Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulations of human resting brain connectivity by kisspeptin enhance sexual and emotional functions

BACKGROUND. Resting brain connectivity is a crucial component of human behavior demonstrated by disruptions in psychosexual and emotional disorders. Kisspeptin, a recently identified critical reproductive hormone, can alter activity in certain brain structures but its effects on resting brain connectivity and networks in humans remain elusive. METHODS. We determined the effects of kisspeptin on resting brain connectivity (using functional neuroimaging) and behavior (using psychometric analyses) in healthy men, in a randomized double-blinded 2-way placebo-controlled study. RESULTS. Kisspeptin’s modulation of the default mode network (DMN) correlated with increased limbic activity in response to sexual stimuli (globus pallidus r = 0.500, P = 0.005; cingulate r = 0.475, P = 0.009). Furthermore, kisspeptin’s DMN modulation was greater in men with less reward drive (r = –0.489, P = 0.008) and predicted reduced sexual aversion (r = –0.499, P = 0.006), providing key functional significance. Kisspeptin also enhanced key mood connections including between the amygdala-cingulate, hippocampus-cingulate, and hippocampus–globus pallidus (all P < 0.05). Consistent with this, kisspeptin’s enhancement of hippocampus–globus pallidus connectivity predicted increased responses to negative stimuli in limbic structures (including the thalamus and cingulate [all P < 0.01]). CONCLUSION. Taken together, our data demonstrate a previously unknown role for kisspeptin in the modulation of functional brain connectivity and networks, integrating these with reproductive hormones and behaviors. Our findings that kisspeptin modulates resting brain connectivity to enhance sexual and emotional processing and decrease sexual aversion, provide foundation for kisspeptin-based therapies for associated disorders of body and mind. FUNDING. NIHR, MRC, and Wellcome Trust.
Prognostic factors for postoperative survival among patients with rhabdomyosarcoma of the limbs

Background Rhabdomyosarcoma (RMS) is a rare malignant soft tissue sarcoma with a poor outcome and unclear prognostic factors. The purpose of this study was to analyze the prognostic postoperative survival factors among patients with RMS of the limbs. Methods Postoperative data on patients with RMS of the limbs from 1983 to 2013 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database of the US National Cancer Institute. Both overall survival (OS) and cancer-specific survival (CSS) were assessed using the Kaplan–Meier method (to obtain OS and CSS curves) and a Cox proportional hazards regression model. Results In total, 385 cases were obtained from the SEER database. The 5- and 10-year OS rates of the entire group were 51.5% and 42.2%, respectively. The 5- and 10-year CSS rates were 56.7% and 50.7%, respectively. Univariate analysis revealed that age, location, tumor stage, tumor size, and radiation therapy (RT) were associated with OS. Age, tumor stage, tumor size, and RT were associated with CSS. Age, tumor stage, tumor size, and RT were also independent predictors of both OS and CSS. Conclusion Young age, no metastasis at presentation, smaller tumor size, and RT are favorable factors for prolonging survival among patients with RMS of the limbs after surgery.
Evaluating the impact of corpora used to train distributed text representation models for noisy and short texts

The traditional bag of words has well-known short-comings. Distributed representations have emerged as an alter- native and became the state-of-the-art in textual representation. However, most of the existing researches evaluated these repre- sentations using formal and well-written text corpora to generate the language model which is later applied to traditional text categorization problems. There is no evidence the same models are suitable to deal with short and noisy texts (e.g., messages from social networks and instant messengers). In addition, there is no consensus on which of the existing techniques for training distributed representation of words is the best available choice to be used as a baseline for further comparisons. In this way, this study evaluates if language models created from a corpus extracted from the domain is more appropriate than the ones created from a corpus of formal text. Moreover, we provide a comparison between the most traditional techniques used to create models of distributed representation of texts by applying them in polarity detection of short and noisy messages. Our experiments were diligently designed and allowed us to confirm our hypothesis that training distributed representation models with a corpus composed by text with same characteristics of the application domain is more recommended than using a formal and well-written one.
Eye movements while judging faces for trustworthiness and dominance

Past studies examining how people judge faces for trustworthiness and dominance have suggested that they use particular facial features (e.g. mouth features for trustworthiness, eyebrow and cheek features for dominance ratings) to complete the task. Here, we examine whether eye movements during the task reflect the importance of these features. We here compared eye movements for trustworthiness and dominance ratings of face images under three stimulus configurations: Small images (mimicking large viewing distances), large images (mimicking face to face viewing), and a moving window condition (removing extrafoveal information). Whereas first area fixated, dwell times, and number of fixations depended on the size of the stimuli and the availability of extrafoveal vision, and varied substantially across participants, no clear task differences were found. These results indicate that gaze patterns for face stimuli are highly individual, do not vary between trustworthiness and dominance ratings, but are influenced by the size of the stimuli and the availability of extrafoveal vision.
Slicc damage index score in systemic lupus erythematosus patients and its associated factors

Abstract The aims of this study were to determine damage index in systemic lupus erythematosus (SLE) patients based on Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) Damage Index (SDI) and to determine the laboratory and clinico-demographic factors affecting SDI. This is a retrospective cohort study of 94 SLE patients attending rheumatology clinics in 2 local hospitals in Kelantan, Malaysia. The patients were divided into 2 groups based on SDI score assigned by the attending physician, 0 (without damage) or ≥1 (with damage). Newly diagnosed SLE patients with disease duration less than 6 months were excluded. A total of 45 (47.9%) SLE patients showed damage by SDI score. Majority of the subjects had neuropsychiatric damages (21/94; 22.3%) followed by skin (12/94; 12.8%) and musculoskeletal (6/94; 6.4%) damage. SDI score was significantly associated with higher disease duration (6.2 ± 6.57 years vs 4.5 ± 3.7 years; P = .018), lower prednisolone dose (8.74 ± 10.89 mg vs 4.89 ± 3.81 mg; P < .001), hypertension (P = .007), and exposure to cyclophosphamide (P = .004). Hypertension (P = .020), exposure to cyclophosohamide (P = 0.013), and lower prednisolone dose (P = .023) were significantly associated with damage by multivariable analysis. Higher SDI score was significantly associated with exposure to cyclophosphamide, suggesting that lower cyclophosphamide doses or alternative therapeutic agents are recommended.
Surgical site infections post cesarean section

The incidence of cesarean section in india was 7.1% in 1998 and there is 16.7% rise in the rates annually in India. The rates of SSI are considered as an indicator of the quality of surgical and postoperative care provided by the hospitals. Knowledge of the organisms causing SSI and their antibiotic sensitivity and resistance patterns provide an insight into the current antibiotic prescription practices and the factors affecting these practices. The present study helps to know the risk factors and the organisms causing SSI in our hospital and their sensitivity to different antibiotics which help in formulating infection control practices.
The Effect of Color Scales on Climate Scientists’ Objective and Subjective Performance in Spatial Data Analysis Tasks

Geographical maps encoded with rainbow color scales are widely used by climate scientists. Despite a plethora of evidence from the visualization and vision sciences literature about the shortcomings of the rainbow color scale, they continue to be preferred over perceptually optimal alternatives. To study and analyze this mismatch between theory and practice, we present a web-based user study that compares the effect of color scales on performance accuracy for climate-modeling tasks. In this study, we used pairs of continuous geographical maps generated using climatological metrics for quantifying pairwise magnitude difference and spatial similarity. For each pair of maps, 39 scientist-observers judged: i) the magnitude of their difference, ii) their degree of spatial similarity, and iii) the region of greatest dissimilarity between them. Besides the rainbow color scale, two other continuous color scales were chosen such that all three of them covaried two dimensions (luminance monotonicity and hue banding), hypothesized to have an impact on task performance. We also analyzed subjective performance measures, such as user confidence, perceived accuracy, preference, and familiarity in using the different color scales. We found that monotonic luminance scales produced significantly more accurate judgments of magnitude difference but were not superior in spatial comparison tasks, and that hue banding had differential effects based on the task and conditions. Scientists expressed the highest preference and perceived confidence and accuracy with the rainbow, despite its poor performance on the magnitude comparison tasks. We also report on interesting interactions among stimulus conditions, tasks, and color scales, that lead to open research questions.
A Span-Extraction Dataset for Chinese Machine Reading Comprehension

Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, the existing reading comprehension datasets are mostly in English. In this paper, we introduce a Span-Extraction dataset for Chinese machine reading comprehension to add language diversities in this area. The dataset is composed by near 20,000 real questions annotated on Wikipedia paragraphs by human experts. We also annotated a challenge set which contains the questions that need comprehensive understanding and multi-sentence inference throughout the context. We present several baseline systems as well as anonymous submissions for demonstrating the difficulties in this dataset. With the release of the dataset, we hosted the Second Evaluation Workshop on Chinese Machine Reading Comprehension (CMRC 2018). We hope the release of the dataset could further accelerate the Chinese machine reading comprehension research. Resources are available: https://github.com/ymcui/cmrc2018
Neural dynamics of selective attention deficits in HIV-associated neurocognitive disorder

Objective To identify the neural markers of attention dysfunction in patients with HIV-associated neurocognitive disorder (HAND). Methods Sixty participants, including 40 HIV-infected adults (half with HAND) and 20 demographically matched controls performed a visual selective attention task while undergoing high-density magnetoencephalography. Neuronal activity related to selective attention processing was quantified and compared across the 3 groups, and correlated with neuropsychological measures of attention and executive function. Spontaneous neural activity was also extracted from these attention-related cortical areas and examined with respect to HAND status. Results HIV-infected participants with and without HAND exhibited behavioral selective attention deficits on the magnetoencephalography task, as indicated by an increased flanker effect. Neuronal measures of flanker interference activity in the alpha and theta range revealed differential dynamics in attention-related brain areas across the 3 groups, especially in those with HAND. In addition, theta range flanker interference activity in the left inferior frontal and dorsolateral prefrontal cortex was associated with executive function and attention composite scores, respectively. Progressively stronger spontaneous alpha and theta activity was also found in unimpaired HIV-infected and HAND participants relative to controls across brain regions implicated in different components of attention processing. Conclusions Behavioral and neuronal metrics of selective attention performance distinguish participants with HAND from controls and unimpaired HIV-infected participants. These metrics, along with measures of local spontaneous neural activity, may hold promise as early markers of cognitive decline in participants with HIV infection and be useful prognostic indicators for HAND.
Market Model Benchmark Suite for Machine Learning Techniques

Recent developments in deep-reinforcement learning have yielded promising results in artificial games and test domains. To explore opportunities and evaluate the performance of these machine learning techniques, various benchmark suites are available, such as the Arcade Learning Environment, rllab, OpenAI Gym, and the StarCraft II Learning Environment. This set of benchmark suites is extended with the open business simulation model described here, which helps to promote the use of machine learning techniques as valueadding tools in the context of strategic decision making and economic model calibration and harmonization. The benchmark suite extends the current state-of-the-art problems for deep-reinforcement learning by offering an infinite state and action space for multiple players in a non-zero-sum game environment of imperfect information. It provides a model that can be characterized as both a credit assignment problem and an optimization problem. Experiments with this suite? s deep-reinforcement learning algorithms, which yield remarkable results for various artificial games, highlight that stylized market behavior can be replicated, but the infinite action space, simultaneous decision making, and imperfect information pose a computational challenge. With the directions provided, the benchmark suite can be used to explore new solutions in machine learning for strategic decision making and model calibration.
Abaloparatide versus teriparatide: a head to head comparison of effects on fracture healing in mouse models

Background and purpose — Teriparatide accelerates fracture healing in animals and probably in man. Abaloparatide is a new drug with similar although not identical effects on the teriparatide receptor. Given at 4 times the teriparatide dose in a human osteoporosis trial, abaloparatide increased bone density more than teriparatide, and both reduced fracture risk. We investigated in mice whether abaloparatide stimulates fracture healing, and if it does so with the suggested dose effect relation (4:1). Patients and methods — In a validated mouse model for metaphyseal healing (burr hole with screw pull-out), 96 mice were randomly allocated to 11 groups: control (saline), teriparatide or abaloparatide, where teriparatide and abaloparatide were given at 5 different doses each. In a femoral shaft osteotomy model, 24 mice were randomly allocated to 3 groups: control (saline), teriparatide (15 µg/kg) or abaloparatide (60 µg/kg). Each treatment was given daily via subcutaneous injections. Results were evaluated by mechanical testing and microCT. Results — In the metaphyseal model, a dose-dependent increase in screw pull-out force could be seen. In a linear regression analysis (r = 0.78) each increase in ln(dose) by 1 (regardless of drug type) was associated with an increase in pull-out force by 1.50 N (SE 0.18) (p < 0.001). Changing drug from teriparatide to abaloparatide increased the force by 1.41 N (SE 0.60; p = 0.02). In the diaphyseal model, the callus density was 23% (SD 10), 38% (SD 10), and 47% (SD 2) for control, for teriparatide and abaloparatide respectively. Both drugs were significantly different from controls (p = 0.001 and p = 0.008), but not from each other. Interpretation — Both drugs improve fracture healing, but in these mouse models, the potency per µg of abaloparatide seems only 2.5 times that of teriparatide, rather than the 4:1 relation chosen in the clinical abaloparatide–teriparatide comparison trial.
Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data

Searching for high-dimensional vector data with high accuracy is an inevitable search technology for various types of data. Graph-based indexes are known to reduce the query time for high-dimensional data. To further improve the query time by using graphs, we focused on the indegrees and outdegrees of graphs. While a sufficient number of incoming edges (indegrees) are indispensable for increasing search accuracy, an excessive number of outgoing edges (outdegrees) should be suppressed so as to not increase the query time. Therefore, we propose three degree-adjustment methods: static degree adjustment of not only outdegrees but also indegrees, dynamic degree adjustment with which outdegrees are determined by the search accuracy users require, and path adjustment to remove edges that have alternative search paths to reduce outdegrees. We also show how to obtain optimal degree-adjustment parameters and that our methods outperformed previous methods for image and textual data.
Adipose-derived stromal vascular fraction aids epithelialisation and angiogenesis in an animal model.

OBJECTIVE Limited data exist regarding the correlation between adipose-derived stromal vascular fraction (SVF) and wound healing. The aim of this study was to investigate the direct effect of intradermally injected SVF on full-thickness cutaneous wounds in a murine model. METHOD Wistar rats were divided into three groups (A, B and C) according to their day of euthanasia (day 7, 16 and 21). Inguinal fat pad was excised and SVF enzymatically extracted. Full-thickness cutaneous wounds were created on each side of the dorsum; SVF injected intradermally at one side while the contralateral wound served as control receiving normal saline. Postoperatively, evaluation of wound healing was performed by planimetry (percentages of wound contraction, epithelialisation and total wound healing) on days 0, 3, 5, 7, 10, 13, 16 and 21, and histology and immunochemistry (cellular infiltration score, collagen production score, neoangiogenesis and epithelial thickness) on days 7, 16 and 21. RESULTS Despite the high rate of wound contraction, it was significantly lower in the SVF-treated wounds on day 21 (p=0.037). On days 13, 16 and 21, the percentages of epithelialisation were higher in the SVF-treated wounds compared with control wounds (p=0.026, p=0.048 and p=0.05, respectively). Histologically, the number of new vessels was significantly higher in the SVF-treated wounds compared with controls on days seven (p=0.028) and 16 (p=0.027). This was also confirmed by immunohistochemistry. No significant differences were found between treated and control wounds regarding cellular infiltration score, collagen production score and epithelial thickness. CONCLUSION Data indicate that intradermally injected SVF increases angiogenesis and enhances epithelialisation in full-thickness cutaneous wounds in rats.
Influence of the Right Ventricular Lead Location on Ventricular Arrhythmias in Cardiac Resynchronization Therapy

Background: The influence of different right ventricular lead locations on ventricular arrhythmias (VTA) in patients with a cardiac resynchronization therapy (CRT) is not clear. This study aimed to evaluate the influence on VTA in patients with a CRT when right ventricular lead was positioned at the right ventricular middle septum (RVMS) and the right ventricular apical (RVA). Methods: A total of 352 patients implanted with a CRT-defibrillator (CRT-D) between May 2012 and July 2016 in the Department of Cardiology of Anhui Provincial Hospital were included. Two-year clinical and pacemaker follow-up data were collected to evaluate the influence of the right ventricular lead location on VTA. Patients were divided into the RVMS group (n = 155) and the RVA group (n = 197) based on the right ventricular lead position. The VTA were compared between these two groups using a Kaplan-Meier curve and Cox multivariate analysis. Results: When the left ventricular lead location was not considered, RVMS and RVA locations did not affect VTA. However, the subgroup analysis results showed that when the left ventricular lead was positioned at the anterolateral cardiac vein (ALCV), the RVMS group had an increased risk of ventricular arrhythmias and appropriate defibrillation (hazard ratio [HR] = 3.29, P = 0.01 and HR = 4.33, P < 0.01, respectively); when the left ventricular lead was at the posterolateral cardiac vein (PLCV), these risks in the RVMS group decreased (HR = 0.45, P = 0.02 and HR = 0.33, P < 0.01, respectively), and when the left ventricular lead was at the lateral cardiac vein, there was no difference between the two groups. In regard to inappropriate defibrillation, there was no significant difference among all these groups. Conclusions: When the left ventricular lead was positioned at ALCV or PLCV, the right ventricular lead location was associated with VTA and appropriate defibrillation after CRT. Greater distances between leads not only improved cardiac function but also may reduce the risk of VTA.
Fusion of Interest Point/Image based descriptors for efficient person re-identification

The paper proposes a novel video-based person re-identification system that consists of describing a person using both Interest Points (IP) and Image-based features. The Image-based descriptor extracts global image representation that includes the silhouette but also possibly extra objects (i.e animal, stroller, etc) while the IP-based descriptor extracts salient points associated each with a local region of one of the objects. Two reidentification systems are proposed: an IP-based system using SURF interest points matched via sparse representation, and Image-based system using a Convolutional Neural Network. To harness both representations, we propose a fusing strategy based on the scores product rule, the scores being vote vectors associated with each descriptor for each person. Our proposal is evaluated on the large public dataset PRID-2011 and the results show its effectiveness compared to the state of the art.