Study of a new airfoil used in reversible axial fans

The characteristics of the reverse ventilation of axial flow are analyzed. An s shaped airfoil with a double circular arc was tested in a wind tunnel. The experimental results showed that the characteristics of this new airfoil in reverse ventilation are the same as those in normal ventilation, and that this airfoil is better than the existing airfoils used on reversible axial fans

Increased levels of soluble CD226 in sera accompanied by decreased membrane CD226 expression on peripheral blood mononuclear cells from cancer patients

<p>Abstract</p> <p>Background</p> <p>As a cellular membrane triggering receptor, CD226 is involved in the NK cell- or CTL-mediated lysis of tumor cells of different origin, including freshly isolated tumor cells and tumor cell lines. Here, we evaluated soluble CD226 (sCD226) levels in sera, and membrane CD226 (mCD226) expression on peripheral blood mononuclear cells (PBMC) from cancer patients as well as normal subjects, and demonstrated the possible function and origin of the altered sCD226, which may provide useful information for understanding the mechanisms of tumor escape and for immunodiagnosis and immunotherapy.</p> <p>Results</p> <p>Soluble CD226 levels in serum samples from cancer patients were significantly higher than those in healthy individuals (<it>P </it>< 0.001), while cancer patients exhibited lower PBMC mCD226 expression than healthy individuals (<it>P </it>< 0.001). CD226-Fc fusion protein could significantly inhibit the cytotoxicity of NK cells against K562 cells in a dose-dependent manner. Furthermore, three kinds of protease inhibitors could notably increase mCD226 expression on PMA-stimulated PBMCs and Jurkat cells with a decrease in the sCD226 level in the cell culture supernatant.</p> <p>Conclusion</p> <p>These findings suggest that sCD226 might be shed from cell membranes by certain proteases, and, further, sCD226 may be used as a predictor for monitoring cancer, and more important, a possible immunotherapy target, which may be useful in clinical application.</p

Transcriptome analysis reveals salt-stress-regulated biological processes and key pathways in roots of cotton (Gossypium hirsutum L.)

AbstractHigh salinity is one of the main factors limiting cotton growth and productivity. The genes that regulate salt stress in TM-1 upland cotton were monitored using microarray and real-time PCR (RT-PCR) with samples taken from roots. Microarray analysis showed that 1503 probe sets were up-regulated and 1490 probe sets were down-regulated in plants exposed for 3h to 100mM NaCl, and RT-PCR analysis validated 42 relevant/related genes. The distribution of enriched gene ontology terms showed such important processes as the response to water stress and pathways of hormone metabolism and signal transduction were induced by the NaCl treatment. Some key regulatory gene families involved in abiotic and biotic sources of stress such as WRKY, ERF, and JAZ were differentially expressed. Our transcriptome analysis might provide some useful insights into salt-mediated signal transduction pathways in cotton and offer a number of candidate genes as potential markers of tolerance to salt stress

The emerging role of DOT1L in cell proliferation and differentiation: Friend or foe

Cell proliferation and differentiation are the basic physiological activities of cells. Mistakes in these processes may affect cell survival, or cause cell cycle dysregulation, such as tumorigenesis, birth defects and degenerative diseases. In recent years, it has been found that histone methyltransferase DOT1L is the only H3 lysine 79 methyltransferase, which plays an important role in the process of cell fate determination through monomethylation, dimethylation and trimethylation of H3K79. DOT1L has a pro-proliferative effect in leukemia cells; however, loss of heart-specific DOT1L leads to increased proliferation of cardiac tissue. Additionally, DOT1L has carcinogenic or tumor suppressive effects in different neoplasms. At present, some DOT1L inhibitors for the treatment of MLL-driven leukemia have achieved promising results in clinical trials, but completely blocking DOT1L will also bring some side effects. Thus, this uncertainty suggests that DOT1L has a unique function in cell physiology. In this review, we summarize the primary findings of DOT1L in regulating cell proliferation and differentiation. Correlations between DOT1L and cell fate specification might suggest DOT1L as a therapeutic target for diseases

Intestinal Mucosal Barrier Is Injured by BMP2/4 via Activation of NF- κ

Intestinal ischemic reperfusion (I/R) can cause dysfunction of the intestinal mucosal barrier; however, the mechanism of the intestinal mucosal barrier dysfunction caused by I/R remains unclear. In this study, using intestinal epithelial cells under anaerobic cultivation and an in vivo rat intestinal I/R model, we found that hypoxia and I/R increased the expression of BMP2/4 and upregulated BMP type Ia receptor and BMP type II receptor expression. We also found that exogenous BMP2/4 can activate the ERK and AKT signaling pathways in rat small intestine (IEC-6) cells, thereby activating NF-κB signaling, which leads to increased levels of inflammatory factors, such as TNF-α and IL-6. Furthermore, recombinant BMP2/4 decreased the expression of the tight junction protein occludin via the activation of the NF-κB pathway; these effects were abolished by treatment with the BMP-specific antagonist noggin or the NF-κB inhibitor pyrrolidine dithiocarbamate (PDTC). All these factors can destroy the intestinal mucosal barrier, thereby leading to weaker barrier function. On the basis of these data, we conclude that BMP2/4 may act as the pathogenic basis for intestinal mucosal barrier dysfunction when the intestines suffer an I/R injury. Our results provide background for the development pharmacologic interventions in the management of I/R injury

Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

We introduce Generalized Instruction Tuning (called GLAN), a general and scalable method for instruction tuning of Large Language Models (LLMs). Unlike prior work that relies on seed examples or existing datasets to construct instruction tuning data, GLAN exclusively utilizes a pre-curated taxonomy of human knowledge and capabilities as input and generates large-scale synthetic instruction data across all disciplines. Specifically, inspired by the systematic structure in human education system, we build the taxonomy by decomposing human knowledge and capabilities to various fields, sub-fields and ultimately, distinct disciplines semi-automatically, facilitated by LLMs. Subsequently, we generate a comprehensive list of subjects for every discipline and proceed to design a syllabus tailored to each subject, again utilizing LLMs. With the fine-grained key concepts detailed in every class session of the syllabus, we are able to generate diverse instructions with a broad coverage across the entire spectrum of human knowledge and skills. Extensive experiments on large language models (e.g., Mistral) demonstrate that GLAN excels in multiple dimensions from mathematical reasoning, coding, academic exams, logical reasoning to general instruction following without using task-specific training data of these tasks. In addition, GLAN allows for easy customization and new fields or skills can be added by simply incorporating a new node into our taxonomy.Comment: Work in progres

The Paf1 complex transcriptionally regulates the mitochondrial-anchored protein Atg32 leading to activation of mitophagy

Mitophagy is a critical process that safeguards mitochondrial quality control in order to maintain proper cellular homeostasis. Although the mitochondrial-anchored receptor Atg32-mediated cargo-recognition system has been well characterized to be essential for this process, the signaling pathway modulating its expression as a contribution of governing the mitophagy process remains largely unknown. Here, bioinformatics analyses of epigenetic or transcriptional regulators modulating gene expression allow us to identify the Paf1 complex (the polymerase-associated factor 1 complex, Paf1C,) as a transcriptional repressor of ATG genes. We show that Paf1C suppresses glucose starvation-induced autophagy, but does not affect nitrogen starvation- or rapamycin-induced autophagy. Moreover, we show that Paf1C specifically regulates mitophagy through modulating ATG32 expression. Deletion of the genes encoding two core subunits of Paf1C, Paf1 and Ctr9, increases ATG32 and ATG11 expression and facilitates mitophagy activity. Although Paf1C is required for many histone modifications and gene activation, we show that Paf1C regulates mitophagy independent of its positive regulatory role in other processes. More importantly, we also demonstrate the mitophagic role of PAF1C in mammals. Overall, we conclude that Paf1C maintains mitophagy at a low level through binding the promoter of the ATG32 gene in glucose-rich conditions. Dissociation of Paf1C from ATG32 leads to the increased expression of this gene, and mitophagy induction upon glucose starvation. Thus, we uncover a new role of Paf1C in modulating the mitophagy process at the transcriptional level

Detection and localization of citrus fruit based on improved You Only Look Once v5s and binocular vision in the orchard

Intelligent detection and localization of mature citrus fruits is a critical challenge in developing an automatic harvesting robot. Variable illumination conditions and different occlusion states are some of the essential issues that must be addressed for the accurate detection and localization of citrus in the orchard environment. In this paper, a novel method for the detection and localization of mature citrus using improved You Only Look Once (YOLO) v5s with binocular vision is proposed. First, a new loss function (polarity binary cross-entropy with logit loss) for YOLO v5s is designed to calculate the loss value of class probability and objectness score, so that a large penalty for false and missing detection is applied during the training process. Second, to recover the missing depth information caused by randomly overlapping background participants, Cr-Cb chromatic mapping, the Otsu thresholding algorithm, and morphological processing are successively used to extract the complete shape of the citrus, and the kriging method is applied to obtain the best linear unbiased estimator for the missing depth value. Finally, the citrus spatial position and posture information are obtained according to the camera imaging model and the geometric features of the citrus. The experimental results show that the recall rates of citrus detection under non-uniform illumination conditions, weak illumination, and well illumination are 99.55%, 98.47%, and 98.48%, respectively, approximately 2–9% higher than those of the original YOLO v5s network. The average error of the distance between the citrus fruit and the camera is 3.98 mm, and the average errors of the citrus diameters in the 3D direction are less than 2.75 mm. The average detection time per frame is 78.96 ms. The results indicate that our method can detect and localize citrus fruits in the complex environment of orchards with high accuracy and speed. Our dataset and codes are available at https://github.com/AshesBen/citrus-detection-localization

Efficient and accurate greedy search methods for mining functional modules in protein interaction networks

<p>Abstract</p> <p>Background</p> <p>Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures.</p> <p>Methods</p> <p>In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules.</p> <p>Results</p> <p>The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms.</p> <p>Conclusions</p> <p>Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.</p