Miracle-dz/UniFAR-FTUs huggingface dataset:
RANKL Inhibition in Fibrous Dysplasia of Bone: A Preclinical Study in a Mouse Model of the Human Disease

Fibrous dysplasia of bone/McCune‐Albright syndrome (Polyostotic FD/MAS; OMIM#174800) is a crippling skeletal disease caused by gain‐of‐function mutations of Gsα. Enhanced bone resorption is a recurrent histological feature of FD and a major cause of fragility of affected bones. Previous work suggests that increased bone resorption in FD is driven by RANKL and some studies have shown that the anti‐RANKL monoclonal antibody, denosumab, reduces bone turnover and bone pain in FD patients. However, the effect of RANKL inhibition on the histopathology of FD and its impact on the natural history of the disease remain to be assessed. In this study, we treated the EF1α‐GsαR201C mice, which develop an FD‐like phenotype, with an anti‐mouse RANKL monoclonal antibody. We found that the treatment induced marked radiographic and microscopic changes at affected skeletal sites in 2‐month‐old mice. The involved skeletal segments became sclerotic due to the deposition of new, highly mineralized bone within developing FD lesions and showed a higher mechanical resistance compared to affected segments from untreated transgenic mice. Similar changes were also detected in older mice with a full‐blown skeletal phenotype. The administration of anti‐mouse RANKL antibody arrested the growth of established lesions and, in young mice, prevented the appearance of new ones. However, after drug withdrawal, the newly formed bone was remodelled into FD tissue and the disease progression resumed in young mice. Taken together, our results show that the anti‐RANKL antibody significantly affected the bone pathology and natural history of FD in the mouse. Pending further work on the prevention and management of relapse after treatment discontinuation, our preclinical study suggests that RANKL inhibition may be an effective therapeutic option for FD patients. © 2019 American Society for Bone and Mineral Research.
A Descriptive Analysis of an Ambulatory Kidney Palliative Care Program.

Background: Many patients with serious kidney disease have an elevated symptom burden, high mortality, and poor quality of life. Palliative care has the potential to address these problems, yet nephrology patients frequently lack access to this specialty. Objectives: We describe patient demographics and clinical activities of the first 13 months of an ambulatory kidney palliative care (KPC) program that is integrated within a nephrology practice. Design/Measurements: Utilizing chart abstractions, we characterize the clinic population served, clinical service utilization, visit activities, and symptom burden as assessed using the Integrated Palliative Care Outcome Scale-Renal (IPOS-R), and patient satisfaction. Results: Among the 55 patients served, mean patient age was 72.0 years (standard deviation [SD] = 16.7), 95% had chronic kidney disease stage IV or V, and 46% had a Charlson Comorbidity Index >8. The mean IPOS-R score at initial visit was 16 (range = 0-60; SD = 9.1), with a mean of 7.5 (SD = 3.7) individual physical symptoms (range = 0-15) per patient. Eighty-seven percent of initial visits included an advance care planning conversation, 55.4% included a medication change for symptoms, and 35.5% included a dialysis decision-making conversation. Overall, 96% of patients who returned satisfaction surveys were satisfied with the care they received and viewed the KPC program positively. Conclusions: A model of care that integrates palliative care with nephrology care in the ambulatory setting serves high-risk patients with serious kidney disease. This KPC program can potentially meet documented gaps in care while achieving patient satisfaction. Early findings from this program evaluation indicate opportunities for enhanced patient-centered palliative nephrology care.
Increase in Grasp Force Reflects a Desire to Improve Movement Precision

Abstract Grasping is an action engraved in the human genome, enabling newborn infants to hang from a monkey-bar immediately after birth. The grasp force provides rich information about the brain’s control of arm movements. In this study, we tested the hypothesis that the grasp force increases to improve the hand’s movement precision during reaching. In two reaching experiments, subjects increased grasp force to suppress movement imprecision that arose from both self-generated motor noise and from an unpredictable environment. Furthermore, the grasp force did not increase constantly, but increased specifically along the movement where the hand’s deviation was greatest. The increased grasp was premeditated and was not a reaction to environmental forces, suggesting that the central nervous system has a predictive, state-dependent model of movement precision during reaching. The grasp force provides a high temporal resolution and calibration-less estimate of movement precision adaptation.
Comparison of Female Athlete Triad Coalition and RED-S risk assessment tools

ABSTRACT The Female Athlete Triad Coalition (Triad Coalition) and Relative Energy Deficiency in Sport (RED-S) consensus statements each include risk assessment tools to guide athlete eligibility decisions. This study examined how these tools categorized the same set of individuals to an overall risk factor score and qualitatively compared athlete eligibility decisions resulting from each tool. Exercising women (n = 166) with complete screening/baseline datasets from multiple previously conducted studies were assessed. Data used for risk assessment included: anthropometric measurements, dual-energy x-ray absorptiometry scans, exercise and health status surveys, and two disordered eating questionnaires (Three Factor Eating Questionnaire and Eating Disorder Inventory). Individuals were scored on each tool and subsequently categorized as either fully cleared, provisionally cleared, or restricted from play. Based on the Triad Coalition tool, 25.3% of subjects were classified as fully cleared, 62.0% as provisionally cleared, and 12.7% as restricted from play. Based on the RED-S tool, 71.7% of subjects were classified as fully cleared, 18.7% as provisionally cleared, and 9.6% as restricted from play. The Triad Coalition and RED-S tools resulted in different clearance decisions (p < 0.001), with the Triad Coalition tool recommending increased surveillance of a greater number of athletes.
The incremental cost of traumatic brain injury during the first year after a road traffic accident

ABSTRACT This study aims to determine the incremental cost of TBI during the first year after a traffic accident, compared to other patients with similar non-TBI injuries. Secondly, identification of factors associated with medical costs of TBI is pursued. Analyses were performed on administrative data for traffic victims hospitalised in Belgium between 2009 and 2011. Medical costs attributable to the accident are estimated over one year post-injury. Cases with TBI were matched to controls with similar non-TBI injuries to determine the incremental cost of TBI. Both aims of this research were assessed using regression analysis. The incremental cost of TBI is estimated to range between € 10 042 (95%CI [€8198; €11 887]) and €21 715 (95%CI [€13 5889; €29 540]). Age, problems with self-reliance, survival status, the occurrence of acute events and severity of TBI are significant predictors of medical costs. As to healthcare utilisation, MRI usage, inpatient rehabilitation facilities, nursing homes and readmissions to acute hospital stand out as having most influence on costs. This study reveals a considerable incremental cost of TBI. Policy-making bodies should be made aware of this phenomenon and a diversified policy should be considered when financing programs are discussed.
Error Correction Regression Framework for Enhancing the Decoding Accuracies of Ear-EEG Brain–Computer Interfaces

Ear-electroencephalography (EEG) is a promising tool for practical brain–computer interface (BCI) applications because it is more unobtrusive, comfortable, and mobile than a typical scalp-EEG system. However, an ear-EEG has a natural constraint of electrode location (e.g., limited in or around the ear) for acquiring informative brain signals sufficiently. Achieving reliable performance of ear-EEG in specific BCI paradigms that do not utilize brain signals on the temporal lobe around the ear is difficult. For example, steady-state visual evoked potentials (SSVEPs), which are mainly generated in the occipital area, have a significantly attenuated and distorted amplitude in ear-EEG. Therefore, preserving the high level of decoding accuracy is challenging and essential for SSVEP BCI based on ear-EEG. In this paper, we first investigate linear and nonlinear regression methods to increase the decoding accuracy of ear-EEG regarding SSVEP paradigm by utilizing the estimated target EEG signals on the occipital area. Then, we investigate an ensemble method to consider the prediction variability of the regression methods. Finally, we propose an error correction regression (ECR) framework to reduce the prediction errors by adding an additional nonlinear regression process (i.e., kernel ridge regression). We evaluate the ECR framework in terms of single session, session-to-session transfer, and subject-transfer decoding. We also validate the online decoding ability of the proposed framework with a short-time window size. The average accuracies are observed to be 91.11±9.14%, 90.52±8.67%, 86.96±12.13%, and 78.79±12.59%. This paper demonstrates that SSVEP BCI based on ear-EEG can achieve reliable performance with the proposed ECR framework.
Long-term eradication of extranodal natural killer/T-cell lymphoma, nasal type, by induced pluripotent stem cell-derived Epstein-Barr virus-specific rejuvenated T cells in vivo

Functionally rejuvenated induced pluripotent stem cell (iPSC)-derived antigen-specific cytotoxic T lymphocytes (CTL) are expected to be a potent immunotherapy for tumors. When L-asparaginase-containing standard chemotherapy fails in extranodal natural killer/T-cell lymphoma, nasal type (ENKL), no effective salvage therapy exists. The clinical course then is miserable. We demonstrate prolonged and robust eradication of ENKL in vivo by Epstein-Barr virus-specific iPSC-derived antigen-specific CTL, with iPSC-derived antigen-specific CTL persisting as central memory T cells in the mouse spleen for at least six months. The anti-tumor response is so strong that any concomitant effect of the programmed cell death 1 (PD-1) blockade is unclear. These results suggest that long-term persistent Epstein-Barr virus-specific iPSC-derived antigen-specific CTL contribute to a continuous anti-tumor effect and offer an effective salvage therapy for relapsed and refractory ENKL.
Estimation of Domain of Attraction for Aperiodic Sampled-Data Switched Delayed Neural Networks Subject to Actuator Saturation

In this paper, for the case of the asynchronous switching caused by that subsystem’s switching occuring during a sampling interval, the domain of attraction estimation problem is investigated for aperiodic sampled-data switched delayed neural networks (ASDSDNNs) subject to actuator saturation. A parameters-dependent time-scheduled Lyapunov functional consisting of a novel looped-functional is constructed using segmentation technology and linear interpolation. By employing this novel functional and using an average dwell time (ADT) approach, exponential stability criteria are proposed for polytopic uncertain ASDSDNNs subject to actuator saturation. And a relationship between ADT and sampling period is revealed for ASDSDNNs. As a corollary, exponential stability criteria are proposed for nominal ASDSDNNs subject to actuator saturation. Furthermore, by describing the domain of attraction as a time-varying ellipsoid determined by the time-scheduled Lyapunov matrix, the proposed theoretical conditions are transformed into a linear matrix inequality (LMI)-based multi-objective optimization problem. The dynamic estimates of the domain of attraction for ASDSDNNs are solved. Numerical simulation examples are provided to illustrate the effectiveness of the proposed method.
Mechanisms of titanium dioxide nanoparticle‐induced oxidative stress and modulation of plasma glucose in mice

Titanium dioxide nanoparticles (TiO2 NPs) are reported to increase plasma glucose levels in mice at specific doses. The production and accumulation of reactive oxygen species (ROS) is potentially the most important factor underlying the biological toxicity of TiO2 NPs but the underlying mechanisms are unclear at present. Data from genome‐wide analyses showed that TiO2 NPs induce endoplasmic reticulum (ER) stress and ROS generation, leading to the inference that TiO2 NP‐induced ER stress contributes to enhancement of ROS in mice. Resveratrol (Res) effectively relieved TiO2 NP‐induced ER stress and ROS generation by ameliorating expression of a common set of activated genes for both processes, signifying that ER stress and ROS are closely related. TiO2 NP‐induced ER stress occurred earlier than ROS generation. Upon treatment with 4‐phenylbutyric acid to relieve ER stress, plasma glucose levels tended toward normal and TiO2 NP increased ROS production was inhibited. These results suggest that TiO2 NP‐induced ER stress promotes the generation of ROS, in turn, triggering increased plasma glucose levels in mice. In addition, Res that displays the ability to reduce ER stress presents a dietary polyphenol antioxidant that can effectively prevent the toxicological effects of TiO2 NPs on plasma glucose metabolism.
Modified carry skip adder for reducing first block delay

The carry skip adder has low complexity and moderate delays. Within each block, ripple carry is used to produce the sum bits and a carry. When the carry of the first block is generated, skipping produces the next carry with two gate delays per block. The second block cannot pass carry signals until the block generates the first carry. A modified carry skip adder has been designed for reducing the first block delays. Carry lookahead logic is used for the first carry computation. Although the modified carry skip adder uses a few extra gates because of the CIA logic, it provides better speed than the conventional carry skip adder. It certainly works well with fixed-size blocks.
A Retrospective Chart Review of Screening on the Prevalence of Metabolic Syndrome (MetS) in an Irish Community Mental Health Service

Abstract Individuals who are treated with antipsychotic medications are at risk of developing metabolic syndrome (MetS). The comorbidity of a severe mental illness (SMI) and a physical illness has a major impact on the quality of life of these individuals. We conducted a retrospective chart review (RCR) of 214 individuals with a diagnosis of schizophrenia who had been receiving antipsychotic medications for at least 6 months, in five clinical settings in an Irish community mental health service. The aim was to determine the presence of MetS to assist in improving screening practices and directing future practice. The National Cholesterol Education Program High Blood Cholesterol Adult Treatment Panel 111 (NCEP ATP 111) metabolic diagnostic criteria were utilised to determine prevalence. After examining 214 charts we observed that waist circumference varied from 68 to 142 cm, elevated waist circumference over the recommended parameters was recorded in 145 charts. Forty-five percent (n = 98) had blood pressure (BP) readings over 130/85. The range for body mass index (BMI)’s varied from 16 to 54, BMIs over 25 was recorded in 44% (n = 95) of charts. Elevated triglycerides (TG) were recorded in 37% (n = 80) and 45% (n = 97) had reduced HDL-C levels. Elevated glucose levels were found in 25% (n = 54) of the charts examined. The chart review found an overall prevalence rate of 44% (n = 94) for this sample. Regular audit of screening data used for the presence of MetS in individuals with SMI is essential in the detection of physical comorbidities and to improving the quality of life and prevention of premature deaths.
Blood transcriptome and clonal T-cell correlates of response and non-response to eltrombopag therapy in a cohort of patients with chronic immune thrombocytopenia

Immune thrombocytopenia (ITP) is an autoimmune disease characterized by a low platelet count caused by accelerated platelet destruction and/or impaired platelet production. Chronic ITP is defined as ITP lasting for more than 12 months. [1][1] T-cell abnormalities are implicated in ITP pathogenesis.
An Adaptive Motion Decision System For Digital Image Stabilizer Based On Edge Pattern Matching

The effects of various environmental conditions which degrade the performance of a digital image stabilization (DIS) system in a video camera are analyzed. On the basis of the analysis, a new DIS system with an adaptive motion decision system is proposed. The DIS system is composed of (i) a local motion vector generation unit, (ii) a field motion vector generation unit, (iii) an accumulated motion vector generation unit, and (iv) field memory address control and a digital zooming unit. >
Transdiagnostic validity of the MATRICS Consensus Cognitive Battery across the autism-schizophrenia spectrum

Abstract Background Autism Spectrum Disorder (ASD) and schizophrenia are neurodevelopmental disorders which share substantial overlap in cognitive deficits during adulthood. However, treatment evaluation in ASD and treatment comparisons across ASD and schizophrenia are limited by a dearth of empirical work establishing the validity of a standard cognitive battery across ASD and schizophrenia. Promisingly, the MATRICS Consensus Cognitive Battery (MCCB) has been validated in schizophrenia and encompasses cognitive domains that are impacted in ASD. Thus, this study aimed to establish MCCB's generalizability from schizophrenia to ASD. Methods Community-residing adults with schizophrenia (N = 100) and ASD (N = 113) underwent MCCB assessment. Using multigroup confirmatory factor analysis, MCCB's transdiagnostic validity was evaluated by examining whether schizophrenia and ASD demonstrate the same configuration, magnitude, and directionality of relationships within and among measures and their underlying cognitive domains. Results Across schizophrenia and ASD, the same subsets of MCCB measures inform three cognitive domains: processing speed, attention/working memory, and learning. Except for group means in category fluency, continuous performance, and spatial span, both groups show vastly comparable factor structures and characteristics. Conclusions To our knowledge, this study is the first to establish the validity of a standard cognitive battery in adults with ASD and furthermore the first to establish a cognitive battery's comparability across ASD and schizophrenia. Cognitive domain scores can be compared across new samples using weighted sums of MCCB scores resulting from this study. These findings highlight MCCB's applicability to ASD and support its utility for standardizing treatment evaluation of cognitive outcomes across the autism-schizophrenia spectrum.
Perioperative antibiotherapy should replace prophylactic antibiotics in patients undergoing pancreaticoduodenectomy preceded by preoperative biliary drainage

Pancreaticoduodenectomy (PD) remains a morbid surgery. Preoperative biliary drainage (PBD) is often necessary before surgery but is associated with biliary contamination. We compared the postoperative complications of patients undergoing PBD who received the usual prophylactic antibiotics (PAs) or systematic antibiotherapy (ABT).
Cross-View Gait Recognition by Discriminative Feature Learning

Recently, deep learning-based cross-view gait recognition has become popular owing to the strong capacity of convolutional neural networks (CNNs). Current deep learning methods often rely on loss functions used widely in the task of face recognition, e.g., contrastive loss and triplet loss. These loss functions have the problem of hard negative mining. In this paper, a robust, effective, and gait-related loss function, called angle center loss (ACL), is proposed to learn discriminative gait features. The proposed loss function is robust to different local parts and temporal window sizes. Different from center loss which learns a center for each identity, the proposed loss function learns multiple sub-centers for each angle of the same identity. Only the largest distance between the anchor feature and the corresponding cross-view sub-centers is penalized, which achieves better intra-subject compactness. We also propose to extract discriminative spatial–temporal features by local feature extractors and a temporal attention model. A simplified spatial transformer network is proposed to localize the suitable horizontal parts of the human body. Local gait features for each horizontal part are extracted and then concatenated as the descriptor. We introduce long short-term memory (LSTM) units as the temporal attention model to learn the attention score for each frame, e.g., focusing more on discriminative frames and less on frames with bad quality. The temporal attention model shows better performance than the temporal average pooling or gait energy images (GEI). By combing the three aspects, we achieve state-of-the-art results on several cross-view gait recognition benchmarks.
Analysis of Diabetic Retinopathy from the Features of Color Fundus Images using Classifiers

— Diabetic Retinopathy (RD) is a complication of Diabetes that is caused by changes in the blood vessels of the retina. The development of abnormal vessels in the retina may lead to vision blur, distortion or even may cause visual impairment. Hence early detection of RD is essential to avoid blidness. In this paper, an automatic RD detection system has been developed to analyze the presence of lesion (presence of new cells in the retina) in fundus images using the two different classifiers – Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). The fundus images have been preprocessed to improve the performance of early detection by performing filter, watershed transformation segmentation method and feature extraction method. The vessels like candidate segments can be detected based on the different parameters associated with shape, contrast, position, orientation, brightness and the line density. The proposed automatic classifier using SVM performs better detection of the abnormal in the fundus image.