Miracle-dz/UniFAR-FTUs huggingface dataset:
Mycoplasma bovis-Induced Inhibition of Bovine Peripheral Blood Mononuclear Cell Proliferation Is Ameliorated after Blocking the Immune-Inhibitory Programmed Death 1 Receptor

ABSTRACT Mycoplasma bovis-induced immune suppression is a major obstacle faced by the host for controlling infections. M. bovis impairment of antigen-specific T-cell responses is achieved through inhibiting the proliferation of peripheral blood mononuclear cells (PBMCs). This impairment may contribute to the persistence of M. bovis infection in various sites, including lungs, and its systemic spread to various organs such as joints, with the underlying mechanisms remaining elusive. Here, we elucidated the role of the immune-inhibitory receptor programmed death 1 (PD-1) and its ligand (PD-L1) in M. bovis infection. Flow cytometry (FCM) analyses revealed an upregulation of PD-L1 expression on tracheal and lung epithelial cell lines after M. bovis infection. In addition, we found increased PD-L1 expression on purified lung lavage macrophages following M. bovis infection by FCM and determined its localization by immunofluorescence analysis comparing infected and control lung tissue sections. Moreover, M. bovis infection increased the expression of the PD-1 receptor on total PBMCs and in gated CD4+ and CD8+ T-cell subpopulations. We demonstrated that M. bovis infection induced a significant decrease in CD4+ PD-1INT and CD8+ PD-1INT subsets with intermediate PD-1 expression, which functioned as progenitor pools giving rise to CD4+ PD-1HIGH and CD8+ PD-1HIGH subsets with high PD-1 expression levels. We blocked PD-1 receptors on PBMCs using anti-PD-1 antibody at the beginning of infection, leading to a significant restoration of the proliferation of PBMCs. Taken together, our data indicate a significant involvement of the PD-1/PD-L1 inhibitory pathway during M. bovis infection and its associated immune exhaustion, culminating in impaired host immune responses.
Meta-algorithms for Software-Based Packet Classification

We observe that a same rule set can induce very different memory requirement, as well as varying classification performance, when using various well known decision tree based packet classification algorithms. Worse, two similar rule sets, in terms of types and number of rules, can give rise to widely differing performance behaviour for a same classification algorithms. We identify the intrinsic characteristics of rule sets that yield such performance differences, allowing us to understand and predict the performance behaviour of a rule set for various modern packet classification algorithms. Indeed, from our observations, we are able to derive a memory consumption model and an offline algorithm capable of quickly identifying which packet classification is suited to a give rule set. By splitting a large rule set in several subsets and using different packet classification algorithms for different subsets, our Smart Split algorithm is shown to be capable of configuring a multi-component packet classification system that exhibits up to 11 times less memory consumption, as well as up to about 4× faster classification speed, than the state-of-art work [20] for large rule sets. Our Auto PC framework obtains further performance gain by avoiding splitting large rule sets if the memory size of the built decision tree is shown by the memory consumption model to be small.
Online Deep Learning: Growing RBM on the fly

We propose a novel online learning algorithm for Restricted Boltzmann Machines (RBM), namely, the Online Generative Discriminative Restricted Boltzmann Machine (OGD-RBM), that provides the ability to build and adapt the network architecture of RBM according to the statistics of streaming data. The OGD-RBM is trained in two phases: (1) an online generative phase for unsupervised feature representation at the hidden layer and (2) a discriminative phase for classification. The online generative training begins with zero neurons in the hidden layer, adds and updates the neurons to adapt to statistics of streaming data in a single pass unsupervised manner, resulting in a feature representation best suited to the data. The discriminative phase is based on stochastic gradient descent and associates the represented features to the class labels. We demonstrate the OGD-RBM on a set of multi-category and binary classification problems for data sets having varying degrees of class-imbalance. We first apply the OGD-RBM algorithm on the multi-class MNIST dataset to characterize the network evolution. We demonstrate that the online generative phase converges to a stable, concise network architecture, wherein individual neurons are inherently discriminative to the class labels despite unsupervised training. We then benchmark OGD-RBM performance to other machine learning, neural network and ClassRBM techniques for credit scoring applications using 3 public non-stationary two-class credit datasets with varying degrees of class-imbalance. We report that OGD-RBM improves accuracy by 2.5-3% over batch learning techniques while requiring at least 24%-70% fewer neurons and fewer training samples. This online generative training approach can be extended greedily to multiple layers for training Deep Belief Networks in non-stationary data mining applications without the need for a priori fixed architectures.
Non-typhoidal Salmonella serovars associated with invasive and non-invasive disease in the Lao People’s Democratic Republic

Abstract Background Invasive non-typhoidal Salmonella (iNTS) disease is a well-described cause of mortality in children and human immunodeficiency virus (HIV)-infected adults in sub-Saharan Africa. Additionally, there is an ill-defined burden of iNTS disease in Southeast Asia. Methods Aiming to investigate the causative serovars of non-invasive and iNTS disease and their associated antimicrobial susceptibility profiles in the Lao People’s Democratic Republic, we performed multilocus sequence typing and antimicrobial susceptibility profiling on 168 NTS (63 blood and 105 faecal) organisms isolated in Lao between 2000 and 2012. Results Six different serovars were isolated from blood; Salmonella enterica serovar Enteritidis (n=28), S. enterica serovar Typhimurium (n=19) and S. enterica serovar Choleraesuis (n=11) accounted for >90% (58/63) of the iNTS disease cases. In contrast, the isolates from diarrhoeal faeces were comprised of 18 different serovars, the mostly commonly identified being S. enterica Typhimurium (n=28), S. enterica Weltevreden (n=14) and S. enterica Stanley (n=15). S. enterica Enteritidis and S. enterica Choleraesuis were significantly more associated with systemic disease than diarrhoeal disease in this patient group (p<0.001). Conclusions We find a differing distribution of Salmonella sequence types/serovars between those causing iNTS disease and non-invasive disease in Lao. We conclude that there is a small but not insignificant burden of iNTS disease in Lao. Further clinical and epidemiological investigations are required to assess mortality and the role of comorbidities such as HIV.
Validity of the 6 minute walk test in facioscapulohumeral muscular dystrophy

Introduction: In preparation for future clinical trials, we determined the reliability, relationship to measures of disease severity, and consistency across sites of the 6 Minute Walk Test (6MWT) in patients with facioscapulohumeral muscular dystrophy (FSHD). Methods: Genetically defined and clinically affected FSHD participants at 2 sites performed the 6MWT, the Timed Up and Go, and the 30 foot Go/Timed 10 meter test as measures of mobility using standard procedures. Results: Eight‐six participants representing the full range of severity performed the 6MWT. The mean 6MWT distance was 404.3 meters (SD 123.9), with no difference between sites. The 6MWT was reliable (n = 25; intraclass correlation coefficient = 0.99) and demonstrated moderate to strong correlations with lower extremity strength, functional outcomes, and FSHD Clinical Score. Conclusions: The 6MWT is reliable and is associated with other measures of FSHD disease severity. Future directions include assessing its sensitivity to disease progression. Muscle Nerve 55: 333–337, 2017
High-dose renal replacement therapy for acute kidney injury: Systematic review and meta-analysis

Objective:To determine the effect of renal replacement therapy dose on mortality and dialysis dependence in patients with acute kidney injury. Data Sources:MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials to October 2009; PubMed “Related Articles;” bibliographies of included trials; and additional information from trial authors. Study Selection:Randomized and quasi-randomized, controlled trials in adults with acute kidney injury prescribed high- vs. standard-dose continuous renal replacement therapy (≥30 mL/kg/hr vs. <30 mL/kg/hr), intermittent hemodialysis, or sustained low-efficiency dialysis (daily vs. alternate day, or by target biochemistry). Data Extraction:Three authors independently selected studies and extracted data on outcomes and study quality. Meta-analyses used random-effects models. Data Synthesis:Of 5416 citations, 12 trials (n = 3999) met inclusion criteria. Modalities included continuous renal replacement therapy (7 trials), intermittent hemodialysis (3 trials), sustained low-efficiency dialysis (1 trial), and all three (1 trial). Study quality was moderate-high. Meta-analyses found no effect of high-dose renal replacement therapy on mortality (risk ratio, 0.89; 95% confidence interval, 0.77–1.03; 12 trials; n = 3954) or dialysis dependence among survivors (risk ratio, 1.15; 95% confidence interval, 0.92–1.44; 8 trials with events; n = 1743). The effect on mortality was similar (all interaction p values were nonsignificant) in patients with sepsis (risk ratio, 1.02; 95% confidence interval, 0.85–1.23; 9 trials; n = 1786) vs. without sepsis (risk ratio, 0.89; 95% confidence interval, 0.75–1.05; 8 trials; n = 1955), treated exclusively with continuous renal replacement therapy (risk ratio, 0.87; 95% confidence interval, 0.71–1.06; 7 trials; n = 2462) vs. other modalities alone or in combination (risk ratio, 0.92; 95% confidence interval, 0.70–1.21; 5 trials; n = 1492), and in trials with low (risk ratio, 0.96; 95% confidence interval, 0.85–1.09; 6 trials; n = 3475) vs. higher (risk ratio, 0.76; 95% confidence interval, 0.53–1.09; 6 trials; n = 479) risk of bias. Conclusions:High-dose renal replacement therapy in acute kidney injury does not improve patient survival or recovery of renal function overall or in important patient subgroups, including those with sepsis.
Sequential Decoding of Intramuscular EMG Signals via Estimation of a Markov Model

This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.
Cognitive behavior therapy for late‐life generalized anxiety disorder delivered by lay and expert providers has lasting benefits

Peaceful Living, a cognitive‐behavioral treatment (CBT) for late‐life generalized anxiety disorder (GAD), produced positive outcomes in GAD severity, anxiety, depression, insomnia, and mental health quality of life relative to usual care with treatment delivered by either bachelor‐level lay providers (BLPs) or PhD‐level expert providers (PLPs). We examined long‐term maintenance of gains during 12 months following CBT for patients in this trial who received the intervention delivered by BLPs and PLPs and completed post‐treatment assessments.
Central inhibition of granulocyte-macrophage colony-stimulating factor is analgesic in experimental neuropathic pain

Abstract With less than 50% of patients responding to the current standard of care and poor efficacy and selectivity of current treatments, neuropathic pain continues to be an area of considerable unmet medical need. Biological therapeutics such as monoclonal antibodies (mAbs) provide better intrinsic selectivity; however, delivery to the central nervous system (CNS) remains a challenge. Granulocyte-macrophage colony-stimulating factor (GM-CSF) is well described in inflammation-induced pain, and early-phase clinical trials evaluating its antagonism have exemplified its importance as a peripheral pain target. Here, we investigate the role of this cytokine in a murine model of traumatic nerve injury and show that deletion of the GM-CSF receptor or treatment with an antagonizing mAb alleviates pain. We also demonstrate enhanced analgesic efficacy using an engineered construct that has greater capacity to penetrate the CNS. Despite observing GM-CSF receptor expression in microglia and astrocytes, the gliosis response in the dorsal horn was not altered in nerve injured knockout mice compared with wild-type littermate controls as evaluated by ionized calcium binding adapter molecule 1 (Iba1) and glial fibrillary acidic protein, respectively. Functional analysis of glial cells revealed that pretreatment with GM-CSF potentiated lipopolysaccharide-induced release of proinflammatory cytokines. In summary, our data indicate that GM-CSF is a proinflammatory cytokine that contributes to nociceptive signalling through driving spinal glial cell secretion of proinflammatory mediators. In addition, we report a successful approach to accessing CNS pain targets, providing promise for central compartment delivery of analgesics.
Relationships between production and product traits in subpopulations of Bonsmara and Nguni cattle

Ninety bull calves of five Bonsmara strains, viz. Edelheer (E), T-49 (T), Wesselsvlei (W), Roodebos (R) and Belmont Red (BR), and two Nguni sub-populations, viz. Bartlow (B) and non-Bartlow (NB), were fattened under intensive feeding conditions and serially slaughtered at four different slaughter weights. Phylogenetic relationships between the five Bonsmara strains and between the two Nguni subpopulations were determined by means of blood typing. Growth performance, carcass characteristics and meat quality characteristics were compared between the sub-populations of each breed. Genetic distances between the Bonsmara animals confirmed the existence of five genetic subpopulations with variation in genetic distances between them. The genetic distance between the two Nguni subpopulations was very small, indicating genetic similarity. Means for production and product characteristics were adjusted for mean subcutaneous fat percentage by means of analysis of covariance. T gained weight faster and more efficiently on a live and carcass weight basis than the other Bonsmara groups, while B gained carcass and muscle weight more efficiently than NB. T had proportionally more meat in the high-priced cuts of the carcass than W. Muscle of the W line had a higher ageing potential (measured as myofibrillar fragmentation; MFI) than T, resulting in higher tenderness scores for W. Similarly, B had higher MFI for muscle aged for one or seven days, coupled with more tender meat than NB. Pairwise correlations between growth and muscle characteristics indicated that fast growing animals tend to produce less tender meat. South African Journal of Animal Science, Vol 31, Issue 3, Oct – Dec (2001): pp.181-194
A Framework for Rendering, Simulation and Animation of Crowds

Real-time crowd simulation for virtual environment applications requires not only navigation and locomotion in large environments while avoiding obstacles and agents, but also rendering high quality 3D fully articulated figures to enhance realism. In this paper, we present a framework for real-time simulation of crowds. The framework is composed of a Hardware Accelerated Character Animation Library (HALCA), a crowd simulation system that can handle large crowds with high densities (HiDAC), and an Animation Planning Mediator (APM) that bridges the gap between the global position of the agents given by HiDAC and the correct skeletal state so that each agent is rendered with natural locomotion in real-time. The main goal of this framework is to allow high quality visualization and animation of several hundred realistic looking characters (about 5000 polygons each) navigating virtual environments on a single display PC, a HMD (Head Mounted Display), or a CAVE system. Results of several applications on a number of platforms are presented.
Short Internal Sequences Involved in Replication and Virion Accumulation in a Subviral RNA of Turnip Crinkle Virus

ABSTRACT cis-acting sequences and structural elements in untranslated regions of viral genomes allow viral RNA-dependent RNA polymerases to correctly initiate and transcribe asymmetric levels of plus and minus strands during replication of plus-sense RNA viruses. Such elements include promoters, enhancers, and transcriptional repressors that may require interactions with distal RNA sequences for function. We previously determined that a non-sequence-specific hairpin (M1H) in the interior of a subviral RNA (satC) associated with Turnip crinkle virus is required for fitness and that its function might be to bridge flanking sequences (X. Sun and A. E. Simon, J. Virol. 77:7880-7889, 2003). To establish the importance of the flanking sequences in replication and satC-specific virion repression, segments on both sides of M1H were randomized and subjected to in vivo functional selection (in vivo SELEX). Analyses of winning (functional) sequences revealed three different conserved elements within the segments that could be specifically assigned roles in replication, virion repression, or both. One of these elements was also implicated in the molecular switch that releases the 3′ end from its interaction with the repressor hairpin H5, which is possibly involved in controlling the level of minus-strand synthesis.
Mimetic butterflies support Wallace's model of sexual dimorphism

Theoretical and empirical observations generally support Darwin's view that sexual dimorphism evolves due to sexual selection on, and deviation in, exaggerated male traits. Wallace presented a radical alternative, which is largely untested, that sexual dimorphism results from naturally selected deviation in protective female coloration. This leads to the prediction that deviation in female rather than male phenotype causes sexual dimorphism. Here I test Wallace's model of sexual dimorphism by tracing the evolutionary history of Batesian mimicry—an example of naturally selected protective coloration—on a molecular phylogeny of Papilio butterflies. I show that sexual dimorphism in Papilio is significantly correlated with both female-limited Batesian mimicry, where females are mimetic and males are non-mimetic, and with the deviation of female wing colour patterns from the ancestral patterns conserved in males. Thus, Wallace's model largely explains sexual dimorphism in Papilio. This finding, along with indirect support from recent studies on birds and lizards, suggests that Wallace's model may be more widely useful in explaining sexual dimorphism. These results also highlight the contribution of naturally selected female traits in driving phenotypic divergence between species, instead of merely facilitating the divergence in male sexual traits as described by Darwin's model.
miRNA in Macrophage Development and Function.

SIGNIFICANCE MicroRNAs (miRNAs) control cellular gene expression via primarily binding to 3' or 5' untranslated region of the target transcript leading to translational repression or mRNA degradation. In most cases, miRNAs have been observed to fine-tune the cellular responses and, therefore, act as a rheostat rather than an on/off switch. Transcription factor PU.1 is a master switch that controls monocyte/macrophage development from hematopoietic stem cells. Recent Advances: PU.1 induces a specific set of miRNAs while suppressing the miR17-92 cluster to regulate monocyte/macrophage development. In addition to development, miRNAs tightly control the macrophage polarization continuum from proinflammatory M1 or proreparative M2 by regulating expression of key transcription factors involved in the process of polarization. CRITICAL ISSUES miRNAs are intricately involved with fine-tuning fundamental macrophage functions such as phagocytosis, efferocytosis, inflammation, tissue repair, and tumor promotion. Macrophages are secretory cells that participate in intercellular communication by releasing regulatory molecules and microvesicles (MVs). MVs are bilayered lipid membranes packaging a hydrophilic cargo, including proteins and nucleic acids. Macrophage-derived MVs carry functionally active miRNAs that suppress gene expression in target cells via post-transcriptional gene silencing, thus regulating cell function. In summary, miRNAs fine-tune several major facets of macrophage development and function. Such fine-tuning is critical in preventing exaggerated macrophage response to endogenous or exogenous stimuli. FUTURE DIRECTIONS A critical role of miRNAs in the regulation of innate immune response and macrophage biology, including development, differentiation, and activation, has emerged. A clear understanding of such regulation on macrophage function remains to be elucidated. Antioxid. Redox Signal. 25, 795-804.
Privacy-Preserving Cloud-Based Grasp Planning

To support industrial automation, systems such as Grasp-it! and Dex-Net 1.0 provide Grasp Planning as a Service (GPaaS). For example, a manufacturer setting up an automated assembly line for a new product can upload part geometry to the service and receive a ranked set of robust grasp configurations, and the GPaaS can accelerate future grasp planning by statistically analyzing grasps on the part. However, many industrial users may be reluctant to share proprietary details of product geometry with any outside parties. This paper defines a privacypreserving approach to grasp planning and presents an algorithm where a masked version of the part boundary is uploaded along with stable pose configurations, allowing proprietary aspects of the part boundary to remain confidential. One challenge is the tradeoff between grasp coverage and privacy: balancing the desire for a rich set of alternative grasps (coverage) based on analysis of graspable surfaces against the user’s desire to maximize privacy. We introduce a grasp coverage metric based on dispersion, a coverage metric used in motion planning, and we formalize its relationship with privacy (the amount of the object surface that is masked). We implement our algorithm for Dex-Net 1.0 and present case studies of the privacy-coverage tradeoff on a set of 23 industrial parts. Our results suggest that masking the part using the convex hull of the proprietary zone prunes grasps in collision and provides grasp coverage with low distortion of the object similarity metric used to accelerate grasp planning in Dex-Net 1.0. We also find empirically that increasing privacy always leads to decreasing coverage, and that coverage of the set of all grasps with non-zero robustness decreases with an increasing robustness threshold.