Self-supervised Facial Action Unit Detection with Region and Relation Learning

Facial action unit (AU) detection is a challenging task due to the scarcity of manual annotations. Recent works on AU detection with self-supervised learning have emerged to address this problem, aiming to learn meaningful AU representations from numerous unlabeled data. However, most existing AU detection works with self-supervised learning utilize global facial features only, while AU-related properties such as locality and relevance are not fully explored. In this paper, we propose a novel self-supervised framework for AU detection with the region and relation learning. In particular, AU related attention map is utilized to guide the model to focus more on AU-specific regions to enhance the integrity of AU local features. Meanwhile, an improved Optimal Transport (OT) algorithm is introduced to exploit the correlation characteristics among AUs. In addition, Swin Transformer is exploited to model the long-distance dependencies within each AU region during feature learning. The evaluation results on BP4D and DISFA demonstrate that our proposed method is comparable or even superior to the state-of-the-art self-supervised learning methods and supervised AU detection methods.Comment: Accepted by ICASSP 202

Conditional Adversarial Synthesis of 3D Facial Action Units

Employing deep learning-based approaches for fine-grained facial expression analysis, such as those involving the estimation of Action Unit (AU) intensities, is difficult due to the lack of a large-scale dataset of real faces with sufficiently diverse AU labels for training. In this paper, we consider how AU-level facial image synthesis can be used to substantially augment such a dataset. We propose an AU synthesis framework that combines the well-known 3D Morphable Model (3DMM), which intrinsically disentangles expression parameters from other face attributes, with models that adversarially generate 3DMM expression parameters conditioned on given target AU labels, in contrast to the more conventional approach of generating facial images directly. In this way, we are able to synthesize new combinations of expression parameters and facial images from desired AU labels. Extensive quantitative and qualitative results on the benchmark DISFA dataset demonstrate the effectiveness of our method on 3DMM facial expression parameter synthesis and data augmentation for deep learning-based AU intensity estimation

Egg consumption and risk of coronary heart disease and stroke: dose-response meta-analysis of prospective cohort studies

Objective: To investigate and quantify the potential dose-response association between egg consumption and risk of coronary heart disease and stroke. Design: Dose-response meta-analysis of prospective cohort studies. Data sources PubMed and Embase prior to June 2012 and references of relevant original papers and review articles. Eligibility criteria for selecting studies Prospective cohort studies with relative risks and 95% confidence intervals of coronary heart disease or stroke for three or more categories of egg consumption. Results: Eight articles with 17 reports (nine for coronary heart disease, eight for stroke) were eligible for inclusion in the meta-analysis (3 081 269 person years and 5847 incident cases for coronary heart disease, and 4 148 095 person years and 7579 incident cases for stroke). No evidence of a curve linear association was seen between egg consumption and risk of coronary heart disease or stroke (P=0.67 and P=0.27 for non-linearity, respectively). The summary relative risk of coronary heart disease for an increase of one egg consumed per day was 0.99 (95% confidence interval 0.85 to 1.15; P=0.88 for linear trend) without heterogeneity among studies (P=0.97, I2=0%). For stroke, the combined relative risk for an increase of one egg consumed per day was 0.91 (0.81 to 1.02; P=0.10 for linear trend) without heterogeneity among studies (P=0.46, I2=0%). In a subgroup analysis of diabetic populations, the relative risk of coronary heart disease comparing the highest with the lowest egg consumption was 1.54 (1.14 to 2.09; P=0.01). In addition, people with higher egg consumption had a 25% (0.57 to 0.99; P=0.04) lower risk of developing hemorrhagic stroke. Conclusions: Higher consumption of eggs (up to one egg per day) is not associated with increased risk of coronary heart disease or stroke. The increased risk of coronary heart disease among diabetic patients and reduced risk of hemorrhagic stroke associated with higher egg consumption in subgroup analyses warrant further studies

Repetitive transcranial magnetic stimulation as an adjunctive treatment for negative symptoms and cognitive impairment in patients with schizophrenia: a randomized, double-blind, sham-controlled trial

Purpose: Effective treatment options for negative symptoms and cognitive impairment in patients with schizophrenia are still to be developed. The present study was to examine potential benefits of repetitive transcranial magnetic stimulation (rTMS) to improve negative symptoms and cognition in this patient population. Methods: The study was a 4-week, randomized, double-blind sham-controlled trial. Patients with schizophrenia were treated with adjunctive 20-Hz rTMS for 4 weeks or sham condition to the left dorsolateral prefrontal cortex (DLPFC). Negative symptoms were measured using the Scale for the Assessment of Negative Symptoms (SANS) and the Positive and Negative symptom scale (PANSS) negative subscale at baseline and week 4. Cognitive function was measured using the MATRICS Consensus Cognitive Battery (MCCB) at the same two time points. In addition, possible moderators for rTMS treatment efficacy were explored. Results: Sixty patients (33 in the treatment group, 27 in the sham group) completed the study. There was a significant decrease in negative symptoms after 4-week rTMS treatment as measured by the SANS total score and the PANSS negative symptom subscale score. However, there was no significant improvement in cognition with rTMS treatment. Stepwise multiple linear regression analysis suggested that the baseline severity of positive symptoms may predict poorer improvement in negative symptoms at week 4. Conclusion: Twenty-Hz rTMS stimulation over left DLPFC as an adjunctive treatment might be beneficial in improving negative symptoms of schizophrenia. Future studies with a longer treatment duration and a larger sample size are needed. Clinical trial ID: NCT01940939

Association Analysis and Identification of ZmHKT1;5 Variation With Salt-Stress Tolerance

The high-affinity potassium transporter (HKT) genes are essential for plant salt stress tolerance. However, there were limited studies on HKTs in maize (Zea mays), and it is basically unknown whether natural sequence variations in these genes are associated with the phenotypic variability of salt tolerance. Here, the characterization of ZmHKT1;5 was reported. Under salt stress, ZmHKT1;5 expression increased strongly in salt-tolerant inbred lines, which accompanied a better-balanced Na+/K+ ratio and preferable plant growth. The association between sequence variations in ZmHKT1;5 and salt tolerance was evaluated in a diverse population comprising 54 maize varieties from different maize production regions of China. Two SNPs (A134G and A511G) in the coding region of ZmHKT1;5 were significantly associated with different salt tolerance levels in maize varieties. In addition, the favorable allele of ZmHKT1; 5 identified in salt tolerant maize varieties effectively endowed plant salt tolerance. Transgenic tobacco plants of overexpressing the favorable allele displayed enhanced tolerance to salt stress better than overexpressing the wild type ZmHKT1;5. Our research showed that ZmHKT1;5 expression could effectively enhance salt tolerance by maintaining an optimal Na+/K+ balance and increasing the antioxidant activity that keeps reactive oxygen species (ROS) at a low accumulation level. Especially, the two SNPs in ZmHKT1;5 might be related with new amino acid residues to confer salt tolerance in maize.Key Message: Two SNPs of ZmHKT1;5 related with salt tolerance were identified by association analysis. Overexpressing ZmHKT1;5 in tobaccos showed that the SNPs might enhance its ability to regulating Na+/K+ homeostasis

xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Protein language models have shown remarkable success in learning biological information from protein sequences. However, most existing models are limited by either autoencoding or autoregressive pre-training objectives, which makes them struggle to handle protein understanding and generation tasks concurrently. We propose a unified protein language model, xTrimoPGLM, to address these two types of tasks simultaneously through an innovative pre-training framework. Our key technical contribution is an exploration of the compatibility and the potential for joint optimization of the two types of objectives, which has led to a strategy for training xTrimoPGLM at an unprecedented scale of 100 billion parameters and 1 trillion training tokens. Our extensive experiments reveal that 1) xTrimoPGLM significantly outperforms other advanced baselines in 18 protein understanding benchmarks across four categories. The model also facilitates an atomic-resolution view of protein structures, leading to an advanced 3D structural prediction model that surpasses existing language model-based tools. 2) xTrimoPGLM not only can generate de novo protein sequences following the principles of natural ones, but also can perform programmable generation after supervised fine-tuning (SFT) on curated sequences. These results highlight the substantial capability and versatility of xTrimoPGLM in understanding and generating protein sequences, contributing to the evolving landscape of foundation models in protein science

G protein-coupled receptor GPR68 inhibits lymphocyte infiltration and contributes to gender-dependent melanoma growth

IntroductionMelanoma is a common and aggressive type of skin cancer with rising incidence rate globally. Gender is one of the determining factors, and overall males have a higher risk of developing melanoma as well as worse prognosis. Emerging evidence show that GPR68, a G protein-coupled receptor that is sensitive to acid and mechanical stimulations for cellular microenvironment, plays an important role in tumor biology. However, whether GPR68 is involved in gender-dependent regulation of tumor growth is unclear.MethodsWe established a syngeneic melanoma model in Gpr68-deficient mice and investigated tumor growth in males and females. The GPR68 activation-induced cellular responses of melanocytes, including intracellular calcium dynamics, proliferation and migration were measured. The landscape of tumor-infiltrating immune cells were analyzed by flow cytometry and the expression various cytokines were checked by qRT-PCR.ResultsGPR68 is required for melanoma growth in males but dispensable in females. GPR68 is expressed and functional in B16-F10 melanocytes, but the activity of the receptor does not directly contribute to proliferation and migration of the cells. GPR68 inhibits infiltration of CD45+ lymphocytes, CD8+ T cells and NK cells in melanoma in male mice, but has no apparent effect in females. Furthermore, GPR68 functionally inhibits the expression of IFNγ in the tumor infiltrating CD8+ T cells and NK cells as well as the inflammatory cytokine expression in the spleen in male mice but not in females. Our results show the gender-dependent modulatory effect of GPR68 on tumor-infiltrating immune cells and their tumor-killing capacity.DiscussionGPR68 is sensor for acid and mechanical stimulations, which are two important factors in the microenvironment associated with tumor growth and metastasis. Our results suggest a prominent role of the receptor molecules in tumor biology in a gender-dependent manner. Since GPCRs are more feasible to develop small molecule drugs compared to transcription factors, our study demonstrates the potential of GPR68 as a novel druggable therapeutic target for melanoma in male patients

Risks to human and animal health related to the presence of deoxynivalenol and its acetylated and modified forms in food and feed

Deoxynivalenol (DON) is a mycotoxin primarily produced by Fusarium fungi, occurring predominantly in cereal grains. Following the request of the European Commission, the CONTAM Panel assessed the risk to animal and human health related to DON, 3-acetyl-DON (3-Ac-DON), 15-acetyl-DON (15-Ac-DON) and DON-3-glucoside in food and feed. A total of 27,537, 13,892, 7,270 and 2,266 analytical data for DON, 3-Ac-DON, 15-Ac-DON and DON-3-glucoside, respectively, in food, feed and unprocessed grains collected from 2007 to 2014 were used. For human exposure, grains and grain-based products were main sources, whereas in farm and companion animals, cereal grains, cereal by-products and forage maize contributed most. DON is rapidly absorbed, distributed, and excreted. Since 3-Ac-DON and 15-Ac-DON are largely deacetylated and DON-3-glucoside cleaved in the intestines the same toxic effects as DON can be expected. The TDI of 1 μg/kg bw per day, that was established for DON based on reduced body weight gain in mice, was therefore used as a group-TDI for the sum of DON, 3-Ac-DON, 15-Ac-DON and DON-3-glucoside. In order to assess acute human health risk, epidemiological data from mycotoxicoses were assessed and a group-ARfD of 8 μg/kg bw per eating occasion was calculated. Estimates of acute dietary exposures were below this dose and did not raise a health concern in humans. The estimated mean chronic dietary exposure was above the group-TDI in infants, toddlers and other children, and at high exposure also in adolescents and adults, indicating a potential health concern. Based on estimated mean dietary concentrations in ruminants, poultry, rabbits, dogs and cats, most farmed fish species and horses, adverse effects are not expected. At the high dietary concentrations, there is a potential risk for chronic adverse effects in pigs and fish and for acute adverse effects in cats and farmed mink

Auto MPG dataset

Auto MPG dataset includes 398 samples, and each sample is composed of seven inputs (four continuous ones and three multivalued discrete ones) and one continuous output (the fuel consumption)