Miracle-dz/UniFAR-FTUs huggingface dataset:
Early protective effect of CCR‐5 Δ32 heterozygosity on HIV‐1 disease progression: relationship with viral load

Objective:To determine the influence of heterozygosity for the Δ32 mutant CCR-5 allele on HIV-1 disease progression. Design:HIV-1 disease progression and serum viral load were analysed according to the C-C chemokine receptor (CCR)-5 genotype in 412 Caucasian patients (319 men and 93 women) with a known date of seroconversion, who were enrolled in the SEROCO cohort (median follow-up, 74 months). Results:The frequency of heterozygosity for the mutant allele was 17% and did not differ according to sex or risk factor for HIV infection. Heterozygotes were significantly less likely than patients with two functional alleles to have symptomatic primary infection. Their serum viral load was lower during the 6- to 24-month plateau phase after seroconversion. This difference persisted afterwards, although the rate of decline in CD4+ cells was similar. Kaplan-Meier survival curves showed slower progression to clinical AIDS in heterozygotes during the first 7 years following infection (P < 0.02), the two curves tending to join thereafter (overall log-rank test, P = 0.17). However, the interaction term with time did not reach significance in a Cox model. The overall relative risk of progression was 0.67 (95% confidence interval, 0.38–1.18) and was not influenced by adjustment for age at seroconversion or symptomatic primary infection. After adjustment for early viral load the relative risk was 0.83. Pneumocystis carinii pneumonia and toxoplasmosis were less likely to be the first AIDS-defining illness in heterozygotes than in the other patients (0 versus 24.7% of AIDS cases, P = 0.04), despite similar management. Conclusion:Deletion of one CCR-5 gene allele appears to protect against HIV-1 disease progression, mainly during the early years of the infection. Heterozygosity for the deletion leads to persistently lower viral load, and also seems to protect against some opportunistic infections.
Active vibration control of flexible-joint manipulators using accelerometers

Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators. ,First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration. ,By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller. ,The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.
An End-to-End Local-Global-Fusion Feature Extraction Network for Remote Sensing Image Scene Classification

Remote sensing image scene classification (RSISC) is an active task in the remote sensing community and has attracted great attention due to its wide applications. Recently, the deep convolutional neural networks (CNNs)-based methods have witnessed a remarkable breakthrough in performance of remote sensing image scene classification. However, the problem that the feature representation is not discriminative enough still exists, which is mainly caused by the characteristic of inter-class similarity and intra-class diversity. In this paper, we propose an efficient end-to-end local-global-fusion feature extraction (LGFFE) network for a more discriminative feature representation. Specifically, global and local features are extracted from channel and spatial dimensions respectively, based on a high-level feature map from deep CNNs. For the local features, a novel recurrent neural network (RNN)-based attention module is first proposed to capture the spatial layout information and context information across different regions. Gated recurrent units (GRUs) is then exploited to generate the important weight of each region by taking a sequence of features from image patches as input. A reweighed regional feature representation can be obtained by focusing on the key region. Then, the final feature representation can be acquired by fusing the local and global features. The whole process of feature extraction and feature fusion can be trained in an end-to-end manner. Finally, extensive experiments have been conducted on four public and widely used datasets and experimental results show that our method LGFFE outperforms baseline methods and achieves state-of-the-art results.
Pharyngeal microbiome alterations during Neisseria gonorrhoeae infection

Pharyngeal gonorrhoea is a common sexually transmitted infection among ‘men having sex with other men’ (MSM). Neisseria gonorrhoeae (NG) pharyngeal infections are usually characterized by the absence of symptoms, acting as an important reservoir for their further spread. To the best of our knowledge, no information about the composition of the pharyngeal microbiome during an ongoing NG infection is currently available. Therefore, in this study, we characterized the pharyngeal bacterial community profiles associated with NG infection in a well-selected cohort of HIV-negative MSM reporting unsafe oral intercourse. A total of 70 pharyngeal swabs were considered, comparing non-infected subjects (n = 45) versus patients with pharyngeal gonorrhoea (n = 25) whose microbiota composition was analyzed from pharyngeal swabs through sequencing of hypervariable V3-V4 regions of the 16S rRNA gene. The pharyngeal microbiome of all subjects was dominated by Prevotellaceae, Veillonellaceae and Streptococcaceae families. Patients with pharyngeal gonorrhoea harboured a pharyngeal microbiome quite similar to negative subjects. Nevertheless, when looking to less-represented bacterial species (relative abundance approximately 1% or less), an imbalance between aerobe and anaerobe microorganisms was observed in NG-infected patients. In particular, the pharyngeal microbiome of NG-positive individuals was richer in several anaerobes (e.g. Treponema, Parvimonas, Peptococcus, Catonella, Filifactor) and poorer in various aerobe genera (i.e. Pseudomonas, Escherichia), compared to non-infected controls. No significant differences were noticed in the distribution of commensal Neisseria species of the oropharynx between NG-positive and negative subjects. Metabolic variations induced by changes in the microbiome abundance were assessed by a functional prediction of the bacterial metabolic pathways: a more abundant involvement of D-glutamine and D-glutamate metabolism, carbohydrate metabolism, as well as a greater activation of the energy metabolism was observed in patients with pharyngeal gonorrhoea compared to non-infected individuals. Information about the bacterial composition of the pharyngeal microbiome in case of gonorrhoea could shed light on the pathogenesis of the infection and open new perspectives for the prevention and control of this condition.
Extreme down-regulation of chromosome Y and cancer risk in men.

BACKGROUND Understanding the biological differences between sexes in cancer is essential for personalized treatment and prevention. We hypothesized that the extreme down-regulation of chromosome Y gene expression (EDY) is a signature of cancer risk in men and the functional mediator of the reported association between the mosaic loss of chromosome Y (LOY) and cancer. METHODS We advanced a method to measure EDY from transcriptomic data. We studied EDY across 47 nondiseased tissues from the GTEx project (n = 371) and its association with cancer status across 12 cancer studies from the Cancer Genome Atlas (TCGA) (n = 1,774), and seven other studies (n = 7,562). Associations of EDY with cancer status and presence of loss-off function mutations in chromosome X were tested with logistic regression models, while a Fisher's test was used to assess genome-wide association of EDY with the proportion of copy number gains. All statistical tests were two-sided. RESULTS EDY was likely to occur in multiple nondiseased tissues (P<0.001) and statistically significantly associated with the EGFR tyrosine kinase inhibitor resistance pathway (FDR=0.028). EDY strongly associated with cancer risk in men (OR = 3.66, 95%CI = 1.58, 8.46, P = 0.002), adjusted by LOY and age, and its variability was largely explained by several genes of the non-recombinant region (NRY) whose chromosome X homologs showed loss-of-function mutations that co-occurred with EDY during cancer (OR = 2.82, 95%CI = 1.32, 6.01, P = 0.007). EDY associated with a high proportion of EGFR amplifications (OR = 5.64, 95%CI = 3.70, 8.59, FDR<0.001) and EGFR overexpression, along with SRY hypomethylation and NRY hypermethylation, indicating alternative causes of EDY in cancer other than LOY. EDY associations were independently validated for different cancers and exposure to smoking, and its status was accurately predicted from individual methylation patterns. CONCLUSIONS EDY is a male-specific signature of cancer susceptibility that supports the escape from X-inactivation tumor suppressor hypothesis for genes that protect females with respect to males from cancer risk.
Rapid degeneration of neurons in the penumbra region following a small, focal ischemic stroke.

Ischemic stroke causes immediate cell death within the infarct core, whereas cells in the surrounding penumbra region are damaged but can be salvaged. Rapid restoration of blood flow can rescue these cells in the first few hours post-stroke. It remains unclear how long cells within the penumbra region can survive. To address this, we compared the acute cellular response within the ischemic core versus the penumbra region following an Endothelin-1-induced focal ischemic stroke in mice. We used vascular labelling to distinguish the three regions of blood perfusion: the non-perfused core; the hypo-perfused penumbra; and the perfused region. Within 4 hr post-stroke ~ 80% of neurons died in the non-perfused core, while 40% of neurons died in the hypo-perfused region. From 4 to 24 hr post-stroke, surviving neurons within the hypo-perfused region underwent extensive dendritic and axonal degeneration. Breakdown of the blood brain barrier, microglia activation, monocyte/neutrophil infiltration and astrogliosis; however, was not observed until 24 hr post-stroke. The cellular response within the hypo-perfused region was distinct from the non-perfused core. The core was comprised primarily of infiltrating peripheral monocytes and leukocytes, whereas the hypo-perfused region contained activated microglia and astrocytes. This study shows that small, localized ischemic strokes exhibit altered breakdown of the BBB in comparison to larger strokes. Furthermore, the massive degeneration of neuronal processes within the penumbra region suggests that the timeline to salvage surviving neurons is limited. In summary, the findings from this study reinforce the urgent need for therapeutic strategies targeting the acute hours post-stroke.
N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription

A new layer of transcriptional control N6-methyladenosine (m6A) is the most abundant messenger RNA modification in almost all eukaryotes. Liu et al. now show that m6A is also cotranscriptionally added onto various chromosome-associated regulatory RNAs (carRNAs) in mammalian cells. Disruption of m6A modification of these RNAs increases their abundance and promotes gene transcription by increasing the chromatin accessibility. Thus, m6A serves as a switch to regulate carRNA levels by tuning nearby chromatin state and downstream transcription. Science, this issue p. 580 Chromosome-associated regulatory RNAs modified by N6-methyladenosine regulate chromatin and transcription. N6-methyladenosine (m6A) regulates stability and translation of messenger RNA (mRNA) in various biological processes. In this work, we show that knockout of the m6A writer Mettl3 or the nuclear reader Ythdc1 in mouse embryonic stem cells increases chromatin accessibility and activates transcription in an m6A-dependent manner. We found that METTL3 deposits m6A modifications on chromosome-associated regulatory RNAs (carRNAs), including promoter-associated RNAs, enhancer RNAs, and repeat RNAs. YTHDC1 facilitates the decay of a subset of these m6A-modified RNAs, especially elements of the long interspersed element-1 family, through the nuclear exosome targeting–mediated nuclear degradation. Reducing m6A methylation by METTL3 depletion or site-specific m6A demethylation of selected carRNAs elevates the levels of carRNAs and promotes open chromatin state and downstream transcription. Collectively, our results reveal that m6A on carRNAs can globally tune chromatin state and transcription.
Neighborhood Ties Reduced Depressive Symptoms in Older Disaster Survivors: Iwanuma Study, a Natural Experiment

Objective: As most studies relating to mental health and disasters have employed cross-sectional or follow-up assessments about psychological health with post-disaster information, the association between changes in social ties and mental health remains unclear. We examined the relationship between the changes in survivor neighborhood ties and depressive symptoms before and after a natural disaster. Methods: Participants were 3567 individuals aged ≥65 years living in Iwanuma city who had responded to questionnaires by the Japan Gerontological Evaluation Study both predating the 2011 Great East Japan Earthquake and Tsunami, and 2.5 years afterward. Changes in the depressive symptoms were assessed using the geriatric depression scale (GDS) at the baseline and follow-up survey. Changes in the neighborhood ties were assessed by asking the participants about their interactions with people in their neighborhood. Possible confounders were adjusted in a linear regression model. Results: Among the 3111 participants in this analysis, 1073 (34.5%) had increased GDS score after the disaster. There were 336 (10.8%) individuals who had neighborhood ties before the disaster, but had no ties afterward; their mean GDS score increased from 2.93 points in 2010 to 3.19 points in 2013. Among those who had not had ties before and after the disaster the mean GDS score remained almost stable, from 2.19 points in 2010 to 2.12 points in 2013. The participants with post-disaster ties were significantly less likely to have an increased GDS score compared with those who had not had ties before and after the disaster (β = −0.39; 95% confidence interval: −0.72, −0.06). Conclusions: Increased neighborhood ties after the disaster reduced the risk of depressive symptoms even when survivors suffered disaster damages. The study reinforces the importance of social capital in disaster recovery and suggests to local governments and local communities that fostering horizontal, neighborhood ties may improve disaster preparedness and mental health resilience.
Gene Expression and K+ Uptake of Two Tomato Cultivars in Response to Sub-Optimal Temperature

Sub-optimal temperatures can adversely affect tomato (Solanum lycopersicum) growth, and K+ plays an important role in the cold tolerance of plants. However, gene expression and K+ uptake in tomato in response to sub-optimal temperatures are still not very clear. To address these questions, one cold-tolerant tomato cultivar, Dongnong 722 (T722), and one cold-sensitive cultivar, Dongnong 708 (S708), were exposed to sub-optimal (15/10 °C) and normal temperatures (25/18 °C), and the differences in growth, K+ uptake characteristics and global gene expressions were investigated. The results showed that compared to S708, T722 exhibited lower reduction in plant growth rate, the whole plant K+ amount and K+ net uptake rate, and T722 also had higher peroxidase activity and lower K+ efflux rate under sub-optimal temperature conditions. RNA-seq analysis showed that a total of 1476 and 2188 differentially expressed genes (DEGs) responding to sub-optimal temperature were identified in S708 and T722 roots, respectively. Functional classification revealed that most DEGs were involved in “plant hormone signal transduction”, “phenylpropanoid biosynthesis”, “sulfur metabolism” and “cytochrome P450”. The genes that were significantly up-regulated only in T722 were involved in the “phenylpropanoid biosynthesis” and “plant hormone signal transduction” pathways. Moreover, we also found that sub-optimal temperature inhibited the expression of gene coding for K+ transporter SIHAK5 in both cultivars, but decreased the expression of gene coding for K+ channel AKT1 only in S708. Overall, our results revealed the cold response genes in tomato roots, and provided a foundation for further investigation of mechanism involved in K+ uptake in tomato under sub-optimal temperatures.
Signaling Response to Transient Redox Stress in Human Isolated T Cells: Molecular Sensor Role of Syk Kinase and Functional Involvement of IL2 Receptor and L-Selectine

Reactive oxygen species (ROS) are central effectors of inflammation and play a key role in cell signaling. Previous reports have described an association between oxidative events and the modulation of innate immunity. However, the role of redox signaling in adaptive immunity is still not well understood. This work is based on a novel investigation of diamide, a specific oxidant of sulfhydryl groups, and it is the first performed in purified T cell tyrosine phosphorylation signaling. Our data show that ex vivo T cells respond to –SH group oxidation with a distinctive tyrosine phosphorylation response and that these events elicit specific cellular responses. The expression of two essential T-cell receptors, CD25 and CD62L, and T-cell cytokine release is also affected in a specific way. Experiments with Syk inhibitors indicate a major contribution of this kinase in these phenomena. This pilot work confirms the presence of crosstalk between oxidation of cysteine residues and tyrosine phosphorylation changes, resulting in a series of functional events in freshly isolated T cells. Our experiments show a novel role of Syk inhibitors in applying their anti-inflammatory action through the inhibition of a ROS-generated reaction.
Ship Detection Using Deep Convolutional Neural Networks for PolSAR Images

Ship detection plays an important role in many remote sensing applications. However, the performance of the PolSAR ship detection may be degraded by the complicated scattering mechanism, multi-scale size of targets, and random speckle noise, etc. In this paper, we propose a ship detection method for PolSAR images based on modified faster region-based convolutional neural network (Faster R-CNN). The main improvements include proposal generation by adopting multi-level features produced by the convolution layers, which fits ships with different sizes, and the addition of a Deep Convolutional Neural Network (DCNN)-based classifier for training sample generation and coast mitigation. The proposed method has been validated by four measured datasets of NASA/JPL airborne synthetic aperture radar (AIRSAR) and uninhabited aerial vehicle synthetic aperture radar (UAVSAR). Performance comparison with the modified constant false alarm rate (CFAR) detector and the Faster R-CNN has demonstrated that the proposed method can improve the detection probability while reducing the false alarm rate and missed detections.
Profilin1 delivery tunes cytoskeleton dynamics towards CNS axon regeneration.

After trauma, regeneration of adult CNS axons is abortive causing devastating neurologic deficits. Despite progress in rehabilitative care, there is no effective treatment stimulating axon growth following injury. Using models with different regenerative capacities, followed by gain- and loss-of-function analysis, we identified profilin1 (Pfn1) as a coordinator of actin and microtubules (MTs), powering axon growth and regeneration. In growth cones, Pfn1 increased actin retrograde flow, MT growth speed and invasion of filopodia by MTs, orchestrating cytoskeleton dynamics towards axon growth. In vitro, active Pfn1 promoted MT growth in a formin-dependent manner, whereas localization of MTs to growth cone filopodia was facilitated by direct MT binding and interaction with formins. In vivo, Pfn1 ablation limited regeneration of growth-competent axons after sciatic nerve and spinal cord injury. Adeno-associated viral (AAV) delivery of constitutively active Pfn1 to rodents promoted axon regeneration, neuromuscular junction maturation and functional recovery of injured sciatic nerves, and increased the ability of regenerating axons to penetrate the inhibitory spinal cord glial scar. Thus, we identify Pfn1 as an important regulator of axon regeneration and suggest that AAV-mediated delivery of constitutively active Pfn1, together with the identification of modulators of Pfn1 activity, should be considered to treat the injured nervous system.
Short-Term Temporal Convolutional Networks for Dynamic Hand Gesture Recognition

The purpose of gesture recognition is to recognize meaningful movements of human bodies, and gesture recognition is an important issue in computer vision. In this paper, we present a multimodal gesture recognition method based on 3D densely convolutional networks (3D-DenseNets) and improved temporal convolutional networks (TCNs). The key idea of our approach is to find a compact and effective representation of spatial and temporal features, which orderly and separately divide task of gesture video analysis into two parts: spatial analysis and temporal analysis. In spatial analysis, we adopt 3D-DenseNets to learn short-term spatio-temporal features effectively. Subsequently, in temporal analysis, we use TCNs to extract temporal features and employ improved Squeeze-and-Excitation Networks (SENets) to strengthen the representational power of temporal features from each TCNs' layers. The method has been evaluated on the VIVA and the NVIDIA Gesture Dynamic Hand Gesture Datasets. Our approach obtains very competitive performance on VIVA benchmarks with the classification accuracies of 91.54%, and achieve state-of-the art performance with 86.37% accuracy on NVIDIA benchmark.