cerebral infarction, and neurological dysfunction in patients with aSAH was demonstrated. Further randomized trials are warranted to validate these findings with increased sample sizes

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Bifunctional M13 Phage as Enzyme Container for the Reinforced Colorimetric–Photothermal Dual-Modal Sensing of Ochratoxin A

“Point of care” (POC) methods without expensive instruments and special technicians are greatly needed for high-throughput analysis of mycotoxins. In comparison, the most widely used screening method of the conventional enzyme-linked immunosorbent assay (ELISA) confronts low sensitivity and harmful competing antigens. Herein, we develop a plasmonic-photothermal ELISA that allows precise readout by color-temperature dual-modal signals based on enzymatic reaction-induced AuNP aggregation for highly sensitive detection of ochratoxin A (OTA). The bifunctional M13 phage carrying OTA that mimics the mimotope on the end of p3 proteins and abundant biotin molecules on the major p8 proteins is adopted as an eco-friendly competing antigen and enzyme container for amplifying the signal intensity. Under optimal conditions, both colorimetric and photothermal signals enable good dynamic linearity for quantitative OTA detection with the limits of detection at 12.1 and 8.6 pg mL−1, respectively. Additionally, the proposed ELISA was adapted to visual determination with a cutoff limit of 78 pg mL−1 according to a vivid color change from deep blue to red. The recoveries of OTA-spiked corn samples indicate the high accuracy and robustness of the proposed method. In conclusion, our proposed strategy provides a promising method for eco-friendly and sensitive POC screening of OTA. Moreover, it can be easily applied to other analytes by changing the involved specific mimotope sequence

A Cross-Attention Mechanism Based on Regional-Level Semantic Features of Images for Cross-Modal Text-Image Retrieval in Remote Sensing

With the rapid development of remote sensing (RS) observation technology over recent years, the high-level semantic association-based cross-modal retrieval of RS images has drawn some attention. However, few existing studies on cross-modal retrieval of RS images have addressed the issue of mutual interference between semantic features of images caused by “multi-scene semantics”. Therefore, we proposed a novel cross-attention (CA) model, called CABIR, based on regional-level semantic features of RS images for cross-modal text-image retrieval. This technique utilizes the CA mechanism to implement cross-modal information interaction and guides the network with textual semantics to allocate weights and filter redundant features for image regions, reducing the effect of irrelevant scene semantics on retrieval. Furthermore, we proposed BERT plus Bi-GRU, a new approach to generating statement-level textual features, and designed an effective temperature control function to steer the CA network toward smooth running. Our experiment suggested that CABIR not only outperforms other state-of-the-art cross-modal image retrieval methods but also demonstrates high generalization ability and stability, with an average recall rate of up to 18.12%, 48.30%, and 55.53% over the datasets RSICD, UCM, and Sydney, respectively. The model proposed in this paper will be able to provide a possible solution to the problem of mutual interference of RS images with “multi-scene semantics” due to complex terrain objects

A Cross-Attention Mechanism Based on Regional-Level Semantic Features of Images for Cross-Modal Text-Image Retrieval in Remote Sensing

With the rapid development of remote sensing (RS) observation technology over recent years, the high-level semantic association-based cross-modal retrieval of RS images has drawn some attention. However, few existing studies on cross-modal retrieval of RS images have addressed the issue of mutual interference between semantic features of images caused by “multi-scene semantics”. Therefore, we proposed a novel cross-attention (CA) model, called CABIR, based on regional-level semantic features of RS images for cross-modal text-image retrieval. This technique utilizes the CA mechanism to implement cross-modal information interaction and guides the network with textual semantics to allocate weights and filter redundant features for image regions, reducing the effect of irrelevant scene semantics on retrieval. Furthermore, we proposed BERT plus Bi-GRU, a new approach to generating statement-level textual features, and designed an effective temperature control function to steer the CA network toward smooth running. Our experiment suggested that CABIR not only outperforms other state-of-the-art cross-modal image retrieval methods but also demonstrates high generalization ability and stability, with an average recall rate of up to 18.12%, 48.30%, and 55.53% over the datasets RSICD, UCM, and Sydney, respectively. The model proposed in this paper will be able to provide a possible solution to the problem of mutual interference of RS images with “multi-scene semantics” due to complex terrain objects