Smaller Genetic Risk in Catabolic Process Explains Lower Energy Expenditure, More Athletic Capability and Higher Prevalence of Obesity in Africans

Lower energy expenditure (EE) for physical activity was observed in Africans than in Europeans, which might contribute to the higher prevalence of obesity and more athletic capability in Africans. But it is still unclear why EE is lower among African populations. In this study we tried to explore the genetic mechanism underlying lower EE in Africans. We screened 231 common variants with possibly harmful impact on 182 genes in the catabolic process. The genetic risk, including the total number of mutations and the sum of harmful probabilities, was calculated and analyzed for the screened variants at a population level. Results of the genetic risk among human groups showed that most Africans (3 out of 4 groups) had a significantly smaller genetic risk in the catabolic process than Europeans and Asians, which might result in higher efficiency of generating energy among Africans. In sport competitions, athletes need massive amounts of energy expenditure in a short period of time, so higher efficiency of energy generation might help make African-descendent athletes more powerful. On the other hand, higher efficiency of generating energy might also result in consuming smaller volumes of body mass. As a result, Africans might be more vulnerable to obesity compared to the other races when under the same or similar conditions. Therefore, the smaller genetic risk in the catabolic process might be at the core of understanding lower EE, more athletic capability and higher prevalence of obesity in Africans

A Close Look at Spatial Modeling: From Attention to Convolution

Vision Transformers have shown great promise recently for many vision tasks due to the insightful architecture design and attention mechanism. By revisiting the self-attention responses in Transformers, we empirically observe two interesting issues. First, Vision Transformers present a queryirrelevant behavior at deep layers, where the attention maps exhibit nearly consistent contexts in global scope, regardless of the query patch position (also head-irrelevant). Second, the attention maps are intrinsically sparse, few tokens dominate the attention weights; introducing the knowledge from ConvNets would largely smooth the attention and enhance the performance. Motivated by above observations, we generalize self-attention formulation to abstract a queryirrelevant global context directly and further integrate the global context into convolutions. The resulting model, a Fully Convolutional Vision Transformer (i.e., FCViT), purely consists of convolutional layers and firmly inherits the merits of both attention mechanism and convolutions, including dynamic property, weight sharing, and short- and long-range feature modeling, etc. Experimental results demonstrate the effectiveness of FCViT. With less than 14M parameters, our FCViT-S12 outperforms related work ResT-Lite by 3.7% top1 accuracy on ImageNet-1K. When scaling FCViT to larger models, we still perform better than previous state-of-the-art ConvNeXt with even fewer parameters. FCViT-based models also demonstrate promising transferability to downstream tasks, like object detection, instance segmentation, and semantic segmentation. Codes and models are made available at: https://github.com/ma-xu/FCViT

Inverse Fluid Convection Problems in Enclosures

Efficiency, security, and reliability of industrial and domestic processes essentially depend on the deep understanding of their actual processes of fluid flow and heat transfer. Actual processes of fluid flow control and measurements need the development of effect-cause inverse modeling. Extensive investigations on the effect-cause inverse modeling could effectively enhance the efficiency, security, and reliability of these industrial and domestic fluid flow processes

Moderate mutation rate in the SARS coronavirus genome and its implications

BACKGROUND: The outbreak of severe acute respiratory syndrome (SARS) caused a severe global epidemic in 2003 which led to hundreds of deaths and many thousands of hospitalizations. The virus causing SARS was identified as a novel coronavirus (SARS-CoV) and multiple genomic sequences have been revealed since mid-April, 2003. After a quiet summer and fall in 2003, the newly emerged SARS cases in Asia, particularly the latest cases in China, are reinforcing a wide-spread belief that the SARS epidemic would strike back. With the understanding that SARS-CoV might be with humans for years to come, knowledge of the evolutionary mechanism of the SARS-CoV, including its mutation rate and emergence time, is fundamental to battle this deadly pathogen. To date, the speed at which the deadly virus evolved in nature and the elapsed time before it was transmitted to humans remains poorly understood. RESULTS: Sixteen complete genomic sequences with available clinical histories during the SARS outbreak were analyzed. After careful examination of multiple-sequence alignment, 114 single nucleotide variations were identified. To minimize the effects of sequencing errors and additional mutations during the cell culture, three strategies were applied to estimate the mutation rate by 1) using the closely related sequences as background controls; 2) adjusting the divergence time for cell culture; or 3) using the common variants only. The mutation rate in the SARS-CoV genome was estimated to be 0.80 – 2.38 × 10(-3 )nucleotide substitution per site per year which is in the same order of magnitude as other RNA viruses. The non-synonymous and synonymous substitution rates were estimated to be 1.16 – 3.30 × 10(-3 )and 1.67 – 4.67 × 10(-3 )per site per year, respectively. The most recent common ancestor of the 16 sequences was inferred to be present as early as the spring of 2002. CONCLUSIONS: The estimated mutation rates in the SARS-CoV using multiple strategies were not unusual among coronaviruses and moderate compared to those in other RNA viruses. All estimates of mutation rates led to the inference that the SARS-CoV could have been with humans in the spring of 2002 without causing a severe epidemic

Genome-Wide Expression Analysis in Down Syndrome: Insight into Immunodeficiency

Down syndrome (DS) is caused by triplication of Human chromosome 21 (Hsa21) and associated with an array of deleterious phenotypes, including mental retardation, heart defects and immunodeficiency. Genome-wide expression patterns of uncultured peripheral blood cells are useful to understanding of DS-associated immune dysfunction. We used a Human Exon microarray to characterize gene expression in uncultured peripheral blood cells derived from DS individuals and age-matched controls from two age groups: neonate (N) and child (C). A total of 174 transcript clusters (gene-level) with eight located on Hsa21 in N group and 383 transcript clusters including 56 on Hsa21 in C group were significantly dysregulated in DS individuals. Microarray data were validated by quantitative polymerase chain reaction. Functional analysis revealed that the dysregulated genes in DS were significantly enriched in two and six KEGG pathways in N and C group, respectively. These pathways included leukocyte trans-endothelial migration, B cell receptor signaling pathway and primary immunodeficiency, etc., which causally implicated dysfunctional immunity in DS. Our results provided a comprehensive picture of gene expression patterns in DS at the two developmental stages and pointed towards candidate genes and molecular pathways potentially associated with the immune dysfunction in DS

High remission and low relapse with prolonged intensive DMARD therapy in rheumatoid arthritis (PRINT): A multicenter randomized clinical trial

Objectives: To determine whether prolonged intensive disease-modifying antirheumatic drug (DMARD) treatment (PRINT) leads to high remission and low relapse rates in patients with severe rheumatoid arthritis (RA). Methods: In this multicenter, randomized and parallel treatment trial, 346 patients with active RA (disease activity score (28 joints) [DAS28] (erythrocyte sedimentation rate [ESR]) > 5.1) were enrolled from 9 centers. In phase 1, patients received intensive treatment with methotrexate, leflunomide, and hydroxychloroquine, up to 36 weeks, until remission (DAS28 ≤ 2.6) or a low disease activity (2.6 < DAS28 ≤ 3.2) was achieved. In phase 2, patients achieving remission or low disease activity were followed up with randomization to 1 of 2 step-down protocols: leflunomide plus hydroxychloroquine combination or leflunomide monotherapy. The primary endpoints were good European League Against Rheumatism (EULAR) response (DAS28 (ESR) < 3.2 and a decrease of DAS28 by at least 1.2) during the intensive treatment and the disease state retention rate during step-down maintenance treatment. Predictors of a good EULAR response in the intensive treatment period and disease flare in the maintenance period were sought. Results: A good EULAR response was achieved in 18.7%, 36.9%, and 54.1% of patients at 12, 24, and 36 weeks, respectively. By 36 weeks, 75.4% of patients achieved good and moderate EULAR responses. Compared with those achieving low disease activity and a high health assessment questionnaire (HAQ > 0.5), patients achieving remission (DAS28 ≤ 2.6) and low HAQ (≤ 0.5) had a significantly higher retention rate when tapering the DMARDs treatment (P = 0.046 and P = 0.01, respectively). There was no advantage on tapering to combination rather than monotherapy. Conclusions: Remission was achieved in a proportion of patients with RA receiving prolonged intensive DMARD therapy. Low disease activity at the start of disease taper leads to less subsequent flares. Leflunomide is a good maintenance treatment as single treatment