The effect of conditional EFNB1 deletion in the T cell compartment on T cell development and function

<p>Abstract</p> <p>Background</p> <p>Eph kinases are the largest family of cell surface receptor tyrosine kinases. The ligands of Ephs, ephrins (EFNs), are also cell surface molecules. Ephs interact with EFNs transmitting signals in both directions, i.e., from Ephs to EFNs and from EFNs to Ephs. EFNB1 is known to be able to co-stimulate T cells <it>in vitro </it>and to modulate thymocyte development in a model of foetal thymus organ culture. To further understand the role of EFNB1 in T cell immunity, we generated T-cell-specific EFNB1 gene knockout mice to assess T cell development and function in these mice.</p> <p>Results</p> <p>The mice were of normal size and cellularity in the thymus and spleen and had normal T cell subpopulations in these organs. The bone marrow progenitors from KO mice and WT control mice repopulated host spleen T cell pool to similar extents. The activation and proliferation of KO T cells was comparable to that of control mice. Naïve KO CD4 cells showed an ability to differentiate into Th1, Th2, Th17 and Treg cells similar to control CD4 cells.</p> <p>Conclusions</p> <p>Our results suggest that the function of EFNB1 in the T cell compartment could be compensated by other members of the EFN family, and that such redundancy safeguards the pivotal roles of EFNB1 in T cell development and function.</p

AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Can we better anticipate an actor's future actions (e.g. mix eggs) by knowing what commonly happens after his/her current action (e.g. crack eggs)? What if we also know the longer-term goal of the actor (e.g. making egg fried rice)? The long-term action anticipation (LTA) task aims to predict an actor's future behavior from video observations in the form of verb and noun sequences, and it is crucial for human-machine interaction. We propose to formulate the LTA task from two perspectives: a bottom-up approach that predicts the next actions autoregressively by modeling temporal dynamics; and a top-down approach that infers the goal of the actor and plans the needed procedure to accomplish the goal. We hypothesize that large language models (LLMs), which have been pretrained on procedure text data (e.g. recipes, how-tos), have the potential to help LTA from both perspectives. It can help provide the prior knowledge on the possible next actions, and infer the goal given the observed part of a procedure, respectively. To leverage the LLMs, we propose a two-stage framework, AntGPT. It first recognizes the actions already performed in the observed videos and then asks an LLM to predict the future actions via conditioned generation, or to infer the goal and plan the whole procedure by chain-of-thought prompting. Empirical results on the Ego4D LTA v1 and v2 benchmarks, EPIC-Kitchens-55, as well as EGTEA GAZE+ demonstrate the effectiveness of our proposed approach. AntGPT achieves state-of-the-art performance on all above benchmarks, and can successfully infer the goal and thus perform goal-conditioned "counterfactual" prediction via qualitative analysis. Code and model will be released at https://brown-palm.github.io/AntGP

Optimization of Extraction Process of Elaeagnus angustifolia Flower Polysaccharide and Its Proliferation on Probiotic

The study aimed to explore the optimal conditions for the extraction of polysaccharide from Elaeagnus angustifolia flower and its effect on probiotic proliferation in vitro. Polysaccharide was extracted from Elaeagnus angustifolia flower using hot water and ultrasonication. The effects of the material-liquid ratio, duration of ultrasonication, extraction time and extraction temperature on the polysaccharide yield were analyzed. The extraction conditions were optimized by response surface methodology, and the effects of different polysaccharide concentrations (0, 0.5%, 1.0%, 1.5%, 2.0%, and 3.0%) on the proliferation and acid production of three probiotics were compared. The results showed that the optimal extraction conditions of Elaeagnus angustifolia flower polysaccharide were as follows: Material-liquid ratio, 1:25 g/mL, duration of ultrasonication, 21 min, extraction temperature, 72℃, extraction time, 62 min. The polysaccharide yield was 12.45%±0.15%, which was close to the theoretical predicted yield (12.587%). The highest OD values of Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium adolescentis were obtained at a polysaccharide mass concentration of 2%, being 1.23±0.01, 1.06±0.02, and 1.22±0.02, respectively, and the lowest pH values (5.17±0.04, 5.95±0.04, and 5.52±0.02, respectively). The growth of the three probiotics stabilized after the incubation time reached to 40 h. It indicated that Elaeagnus angustifolia flower polysaccharide promoted the proliferation and acid production of three probiotics. These findings indicate the potential of the polysaccharide from Elaeagnus angustifolia flower as a prebiotic and provide a theoretical basis for further research and the utilization of Elaeagnus angustifolia flower resources

miRNA profiling in intrauterine exosomes of pregnant cattle on day 7

Intrauterine exosomes have been identified to be involved in the embryo development and implantation. The aim of this study was to explore the role of miRNAs in intrauterine exosomes in bovine pregnancy. Intrauterine exosomes were collected from uterine flushing fluids of three donor and three recipient Xianan cows 7 days after fertilization. Intrauterine exosomes miRNAs were extracted and the exosomal miRNAs expression levels were analyzed. Sixty miRNAs differed significantly in their amounts between donors and recipients (p-value 1). Twenty-two miRNAs were upregulated and 38 downregulated in the group of donor cows. The bta-miR-184 was the most significant (PBenjamini-Hochberg < 0.001). A total of 9,775 target genes were predicted using the 60 miRNAs. GO and KEGG analysis showed that the target genes were enriched in several biological processes or pathways associated with embryo implantation and endometrial development, such as cell adhesion, cell junction, focal adhesion, and Rap1 signaling pathway. Our findings suggest that, in cattle early pregnancy stage, these differently expressed miRNAs in intrauterine exosomes involved in embryo implantation and endometrial development, which may exert a significant effect and influence the uterine microenvironment for embryo implantation. These results could provide reference for screening and exploring the intrauterine exosomal miRNA affecting embryo implantation