Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety and Efficacy of Low-Level Laser Therapy in Autoimmune Thyroiditis: Long-Term Follow-Up Study

Introduction A randomized clinical trial (RCT) was performed to evaluate the efficacy of low-level laser therapy (LLLT) for hypothyroidism induced by chronic autoimmune thyroiditis (CAT). Objective The objective was to assess the safety and actions of LLLT 6 years after completion of the RCT. Materials and Methods Forty-three participants were invited to participate in this study 6 years after completion of the RCT. Twenty-five were subjected to LLLT (group L), and 18 were subjected to placebo (group P). Primary outcome measure: frequency of thyroid nodules, which were subjected to fine-needle aspiration biopsy. Secondary outcome measures: dose of levothyroxine required to treat hypothyroidism, thyroid peroxidase antibodies (anti-TPO), and anti-thyroglobulin antibodies (anti-Tg). Results In group L, a nodule was observed in three patients, who all had a Bethesda II classification. In group P, a nodule was also observed in three patients, with two classified as Bethesda II and one as Bethesda III. The levothyroxine dose required by group L was significantly lower than that required by group P (P = 0.002). The anti-TPO and anti-Tg levels did not differ between the groups. Conclusion LLLT, by the methods described, has been shown to be safe for the treatment of hypothyroidism resulting from CAT. This trial is registered with ClinicalTrials.gov Identifier: NCT02240563.
Online Learning and Decision-Making under Generalized Linear Model with High-Dimensional Data

We propose a minimax concave penalized multi-armed bandit algorithm under generalized linear model (G-MCP-Bandit) for a decision-maker facing high-dimensional data in an online learning and decision-making process. We demonstrate that the G-MCP-Bandit algorithm asymptotically achieves the optimal cumulative regret in the sample size dimension T , O(log T), and further attains a tight bound in the covariate dimension d, O(log d). In addition, we develop a linear approximation method, the 2-step weighted Lasso procedure, to identify the MCP estimator for the G-MCP-Bandit algorithm under non-iid samples. Under this procedure, the MCP estimator matches the oracle estimator with high probability and converges to the true parameters with the optimal convergence rate. Finally, through experiments based on synthetic data and two real datasets (warfarin dosing dataset and Tencent search advertising dataset), we show that the G-MCP-Bandit algorithm outperforms other benchmark algorithms, especially when there is a high level of data sparsity or the decision set is large.
First-Time Fathers' Experience of Support from Midwives in Maternity Clinics: An Interview Study

Background Research shows that first-time fathers want to take part in preparation for birth and parenthood but they describe being excluded by health professionals. Aim The aim of this study was to illustrate first-time fathers' experiences of support from midwives in maternity clinics as a step in the validation of “The Father Perceived-Professional-Support” (The FaPPS) scale. Methods A qualitative content analysis with an inductive and deductive approach was used; seven first-time fathers were strategically selected and interviewed. In the inductive part the following open question was asked: “How did you perceive the support from the antenatal midwife/midwives? ” In the deductive part, the fathers were asked to respond to the FaPPS scale, in order to receive their thoughts and understanding of the scale, inspired by the “Think-aloud” method. Findings The inductive results showed two main categories: Experience of not knowing what support they needed and Experience of being excluded. The fathers found support from other fathers in parental education classes, but they lack time to discuss. Overall it seems as if the fathers answered both from their own perspective and from the mothers' perspective. This was not evident in the deductive results. The FaPPs scale should therefore include professionals' ability to strengthen social support from other first-time fathers and professionals' ability to offer support to the mother. Conclusion and Clinical Implications. The fathers experienced exclusion both by themselves and also by midwives. Midwives should offer both parents the opportunity to pose questions. It is important for expectant fathers that time for discussion is planned in parental education classes. The FaPPS scale is useful but needs further development. Parts of our result are in line with earlier research, for decades; therefore it is necessary to focus more on support for fathers.
Adversarial Transfer Learning

There is a recent large and growing interest in generative adversarial networks (GANs), which offer powerful features for generative modeling, density estimation, and energy function learning. GANs are difficult to train and evaluate but are capable of creating amazingly realistic, though synthetic, image data. Ideas stemming from GANs such as adversarial losses are creating research opportunities for other challenges such as domain adaptation. In this paper, we look at the field of GANs with emphasis on these areas of emerging research. To provide background for adversarial techniques, we survey the field of GANs, looking at the original formulation, training variants, evaluation methods, and extensions. Then we survey recent work on transfer learning, focusing on comparing different adversarial domain adaptation methods. Finally, we take a look forward to identify open research directions for GANs and domain adaptation, including some promising applications such as sensor-based human behavior modeling.
Nicotine and Cotinine Inhibit Catalase and Glutathione Reductase Activity Contributing to the Impaired Osteogenesis of SCP-1 Cells Exposed to Cigarette Smoke

Cigarette smoking has been identified as a major risk factor for osteoporosis decades ago. Several studies have shown a direct relationship between cigarette smoking, decreased bone mineral density, and impaired fracture healing. However, the mechanisms behind impaired fracture healing and cigarette smoking are yet to be elucidated. Migration and osteogenesis of mesenchymal stem/stromal cells (MSCs) into the fracture site play a vital role in the process of fracture healing. In human nicotine, the most pharmacologically active and major addictive component present in tobacco gets rapidly metabolized to the more stable cotinine. This study demonstrates that physiological concentrations of both nicotine and cotinine do not affect the osteogenic differentiation of MSCs. However, cigarette smoke exposure induces oxidative stress by increasing superoxide radicals and reducing intracellular glutathione in MSCs, negatively affecting osteogenic differentiation. Although, not actively producing reactive oxygen species (ROS) nicotine and cotinine inhibit catalase and glutathione reductase activity, contributing to an accumulation of ROS by cigarette smoke exposure. Coincubation with N-acetylcysteine or L-ascorbate improves impaired osteogenesis caused by cigarette smoke exposure by both activation of nuclear factor erythroid 2-related factor 2 (Nrf2) signaling and scavenging of ROS, which thus might represent therapeutic targets to support fracture healing in smokers.
Transfer learning for vision-based tactile sensing

Due to the complexity of modeling the elastic properties of materials, the use of machine learning algorithms is continuously increasing for tactile sensing applications. Recent advances in deep neural networks applied to computer vision make vision-based tactile sensors very appealing for their high-resolution and low cost. A soft optical tactile sensor that is scalable to large surfaces with arbitrary shape is discussed in this paper. A supervised learning algorithm trains a model that is able to reconstruct the normal force distribution on the sensor’s surface, purely from the images recorded by an internal camera. In order to reduce the training times and the need for large datasets, a calibration procedure is proposed to transfer the acquired knowledge across multiple sensors while maintaining satisfactory performance.
On generation of node distributions for meshless PDE discretizations

In this paper we present an algorithm that is able to generate locally regular node layouts with spatially variable nodal density for interiors of arbitrary domains in two, three and higher dimensions. It is demonstrated that the generated node distributions are suitable to use in the RBF-FD method, which is shown by solving Poisson's and convection-diffusion equations. Additionally, local minimal spacing guarantees are proven for both uniform and variable nodal densities. The presented algorithm has time complexity $O(N)$ to generate $N$ nodes with constant nodal spacing and $O(N \log N)$ to generate variably spaced nodes. Comparison with existing algorithms is performed in terms of node quality, time complexity, execution time and PDE solution accuracy.
RNA Sequencing for Gene Expression Profiles in a Rat Model of Middle Cerebral Artery Occlusion

Gene expression regulatory mechanisms in models of middle cerebral artery occlusion (MCAO) have been assessed in some studies, but questions remain. The discovery of differentially expressed genes (DEGs) between MCAO and control rats analyzed by next-generation RNA sequencing is of particular interest. These DEGs may help guide the clinical diagnosis of stroke and facilitate selection of the optimal treatment strategy. Twenty rats were equally divided into control and MCAO groups. Three rats from each group were randomly selected for RNA sequencing analysis. Sequence reads were obtained from an Illumina HiSeq2500 platform and mapped onto the rat reference genome RN6 using Hisat2. We identified 1,007 significantly DEGs with p<0.05, including 785 upregulated (fold change [FC]>2) and 222 downregulated (FC<0.5) DEGs, in brain tissue from MCAO rats compared with that from control rats, and numerous immune response genes were identified. Gene ontology (GO) analysis revealed that the majority of the most enriched and meaningful biological process terms were mainly involved in immune response, inflammatory response, cell activation, leukocyte migration, cell adhesion, response to external stimulus, cell migration, and response to wounding. Also enriched were immune-related pathways and neural-related pathways. Similar to GO molecular function terms, the enriched terms were mainly related to cytokine receptor activity. Six DEGs were verified by quantitative real-time polymerase chain reaction (qRT-PCR). Protein-protein interaction analysis of these hits revealed that MCAO affects complement and coagulation cascades and chemokine signaling pathway. Our study identified novel biomarkers that could help further elucidate MCAO mechanisms and processes.
Serine Alleviates Dextran Sulfate Sodium-Induced Colitis and Regulates the Gut Microbiota in Mice

Serine alleviates inflammatory responses and is beneficial for gut health; however, whether it exerts any effects on ulcerative colitis or regulates intestinal microbiota remains unknown. We investigated the effects of serine supplementation on colonic morphology, inflammation, and microbiota composition in dextran sulfate sodium (DSS)-induced colitis model in mice. Acute colitis was induced through the oral intake of 3.5% DSS in water for 7 days. Mice with acute colitis were divided into two groups; The DSS and Ser-treated groups were rectally administrated with PBS or 1% (w/v) serine (40 mg/kg body weight) for 7 days. The results showed that serine decreased the disease activity index, as well as myeloperoxidase, eosinophil peroxidase, and proinflammatory cytokine concentrations in colonic tissue, while serine improved colonic morphology and inhibited cell apoptosis in colitis mice. In addition, 16S rRNA phylogenetic sequencing revealed a shift in bacterial community composition, and changes in microbiota functional profiles following serine supplementation, although no significant difference in α-diversity analysis was observed. The effects of serine supplementation helped on the recovery of major perturbations to macrobiotic functions, such as amino acids metabolism; tissue replication and repair; and cell growth and death. Serine might have great potential for the renewal of colonic tissue in DSS-induced colitis.
Learning Implicit Fields for Generative Shape Modeling

We advocate the use of implicit fields for learning generative models of shapes and introduce an implicit field decoder, called IM-NET, for shape generation, aimed at improving the visual quality of the generated shapes. An implicit field assigns a value to each point in 3D space, so that a shape can be extracted as an iso-surface. IM-NET is trained to perform this assignment by means of a binary classifier. Specifically, it takes a point coordinate, along with a feature vector encoding a shape, and outputs a value which indicates whether the point is outside the shape or not. By replacing conventional decoders by our implicit decoder for representation learning (via IM-AE) and shape generation (via IM-GAN), we demonstrate superior results for tasks such as generative shape modeling, interpolation, and single-view 3D reconstruction, particularly in terms of visual quality. Code and supplementary material are available at https://github.com/czq142857/implicit-decoder.
Color Constancy by GANs: An Experimental Survey

In this paper, we formulate the color constancy task as an image-to-image translation problem using GANs. By conducting a large set of experiments on different datasets, an experimental survey is provided on the use of different types of GANs to solve for color constancy i.e. CC-GANs (Color Constancy GANs). Based on the experimental review, recommendations are given for the design of CC-GAN architectures based on different criteria, circumstances and datasets.
Cardiovascular Supportive Therapies for Neonates With Asphyxia — A Literature Review of Pre-clinical and Clinical Studies

Asphyxiated neonates often have hypotension, shock, and poor tissue perfusion. Various “inotropic” medications are used to provide cardiovascular support to improve the blood pressure and to treat shock. However, there is incomplete literature on the examination of hemodynamic effects of these medications in asphyxiated neonates, especially in the realm of clinical studies (mostly in late preterm or term populations). Although the extrapolation of findings from animal studies and other clinical populations such as children and adults require caution, it seems appropriate that findings from carefully conducted pre-clinical studies are important in answering some of the fundamental knowledge gaps. Based on a literature search, this review discusses the current available information, from both clinical studies and animal models of neonatal asphyxia, on common medications used to provide hemodynamic support including dopamine, dobutamine, epinephrine, milrinone, norepinephrine, vasopressin, levosimendan, and hydrocortisone.
WIM: Fast Locomotion in Virtual Reality with Spatial Orientation Gain & without Motion Sickness

For locomotion in Virtual Reality (VR), different approaches exist. While continuously moving across the ground through walking techniques or controller input is considered to be most similar compared to the way we move through physical space, this technique causes motion sickness and results in lack of spatial orientation. Teleportation has been shown to result in less motion sickness, while being slower than moving continuously in most virtual environments. World-in-miniature (WIM) allows the user for changing his/her viewpoint through picking and relocating his/her representing icon in a virtual miniature replica of the VR he/she is located in. To see if WIM may be an alternative locomotion technique to continuous motion, we compared the three locomotion techniques contentious motion, teleportation and, WIM (see Fig. 1). We found that WIM outperforms the other two techniques in navigation time for longer distances. Furthermore, it provides best spatial knowledge while causing least motion sickness among the compared methods. We conclude with proposing to provide VR users with a set of locomotion techniques that allows for continuous motion when only moving little, while WIM could be used for moving over longer distances and in environments that are difficult to oversee.
An Item-Level Analysis of the Posttraumatic Stress Disorder Checklist and the Posttraumatic Growth Inventory and Its Associations With Challenge to Core Beliefs and Rumination

Background: Previous studies have found that rumination and challenge to core beliefs may have a predictive effect on Posttraumatic Stress Disorder (PTSD) and Posttraumatic Growth (PTG) among different samples. In addition, there is some evidence that these variables have different effects on PTSD and PTG, although the latter construct has been the target of a larger body of research and theoretical models. The main objective of the current study is to examine the effect of challenge to core beliefs, intrusive rumination, and deliberate rumination on PTSD and PTG, through an item-level analyses. Methods: The sample was composed of 205 Portuguese women who had been given a breast cancer diagnosis (M = 54.32, SD = 10.05), and who completed the following self-administered questionnaires: the Posttraumatic Stress Disorder Checklist (PCL-C); the Posttraumatic Growth Inventory (PTGI); the Core Beliefs Inventory; and the Event Related Rumination Inventory. Two multivariate multiple regression analyses, using each item of the PCL-C and the PTGI as dependent variables, were conducted. Results: The results demonstrated that challenges to core beliefs predict 17 of the 21 PTGI items and 12 of the 17 PCL-C items. All but one item of the PCL-C are predicted by intrusive rumination, while the variance of only 4 items of the PTGI are explained by deliberate rumination. Conclusion: These findings indicate that women with breast cancer who tend to display higher levels of intrusive rumination are more likely to report PTSD symptoms, and that an examination of one’s core beliefs is predictor of both positive and negative outcomes. In spite of the proven effect of challenge to core beliefs on both variables, this study suggests that this effect has only a minor influence on PTSD, in addition to confirming its major impact on PTG.
Tranexamic Acid for Adults with Melasma: A Systematic Review and Meta-Analysis

Objective Melasma is a highly prevalent, chronic, and pigmentary disorder. This systematic review aims to evaluate the efficacy and safety of tranexamic acid (TA) for the treatment of adults with melasma. Methods We independently searched 3 databases from beginning to 26 April, 2018. The study included 21 eligible trials. Two writers extracted data at the same time independently. Study outcomes were calculated by standardized mean differences (SMD) with 95% confidence intervals (CIs). All statistical analyses were performed using Review Manager Version 5.3 and STATA Version 15.1. Results The combined results showed that the use of TA was associated with reduced Melasma Area and Severity Index (MASI) and Melanin Index (MI). No significant difference in Erythema Index (EI) was observed with TA treatment. Side effects were minor, with a few cases reporting mild gastrointestinal reaction, oligomenorrhoea, hypopigmentation, urticarial rash, and skin irritation xerosis. Conclusion The meta-analysis suggested that TA treatment appeared to be a promising therapeutic approach for melasma.
Modeling spreading processes in complex networks

DE ARRUDA, G. F. Modeling spreading processes in complex networks. 2018. 299 p. Tese (Doutorado em Ciências – Ciências de Computação e Matemática Computacional) – Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos – SP, 2018. Mathematical modeling of spreading processes have been largely studied in the literature, and its presented a boom in the past few years. This is a fundamental task on the understanding and prediction of real spreading processes on top of a population and are subject to many structural and dynamical constraints. Aiming at a better understanding of this processes, we focused in two task: the modeling and the analysis of both dynamical and structural aspects of these processes. Initially, we proposed a new and general model that unifies epidemic and rumor spreading. Besides, regarding the analysis of these processes, we extended the classical formalism to multilayer networks, in which the theory was lacking. Interestingly, this study opened up new challenges concerning the understanding of multilayer networks. More specifically, regarding their spectral properties. In this thesis, we analyzed such processes on top of single and multilayer networks. Thus, throughout our analysis, we followed three complementary approaches: (i) analytical, (ii) numerical and (iii) simulations, mainly Monte Carlo simulations. Our main results are: (i) a new unifying model, enabling us to model and understand spreading processes on large systems, (ii) characterization of new phenomena on multilayer networks, such as layer-wise localization and the barrier effect and (iii) an spectral analysis of multilayer systems, suggesting a universal parameter and proposing a new analytical tool for its analysis. Our contributions enable further research on modeling of spreading processes, also emphasizing the importance of considering the complete multilayer structure instead of any coarse-graining. Additionally, it can be directly applied on the prediction and modeling real processes. Thus, aside from the theoretical interest and its mathematical implications, it also presents important social impact.
Identification of Proteins Differentially Expressed in the Striatum by Melatonin in a Middle Cerebral Artery Occlusion Rat Model—a Proteomic and in silico Approach

Ischemic stroke is characterized by permanent or transient obstruction of blood flow, which initiates a cascading pathological process, starting from acute ATP loss to subsequent membrane depolarization, glutamate excitotoxicity, and calcium overload. Melatonin is a potent antioxidant that exerts protective effects in different experimental stroke models. In this study, melatonin effects were demonstrated by a proteomic and in silico approach. The proteomic study identified differentially expressed proteins by 2D gel electrophoresis in the striatum 24 h after middle cerebral artery occlusion. Proteomic analysis revealed several proteins with aberrant expression and was validated by western blot and immunofluorescence analysis. Homology modeling was performed to build 3D structures for γ-enolase, thioredoxin (TRX), and heat shock 60 (HSP60) by the template crystal structures using a protein data bank as a sequence database. The structure refinement of each model was achieved by energy minimization via molecular dynamic simulation, and the generated models were further assessed for stability by Procheck and ProSA. The models were processed for docking analysis using AutoDock Vina, and post-docking analysis was determined by discovery studio. The proteomic study showed decreased expression of γ-enolase, TRX, and protein phosphatase 2A subunit B and increased expression of collapsin response mediator protein 2 and HSP60 in the striatum after ischemic injury. Treatment with melatonin modulated the expression profiles of these proteins. This study demonstrated the neuroprotective role of melatonin in the ischemic striatum using a proteomic and in silico approach. Collectively, melatonin may act in a multimechanistic way by modulating the expression of several proteins in the ischemic striatum.