Enhancing source code classification effectiveness via prompt learning incorporating knowledge features.

Researchers have investigated the potential of leveraging pre-trained language models, such as CodeBERT, to enhance source code-related tasks. Previous methodologies have relied on CodeBERT's '[CLS]' token as the embedding representation of input sequences for task performance, necessitating additional neural network layers to enhance feature representation, which in turn increases computational expenses. These approaches have also failed to fully leverage the comprehensive knowledge inherent within the source code and its associated text, potentially limiting classification efficacy. We propose CodeClassPrompt, a text classification technique that harnesses prompt learning to extract rich knowledge associated with input sequences from pre-trained models, thereby eliminating the need for additional layers and lowering computational costs. By applying an attention mechanism, we synthesize multi-layered knowledge into task-specific features, enhancing classification accuracy. Our comprehensive experimentation across four distinct source code-related tasks reveals that CodeClassPrompt achieves competitive performance while significantly reducing computational overhead.

PENG ZU Study on Healthy Aging in China (PENG ZU Cohort): Design and Goals.

Life expectancy is increasing, leading to the continuous aging of the population in China. Enhancing the health status of the older population is crucial to achieving healthy aging. The primary objective of the PENG ZU Study on Healthy Aging in China (PENG ZU Cohort) is to understand the natural progression of health status among the aging Chinese population. Specifically, the PENG ZU cohort aims to identify and validate multidimensional aging markers, uncover the underlying mechanisms of systemic aging and functional decline, and develop novel strategies and measures to delay functional decline and adverse health outcomes, while maintaining overall good health. The PENG ZU cohort consists of 26,000 individuals aged 25 to 89 years from seven major geographical regions in China. Diversified data and biospecimens are collected according to standardized procedures at baseline and follow-up visits. Baseline recruitment for the PENG ZU cohort was completed in October 2021. The extensive analysis of multidimensional health-related data and bioresources collected from the cohort is anticipated to develop methods for evaluating functional status and elucidating multilevel, cross-scale interactions and regulatory mechanisms of healthy aging. The findings from this study will enhance the understanding of health changes due to aging, facilitate efficient and effective interventions to maintain functional ability, and reduce the incidence and severity of age-related diseases, thereby further promoting healthy aging.

Dual Regulation Mechanism of Obesity: DNA Methylation and Intestinal Flora.

Obesity is a multifactorial chronic inflammatory metabolic disorder, with pathogenesis influenced by genetic and non-genetic factors such as environment and diet. Intestinal microbes and their metabolites play significant roles in the occurrence and development of obesity by regulating energy metabolism, inducing chronic inflammation, and impacting intestinal hormone secretion. Epigenetics, which involves the regulation of host gene expression without changing the nucleotide sequence, provides an exact direction for us to understand how the environment, lifestyle factors, and other risk factors contribute to obesity. DNA methylation, as the most common epigenetic modification, is involved in the pathogenesis of various metabolic diseases. The epigenetic modification of the host is induced or regulated by the intestinal microbiota and their metabolites, linking the dynamic interaction between the microbiota and the host genome. In this review, we examined recent advancements in research, focusing on the involvement of intestinal microbiota and DNA methylation in the etiology and progression of obesity, as well as potential interactions between the two factors, providing novel perspectives and avenues for further elucidating the pathogenesis, prevention, and treatment of obesity.

Stress transfer law in laboratory hydraulic fracturing experiments.

During the true triaxial hydraulic fracturing experiments, the compression stress applied to the specimen surface cannot be transferred to the interior immediately, resulting in inconsistency with in-situ stress conditions. To quantitatively analyze the stress transfer process from the surface to the interior of the specimen, an experimental method for monitoring the inside stress was proposed based on Fiber Bragg Grating (FBG) sensing technique, based on which the true triaxial stress loading experiments were conducted on a concrete-like specimen of 30 cm × 30 cm × 30 cm. The results show that the stresses inside the specimen require a certain loading time to reach the uniform state. The loading time required for stress transfer from the surface to the interior of the specimen decreases with the increase of compression stresses. The stress transfer process in rock materials is determined by creep. The closure of microcracks results in stress redistribution inside the specimen during creep. Moreover, a 3-D Burgers model is modified to describe the stress transfer process. Finally, the stress transfer phenomenon during hydraulic fracturing was verified by coal fracturing experiments. This study can help to understand the stress transfer mechanism, providing guidance for standardizing the laboratory simulation of in-situ stress.

Role of NLRP3 inflammasome in central nervous system diseases.

The central nervous system (CNS) is the most delicate system in human body, with the most complex structure and function. It is vulnerable to trauma, infection, neurodegeneration and autoimmune diseases, and activates the immune system. An appropriate inflammatory response contributes to defence against invading microbes, whereas an excessive inflammatory response can aggravate tissue damage. The NLRP3 inflammasome was the first one studied in the brain. Once primed and activated, it completes the assembly of inflammasome (sensor NLRP3, adaptor ASC, and effector caspase-1), leading to caspase-1 activation and increased release of downstream inflammatory cytokines, as well as to pyroptosis. Cumulative studies have confirmed that NLRP3 plays an important role in regulating innate immunity and autoimmune diseases, and its inhibitors have shown good efficacy in animal models of various inflammatory diseases. In this review, we will briefly discuss the biological characteristics of NLRP3 inflammasome, summarize the recent advances and clinical impact of the NLRP3 inflammasome in infectious, inflammatory, immune, degenerative, genetic, and vascular diseases of CNS, and discuss the potential and challenges of NLRP3 as a therapeutic target for CNS diseases.

Microbial contribution to 14 biogenic amines accumulation in refrigerated raw and deep-fried hairtails (Trichiurus lepturus).

Biogenic amines (BAs) produced by microbial decarboxylation of amino acids are crucial toxic nitrogenous compounds in fish. An optimized ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method with simple pretreatment was established to detect 14 BAs in both raw (control check, CK) and deep-fried (DF) hairtails. This method exhibited a good linear relationship with average recoveries of 73.3-120.0 % and relative standard deviations of 2.5-10.0 %, respectively. The total BAs in CK and DF hairtails decreased sharply to 338.2 and 25.3 mg/kg on the 9th day, respectively. Four BAs, including cadaverine (CAD), histamine (HIS), tyramine (TYR), and putrescine (PUT) accounted for 92.5-99.9 % of total BAs were selected as the dominant BAs. Bacterial analysis showed that the abundance of DF was relatively low. Further correlation analysis proved that Vibrio had a significant (p < 0.05) positive correlation with total BAs and could be the main BA-producing bacterium in DF hairtail. This work provides new evidence of the accumulation of BAs in refrigerated hairtail.

Inpainting with Separable Mask Update Convolution Network.

Image inpainting is an active area of research in image processing that focuses on reconstructing damaged or missing parts of an image. The advent of deep learning has greatly advanced the field of image restoration in recent years. While there are many existing methods that can produce high-quality restoration results, they often struggle when dealing with images that have large missing areas, resulting in blurry and artifact-filled outcomes. This is primarily because of the presence of invalid information in the inpainting region, which interferes with the inpainting process. To tackle this challenge, the paper proposes a novel approach called separable mask update convolution. This technique automatically learns and updates the mask, which represents the missing area, to better control the influence of invalid information within the mask area on the restoration results. Furthermore, this convolution method reduces the number of network parameters and the size of the model. The paper also introduces a regional normalization technique that collaborates with separable mask update convolution layers for improved feature extraction, thereby enhancing the quality of the restored image. Experimental results demonstrate that the proposed method performs well in restoring images with large missing areas and outperforms state-of-the-art image inpainting methods significantly in terms of image quality.

Therapeutic potential of MSCs and MSC-derived extracellular vesicles in immune thrombocytopenia.

Immune thrombocytopenia (ITP) is an acquired autoimmune disease involving a variety of immune cells and factors. Despite being a benign disease, it is still considered incurable due to its complex pathogenesis. Mesenchymal stem cells (MSCs), with low immunogenicity, pluripotent differentiation, and immunomodulatory ability, are widely used in a variety of autoimmune diseases. In recent years, impaired bone marrow mesenchymal stem cells (BMMSCs) were found to play an important role in the pathogenesis of ITP; and the therapeutic role of MSCs in ITP has also been supported by increasing evidence with encouraging efficacy. MSCs hold promise as a new approach to treat or even cure refractory ITP. Extracellular vesicles (EVs), as novel carriers in the "paracrine" mechanism of MSCs, are the focus of MSCs. Encouragingly, several studies suggested that EVs may perform similar functions as MSCs to treat ITP. This review summarized the role of MSCs in the pathophysiology and treatment of ITP.

MSC-EVs transferring mitochondria and related components: A new hope for the treatment of kidney disease.

Kidney disease is a serious hazard to human health. Acute or chronic renal disease will have a significant negative impact on the body's metabolism. The involvement of mitochondria in renal illness has received a lot of interest as research on kidney disease has advanced. Extracellular vesicles are gaining popularity as a means of intercellular communication in recent years. They have a close connection to both the nephropathy process and the intercellular transfer of mitochondria. The goal of this review is to present the extracellular vesicle transport mitochondria and its related biologically active molecules as new therapeutic options for the treatment of clinical kidney disease. This review focuses on the extracellular vesicles through the transfer of mitochondria and its related bioactive molecules, which affect mitochondrial energy metabolism, take part in immune regulation, and secrete outside the body.

Oral Realgar-Indigo Naturalis Formula Treatment for Acute Promyelocytic Leukemia in Children: A Randomized, Control Clinical Trial.

Objective: To analyze the efficacy, safety, and economy of RIF compared with intravenous arsenic trioxide (ATO) for the induction and consolidation therapy of pediatric APL. Materials and Methods: In this randomized control clinical trial (NCT02200978), children with newly diagnosed APL from June 2013 to December 2017 were randomly divided into RIF and ATO groups. The groups were treated with RIF or ATO in combination with all-trans retinoic acid (ARTA) and conventional chemotherapeutic drugs during induction and consolidation therapy. Results: Ninteen patients were enrolled, including eight in the RIF group and 11 in the ATO group. After induction therapy, the bone marrow morphologic complete remission (CR) rate, the median time to CR, and molecular remission (promyelocytic leukemia protein (PML)/retinoic acid receptor α (RARα) conversion) rates showed no significant differences between patients in the RIF versus ATO groups (100% vs. 100%, p=1.000; 22 vs. 24 days, p=0.395; 28.5% vs. 54.5%, p=0.367, resp.). After consolidation therapy, the molecular remission rate was 100% in both groups. At the end of more than two years of follow-up, the disease-free survival (DFS) rate was 100% in both groups. Conclusion: Oral RIF can achieve similar efficacy to intravenous ATO for APL in children with good safety, less toxicity, fewer side effects, and fewer inpatient days. Therefore, oral RIF can be used as an alternative to intravenous ATO for the treatment of APL in children.

Human umbilical cord mesenchymal stem cells derived extracellular vesicles regulate acquired immune response of lupus mouse in vitro.

Systemic lupus erythematosus (SLE) is an autoimmune disease involving multiple systems. Immunopathology believes that abnormal T cell function and excessive production of autoantibodies by B cells are involved in multi-organ damage. Human umbilical cord mesenchymal stem cells (hUCMSCs) therapies have endowed with promise in SLE, while the function of MSC-derived extracellular vesicles (MSC-EVs) was still unclear. Extracellular vesicles (EVs) are subcellular components secreted by a paracellular mechanism and are essentially a group of nanoparticles. EVs play a vital role in cell-to-cell communication by acting as biological transporters. New evidence has shown beneficial effects of MSC-EVs on autoimmune diseases, such as their immunomodulatory properties. In this study, we investigated whether hUCMSCs derived extracellular vesicles (hUCMSC-EVs) could regulate abnormal immune responses of T cells or B cells in SLE. We isolated splenic mononuclear cells from MRL/lpr mice, a classical animal model of SLE. PBS (Phosphate-buffered saline), 2 × 105 hUCMSCs, 25 µg/ml hUCMSC-EVs, 50 µg/ml hUCMSC-EVs were co-cultured with 2 × 106 activated splenic mononuclear cells for 3 days in vitro, respectively. The proportions of CD4+ T cell subsets, B cells and the concentrations of cytokines were detected. Both hUCMSCs and hUCMSC-EVs inhibited CD4+ T cells, increased the production of T helper (Th)17 cells, promoted the production of interleukin (IL)-17 and transforming growth factor beta1 (TGF-ß1) (P < 0.05), although they had no significant effects on Th1, Th2, T follicular helper (Tfh), regulatory T (Treg) cells and IL-10 (P > 0.05); only hUCMSCs inhibited CD19+ B cells, promoted the production of interferon-gamma (IFN-γ) and IL-4 (P < 0.05). hUCMSCs exert immunoregulatory effects on SLE at least partially through hUCMSC-EVs in vitro, therefore, hUCMSC-EVs play novel and potential regulator roles in SLE.

Rule extraction from biased random forest and fuzzy support vector machine for early diagnosis of diabetes.

Due to concealed initial symptoms, many diabetic patients are not diagnosed in time, which delays treatment. Machine learning methods have been applied to increase the diagnosis rate, but most of them are black boxes lacking interpretability. Rule extraction is usually used to turn on the black box. As the number of diabetic patients is far less than that of healthy people, the rules obtained by the existing rule extraction methods tend to identify healthy people rather than diabetic patients. To address the problem, a method for extracting reduced rules based on biased random forest and fuzzy support vector machine is proposed. Biased random forest uses the k-nearest neighbor (k-NN) algorithm to identify critical samples and generates more trees that tend to diagnose diabetes based on critical samples to improve the tendency of the generated rules for diabetic patients. In addition, the conditions and rules are reduced based on the error rate and coverage rate to enhance interpretability. Experiments on the Diabetes Medical Examination Data collected by Beijing Hospital (DMED-BH) dataset demonstrate that the proposed approach has outstanding results (MCC = 0.8802) when the rules are similar in number. Moreover, experiments on the Pima Indian Diabetes (PID) and China Health and Nutrition Survey (CHNS) datasets prove the generalization of the proposed method.

The Role of B1 Cells in Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by multisystemic and multi-organ involvement, recurrent relapses and remissions, and the presence of large amounts of autoantibodies in the body as the main clinical features. The mechanisms involved in this disease are complex and remain poorly understood; however, they are generally believed to be related to genetic susceptibility factors, external stimulation of the body's immune dysfunction, and impaired immune regulation. The main immune disorders include the imbalance of T lymphocyte subsets, hyperfunction of B cells, production of large amounts of autoantibodies, and further deposition of immune complexes, which result in tissue damage. Among these, B cells play a major role as antibody-producing cells and have been studied extensively. B1 cells are a group of important innate-like immune cells, which participate in various innate and autoimmune processes. Yet the role of B1 cells in SLE remains unclear. In this review, we focus on the mechanism of B1 cells in SLE to provide new directions to explore the pathogenesis and treatment modalities of SLE.

Numerical simulation study on the crack propagation of conglomerate.

The conglomerate reservoir is rich in oil and gas reserves; however, the gravel's mechanical properties and laws are difficult to gain through laboratory experiments, which furthermore constrain the hydraulic fracturing design. To analyse the failure law of conglomerate, we simulated the uniaxial compression test based on discrete element software PFC2D and analysed the effect of different cementation strength, gravel content and gravel geometry on the rock deformation and failure characteristics. Results show that (i) as the cementation strength decreases, the compressive strength and elasticity modulus both reduce clearly, while the crack shapes get more complex and the critical value is 0.3; (ii) as the gravel content increases, the conglomerate strength first decreases then increases under the influences of cracks bypassing gravels; cementation strength and gravel content of the conglomerate both contribute to the increase in local additional stress, which leads to a series of changes in crack shapes and mechanical properties of the conglomerate. Based on the above research, the conglomerate strength and crack shapes after failure are relatively complex due to the common influence of cementation strength and gravel content. The gravel edge crack caused by stress concentration is the micro-mechanism that affects the conglomerate mechanical properties.

Management and Clinical Outcome of Posterior Reversible Encephalopathy Syndrome in Pediatric Oncologic/Hematologic Diseases: A PRES Subgroup Analysis With a Large Sample Size.

This study investigated the management and clinical outcomes along with associated factors of posterior reversible encephalopathy syndrome (PRES) in childhood hematologic/oncologic diseases. We present data from children with hematologic/oncologic diseases who developed PRES after treatment of the primary disease with chemotherapy and hematopoietic stem cell transplantation (HSCT) at 3 medical centers in Changsha, China from 2015 to 2020, and review all previously reported cases with the aim of determining whether this neurologic manifestation affects the disease prognosis. In the clinical cohort of 58 PRES patients, hypertension [pooled odds ratio (OR) = 4.941, 95% confidence interval (CI): 1.390, 17.570; P = 0.001] and blood transfusion (OR = 14.259, 95% CI: 3.273, 62.131; P = 0.001) were significantly associated with PRES. Elevated platelet (OR = 0.988, 95% CI: 0.982, 0.995; P < 0.001), hemoglobin (OR = 0.924, 95% CI: 0.890, 0.995; P < 0.001), and blood sodium (OR = 0.905, 95% CI: 0.860, 0.953; P < 0.001), potassium (OR = 0.599, 95% CI: 0.360, 0.995; P = 0.048), and magnesium (OR = 0.093, 95% CI: 0.016, 0.539; P = 0.008) were protective factors against PRES. Data for 440 pediatric PRES patients with hematologic/oncologic diseases in 21 articles retrieved from PubMed, Web of Science, and Embase databases and the 20 PRES patients from our study were analyzed. The median age at presentation was 7.9 years. The most common primary diagnosis was leukemia (62.3%), followed by solid tumor (7.7%) and lymphoma (7.5%). Most patients (65.0%) received chemotherapy, including non-induction (55.2%) and induction (44.8%) regimens; and 86.5% used corticosteroids before the onset of PRES. Although 21.0% of patients died during follow-up, in most cases (93.2%) this was not attributable to PRES but to severe infection (27.3%), underlying disease (26.1%), graft-vs.-host disease (14.8%), multiple organ dysfunction syndrome (8.0%), and respiratory failure (3.4%). PRES was more common with HSCT compared to chemotherapy and had a nearly 2 times higher mortality rate in patients with oncologic/hematologic diseases than in those with other types of disease. Monitoring neurologic signs and symptoms in the former group is therefore critical for ensuring good clinical outcomes following treatment of the primary malignancy.

Natural Killer Cell-Derived Extracellular Vesicles: Novel Players in Cancer Immunotherapy.

Natural killer (NK) cells are critical components of host innate immunity and function as the first line of defense against tumors and viral infection. There is increasing evidence that extracellular vesicles (EVs) are involved in the antitumor activity of NK cells. NK cell-derived EVs (NKEVs) carrying cargo such as cytotoxic proteins, microRNAs, and cytokines employ multiple mechanisms to kill tumor cells, but also exhibit immunomodulatory activity by stimulating other immune cells. Several studies have reported that NKEVs can reverse immune suppression under tolerogenic conditions and contribute to NK-mediated immune surveillance against tumors. Thus, NKEVs are a promising tool for cancer immunotherapy. In this review, we describe the biological effects and potential applications of NKEVs in antitumor immunity.

Self-selective attention using correlation between instances for distant supervision relation extraction.

Distant supervision relation extraction methods are widely used to extract relational facts in text. The traditional selective attention model regards instances in the bag as independent of each other, which makes insufficient use of correlation information between instances and supervision information of all correctly labeled instances, affecting the performance of relation extractor. Aiming at this problem, a distant supervision relation extraction method with self-selective attention is proposed. The method uses a layer of convolution and self-attention mechanism to encode instances to learn the better semantic vector representation of instances. The correlation between instances in the bag is used to assign a higher weight to all correctly labeled instances, and the weighted summation of instances in the bag is used to obtain a bag vector representation. Experiments on the NYT dataset show that the method can make full use of the information of all correctly labeled instances in the bag. The method can achieve better results as compared with baselines.

Deep supervised learning with mixture of neural networks.

Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single model to perform well on the classification tasks. In this paper, we propose mixture model based on DNNs (MoNNs), a supervised approach to perform classification tasks with a gating network and multiple local expert models. We use a neural network as a gating function and use DNNs as local expert models. The gating network split the heterogeneous data into several homogeneous components. DNNs are combined to perform classification tasks in each component. Moreover, we use EM (Expectation Maximization) as an optimization algorithm. Experiments proved that our MoNNs outperformed the other compared methods on determination of diabetes, determination of benign or malignant breast cancer, and handwriting recognition. Therefore, the MoNNs can solve the problem of data heterogeneity and have a good effect on classification tasks.

Immunoregulatory Effects of Mitochondria Transferred by Extracellular Vesicles.

Mitochondria participate in immune regulation through various mechanisms, such as changes in the mitochondrial dynamics, as metabolic mediators of the tricarboxylic acid cycle, by the production of reactive oxygen species, and mitochondrial DNA damage, among others. In recent years, studies have shown that extracellular vesicles are widely involved in intercellular communication and exert important effects on immune regulation. Recently, the immunoregulatory effects of mitochondria from extracellular vesicles have gained increasing attention. In this article, we review the mechanisms by which mitochondria participate in immune regulation and exert immunoregulatory effects upon delivery by extracellular vesicles. We also focus on the influence of the immunoregulatory effects of mitochondria from extracellular vesicles to further shed light on the underlying mechanisms.