Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptomic Signature of Right Ventricular Failure in Experimental Pulmonary Arterial Hypertension: Deep Sequencing Demonstrates Mitochondrial, Fibrotic, Inflammatory and Angiogenic Abnormalities

Right ventricular failure (RVF) remains the leading cause of death in pulmonary arterial hypertension (PAH). We investigated the transcriptomic signature of RVF in hemodynamically well-phenotyped monocrotaline (MCT)-treated, male, Sprague-Dawley rats with severe PAH and decompensated RVF (increased right ventricular (RV) end diastolic volume (EDV), decreased cardiac output (CO), tricuspid annular plane systolic excursion (TAPSE) and ventricular-arterial decoupling). RNA sequencing revealed 2547 differentially regulated transcripts in MCT-RVF RVs. Multiple enriched gene ontology (GO) terms converged on mitochondria/metabolism, fibrosis, inflammation, and angiogenesis. The mitochondrial transcriptomic pathway is the most affected in RVF, with 413 dysregulated genes. Downregulated genes included TFAM (−0.45-fold), suggesting impaired mitochondrial biogenesis, CYP2E1 (−3.8-fold), a monooxygenase which when downregulated increases oxidative stress, dehydrogenase/reductase 7C (DHRS7C) (−2.8-fold), consistent with excessive autonomic activation, and polypeptide N-acetyl-galactose-aminyl-transferase 13 (GALNT13), a known pulmonary hypertension (PH) biomarker (−2.7-fold). The most up-regulated gene encodes Periostin (POSTN; 4.5-fold), a matricellular protein relevant to fibrosis. Other dysregulated genes relevant to fibrosis include latent-transforming growth factor beta-binding protein 2 (LTBP2), thrombospondin4 (THBS4). We also identified one dysregulated gene relevant to all disordered transcriptomic pathways, ANNEXIN A1. This anti-inflammatory, phospholipid-binding mediator, is a putative target for therapy in RVF-PAH. Comparison of expression profiles in the MCT-RV with published microarray data from the RV of pulmonary artery-banded mice and humans with bone morphogenetic protein receptor type 2 (BMPR2)-mutations PAH reveals substantial conservation of gene dysregulation, which may facilitate clinical translation of preclinical therapeutic and biomarkers studies. Transcriptomics reveals the molecular fingerprint of RVF to be heavily characterized by mitochondrial dysfunction, fibrosis and inflammation.
Hamiltonian Descent Methods

We propose a family of optimization methods that achieve linear convergence using first-order gradient information and constant step sizes on a class of convex functions much larger than the smooth and strongly convex ones. This larger class includes functions whose second derivatives may be singular or unbounded at their minima. Our methods are discretizations of conformal Hamiltonian dynamics, which generalize the classical momentum method to model the motion of a particle with non-standard kinetic energy exposed to a dissipative force and the gradient field of the function of interest. They are first-order in the sense that they require only gradient computation. Yet, crucially the kinetic gradient map can be designed to incorporate information about the convex conjugate in a fashion that allows for linear convergence on convex functions that may be non-smooth or non-strongly convex. We study in detail one implicit and two explicit methods. For one explicit method, we provide conditions under which it converges to stationary points of non-convex functions. For all, we provide conditions on the convex function and kinetic energy pair that guarantee linear convergence, and show that these conditions can be satisfied by functions with power growth. In sum, these methods expand the class of convex functions on which linear convergence is possible with first-order computation.
Plant A20/AN1 protein serves as the important hub to mediate antiviral immunity

Salicylic acid (SA) is a key phytohormone that mediates a broad spectrum of resistance against a diverse range of viruses; however, the downstream pathway of SA governed antiviral immune response remains largely to be explored. Here, we identified an orchid protein containing A20 and AN1 zinc finger domains, designated Pha13. Pha13 is up-regulated upon virus infection, and the transgenic monocot orchid and dicot Arabidopsis overexpressing orchid Pha13 conferred greater resistance to different viruses. In addition, our data showed that Arabidopsis homolog of Pha13, AtSAP5, is also involved in virus resistance. Pha13 and AtSAP5 are early induced by exogenous SA treatment, and participate in the expression of SA-mediated immune responsive genes, including the master regulator gene of plant immunity, NPR1, as well as NPR1-independent virus defense genes. SA also induced the proteasome degradation of Pha13. Functional domain analysis revealed that AN1 domain of Pha13 is involved in expression of orchid NPR1 through its AN1 domain, whereas dual A20/AN1 domains orchestrated the overall virus resistance. Subcellular localization analysis suggested that Pha13 can be found localized in the nucleus. Self-ubiquitination assay revealed that Pha13 confer E3 ligase activity, and the main E3 ligase activity was mapped to the A20 domain. Identification of Pha13 interacting proteins and substrate by yeast two-hybrid screening revealed mainly ubiquitin proteins. Further detailed biochemical analysis revealed that A20 domain of Pha13 binds to various polyubiquitin chains, suggesting that Pha13 may interact with multiple ubiquitinated proteins. Our findings revealed that Pha13 serves as an important regulatory hub in plant antiviral immunity, and uncover a delicate mode of immune regulation through the coordination of A20 and/or AN1 domains, as well as through the modulation of E3 ligase and ubiquitin chain binding activity of Pha13.
Longitudinal Findings of MRI and PET in West Syndrome with Subtle Focal Cortical Dysplasia

BACKGROUND AND PURPOSE: Despite the development of neuroimaging, identification of focal cortical dysplasia remains challenging. The purpose of this study was to show the longitudinal changes of MR imaging and FDG-PET in patients with West syndrome and subtle focal cortical dysplasia. MATERIALS AND METHODS: Among 52 consecutive patients with West syndrome, 4 were diagnosed with subtle focal cortical dysplasia on 3T MR imaging. MR imaging and PET findings were evaluated longitudinally at onset and at 12 and 24 months of age. RESULTS: At the onset of West syndrome, MR imaging demonstrated focal signal abnormalities of the subcortical white matter in 2 patients. In the other 2 patients, focal subcortical high-intensity signals became visible on follow-up T2WI as myelination progressed. PET at onset showed focal cortical hypometabolism in 3 patients, with 1 of these patients also having focal hypermetabolism and 1 having normal findings. On PET at 24 months, hypometabolism persisted in 2 patients and disappeared in 1, and hypermetabolism disappeared in 1. In 1 patient with normal MR imaging and PET findings at onset, focal hyperintensity and hypometabolism first appeared at 24 months of age. The findings on MR imaging and PET in these patients evolved differently with brain maturation and the clinical course. CONCLUSIONS: Subtle focal cortical dysplasia can be undetectable on MR imaging at the onset of West syndrome and is not always accompanied by hypometabolism or hypermetabolism on PET. Longitudinal MR imaging and PET studies may be useful for detecting such lesions. Even in West syndrome with a congenital structural abnormality, PET findings evolve differently with brain maturation and the clinical condition.
Modulation of septin higher-order structure by the Cdc28 protein kinase

Septins are a family of eukaryotic guanosine phosphate-binding proteins that form linear heterooligomeric complexes, which, in turn, polymerize end-on-end into filaments. These filaments further assemble into higher-order structures at distinct subcellular locations. Dynamic changes in the organization of septin cortex structures appear during cell cycle progression. A variety of regulatory proteins and posttranslational modifications are involved in changes to the structure of septin assemblies during the entire cell cycle. In particular, septin-associated protein kinases mediate changes to septin higher order structures or interconnect cellular morphogenesis with the cell cycle. Yeast cyclin-dependent kinase, a master cell cycle regulator, is required for the initiation of a new septin ring. Here, using epifluoresence and electron microscopy, we show that upon phosphorylation by the Cdc28 kinase, septin filaments disassemble into hetero-octameric building blocks, and that filament depolymerization is specifically G1 cyclin-dependent.
Reversal of Triple-Negative Breast Cancer EMT by miR-200c Decreases Tryptophan Catabolism and a Program of Immunosuppression

Tryptophan-2,3-dioxygenase (TDO2), a rate-limiting enzyme in the tryptophan catabolism pathway, is induced in triple-negative breast cancer (TNBC) by inflammatory signals and anchorage-independent conditions. TNBCs express extremely low levels of the miR-200 family compared with estrogen receptor–positive (ER+) breast cancer. In normal epithelial cells and ER+ breast cancers and cell lines, high levels of the family member miR-200c serve to target and repress genes involved in epithelial-to-mesenchymal transition (EMT). To identify mechanism(s) that permit TNBC to express TDO2 and other proteins not expressed in the more well-differentiated ER+ breast cancers, miRNA-200c was restored in TNBC cell lines. The data demonstrate that miR-200c targeted TDO2 directly resulting in reduced production of the immunosuppressive metabolite kynurenine. Furthermore, in addition to reversing a classic EMT signature, miR-200c repressed many genes encoding immunosuppressive factors including CD274/CD273, HMOX-1, and GDF15. Restoration of miR-200c revealed a mechanism, whereby TNBC hijacks a gene expression program reminiscent of that used by trophoblasts to suppress the maternal immune system to ensure fetal tolerance during pregnancy. Implications: Knowledge of the regulation of tumor-derived immunosuppressive factors will facilitate development of novel therapeutic strategies that complement current immunotherapy to reduce mortality for patients with TNBC.
Adaptive Temporal Pooling for Object Detection using Dynamic Vision Sensor

Dynamic Vision Sensor (DVS) is a kind of asynchronous sensor which can capture visual information with low power consumption. Encouraged by the superior properties of DVS, we propose a novel object detection method for DVS. The imaging of DVS is highly related to the object motion speed. For sparse events induced by slow motions, directly applying existing object detection methods cannot obtain reliable features, leading to loss in performance. For this issue, we introduce a new model to extract motion invariant features for object detection using DVS, namely recursive adaptive temporal pooling. The model works in a recursive manner and adaptively integrates features in varied time interval into a holistic representation for current time-step with respect to the motion speed. The pooled features are then fed into a detection sub-network to produce the final results. Our framework is end-to-end trainable and is highly efficient benefitting from the recursive manner and the characteristics of DVS data. Our method is evaluated on a large DVS dataset with about 100k ground-truth images and compared with the state-of-the-art methods. Experiments demonstrate the effectiveness and efficiency of our method. c © 2017. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. 2 JIA LI ET AL: ADAPTIVE TEMPORAL POOLING FOR OBJECT DETECTION Figure 1: (a) (e) are the spatial-temporal volume of the same event stream, with each dot representing an event. The motion in the stream is slow at the first and gets fast at the end. (b)(c)(d) are DVS images with certain integration time interval. With the same integration time interval, the contours of the hands show clearly for fast motion (b) while very sparse events are generated for slow motion (c). However, within a longer time interval, the contours of the hands in slow motion become clear as shown in (d).
Claims, Evidence, and Reasoning: Demystifying Data during a Unit on Simple Machines.

fifth-grade class is in the middle of a unit on simple machines. The teacher, Mr. Martin, asks his class, “Does a lever make work easier? ” One student responds, “I think it makes work easier,” another student disagrees stating, “I think it depends. ” Mr. Martin then responds, “Each of you has just stated a claim. By the end of our investigations today you will be able to provide evidence to prove which claim is actually correct. ”
TeamSTEPPS® : An evidence-based approach to reduce clinical errors threatening safety in outpatient settings: An integrative review.

OBJECTIVE The objective of this integrative review of literature was to investigate and evaluate feasibility and potential for success of TeamSTEPPS® implementation, the influence of TeamSTEPPS for Office-Based Care on the clinical error rate in a private outpatient clinic, and influence of TeamSTEPPS for Office-Based Care on patient satisfaction. BACKGROUND Patient safety remains a top priority for all health care providers in all clinical settings. Despite multiple varied efforts, clinical errors directly attributed to communication are consistently at the top of the list of root causes, although improvement strategies such as Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) have been implemented, there is insufficient data reported measuring the influence of this intervention on patient safety, clinical errors related to communication, and patient satisfaction. SEARCH STRATEGY A systematic search of the electronic databases MEDLINE Complete, CINAHL Complete, Embase, and Science Direct was conducted to seek literature that reported the effectiveness of the TeamSTEPPS tool to reduce clinical errors, improve communication, and increase patient satisfaction. Nineteen studies met inclusion criteria. Levels of evidence for each study was determined using the 2009 American Association of Critical Care Nursing (AACN) levels. CONCLUSIONS The present review is consistent with marked improvement in communication, decrease in clinical error rates, and improvement in patient satisfaction. There is a significant need for evaluation of the impact of this validated toolkit from the Agency for Healthcare Research and Quality to maintain a sustainable health care environment for all stakeholders. As a result of this integrative review, a quality improvement project related to both the primary and secondary end points is in progress.
Pseudobulbar affect after stroke: a narrative review

ABSTRACT Background: Pseudobulbar affect (PBA) is a neuropsychological condition of emotional lability and affective dysregulation associated with a variety of neurological conditions such as stroke, traumatic brain disease, and neurodegenerative disease. The true prevalence and medico-social burden of PBA associated with stroke is unclear. Often confused with post-stroke mood disorders, PBA is under-recognized and under-treated. Objective: To provide a comprehensive narrative synthesis of published literature on the topic of PBA. Methods: Literature review was performed by searching the key words “pseudobulbar atrophy”, “emotional incontinence,” and “stroke” in PubMed. Only manuscripts published in English were appraised and relevant content was extracted, synthesized, and summarized. Results: A narrative overview was performed on the following topics: epidemiology, pathophysiology, clinical features of differential diagnosis, impact on public health, and therapeutic options. Conclusion: PBA remains an under-treated condition with significant psychosocial burden on both effected stroke survivors and their families. Advances have been made in developing consensus-based clinical diagnostic criteria for PBA. Early identification and prompt initiation of therapeutic measures are required in these stroke patients. Further research is needed to develop better PBA diagnostic criteria and more cost-effective therapeutic treatment options.
High-Accuracy Inference in Neuromorphic Circuits using Hardware-Aware Training

Neuromorphic Multiply-And-Accumulate (MAC) circuits utilizing synaptic weight elements based on SRAM or novel Non-Volatile Memories (NVMs) provide a promising approach for highly efficient hardware representations of neural networks. NVM density and robustness requirements suggest that off-line training is the right choice for ``edge'' devices, since the requirements for synapse precision are much less stringent. However, off-line training using ideal mathematical weights and activations can result in significant loss of inference accuracy when applied to non-ideal hardware. Non-idealities such as multi-bit quantization of weights and activations, non-linearity of weights, finite max/min ratios of NVM elements, and asymmetry of positive and negative weight components all result in degraded inference accuracy. In this work, it is demonstrated that non-ideal Multi-Layer Perceptron (MLP) architectures using low bitwidth weights and activations can be trained with negligible loss of inference accuracy relative to their Floating Point-trained counterparts using a proposed off-line, continuously differentiable HW-aware training algorithm. The proposed algorithm is applicable to a wide range of hardware models, and uses only standard neural network training methods. The algorithm is demonstrated on the MNIST and EMNIST datasets, using standard MLPs.
Adversarial Feature Sampling Learning for Efficient Visual Tracking

The tracking-by-detection tracking framework usually consists of two stages: drawing samples around the target object and classifying each sample as either the target object or background. Current popular trackers under this framework typically draw many samples from the raw image and feed them into the deep neural networks, resulting in high computational burden and low tracking speed. In this article, we propose an adversarial feature sampling learning (AFSL) method to address this problem. A convolutional neural network is designed, which takes only one cropped image around the target object as input, and samples are collected from the feature maps with spatial bilinear resampling. To enrich the appearance variations of positive samples in the feature space, which has limited spatial resolution, we fuse the high-level features and low-level features to better describe the target by using a generative adversarial network. Extensive experiments on benchmark data sets demonstrate that the proposed ASFL achieves leading tracking accuracy while significantly accelerating the speed of tracking-by-detection trackers. Note to Practitioners—Visual tracking can be applied in many intelligent automation systems, such as robotic intelligent navigation system, intelligent human–computer interaction system, and so on. In a robotic intelligent navigation system, visual tracking can generate target’s motion trajectory from image sequences. Visual tracking can also obtain body movement information automatically during the interactive process in the intelligent human–computer interaction system. Accuracy and speed are two key indicators for visual tracking, and intelligent automation systems usually need a tracker with more accuracy and faster speed. This article aims to develop a fast and accurate tracking method by adversarial feature sampling learning (AFSL). In the concrete implementation process, AFSL gets samples by sampling in the feature space rather than on raw images to reduce computation. Then, an adversarial learning mechanism is adopted to boost the sampling features and enrich the target appearances in the feature space to improve the tracking accuracy. The proposed tracker is proven to be effective to keep leading tracking accuracy while significantly accelerating the tracking speed.
Antigen binding allosterically promotes Fc receptor recognition

ABSTRACT A key question in immunology is whether antigen recognition and Fc receptor (FcR) binding are allosterically linked. This question is also relevant for therapeutic antibody design. Antibody Fab and Fc domains are connected by flexible unstructured hinge region. Fc chains have conserved glycosylation sites at Asn297, with each conjugated to a core heptasaccharide and forming biantennary Fc glycan. The glycans modulate the Fc conformations and functions. It is well known that the antibody Fab and Fc domains and glycan affect antibody activity, but whether these elements act independently or synergistically is still uncertain. We simulated four antibody complexes: free antibody, antigen-bound antibody, FcR-bound antibody, and an antigen-antibody-FcR complex. We found that, in the antibody’s “T/Y” conformation, the glycans, and the Fc domain all respond to antigen binding, with the antibody population shifting to two dominant clusters, both with the Fc-receptor binding site open. The simulations reveal that the Fc-glycan-receptor complexes also segregate into two conformational clusters, one corresponding to the antigen-free antibody-FcR baseline binding, and the other with an antigen-enhanced antibody-FcR interaction. Our study confirmed allosteric communications in antibody-antigen recognition and following FcR activation. Even though we observed allosteric communications through the IgG domains, the most important mechanism that we observed is the communication via population shift, stimulated by antigen binding and propagating to influence FcR recognition.
Pansharpening via Locality-Constrained Sparse Representation

Recently, sparse representation based approaches have been shown an effective performance for pansharpening. However, these methods imposed `0 or `1 -norm constraints on the sparse coefficients. The local similarity of sparse coefficients was ignored. Motivated by the importance of data locality, in this paper, we propose a locality-constrained sparse representation algorithm for pansharpening, which keeps the data locality during the sparse representation process. The learned dictionary is able to preserve local data structure, resulting in improved data representation. During the sparse coding stage, analytical solutions are provided based on the basis of mathematic deduction. The pansharpening results show that the proposed method is competitive to the other well-known fusion methods.
Leadless left ventricular endocardial pacing: a real alternative or a luxury for a few?

In the May 2017 issue of JACC Reddy et al . (1) reported the results of a prospective multicenter non-randomized study (SELECT-LV), assessing the safety and the performance of biventricular pacing obtained with a wireless, ultrasound (US) based, left ventricular (LV) endocardial system (WiSE-CRT; EBR system, Sunnyvale, California, USA).