Miracle-dz/UniFAR-FTUs huggingface dataset:
Hematopoietic cell‐derived RELMα regulates hookworm immunity through effects on macrophages

Resistin‐like molecule α (RELMα) is a highly secreted protein in type 2 (Th2) cytokine‐induced inflammation including helminth infection and allergy. In infection with Nippostrongylus brasiliensis (Nb), RELMα dampens Th2 inflammatory responses. RELMα is expressed by immune cells, and by epithelial cells (EC); however, the functional impact of immune versus EC‐derived RELMα is unknown. We generated bone marrow (BM) chimeras that were RELMα deficient (RELMα−/−) in BM or non BM cells and infected them with Nb. Non BM RELMα−/− chimeras had comparable inflammatory responses and parasite burdens to RELMα+/+ mice. In contrast, both RELMα−/− and BM RELMα−/− mice exhibited increased Nb‐induced lung and intestinal inflammation, correlated with elevated Th2 cytokines and Nb killing. CD11c+ lung macrophages were the dominant BM‐derived source of RELMα and can mediate Nb killing. Therefore, we employed a macrophage‐worm co‐culture system to investigate whether RELMα regulates macrophage‐mediated Nb killing. Compared to RELMα+/+ macrophages, RELMα−/− macrophages exhibited increased binding to Nb and functionally impaired Nb development. Supplementation with recombinant RELMα partially reversed this phenotype. Gene expression analysis revealed that RELMα decreased cell adhesion and Fc receptor signaling pathways, which are associated with macrophage‐mediated helminth killing. Collectively, these studies demonstrate that BM‐derived RELMα is necessary and sufficient to dampen Nb immune responses, and identify that one mechanism of action of RELMα is through inhibiting macrophage recruitment and interaction with Nb. Our findings suggest that RELMα acts as an immune brake that provides mutually beneficial effects for the host and parasite by limiting tissue damage and delaying parasite expulsion.
Aesthetic Comparison of Two Different Types of Web-Space Reconstruction for Finger Syndactyly

Background: Syndactyly reconstruction incorporates techniques of applying skin grafts or dorsal advancement flaps without the use of skin grafts. Comparative outcome studies of these two approaches are lacking. The authors’ study compares the long-term aesthetic outcomes of these two flap techniques. Methods: Forty-five patients were included in the authors’ study. The methods of reconstruction used were a dorsally based rectangular flap with skin graft from the groin and a dorsal pentagonal advancement flap without skin grafting. Eighteen independent raters completed a visual analogue scale and a unique classification scale to subjectively assess aesthetic outcomes. The authors used univariate analyses to determine which variables significantly influenced the outcome score. The authors then used multivariable regression models to compare the two flap types. Results: Dorsally based rectangular flaps with skin graft had statistically significantly better visual analogue scale scores and greater odds of receiving an “excellent” rating compared with dorsal pentagonal advancement flaps. Conclusions: Despite the use of skin grafting, with its associated donor-site morbidity, dorsal rectangular flaps may offer better overall aesthetic outcomes for patients. Future comparative studies should incorporate functional and patient-reported outcomes to better assess the optimal reconstruction type. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
Noncontact In-Bed Measurements of Physiological and Behavioral Signals Using an Integrated Fabric-Sheet Sensing Scheme

Home monitoring requires measuring the physiological and behavioral signals without impairing a subject's everyday life. This paper presents an integrated and noncontact approach for obtaining simultaneous physiological and behavioral signals of recumbent humans in beds using a home-monitoring application. In the proposed approach, a fabric-sheet unified sensing electrode (FUSE) obtains physiological signals by recording the electrocardiogram (ECG), chest and abdominal respiratory movements (RMs), and ballistocardiogram (BCG). The FUSE also detects the behavioral signals of body proximity (BPx) and lateral/supine lying postures. A prototype system with FUSE was validated in a short-term experiment and 6-h overnight measurements on two different groups composed of seven lying subjects. The results confirmed that the approach senses each signal independently and records the ECG, RMs, BCG, and BPx signals simultaneously. The mean sensitivities of the R and T waves of the ECG during sleep were 86.1% and 88.0%, respectively, whereas those of the chest and abdominal RMs were 90.7% and 90.1%, respectively. Although our prototype system has room for improvement, the results suggest that our approach enables the unconstrained, nocturnal monitoring of the physiological and behavioral signals in recumbent humans. The at-home monitoring of the physiological and behavioral signals is expected to contribute to cost-effective personalized healthcare in the future. This noncontact and easy-to-install system for in-bed measurements can facilitate a new era of home monitoring.
Gene expression of matrix metalloproteinase 9 (MMP9), matrix metalloproteinase 13 (MMP13), vascular endothelial growth factor (VEGF) and fibroblast growth factor 23 (FGF23) in femur and vertebra tissues of the hypovitaminosis D kyphotic pig model

Abstract The hypovitaminosis D kyphotic pig provides a reliable model to study the initiation of bone lesions caused by maternal vitamin D (D) deficiencies. Matrix metalloproteinases (MMP; specifically, MMP9 and MMP13) and vascular endothelial growth factor (VEGF) are important in endochondral ossification and are potentially regulated by D. Fibroblast growth factor 23 (FGF23) is interrelated with D homoeostasis and bone mineralisation. Relative mRNA expression of MMP9, MMP13, VEGF and FGF23 was measured in pig femur and vertebra. Sows (n 37) were fed diets with 0 (−D), 8·125 (+D) or 43·750 (++D) µg D3/kg throughout gestation and lactation. At weaning (3 weeks), pigs were fed diets with 0 (−D) or 7·0 (+D) µg D3/kg, each with 75 and 95 % (LCaP) or 150 and 120 % (HCaP) of the Ca and P requirements. Pigs at birth (n 27), 3 weeks (n 27) and after the nursery period (7 weeks; n 72) were euthanised for analysis. At 3 weeks, femur MMP9 expression of pigs produced by +D or ++D sows was reduced (P<0·05) to 0·5-fold and VEGF expression to 0·4-fold compared with pigs from –D sows. At 7 weeks, MMP9 expression was reduced (P<0·05) to 0·45-fold in femur and 0·58-fold in vertebra from pigs produced by +D or ++D sows compared with pigs from −D sows. Pig femur VEGF expression was reduced to 0·75-fold in pigs produced by ++D sows. MMP9 and VEGF mRNA expression offer potential markers for the initiation of bone lesions in the hypovitaminosis D kyphotic pig model.
Consensus Coexpression Network Analysis Identifies Key Regulators of Flower and Fruit Development in Wild Strawberry1[OPEN]

Consensus co-expression networks generate robust gene clusters and yield important insights into fertilization-induced iron transport and key floral regulators in wild strawberry. The diploid strawberry, Fragaria vesca, is a developing model system for the economically important Rosaceae family. Strawberry fleshy fruit develops from the floral receptacle and its ripening is nonclimacteric. The external seed configuration of strawberry fruit facilitates the study of seed-to-fruit cross tissue communication, particularly phytohormone biosynthesis and transport. To investigate strawberry fruit development, we previously generated spatial and temporal transcriptome data profiling F. vesca flower and fruit development pre- and postfertilization. In this study, we combined 46 of our existing RNA-seq libraries to generate coexpression networks using the Weighted Gene Co-Expression Network Analysis package in R. We then applied a post-hoc consensus clustering approach and used bootstrapping to demonstrate consensus clustering’s ability to produce robust and reproducible clusters. Further, we experimentally tested hypotheses based on the networks, including increased iron transport from the receptacle to the seed postfertilization and characterized a F. vesca floral mutant and its candidate gene. To increase their utility, the networks are presented in a web interface (www.fv.rosaceaefruits.org) for easy exploration and identification of coexpressed genes. Together, the work reported here illustrates ways to generate robust networks optimized for the mining of large transcriptome data sets, thereby providing a useful resource for hypothesis generation and experimental design in strawberry and related Rosaceae fruit crops.
A randomized placebo-controlled clinical trial of nicotinamide riboside in obese men: safety, insulin-sensitivity, and lipid-mobilizing effects.

Background Animal studies suggest a positive role for nicotinamide riboside (NR) on insulin sensitivity and hepatic steatosis in models of obesity and type 2 diabetes. NR, an NAD+ precursor, is a member of the vitamin B-3 family now available as an over-the-counter supplement. Although data from preclinical trials appear consistent, potential effects and safety need to be evaluated in human clinical trials. Objective The aim of this study was to test the safety of dietary NR supplementation over a 12-wk period and potential to improve insulin sensitivity and other metabolic parameters in obese, insulin-resistant men. Design In an investigator-initiated randomized, placebo-controlled, double-blinded, and parallel-group designed clinical trial, forty healthy, sedentary men with a body mass index (BMI) > 30 kg/m2, age-range 40-70 y were randomly assigned to 12 wk of NR (1000 mg twice daily) or placebo. We determined the effects of NR supplementation on insulin sensitivity by a hyperinsulinemic euglycemic clamp and substrate metabolism by indirect calorimetry and labeled substrates of tritiated glucose and palmitate. Body composition and fat mass distribution were determined by whole-body dual-energy X-ray absorptiometry (DXA) and MRI scans, and measurements of intrahepatic lipid content were obtained by MR spectroscopy. Results Insulin sensitivity, endogenous glucose production, and glucose disposal and oxidation were not improved by NR supplementation. Similarly, NR supplementation had no effect on resting energy expenditure, lipolysis, oxidation of lipids, or body composition. No serious adverse events due to NR supplementation were observed and safety blood tests were normal. Conclusion 12 wk of NR supplementation in doses of 2000 mg/d appears safe, but does not improve insulin sensitivity and whole-body glucose metabolism in obese, insulin-resistant men. This trial was registered at clinicaltrials.gov as NCT02303483.
Aspect opinion expression and rating prediction via LDA–CRF hybrid

Abstract In this paper, we study the problem of aspect-based sentiment analysis. Our model simultaneously extracts aspect-specific opinion expressions and determines the rating for each aspect in reviews. Previous works have mainly focused on the problem of opinion phrase extraction and aspect rating prediction in a pipelined manner and are not able to capture the dependencies of aspect opinion expression on aspect rating and vice-versa. They are also unable to discover aspect-specific opinion expressions and their associated rating scores. We present a joint modelling approach to extract aspect-specific sentiment expression and aspect rating prediction simultaneously. This paper proposes a novel LDA–CRF hybrid model which employs discriminative conditional random field component for phrase extraction, a regression component for rating prediction and a generative component for grouping aspect–sentiment expressions (aspect-specific opinion expressions) into coherent topics. To show the effectiveness of our approach, we evaluate the performance of the model on both task: (i) aspect-specific opinion expressions and (ii) rating prediction on the dataset of hotel and restaurant reviews from TripAdvisor.com. Experimental results show that both task potentially reinforce each other and joint modeling outperformed state-of-the-art baselines for each individual tasks.
Superior explicit memory despite severe developmental amnesia: In‐depth case study and neural correlates

The acquisition of new semantic memories is sometimes preserved in patients with hippocampal amnesia. Robust evidence for this comes from case reports of developmental amnesia suggesting that low‐to‐normal levels of semantic knowledge can be achieved despite compromised episodic learning. However, it is unclear whether this relative preservation of semantic memory results from normal acquisition and retrieval or from residual episodic memory, combined with effortful repetition. Furthermore, lesion studies have mainly focused on the hippocampus itself, and have seldom reported the state of structures in the extended hippocampal system. Preserved components of this system may therefore mediate residual episodic abilities, contributing to the apparent semantic preservation. We report an in‐depth study of Patient KA, a 27‐year‐old man who had severe hypoxia at birth, in which we carefully explored his residual episodic learning abilities. We used novel speeded recognition paradigms to assess whether KA could explicitly acquire and retrieve new context‐free memories. Despite a pattern of very severe amnesia, with a 44‐point discrepancy between his intelligence and memory quotients, KA exhibited normal‐to‐superior levels of knowledge, even under strict time constraints. He also exhibited normal‐to‐superior recognition memory for new material, again under strict time constraints. Multimodal neuroimaging revealed an unusual pattern of selective atrophy within each component of the extended hippocampal system, contrasting with the preservation of anterior subhippocampal cortices. A cortical thickness analysis yielded a pattern of thinner but also thicker regional cortices, pointing toward specific temporal lobe reorganization following early injury. We thus report the first case of superior explicit learning and memory in a severe case of amnesia, raising important questions about how such knowledge can be acquired.
Self-Paced Learning-Based Probability Subspace Projection for Hyperspectral Image Classification

In this paper a self-paced learning-based probability subspace projection (SL-PSP) method is proposed for hyperspectral image classification. First, a probability label is assigned for each pixel, and a risk is assigned for each labeled pixel. Then, two regularizers are developed from a self-paced maximum margin and a probability label graph, respectively. The first regularizer can increase the discriminant ability of features by gradually involving the most confident pixels into the projection to simultaneously push away heterogeneous neighbors and pull inhomogeneous neighbors. The second regularizer adopts a relaxed clustering assumption to make avail of unlabeled samples, thus accurately revealing the affinity between mixed pixels and achieving accurate classification with very few labeled samples. Several hyperspectral data sets are used to verify the effectiveness of SL-PSP, and the experimental results show that it can achieve the state-of-the-art results in terms of accuracy and stability.
CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs

Various studies have empirically shown that the majority of Java and Android applications misuse cryptographic libraries, causing devastating breaches of data security. It is crucial to detect such misuses early in the development process. To detect cryptography misuses, one must define secure uses first, a process mastered primarily by cryptography experts but not by developers. In this paper, we present CrySL, a specification language for bridging the cognitive gap between cryptography experts and developers. CrySL enables cryptography experts to specify the secure usage of the cryptographic libraries they provide. We have implemented a compiler that translates such CrySL specification into a context-sensitive and flow-sensitive demand-driven static analysis. The analysis then helps developers by automatically checking a given Java or Android app for compliance with the CrySL-encoded rules. We have designed an extensive CrySL rule set for the Java Cryptography Architecture (JCA), and empirically evaluated it by analyzing 10,000 current Android apps and all 204,788 current Java software artefacts on Maven Central. Our results show that misuse of cryptographic APIs is still widespread, with 95 percent of apps and 63 percent of Maven artefacts containing at least one misuse. Our easily extensible CrySL rule set covers more violations than previous special-purpose tools that contain hard-coded rules, while still offering a more precise analysis.
Physics-Based Quadratic Deformation Using Elastic Weighting

This paper presents a spatial reduction framework for simulating nonlinear deformable objects interactively. This reduced model is built using a small number of overlapping quadratic domains as we notice that incorporating high-order degrees of freedom (DOFs) is important for the simulation quality. Departing from existing multi-domain methods in graphics, our method interprets deformed shapes as blended quadratic transformations from nearby domains. Doing so avoids expensive safeguards against the domain coupling and improves the numerical robustness under large deformations. We present an algorithm that efficiently computes weight functions for reduced DOFs in a physics-aware manner. Inspired by the well-known multi-weight enveloping technique, our framework also allows subspace tweaking based on a few representative deformation poses. Such elastic weighting mechanism significantly extends the expressivity of the reduced model with light-weight computational efforts. Our simulator is versatile and can be well interfaced with many existing techniques. It also supports local DOF adaption to incorporate novel deformations (i.e., induced by the collision). The proposed algorithm complements state-of-the-art model reduction and domain decomposition methods by seeking for good trade-offs among animation quality, numerical robustness, pre-computation complexity, and simulation efficiency from an alternative perspective.
A Novel Approach for Real-Time Recognition of Epileptic Seizures Using Minimum Variance Modified Fuzzy Entropy

Objective: Validation of epileptic seizures annotations from long-term electroencephalogram (EEG) recordings is a tough and tedious task for the neurological community. It is a well-known fact that computerized qualitative methods thoroughly assess the complex brain dynamics toward seizure detection and proven as one of the acceptable clinical indicators. Methods: This research study suggests a novel approach for real-time recognition of epileptic seizure from EEG recordings by a technique referred as minimum variance modified fuzzy entropy (MVMFzEn). Multichannel EEG recordings of 4.36 h of epileptic seizures and 25.74 h of normal EEG were considered. Signal processing techniques such as filters and independent component analysis were appropriated to reduce noise and artifacts. Unlike, the predefined fuzzy membership function, the modified fuzzy entropy utilizes relative energy as a membership function followed by scaling operation to obtain the feature. Results: Results revealed that MVMFzEn drops abruptly during an epileptic activity and this fact was used to set a threshold. An automated threshold derived from MVMFzEn assesses the classification efficiency of the given data during validation. It was observed from the results that the proposed method yields a classification accuracy of 100% without the use of any classifier. Conclusion: The graphical user interface was designed in MATLAB to automatically label the normal and epileptic segments in the long-term EEG recordings. Significance: The ground truth clinical validation using validation specificity and validation sensitivity confirms the suitability of the proposed technique for automated annotation of epileptic seizures in real time.
A Survey of Feature Extraction in Dermoscopy Image Analysis of Skin Cancer

Dermoscopy image analysis (DIA) is a growing field, with works being published every week. This makes it difficult not only to keep track of all the contributions, but also for new researchers to identify relevant information and new directions to be explored. Several surveys have been written in the past decade, but these tend to cover all of the steps of a CAD system, which can be overwhelming. Moreover, in these works, each of the steps is briefly discussed due to lack of space. Among the different blocks of the CAD system, the most relevant is the one devoted to feature extraction. This is also the block where existing works exhibit the most variability. Therefore, we believe that it is important to review the state-of-the-art on this matter. This work thoroughly explores the several types of features that have been used in DIA. A discussion on their relevance and limitations, as well as suggestions for future research are provided.
Feature Extraction of Galvanic Skin Responses by Nonnegative Sparse Deconvolution

Wearable sensors are increasingly taking part in daily activities, not only because of the recent society health concern, but also due to their relevance in the medical industry. In this paper, a galvanic skin response (GSR) extraction technique has been developed in order to interpret electrodermal activity (EDA) records, which can be useful both for ambulatory and health applications. The core of the proposed approach is a novel feature extraction scheme that is based on a nonnegative sparse deconvolution of the observed GSR signals. Unlike previous approaches, the resulting SparsEDA algorithm is fast (immediately extracting the skin conductance level and response), efficient (being able to work with any sampling rate and signal length), and highly interpretable (due to the sparsity of the extracted phasic component of the GSR). Results on real data from 100 different subjects confirm the good performance of the method, which has been released through a free web-based code repository.
An Error Transformation Approach for Connectivity-Preserving and Collision-Avoiding Formation Tracking of Networked Uncertain Underactuated Surface Vessels

This paper investigates a distributed connectivity-preserving and collision-avoiding formation tracking problem of networked uncertain underactuated surface vessels (USVs) with heterogeneous limited communication ranges. All nonlinearities in the dynamic model are assumed to be completely unknown. Compared with the existing formation tracking results for USVs, our primary contribution is to develop a new nonlinearly transformed formation error for achieving the initial connectivity preservation, the collision avoidance, and the distributed formation tracking without switching the desired formation pattern and using any additional potential functions. In other words, these three objectives can be achieved by using only one transformed formation error surface. The local tracker design strategy using the nonlinearly transformed error is established under the direct graph topology, where the adaptive function approximation technique and the auxiliary variables are employed to compensate for uncertain nonlinearities and to deal with the underactuated problem of USVs, respectively. Finally, the Lyapunov stability analysis and simulations are performed to verify the effectiveness of the proposed theoretic result.