Miracle-dz/UniFAR-FTUs huggingface dataset:
Innovative Application of a Home-Based and Remote Sensing Cardiac Rehabilitation Protocol in Chinese Patients After Percutaneous Coronary Intervention.

BACKGROUND Medical care for the Chinese population has been focused on first-line activities, that is, therapy, but with little follow-up on treated patients. However, efficacy of therapy is highly dependent upon post-therapy recovery. For coronary heart disease (CHD), home-based cardiac telerehabilitation (HBCTR) is an alternative to hospital-based or center-based cardiac rehabilitation, and is an innovative approach to enhance recovery, but the approach is seldom used in China. Our preliminary survey in Shantou, China, indicated that most CHD patients showed a positive attitude toward the HBCTR technology. Our follow-up study was focused on assessing the effect of the HBCTR program in low-risk patients after percutaneous coronary intervention (PCI). MATERIALS AND METHODS A two-arm randomized controlled trial was conducted at the First Affiliated Hospital of the Shantou University Medical College, China. The effectiveness of this program was measured by using blood pressure, Six-Minute Walking Test (6MWT), Fagerstrom Test for Nicotine Dependence (FTND), Cardiac Depression Scale (CDS), and SF-36 Health Survey (SF36). RESULTS A total of 80 post-PCI patients were recruited and randomly divided into two equal groups. Based upon our effort, the usual care (UC) group received paper-based CHD educational booklets and biweekly outpatient review. The HBCTR group carried out outdoor walking/jogging exercise with real-time physiological monitoring along with CHD education materials. After the 6-week intervention, the 6MWT, SF36 (PCS, MCS), FTND and CDS in both groups were found to have significantly improved compared with baseline. In addition, the improvements in SF36, FTND scores, and 6MWT distance in the HBCTR group were significantly better than those in the UC group (p < 0.05). CONCLUSION Our observations indicated that the HBCTR program may be applied successfully in Chinese patients who had very little technical skills and its application may be highly cost-effective.
Follow-up of Lesions with Equivocal Radiotracer Uptake on PSMA-Targeted PET in Patients with Prostate Cancer: Predictive Values of the PSMA-RADS-3A and PSMA-RADS-3B Categories

Prostate-specific membrane antigen (PSMA)–targeted PET imaging has become commonly used in patients with prostate cancer (PCa). The PSMA reporting and data system version 1.0 (PSMA-RADS version 1.0) categorizes lesions on the basis of the likelihood of PCa involvement, with PSMA-RADS-3A (soft-tissue) and PSMA-RADS-3B (bone) lesions being indeterminate for the presence of disease. We retrospectively reviewed the imaging follow-up of such lesions to determine the rate at which they underwent changes suggestive of underlying PCa. Methods: PET/CT imaging with 18F-DCFPyL was performed in 110 patients with PCa, and lesions were categorized according to PSMA-RADS version 1.0. The study reported herein is a retrospective analysis of those patients. Fifty-six of 110 (50.9%) patients were determined to have indeterminate PSMA-RADS-3A or PSMA-RADS-3B lesions, and 22 of 56 (39.3%) patients had adequate follow-up to be included in the analysis (median follow-up time was 10 mo [range, 3–22 mo]). The SUVmax of the lesions was obtained, and the ratios of SUVmax of the lesions to SUVmean of blood pool (SUVmax-lesion/SUVmean-bloodpool) were calculated. Predetermined criteria were used to evaluate the PSMA-RADS-3A and PSMA-RADS-3B lesions on follow-up imaging to determine whether they demonstrated evidence of underlying malignancy. Results: A total of 46 lesions in 22 patients were considered indeterminate for PCa (i.e., PSMA-RADS-3A [32 lesions] or PSMA-RADS-3B [14 lesions]) and were evaluable on follow-up imaging. Twenty-seven of 46 (58.7%) lesions demonstrated changes suggesting they were true-positive for PCa. These lesions included 24 of 32 (75.0%) PSMA-RADS-3A lesions and 3 of 14 (21.4%) lesions categorized as PSMA-RADS-3B. The ranges of SUVmax and SUVmax-lesion/SUVmean-bloodpool overlapped between those lesions demonstrating changes consistent with malignancy on follow-up imaging and those lesions that remained unchanged on follow-up. The presence of additional definitive sites of PCa (PSMA-RADS-4 and PSMA-RADS-5) increases the likelihood that indeterminate lesions will manifest as true-positive on follow-up imaging. Conclusion: PSMA-RADS-3A and PSMA-RADS-3B lesions are truly indeterminate in that proportions of findings in both categories demonstrate evidence of malignancy on follow-up imaging. Overall, PSMA-RADS-3A lesions are more likely than PSMA-RADS-3B lesions to represent sites of PCa, and this information should be considered when guiding patient therapy.
Driving Ability in Alzheimer Disease Spectrum: Neural Basis, Assessment, and Potential Use of Optic Flow Event-Related Potentials

Driving requires multiple cognitive functions including visuospatial perception and recruits widespread brain networks. Recently, traffic accidents in dementia, particularly in Alzheimer disease spectrum (ADS), have increased and become an urgent social problem. Therefore, it is necessary to develop the objective and reliable biomarkers for driving ability in patients with ADS. Interestingly, even in the early stage of the disease, patients with ADS are characterized by the impairment of visuospatial function such as radial optic flow (OF) perception related to self-motion perception. For the last decade, we have studied the feasibility of event-related potentials (ERPs) in response to radial OF in ADS and proposed that OF-ERPs provided an additional information on the alteration of visuospatial perception in ADS (1, 2). Hence, we hypothesized that OF-ERPs can be a possible predictive biomarker of driving ability in ADS. In this review, the recent concept of neural substrates of driving in healthy humans are firstly outlined. Second, we mention the alterations of driving performance and its brain network in ADS. Third, the current status of assessment tools for driving ability is stated. Fourth, we describe ERP studies related to driving ability in ADS. Further, the neural basis of OF processing and OF-ERPs in healthy humans are mentioned. Finally, the application of OF-ERPs to ADS is described. The aim of this review was to introduce the potential use of OF-ERPs for assessment of driving ability in ADS.
Two-level Precoding for High Throughput Satellites with non-Cooperative Gateways

This paper considers the design of an onboard beamforming network for a multibeam satellite managed by several gateways. This design, based on the SLNR (Signal-to-Leakage and Noise Ratio) criterion, can be fixed based on second-order statistics of the channel. The mitigation of the co-channel interference caused by the reuse of the spectral resources across beams is complemented by multi-cluster on-ground precoders, designed to fight the intra-cluster multiuser interference. These multicluster on-ground precoders are also able to limit some of the intra-cluster interference posed into the network in an autonomous way. Fruitful connections with recent twolevel interference mitigation schemes for terrestrial systems can be made.
Determining the parameters of high amplification microlensing events by means of statistical machine learning techniques

Abstract Strong gravitational microlensing (GM) events provide us a possibility to determine both the parameters of microlensed source and microlens. GM can be an important clue to understand the nature of dark matter on comparably small spatial and mass scales (i.e. substructure), especially when speaking about the combination of astrometrical and photometrical data about high amplification microlensing events (HAME). In the same time, fitting of HAME lightcurves of microlensed sources is quite time-consuming process. That is why we test here the possibility to apply the statistical machine learning techniques to determine the source and microlens parameters for the set of HAME lightcurves, using the simulated set of amplification curves of sources microlensed by point masses and clumps of DM with various density profiles.
MDCN: Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection

Object detection in challenging situations such as scale variation, occlusion, and truncation depends not only on feature details but also on contextual information. Most previous networks emphasize too much on detailed feature extraction through deeper and wider networks, which may enhance the accuracy of object detection to certain extent. However, the feature details are easily being changed or washed out after passing through complicated filtering structures. To better handle these challenges, the paper proposes a novel framework, multi-scale, deep inception convolutional neural network (MDCN), which focuses on wider and broader object regions by activating feature maps produced in the deep part of the network. Instead of incepting inner layers in the shallow part of the network, multi-scale inceptions are introduced in the deep layers. The proposed framework integrates the contextual information into the learning process through a single-shot network structure. It is computational efficient and avoids the hard training problem of previous macro feature extraction network designed for shallow layers. Extensive experiments demonstrate the effectiveness and superior performance of MDCN over the state-of-the-art models.
Remote ischemic post-conditioning promotes hematoma resolution via AMPK-dependent immune regulation

Spontaneous intracerebral hemorrhage (ICH) produces the highest acute mortality and worst outcomes of all stroke subtypes. Hematoma volume is an independent determinant of ICH patient outcomes, making clot resolution a primary goal of clinical management. Herein, remote-limb ischemic post-conditioning (RIC), the repetitive inflation–deflation of a blood pressure cuff on a limb, accelerated hematoma resolution and improved neurological outcomes after ICH in mice. Parabiosis studies revealed RIC accelerated clot resolution via a humoral-mediated mechanism. Whereas RIC increased anti-inflammatory macrophage activation, myeloid cell depletion eliminated the beneficial effects of RIC after ICH. Myeloid-specific inactivation of the metabolic regulator, AMPK&agr;1, attenuated RIC-induced anti-inflammatory macrophage polarization and delayed hematoma resolution, providing a molecular link between RIC and immune activation. Finally, chimera studies implicated myeloid CD36 expression in RIC-mediated neurological recovery after ICH. Thus, RIC, a clinically well-tolerated therapy, noninvasively modulates innate immune responses to improve ICH outcomes. Moreover, immunometabolic changes may provide pharmacodynamic blood biomarkers to clinically monitor the therapeutic efficacy of RIC.
Estimating Attractor Reachability in Asynchronous Logical Models

Logical models are well-suited to capture salient dynamical properties of regulatory networks. For networks controlling cell fate decisions, cell fates are associated with model attractors (stable states or cyclic attractors) whose identification and reachability properties are particularly relevant. While synchronous updates assume unlikely instantaneous or identical rates associated with component changes, the consideration of asynchronous updates is more realistic but, for large models, may hinder the analysis of the resulting non-deterministic concurrent dynamics. This complexity hampers the study of asymptotical behaviors, and most existing approaches suffer from efficiency bottlenecks, being generally unable to handle cyclical attractors and quantify attractor reachability. Here, we propose two algorithms providing probability estimates of attractor reachability in asynchronous dynamics. The first algorithm, named Firefront, exhaustively explores the state space from an initial state, and provides quasi-exact evaluations of the reachability probabilities of model attractors. The algorithm progresses in breadth, propagating the probabilities of each encountered state to its successors. Second, Avatar is an adapted Monte Carlo approach, better suited for models with large and intertwined transient and terminal cycles. Avatar iteratively explores the state space by randomly selecting trajectories and by using these random walks to estimate the likelihood of reaching an attractor. Unlike Monte Carlo simulations, Avatar is equipped to avoid getting trapped in transient cycles and to identify cyclic attractors. Firefront and Avatar are validated and compared to related methods, using as test cases logical models of synthetic and biological networks. Both algorithms are implemented as new functionalities of GINsim 3.0, a well-established software tool for logical modeling, providing executable GUI, Java API, and scripting facilities.
Endoglycosidase S Enables a Highly Simplified Clinical Chemistry Procedure for Direct Assessment of Serum IgG Undergalactosylation in Chronic Inflammatory Disease*

IgG galactosylation is a biomarker for assessment of chronic inflammatory diseases that has until now not reached the clinic because of complex sample preparation requirements, including IgG purification. We developed a new assay for the measurement of IgG galactosylation which can be performed entirely in liquid phase, without the need for IgG purification, finally paving the way for clinical implementation of this promising biomarker. Graphical Abstract Highlights Selective release of IgG Fc glycans in crude serum by endoglycosidase S. CE-LIF-based measurements of IgG undergalactosylation levels (UGS). UGS as a biomarker: Stratification of non-alcoholic steatohepatitis patients and controls. Over the past 30 years, it has been firmly established that a wide spectrum of (autoimmune) diseases such as rheumatoid arthritis, Crohn's and lupus, but also other pathologies like alcoholic and non-alcoholic steatohepatitis (ASH and NASH) are driven by chronic inflammation and are hallmarked by a reduced level of serum IgG galactosylation. IgG (under)galactosylation is a promising biomarker to assess disease severity, and monitor and adjust therapy. However, this biomarker has not been implemented in routine clinical chemistry because of a complex analytical procedure that necessitates IgG purification, which is difficult to perform and validate at high throughput. We addressed this issue by using endo-β-N-acetylglucosaminidase from Streptococcus pyogenes (endoS) to specifically release Fc N-glycans in whole serum. The entire assay can be completed in a few hours and only entails adding endoS and labeling the glycans with APTS. Glycans are then readily analyzed through capillary electrophoresis. We demonstrate in two independent patient cohorts that IgG undergalactosylation levels obtained with this assay correlate very well with scores calculated from PNGaseF-released glycans of purified antibodies. Our new assay allows to directly and specifically measure the degree of IgG galactosylation in serum through a fast and completely liquid phase protocol, without the requirement for antibody purification. This should help advancing this biomarker toward clinical implementation.
Genome-Wide Identification, Classification and Expression Analysis of the HSP Gene Superfamily in Tea Plant (Camellia sinensis)

Heat shock proteins (HSPs) function as molecular chaperones. These proteins are encoded by a multigene family whose members play crucial roles in plant growth, development and stress response. However, little is known about the HSP gene superfamily in tea plant. In this study, a total of 47 CsHSP genes were identified, including 7 CsHSP90, 18 CsHSP70, and 22 CssHSP genes. Phylogenetic and composition analyses showed that CsHSP proteins in the same subfamily have similar gene structures and conserved motifs, but significant differences exist in the different subfamilies. In addition, expression analysis revealed that almost all CsHSP genes were specifically expressed in one or more tissues, and significantly induced under heat and drought stress, implying that CsHSP genes play important roles in tea plant growth, development, and response to heat and drought stress. Furthermore, a potential interaction network dominated by CsHSPs, including HSP70/HSP90 organizing protein (HOP) and heat shock transcription factor (HSF), is closely related to the abovementioned processes. These results increase our understanding of CsHSP genes and their roles in tea plant, and thus, this study could contribute to the cloning and functional analysis of CsHSP genes and their encoded proteins in the future.
Logarithmic Regret in the Dynamic and Stochastic Knapsack Problem with Equal Rewards

We study a dynamic and stochastic knapsack problem in which a decision maker is sequentially presented with items arriving according to a Bernoulli process over n discrete time periods. Items have equal rewards and independent weights that are drawn from a known nonnegative continuous distribution F. The decision maker seeks to maximize the expected total reward of the items that the decision maker includes in the knapsack while satisfying a capacity constraint and while making terminal decisions as soon as each item weight is revealed. Under mild regularity conditions on the weight distribution F, we prove that the regret—the expected difference between the performance of the best sequential algorithm and that of a prophet who sees all of the weights before making any decision—is, at most, logarithmic in n. Our proof is constructive. We devise a reoptimized heuristic that achieves this regret bound.
p58IPK Is an Endogenous Neuroprotectant for Retinal Ganglion Cells

p58IPK is an endoplasmic reticulum (ER)-resident chaperone playing a critical role in facilitating protein folding and protein homeostasis. Previously, we have demonstrated that p58IPK is expressed broadly in retinal neurons including retinal ganglion cells (RGCs) and loss of p58IPK results in age-related RGC degeneration. In the present study, we investigate the role of p58IPK in neuroprotection by in vitro and in vivo studies using primary RGC culture and two well-established disease-relevant RGC injury models: retinal ischemia/reperfusion (I/R) and microbead-induced ocular hypertension. Our results demonstrate that in both in vivo models, p58IPK −/− mice exhibit significantly increased RGC loss compared to wild type (WT) mice. In vitro, p58IPK-deficient RGCs show reduced viability and are more susceptible to cell death induced by the ER stress inducer tunicamycin (TM). Overexpression of p58IPK by adeno-associated virus (AAV) significantly diminishes TM-induced cell death in both WT and p58IPK −/− RGCs. Interestingly, we find that loss of p58IPK leads to reduced mRNA expression, but not the protein level, of mesencephalic astrocyte-derived neurotrophic factor (MANF), a neurotrophic factor that resides in the ER. Treatment with recombinant MANF protein protects R28 retinal neural cells and mouse retinal explants from TM-induced cell death. Taken together, our study suggests that p58IPK functions as an endogenous neuroprotectant for RGCs. The mechanisms underlying p58IPK’s neuroprotective action and the potential interactions between p58IPK and MANF warrant future investigation.
A fully autonomous terrestrial bat-like acoustic robot

Echolocating bats rely on active sound emission (echolocation) for mapping novel environments and navigating through them. Many theoretical frameworks have been suggested to explain how they do so, but few attempts have been made to build an actual robot that mimics their abilities. Here, we present the ‘Robat’—a fully autonomous bat-like terrestrial robot that relies on echolocation to move through a novel environment while mapping it solely based on sound. Using the echoes reflected from the environment, the Robat delineates the borders of objects it encounters, and classifies them using an artificial neural-network, thus creating a rich map of its environment. Unlike most previous attempts to apply sonar in robotics, we focus on a biological bat-like approach, which relies on a single emitter and two ears, and we apply a biological plausible signal processing approach to extract information about objects’ position and identity.
Effectiveness of body image directed interventions in patients with anorexia nervosa: A systematic review

OBJECTIVE Body image (BI) disturbances are one of the core symptoms of anorexia nervosa (AN). They have been shown to be associated with depression and anxiety at all treatment stages and are a reliable predictor of relapse. Considering the importance for the course of AN, direct targeting of BI disturbances is still underemphasized in the treatment of patients with AN. METHOD In this systematic review, conducted according to the PRISMA statement, the evidence on BI directed interventions in AN is synthesized. RESULTS N = 11 studies investigating mirror exposure, video confrontation, virtual reality body exposure and treatment programs were analyzed. No systematic risk of bias within or across studies could be identified. The included studies show that BI directed interventions may be efficacious in improving BI related outcomes. However, the evidence regarding an additional effect of BI interventions added to established treatments for patients with AN, is unclear. DISCUSSION The evidence base on BI interventions for patients with AN is scarce. It is not possible to identify types of BI intervention that can be seen as the most promising. Advantages of new technologies such as virtual reality or a combination of BI interventions with techniques for stress reduction are discussed.
C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

Abstract In the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We present C 3 (Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.