Balanced Audiovisual Dataset for Imbalance Analysis

The imbalance problem is widespread in the field of machine learning, which also exists in multimodal learning areas caused by the intrinsic discrepancy between modalities of samples. Recent works have attempted to solve the modality imbalance problem from algorithm perspective, however, they do not fully analyze the influence of modality bias in datasets. Concretely, existing multimodal datasets are usually collected under specific tasks, where one modality tends to perform better than other ones in most conditions. In this work, to comprehensively explore the influence of modality bias, we first split existing datasets into different subsets by estimating sample-wise modality discrepancy. We surprisingly find that: the multimodal models with existing imbalance algorithms consistently perform worse than the unimodal one on specific subsets, in accordance with the modality bias. To further explore the influence of modality bias and analyze the effectiveness of existing imbalance algorithms, we build a balanced audiovisual dataset, with uniformly distributed modality discrepancy over the whole dataset. We then conduct extensive experiments to re-evaluate existing imbalance algorithms and draw some interesting findings: existing algorithms only provide a compromise between modalities and suffer from the large modality discrepancy of samples. We hope that these findings could facilitate future research on the modality imbalance problem.Comment: website:https://gewu-lab.github.io/Balanced-Audiovisual-Dataset

LBH589 Enhances T Cell Activation In Vivo and Accelerates Graft-versus-Host Disease in Mice

Histone deacetylase inhibitors (HDACis) are a new class of compounds that induce acetylation of histone lysine tails in chromatin and modify gene expression. The Food & Drug Administration approved HDACi, Vorinostat, or suberoylanilide hydroxamic acid (SAHA), has been shown to inhibit tumor cell growth and the production of proinflammatory cytokines. In preclinical allogeneic transplant models, SAHA induces graft-versus-host disease (GVHD) amelioration in treated mice without impairing graft-versus-leukemia. LBH589 (Panobinostat), a structurally novel cinnamic hydroxamic acid class, is an HDACi more potent than SAHA. In the current work, we tested the hypothesis that LBH589 would be highly effective in the prevention of GVHD. Using mouse model of allogeneic bone marrow transplant (BMT), we unexpectedly found that treatment with LBH589 accelerated GVHD, in contrast to the treatment with SAHA that alleviated GVHD. Accelerated GVHD in the recipients treated with LBH589 was associated with elevated Th1 cytokines in recipient serum, enhanced CXCR3 expression on donor T cells, and T cell infiltration in the liver. The current study highlights the distinct effects of pan HDACi on allogeneic BMT and alerts that LBH589 (Panobinostat) could have an adverse effect on GVHD, and possibly on other inflammatory diseases

β-AR Blockers Suppresses ER Stress in Cardiac Hypertrophy and Heart Failure

Long-term β-adrenergic receptor (β-AR) blockade reduces mortality in patients with heart failure. Chronic sympathetic hyperactivity in heart failure causes sustained β-AR activation, and this can deplete Ca(2+) in endoplasmic reticulum (ER) leading to ER stress and subsequent apoptosis. We tested the effect of β-AR blockers on ER stress pathway in experimental model of heart failure.ER chaperones were markedly increased in failing hearts of patients with end-stage heart failure. In Sprague-Dawley rats, cardiac hypertrophy and heart failure was induced by abdominal aortic constriction or isoproterenol subcutaneous injection. Oral β-AR blockers treatment was performed in therapy groups. Cardiac remodeling and left ventricular function were analyzed in rats failing hearts. After 4 or 8 weeks of banding, rats developed cardiac hypertrophy and failure. Cardiac expression of ER chaperones was significantly increased. Similar to the findings above, sustained isoproterenol infusion for 2 weeks induced cardiac hypertrophy and failure with increased ER chaperones and apoptosis in hearts. β-AR blockers treatment markedly attenuated these pathological changes and reduced ER stress and apoptosis in failing hearts. On the other hand, β-AR agonist isoproterenol induced ER stress and apoptosis in cultured cardiomyocytes. β-AR blockers largely prevented ER stress and protected myocytes against apoptosis. And β-AR blockade significantly suppressed the overactivation of CaMKII in isoproterenol-stimulated cardiomyocytes and failing hearts in rats.Our results demonstrated that ER stress occurred in failing hearts and this could be reversed by β-AR blockade. Alleviation of ER stress may be an important mechanism underlying the therapeutic effect of β-AR blockers on heart failure

A New Adversarial Domain Generalization Network Based on Class Boundary Feature Detection for Bearing Fault Diagnosis

In recent years, many researchers have attempted to achieve cross-domain diagnosis of faults through domain adaptation (DA) methods. However, owing to the complex physical environments, applications of DA-based approach are not guaranteed to unknown operating environments. Some existing domain generalization (DG) methods require enough fully labeled source domains to train, which are often unavailable in practical settings. In this study, an adversarial domain generalization network (ADGN) based on class boundary feature detection is proposed. The ADGN can diagnose faults in unknown operating environments, and only one fully labeled domain is used in training. Although ADGN has to access fully unlabeled auxiliary domains, a large number of unlabeled samples exist under actual working conditions. In our method, fuzzy features at a classification boundary are detected by maximizing the classifier differences. Better feature mapping functions and domain-invariant features are obtained by adversarial training. As the training proceeds, the differences in the distribution of features among the source, auxiliary, and unknown domains become smaller so domain-invariant features can be used for fault diagnosis in unknown operating environments. Comprehensive experiments showed that ADGN can achieve higher fault diagnosis accuracies than other methods when only one fully labeled domain is used in an unknown operating environment. The ADGN can even cope comfortably with complex transfer tasks with different speeds and loads

Effects of Casein, Chicken, and Pork Proteins on the Regulation of Body Fat and Blood Inflammatory Factors and Metabolite Patterns Are Largely Dependent on the Protein Level and Less Attributable to the Protein Source

The impact of meat protein on metabolic regulation is still disputed and may be influenced by protein level. This study aimed to explore the effects of casein, pork, and chicken proteins at different protein levels (40% E vs 20% E) on body weight regulation, body fat accumulation, serum hormone levels, and inflammatory factors/metabolites in rats maintained on high-fat (45% E fat) diets for 84 d. Increased protein levels resulted in a significant reduction in body fat mass and an increase in the serum levels of the anti-inflammatory cytokine IL-10, independent of protein source. Analysis of blood via untargeted metabolomics analysis identified eight, four, and four metabolites significantly altered by protein level, protein source, and a protein level-source interaction, respectively. Together, the effects of casein, chicken, and pork protein on the regulation of body fat accumulation and blood metabolite profile are largely dependent on protein level and less attributable to the protein source

Optimization of a static headspace GC-MS method and its application in metabolic fingerprinting of the leaf volatiles of 42 citrus cultivars

Citrus leaves, which are a rich source of plant volatiles, have the beneficial attributes of rapid growth, large biomass, and availability throughout the year. Establishing the leaf volatile profiles of different citrus genotypes would make a valuable contribution to citrus species identification and chemotaxonomic studies. In this study, we developed an efficient and convenient static headspace (HS) sampling technique combined with gas chromatography-mass spectrometry (GC-MS) analysis and optimized the extraction conditions (a 15-min incubation at 100 ˚C without the addition of salt). Using a large set of 42 citrus cultivars, we validated the applicability of the optimized HS-GC-MS system in determining leaf volatile profiles. A total of 83 volatile metabolites, including monoterpene hydrocarbons, alcohols, sesquiterpene hydrocarbons, aldehydes, monoterpenoids, esters, and ketones were identified and quantified. Multivariate statistical analysis and hierarchical clustering revealed that mandarin (Citrus reticulata Blanco) and orange (Citrus sinensis L. Osbeck) groups exhibited notably differential volatile profiles, and that the mandarin group cultivars were characterized by the complex volatile profiles, thereby indicating the complex nature and diversity of these mandarin cultivars. We also identified those volatile compounds deemed to be the most useful in discriminating amongst citrus cultivars. This method developed in this study provides a rapid, simple, and reliable approach for the extraction and identification of citrus leaf volatile organic compound, and based on this methodology, we propose a leaf volatile profile-based classification model for citrus

NEDD9 Is a Positive Regulator of Epithelial-Mesenchymal Transition and Promotes Invasion in Aggressive Breast Cancer

Epithelial to mesenchymal transition (EMT) plays an important role in many biological processes. The latest studies revealed that aggressive breast cancer, especially the triple-negative breast cancer (TNBC) subtype was frequently associated with apparent EMT, but the mechanisms are still unclear. NEDD9/HEF1/Cas-L is a member of the Cas protein family and was identified as a metastasis marker in multiple cancer types. In this study, we wished to discern the role of NEDD9 in breast cancer progression and to investigate the molecular mechanism by which NEDD9 regulates EMT and promotes invasion in triple-negative breast cancer. We showed that expression of NEDD9 was frequently upregulated in TNBC cell lines, and in aggressive breast tumors, especially in TNBC subtype. Knockdown of endogenous NEDD9 reduced the migration, invasion and proliferation of TNBC cells. Moreover, ectopic overexpression of NEDD9 in mammary epithelial cells led to a string of events including the trigger of EMT, activation of ERK signaling, increase of several EMT-inducing transcription factors and promotion of their interactions with the E-cadherin promoter. Data presented in this report contribute to the understanding of the mechanisms by which NEDD9 promotes EMT, and provide useful clues to the evaluation of the potential of NEDD9 as a responsive molecular target for TNBC chemotherapy