Vietnamese Voluntary Foundation

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model that requires a triplet of text, before, and after images for retraining over a text-to-image model. Such crafting triplets and retraining processes limit the scalability and generalization of editing. In this paper, we present a framework based on any single text-to-image model without reliance on the explicit image-to-image model thus enhancing the generalizability and scalability. Specifically, by leveraging the probability-flow ordinary equation, we construct a diffusion bridge to transfer the distribution between before-and-after images under the text guidance. By optimizing the text via the bridge, the framework adaptively textualizes the editing transformation conveyed by visual prompts into text embeddings without other models. Meanwhile, we introduce differential attention control during optimization, which disentangles the text embedding from the invariance of the before-and-after images and makes it solely capture the delicate transformation and generalize to edit various images. Experiments on real images validate competitive results on the generalization, contextual coherence, and high fidelity for delicate editing with just one image pair as the visual prompt.

Endoplasmic-reticulum resident inositol-requiring enzyme 1α (IRE1) supports protein homeostasis via its cytoplasmic kinase-RNase module. Known cancer dependency on IRE1 entails its enzymatic activation of the transcription factor XBP1s and of regulated RNA decay. We discovered surprisingly that some cancer cell lines require IRE1 but not its enzymatic activity. IRE1 knockdown but not enzymatic IRE1 inhibition or XBP1 disruption attenuated cell cycle progression and tumor growth. IRE1 silencing led to activation of TP53 and CDKN1A/p21 in conjunction with increased DNA damage and chromosome instability, while decreasing heterochromatin as well as DNA and histone H3K9me3 methylation. Immunoelectron microscopy detected some endogenous IRE1 protein at the nuclear envelope. Thus, cancer cells co-opt IRE1 either enzymatically or nonenzymatically, which has significant implications for IRE1's biological role and therapeutic targeting.

Abstract Background The genetic profile that is needed to identify talents has been studied extensively in recent years. The main objective of this investigation was to approach, for the first time, the study of genetic variants in several polygenic profiles and their role in elite endurance and professional football performance by comparing the allelic and genotypic frequencies to the non-athlete population. Methods Genotypic and allelic frequencies were determined in 452 subjects; 292 professional athletes (160 elite endurance athletes and 132 professional football players) and 160 non-athlete subjects. Genotyping of liver metabolism, iron metabolism and energy efficiency, cardiorespiratory fitness and muscle performance was performed by Polymerase Chain Reaction-Single Nucleotide Primer Extension (PCR-SNPE). The combination of the polymorphisms for the “optimal” polygenic profile was quantified using the genotype score (GS) and total genotype score (TGS). Results Statistical differences were found in the genetic distributions between professional athletes and the non-athlete population in liver metabolism, iron metabolism and energy efficiency, and muscle performance (p<0.001). The binary logistic regression model showed a favourable OR (odds ratio) of being a professional athlete against a non-athlete in liver metabolism (OR: 1.965; 95% CI: 1.285–3.016; p=0.002), iron metabolism and energy efficiency (OR: 2.213; 95% CI: 1.425-3.438; p<0.001), and muscle performance (OR: 2.700; 95% CI: 1.750-4.165; p<0.001) in the polymorphisms studied. Conclusions Genetic distribution in professional athletes as regards endurance (professional cyclists and elite runners) and professional football players shows genetic selection in these sports disciplines.

Antiangiogenic therapies that target the VEGF pathway have been used clinically to combat cancer for over a decade. Beyond having a direct impact on blood vessel development and tumor perfusion, accumulating evidence indicates that these agents also affect antitumor immune responses. Numerous clinical trials combining antiangiogenic drugs with immunotherapies for the treatment of cancer are ongoing, but a mechanistic understanding of how disruption of tumor angiogenesis may impact immunity is not fully discerned. Here, we reveal that blockade of VEGF-A with a mAb to VEGF augments activation of CD8+ T cells within tumors and potentiates their capacity to produce cytokines. We demonstrate that this phenomenon relies on the disruption of VEGFR2 signaling in the tumor microenvironment but does not affect CD8+ T cells directly. Instead, the augmented functional capacity of CD8+ T cells stems from increased tumor hypoxia that initiates a hypoxia-inducible factor-1α program within CD8+ T cells that directly enhances cytokine production. Finally, combinatorial administration of anti-VEGF with an immunotherapeutic antibody, anti-OX40, improved antitumor activity over single-agent treatments. Our findings illustrate that anti-VEGF treatment enhances CD8+ T-cell effector function and provides a mechanistic rationale for combining antiangiogenic and immunotherapeutic drugs for cancer treatment.