Miracle-dz/UniFAR-FTUs huggingface dataset:
PERK mediates the IRES-dependent translational activation of mRNAs encoding angiogenic growth factors after ischemic stress

PERK may promote blood vessel growth in oxygen-deprived muscles by ensuring the production of angiogenic factors. PERKing blood flow during ischemia Oxygen deprivation of tissues occurs both physiologically, such as during exercise, and pathologically, such as during stroke or heart attack. The oxygen deprivation that occurs during ischemia causes endoplasmic reticulum (ER) stress, during which most mRNA translation is inhibited to conserve cellular resources. But in ischemic muscles, some mRNAs are translated through an alternative mechanism. These include those encoding VEGF and FGF-2, factors that stimulate blood vessel formation. Philippe et al. found that ER stress in cells and in mice activated the translation of the mRNAs for VEGF and FGF-2 through the alternative mechanism. The kinase PERK, which is activated during ER stress, mediated this translational activation. Administration of a PERK inhibitor to mice before ischemia prevented the translation of the mRNAs for VEGF and FGF-2, raising the possibility that PERK manipulation could be used to increase blood flow in ischemic tissues. Angiogenesis is induced by various conditions, including hypoxia. Although cap-dependent translation is globally inhibited during ischemia, the mRNAs encoding two important proangiogenic growth factors, vascular endothelial growth factor (VEGF) and fibroblast growth factor 2 (FGF-2), are translated at early time points in ischemic muscle. The translation of these mRNAs can occur through internal ribosome entry sites (IRESs), rather than through cap-dependent translation. Hypoxic conditions also induce the unfolded protein response (UPR) and endoplasmic reticulum (ER) stress, leading us to assess the interplay between hypoxia, ER stress, and IRES-mediated translation of FGF-2 and VEGF. We found that unlike cap-dependent translation, translation through FGF-2 and VEGF IRESs was efficient in cells and transgenic mice subjected to ER stress–inducing stimuli. We identified PERK, a kinase that is activated by ER stress, as the driver of VEGF and FGF-2 IRES–mediated translation in cells and in mice expressing IRES-driven reporter genes and exposed to hypoxic stress. These results demonstrate the role of IRES-dependent translation in the induction of the proangiogenic factors VEGF and FGF-2 in response to acute hypoxic stress. Furthermore, the PERK pathway could be a viable pharmacological target to improve physiological responses to ischemic situations.
Evaluating the Consistency of Current Mainstream Wearable Devices in Health Monitoring: A Comparison Under Free-Living Conditions

Background Wearable devices are gaining increasing market attention; however, the monitoring accuracy and consistency of the devices remains unknown. Objective The purpose of this study was to assess the consistency of the monitoring measurements of the latest wearable devices in the state of normal activities to provide advice to the industry and support to consumers in making purchasing choices. Methods Ten pieces of representative wearable devices (2 smart watches, 4 smart bracelets of Chinese brands or foreign brands, and 4 mobile phone apps) were selected, and 5 subjects were employed to simultaneously use all the devices and the apps. From these devices, intact health monitoring data were acquired for 5 consecutive days and analyzed on the degree of differences and the relationships of the monitoring measurements by the different devices. Results The daily measurements by the different devices fluctuated greatly, and the coefficient of variation (CV) fluctuated in the range of 2-38% for the number of steps, 5-30% for distance, 19-112% for activity duration, . 1-17% for total energy expenditure (EE), 22-100% for activity EE, 2-44% for sleep duration, and 35-117% for deep sleep duration. After integrating the measurement data of 25 days among the devices, the measurements of the number of steps (intraclass correlation coefficient, ICC=.89) and distance (ICC=.84) displayed excellent consistencies, followed by those of activity duration (ICC=.59) and the total EE (ICC=.59) and activity EE (ICC=.57). However, the measurements for sleep duration (ICC=.30) and deep sleep duration (ICC=.27) were poor. For most devices, there was a strong correlation between the number of steps and distance measurements (R2>.95), and for some devices, there was a strong correlation between activity duration measurements and EE measurements (R2>.7). A strong correlation was observed in the measurements of steps, distance and EE from smart watches and mobile phones of the same brand, Apple or Samsung (r>.88). Conclusions Although wearable devices are developing rapidly, the current mainstream devices are only reliable in measuring the number of steps and distance, which can be used as health assessment indicators. However, the measurement consistencies of activity duration, EE, sleep quality, and so on, are still inadequate, which require further investigation and improved algorithms.
Retrofitting reinforced concrete beams by bolting steel plates to their sides -Part 2: Transverse interaction and rigid plastic design

In a companion paper, tests on bolted side plated beams have shown that side plates can substantially increase the strength of existing reinforced concrete beams with little if any loss of ductility and, furthermore, induce a gradual mode of failure after commencement of concrete crushing. However, it was also shown that transverse interaction between the side plates and the reinforced concrete beam, that is vertical slip and which is a concept unique to side plated beams, is detrimental. Transverse interaction increases the forces on the bolt shear connectors and, hence, weakens the beam. It also reduces the ability of the composite plated beam to yield and, hence, to attain its full flexural capacity. The generic concept of transverse interaction will be described in this paper and the results used to develop a new form of rigid plastic analysis for bolted side plated beams which is illustrated with an application.
Monoclonal Antibodies Targeting the Alpha-Exosite of Botulinum Neurotoxin Serotype/A Inhibit Catalytic Activity

The paralytic disease botulism is caused by botulinum neurotoxins (BoNT), multi-domain proteins containing a zinc endopeptidase that cleaves the cognate SNARE protein, thereby blocking acetylcholine neurotransmitter release. Antitoxins currently used to treat botulism neutralize circulating BoNT but cannot enter, bind to or neutralize BoNT that has already entered the neuron. The light chain endopeptidase domain (LC) of BoNT serotype A (BoNT/A) was targeted for generation of monoclonal antibodies (mAbs) that could reverse paralysis resulting from intoxication by BoNT/A. Single-chain variable fragment (scFv) libraries from immunized humans and mice were displayed on the surface of yeast, and 19 BoNT/A LC-specific mAbs were isolated by using fluorescence-activated cell sorting (FACS). Affinities of the mAbs for BoNT/A LC ranged from a KD value of 9.0×10−11 M to 3.53×10−8 M (mean KD 5.38×10−9 M and median KD 1.53×10−9 M), as determined by flow cytometry analysis. Eleven mAbs inhibited BoNT/A LC catalytic activity with IC50 values ranging from 8.3 ~73×10−9 M. The fine epitopes of selected mAbs were also mapped by alanine-scanning mutagenesis, revealing that the inhibitory mAbs bound the α-exosite region remote from the BoNT/A LC catalytic center. The results provide mAbs that could prove useful for intracellular reversal of paralysis post-intoxication and further define epitopes that could be targeted by small molecule inhibitors.
Integration of Gravitational Torques in Cerebellar Pathways Allows for the Dynamic Inverse Computation of Vertical Pointing Movements of a Robot Arm

Background Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). Methodology/Principal Findings This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. Conclusions/Significance This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field.
Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer-Broadleaf Forest: Comparison with Airborne Laser Scanning

Unmanned aerial vehicles (UAVs) and digital photogrammetric techniques are two recent advances in remote sensing (RS) technology that are emerging as alternatives to high-cost airborne laser scanning (ALS) data sources. Despite the potential of UAVs in forestry applications, very few studies have included detailed analyses of UAV photogrammetric products at larger scales or over a range of forest types, including mixed conifer–broadleaf forests. In this study, we assessed the performance of fixed-wing UAV photogrammetric products of a mixed conifer–broadleaf forest with varying levels of canopy structural complexity. We demonstrate that fixed-wing UAVs are capable of efficiently collecting image data at local scales and that UAV imagery can be effectively utilized with digital photogrammetric techniques to provide detailed automated reconstruction of the three-dimensional (3D) canopy surface of mixed conifer–broadleaf forests. When combined with an accurate digital terrain model (DTM), UAV photogrammetric products are promising for producing reliable structural measurements of the forest canopy. However, the performance of UAV photogrammetric products is likely to be influenced by the structural complexity of the forest canopy. Furthermore, we highlight the potential of fixed-wing UAVs in operational forest management at the forest management compartment level, for acquiring high-resolution imagery at low cost. A future direction of this research would be to address the issue of how well the photogrammetric products can predict the actual structure of mixed conifer–broadleaf forests.
Human Mesenchymal Stem Cells Behavior on Synthetic Coral Scaffold

For bone tissue engineering, corals have long history to be used as scaffold to promote bone regeneration. However the use of a lot of corals may damage their habitates. For this reason, a strategy to mimic coral in a synthetic form is needed. As an ideal scaffold, synthetic coral must provide structure and initial support for cell attachment and proliferation. The aim of this study was to investigate the attachment and proliferation of human Mesenchymal Stem Cells (h-MSC) on synthetic coral scaffold, to provide information on the behavior of h-MSC on the designated scaffold. Synthetic coral scaffolds were prepared from bovine gelatine and CaCO3 with 5:5 in 10% w/v concentration in aquadest. Sodium citrate was used as dispersant in the suspension. Gelatin-CaCO3 suspension was moulded in a plastic cover of 24 well plate, then freezed at -20°C for 24 hours, freeze dried for 24 hours and continued by dehydrothermal crosslinking for 72 hours. After the fabrication, synthetic coral scaffolds were subjects to cover the bottom of the well for cell culture. Human Mesenchymal Stem Cells (h-MSC) were seeded and divided into 2 groups, control group without scaffold and the one with scaffold. All groups were incubated for 3, 6, and 24 hours. Cells attatchment were determined by deduction of the cells unattached from total cells seeding. Proliferation of h-MSC were done in 3 groups ie. , control group without scaffold, scaffold only and scaffold incorporated Platelet Rich Plasma (PRP) in the bottom of well. All groups were incubated for 24, 48 and 72 hours. Human Mesenchymal Stem Cells attached faster to synthetic coral scaffold than the control. Its proliferation behavior was faster in the scaffold incorporated PRP, showing better interaction of scaffold and cells with the incorporation of morphogenetic factor.
COCACOLA: binning metagenomic contigs using sequence COmposition, read CoverAge, CO‐alignment and paired‐end read LinkAge

Motivation: The advent of next‐generation sequencing technologies enables researchers to sequence complex microbial communities directly from the environment. Because assembly typically produces only genome fragments, also known as contigs, instead of an entire genome, it is crucial to group them into operational taxonomic units (OTUs) for further taxonomic profiling and down‐streaming functional analysis. OTU clustering is also referred to as binning. We present COCACOLA, a general framework automatically bin contigs into OTUs based on sequence composition and coverage across multiple samples. Results: The effectiveness of COCACOLA is demonstrated in both simulated and real datasets in comparison with state‐of‐art binning approaches such as CONCOCT, GroopM, MaxBin and MetaBAT. The superior performance of COCACOLA relies on two aspects. One is using L1 distance instead of Euclidean distance for better taxonomic identification during initialization. More importantly, COCACOLA takes advantage of both hard clustering and soft clustering by sparsity regularization. In addition, the COCACOLA framework seamlessly embraces customized knowledge to facilitate binning accuracy. In our study, we have investigated two types of additional knowledge, the co‐alignment to reference genomes and linkage of contigs provided by paired‐end reads, as well as the ensemble of both. We find that both co‐alignment and linkage information further improve binning in the majority of cases. COCACOLA is scalable and faster than CONCOCT, GroopM, MaxBin and MetaBAT. Availability and implementation: The software is available at https://github.com/younglululu/COCACOLA. Contact: fsun@usc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Coir fibre composites: from fibre properties to interfacial adhesion and mechanical properties of composites

Vietnamese coir fibres are studied and modified for use in composite materials. Tensile properties of the fibres are characterized using single fibre tensile tests, in which optical strain mapping is used to determine fibre strain, to produce more reliable values of Emodulus and strain at failure. In this study, the interface of unidirectional (UD) composites of untreated and 5% alkali treated coir fibres in thermoplastic matrices (polypropylene, maleic anhydride grafted polypropylene and polyvinylidene fluoride) is investigated using wetting analysis and interfacial mechanical tests. The results show that the interfacial adhesion of both untreated and treated fibres with maleic anhydride grafted polypropylene and polyvinylidene fluoride are higher than in case of polypropylene. When comparing untreated and treated fibres, the interfacial strength of the alkali treated fibre composites is increased. Mechanical properties of the UD composites are assessed by flexural tests in fibre direction and unnotched Izod impact tests. In agreement with the interface evaluation, higher flexural strength and stiffness are found in treated fibre composites, probably thanks to the better interfacial adhesion. The impact strength of coir thermoplastic composite is not significantly different from that of neat polymer, while coir fibres can improve the toughness of the epoxy by minimum a factor of three, when the impact strength is considered as toughness indicator.
Control-Aware Motion Planning for Task-Constrained Aerial Manipulation

This letter presents a new method to address the problem of task-constrained motion planning for aerial manipulators. We propose a control-aware planner based on the paradigm of tight coupling between planning and control. Such paradigm is especially useful in aerial manipulation, where the separation between planning and control is not advisable. The proposed sampling based motion planner uses a controller composed of a second-order inverse kinematics algorithm and a dynamic tracker, as a local planner, thus allowing a more natural consideration of the closed-loop system dynamics. For task-constrained motions, this method let us to sample directly in the reduced and more relevant task space, predict the behavior of the controller avoiding motions that bring to singularities or large tracking errors, and guarantee the correct execution of the maneuver. The method is tested in simulation for a multidirectional-thrust vehicle endowed with a 2-DoF manipulator. The proposed approach is very general, and could be applied to ground and underwater robotic systems to perform manipulation or inspection tasks.
mHealth text and voice communication for monitoring people with chronic diseases in low-resource settings: a realist review

Background Routine monitoring by patients and healthcare providers to manage chronic disease is vital, though this can be challenging in low-resourced health systems. Mobile health (mHealth) has been proposed as one way to improve management of chronic diseases. Past mHealth reviews have proposed the need for a greater understanding around how the theoretical constructs in mHealth interventions actually work. In response, we synthesised evidence from primary studies on monitoring of chronic diseases using two-way digital text or voice communication between a patient and health worker. We did this in order to understand the important considerations for the design of mHealth interventions. Method Articles retrieved were systematically screened and analysed to elicit explanations of mHealth monitoring interventions. These explanations were consolidated into programme theory and compared with existing theory and frameworks. We identified variation in outcomes to understand how context moderates the outcome. Results Four articles were identified—monitoring of hypertension and HIV/AIDS from: Kenya, Pakistan, Honduras and Mexico and South Africa. Six components were found in all four interventions: reminders, patient observation of health state, motivational education/advice, provision of support communication, targeted actions and praise and encouragement. Intervention components were mapped to existing frameworks and theory. Variation in outcome identified in subgroup analysis suggests greater impact is achieved with certain patient groups, such as those with low literacy, those with stressful life events or those early in the disease trajectory. There was no other evidence in the included studies of the effect of context on the intervention and outcome. Conclusion mHealth interventions for monitoring chronic disease in low-resource settings, based on existing frameworks and theory, can be effective. A match between what the intervention provides and the needs or social factors relevant to specific patient group increases the effect. It was not possible to understand the impact of context on intervention and outcome beyond these patient-level measures as no evidence was provided in the study reports.
Compact, Printed, Tri-Band Loop Antenna With Capacitively-Driven Feed and End-Loaded Inductor for Notebook Computer Applications

The shorted monopoles and the planar inverted-F antennas have been utilized for wireless local area network (WLAN) notebook applications for years. This paper presents an alternative and yet promising antenna type with a compact and smaller size of 5 mm $\times20$ mm to operate in the 2.4 GHz (2400–2484 MHz), 5.2 GHz (5150–5350 MHz), and 5.8 GHz (5725–5825 MHz) WLAN bands. The loop antenna, formed on a 0.4-mm-thick FR4 substrate, was adopted in this study. The loop radiator comprised a capacitively-driven feed and an end-loaded inductor. The capacitively-driven feed allowed the antenna to generate the quarter-wavelength loop resonance for possible lowest resonant mode excitation in addition to the loop’s half-wavelength mode. By loading an inductor at the loop end to be connected to the small antenna ground, the operating frequencies of the quarter- and half-wavelength resonances were further decreased to cover the 2.4 and 5.2/5.8 GHz bands with good input impedance therein.
Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis

Aims Traditional prognostic risk assessment in patients undergoing non-invasive imaging is based upon a limited selection of clinical and imaging findings. Machine learning (ML) can consider a greater number and complexity of variables. Therefore, we investigated the feasibility and accuracy of ML to predict 5-year all-cause mortality (ACM) in patients undergoing coronary computed tomographic angiography (CCTA), and compared the performance to existing clinical or CCTA metrics. Methods and results The analysis included 10 030 patients with suspected coronary artery disease and 5-year follow-up from the COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter registry. All patients underwent CCTA as their standard of care. Twenty-five clinical and 44 CCTA parameters were evaluated, including segment stenosis score (SSS), segment involvement score (SIS), modified Duke index (DI), number of segments with non-calcified, mixed or calcified plaques, age, sex, gender, standard cardiovascular risk factors, and Framingham risk score (FRS). Machine learning involved automated feature selection by information gain ranking, model building with a boosted ensemble algorithm, and 10-fold stratified cross-validation. Seven hundred and forty-five patients died during 5-year follow-up. Machine learning exhibited a higher area-under-curve compared with the FRS or CCTA severity scores alone (SSS, SIS, DI) for predicting all-cause mortality (ML: 0.79 vs. FRS: 0.61, SSS: 0.64, SIS: 0.64, DI: 0.62; P< 0.001). Conclusions Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.