Miracle-dz/UniFAR-FTUs huggingface dataset:
Thiazolidinedione induces a therapeutic effect on hepatosteatosis by regulating stearoyl-CoA desaturase-1, lipase activity, leptin and resistin

Hepatosteatosis is a disease present worldwide, which presents a number of health problems. Recently, thiazolidinedione (TZD) has been used as a therapy for lipid disorders. The present study demonstrates the potential of TZD as a treatment for hepatosteatosis and its mechanism of action, particularly focusing on its role in lipid metabolism. A total of 60 (80–90 g) rats were divided into three groups: A normal group with a standard diet, a high-fat, high-carbohydrate diet (HFCD) group or a HFCD+TZD group (n=20/group). The HFCD induced hepatosteatosis over a period of 12 weeks and the HFCD+TZD group were administered TZD in weeks 13–16. Blood and tissue samples were collected to measure hepatic function, the lipid profile, metabolism and hormone biomarkers, including serum triglyceride (TG), lipoprotein lipase (LPL), stearoyl-CoA desaturase (SCD-1), leptin and resistin. The HFCD-fed rats exhibited a significant increase in serum TG, total cholesterol, low-density lipoproteins, alanine transaminase and bilirubin compared with the normal group as well as a significant decrease in high-density lipoprotein. In addition, serum leptin and resistin were significantly elevated in the HFCD group compared with the normal group. The administration of TZD significantly increased SCD-1 activity and significantly inhibited LPL activity. It also attenuated the changes in the lipid profiles and normalized serum leptin and resistin levels. The results of the present study indicated that HFCD induced lipid abnormalities associated with hypertriglyceridemia, hypercholesterolemia and hepatosteatosis. These changes resulted from disruption to leptin and resistin, which may be due to alterations in LPL and SCD-1 activity. TZD mitigated the effects of HFCD-induced hepatosteatosis, indicating a possible regulatory effect of TZD in the development of hepatosteatosis. The authors suggest that the manipulation of SCD-1 and lipase by TZD may be useful as a treatment for hepatosteatosis.
Turning off the empathy switch: Lower empathic concern for the victim leads to utilitarian choices of action

Empathy enables people to vicariously experience the other’s pain. At the same time, the focus of empathy can be narrow and reserved for a limited number of people. In sacrificial dilemmas, non-empathic people are more likely to sacrifice one person for greater good. However, no study has investigated the role of diminished empathic concern for the victim in utilitarian choices of action. In two studies, we investigated how empathy actually experienced in sacrificial dilemmas affects a decision to perform a harmful action onto the victim. In Study 1 (N = 275), participants were asked to rate the extent to which they were feeling two divergent tropes of affective empathy: other-oriented empathy (empathic concern) and self-oriented empathy (personal distress). Results showed that lower levels of other-focused empathy for the victim predicted utilitarian choices of action. In Study 2 (N = 170), participants were asked to rate the extent to which they empathized with the victim and the saved. We also assessed dispositional empathy and psychopathy to test a hypothesis that psychopathy mediates the relationship between lower empathy for the victim and utilitarian choices of action. Results supported this hypothesis, whereas dispositional empathy was not significantly correlated with utilitarian choices of action. Overall, lower empathy experienced in the dilemma situation was associated with utilitarian choices of action, and this was specific to reduced empathic concern for the victim. People choose to pursue the utilitarian end that accompanies harm onto the other as a mean when the victim is out of their empathic focus.
Subpixel Semantic Flow

Dense semantic correspondence is usually cast as a variational optimization problem. Current methods generally focus on obtaining more discriminative features (to improve the data/correspondence term), and adopt a message-passing algorithm for inference, which is generally a variant of loopy belief propagation. One drawback of such optimization is that the flow vectors are constrained to be discrete variables resulting in pixel resolution, “blocky” flow fields. The main hinderance to formulating the problem in continuous space, and hence solving the problem at subpixel resolution, is the use of histogram based descriptors such as SIFT, HOG, etc. Such sparse feature descriptors are distinctive but linearize poorly. In this paper, we revisit a classic dense descriptor, namely Geometric Blur, which is, in contrast, extracted from a linear filter (spatially varying Gaussian) response that can be linearized and therefore interpolated at subpixel values. In addition to the data and smoothness terms used in variational models, we also add a term promoting bidirectional flow consistency. As there is no longer a finite set of values a flow vector can take, we use gradient descent based continuous optimization. We present promising results encouraging the use of gradient based continuous optimization in establishing dense semantic correspondences. The proposed subpixel approach is applicable to any dense descriptor, including the mid-level convolutional layer outputs of convolutional neural networks (CNNs).
An ER surface retrieval pathway safeguards the import of mitochondrial membrane proteins in yeast

ER-SURF protein import into mitochondria Eukaryotic cells contain membrane-bound organelles, defined by distinct protein compositions. Almost all cellular proteins are synthesized in the cytosol, and thus, organelle-resident proteins must be directed to their appropriate location after synthesis. Working in yeast, Hansen et al. identified a protein-targeting paradigm termed ER-SURF, in which the membrane expanse of the endoplasmic reticulum (ER) serves as a “capture net” for mitochondrial proteins. This process productively redirected mitochondrial precursor proteins for efficient mitochondrial import. Thus, two distinct organelles, once thought to be mutually exclusive protein destinations, can cooperate during protein targeting. Science, this issue p. 1118 The endoplasmic reticulum surface plays a part in the productive targeting of membrane proteins to mitochondria. The majority of organellar proteins are translated on cytosolic ribosomes and must be sorted correctly to function. Targeting routes have been identified for organelles such as peroxisomes and the endoplasmic reticulum (ER). However, little is known about the initial steps of targeting of mitochondrial proteins. In this study, we used a genome-wide screen in yeast and identified factors critical for the intracellular sorting of the mitochondrial inner membrane protein Oxa1. The screen uncovered an unexpected path, termed ER-SURF, for targeting of mitochondrial membrane proteins. This pathway retrieves mitochondrial proteins from the ER surface and reroutes them to mitochondria with the aid of the ER-localized chaperone Djp1. Hence, cells use the expanse of the ER surfaces as a fail-safe to maximize productive mitochondrial protein targeting.
Wholegrain Intake and Risk of Type 2 Diabetes: Evidence from Epidemiological and Intervention Studies

Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases and represents a leading cause of morbidity and mortality because of its related complications. The alarming rise in T2DM prevalence worldwide poses enormous challenges in relation to its social, economic, and a clinical burden requiring appropriate preventive strategies. Currently, lifestyle modifications—including approaches to promote a moderate body weight reduction and to increase regular physical exercise—are the first crucial intervention for T2DM prevention. In the light of the difficulty in reducing body weight and in long-term maintenance of weight loss, quality changes in dietary patterns—in terms of macro and micronutrient composition—can also strongly affect the development of T2DM. This may provide a more practical and suitable preventative approach than simply implementing caloric restriction. Along this line, there is increasing evidence that wholegrain consumption in substitution of refined grains is associated with a reduction of the incidence of several non-communicable chronic diseases. The aim of the present review is to summarize the current evidence from observational and randomized controlled clinical trials on the benefits of wholegrain on T2DM prevention and treatment. Plausible mechanisms by which wholegrain could act on glucose homeostasis and T2DM prevention are also evaluated. Altogether, the totality of the available evidence supports present dietary recommendations promoting wholegrain foods for the prevention and treatment of T2DM.
Immunoexpression of claudins 4 and 7 among invasive breast carcinoma subtypes: A large diagnostic study using tissue microarray

Molecular phenotyping and tissue microarray (TMA) studies have identified distinct invasive breast carcinoma subtypes: Luminal A, luminal B, enriched with overexpressed human epidermal growth factor receptor 2 (HER-2) and triple-negative, i.e., negative for HER-2, as well as for estrogen and progesterone receptor (ER and PR, respectively) expression. These subtypes are useful in clinical management, since they bear distinct prognoses and predictive responses to targeted therapy. However, although molecular profiling provides important prognostic indicators, breast cancer risk stratification remains a challenge in triple-negative cases. What is referred to as claudin-low subtype was identified as a triple-negative subset that is associated with more aggressive tumor behavior and worse prognosis. However, the immunohistochemical expression of claudins has not yet been standardized. Our objective was to verify whether the immunoexpression of claudins 4 and 7 (the main claudins specifically expressed in human breast tissue) in TMA is associated with survival and prognosis in luminal A, HER-2 and triple-negative molecular subtypes. In this diagnostic study, we investigated ER/PR receptor status, HER-2, claudin 4 and 7 expression and stem cell CD44/24 profiles, and verified the association with prognosis and survival outcomes in 803 invasive breast carcinoma cases arranged in four TMAs. Among these, 503 (62.6%) were positive for claudin 4 and 369 (46.0%) for claudin 7. Claudin 4 exhibited the lowest expression in luminal A and triple-negative subtypes, and the highest frequency of expression in HER-2-enriched subtypes, whereas claudin 7 staining was not associated with any subtype. The stem cell phenotype was not associated with subgroups or claudins 4 and 7. Claudin immunoexpression profile was not able to distinguish between patients with better or worse prognosis, and it was not correlated to triple-negative cases. Therefore, it may be concluded that the immunoexpression of claudins 4 and 7, individually or within the usual immunohistochemical context (ER, PR and HER-2), does not provide additional prognostic information on breast cancer subtypes.
Pathwise Dynamic Programming

We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and upper bounds ensures that the method is applicable even when the dynamic program does not satisfy a comparison principle. We apply our method to three nonlinear option pricing problems, pricing under bilateral counterparty risk, under uncertain volatility, and under negotiated collateralization.
Case Study Evaluation of an Initiative to Help Small and Limited-Resource Farmers Supply Produce Commercially

The evaluation of a university-based initiative to assist small and limited-resource farmers to supply produce commercially is presented as a case study that examined sample findings in the areas of research, extension, education and integration, and enterprise, which described the business aspect. The sample findings presented were from research efforts to provide sustainable irrigation, extension efforts to provide integrated pest management training, integrated efforts to provide food safety training and technical assistance, and an economic assessment of the impacts on the household economy. Although it may be validly argued to the contrary, it was concluded that the findings from the various efforts in research, extension, and enterprise were significant and substantial. The examination of all four areas was shown to provide a broader, more comprehensive evaluation of the program.
Effects of a group activity-based motivational enhancement therapy program on social media addictive behaviors among junior high school students in Thailand: a cluster randomized trial

Purpose This study aimed to assess the effects of a group activity-based motivational enhancement therapy (GA-MET) program on social media addictive behaviors among junior high school students. Materials and methods This cluster randomized trial was performed in 245 junior high school students who used social media in the lower part of northeast Thailand. The GA-MET program group and the control group sessions lasted 8 weeks and were followed up 4 weeks later. The addictive social media behaviors, average duration of social media usage during weekdays and weekends (hours/day), child behaviors, self-esteem, and depression were investigated using a self-reported questionnaire. Multivariable linear regression was used to compare the mean and 95% CIs between two groups. Results The GA-MET program significantly decreased the average duration of social media usage during weekdays and weekends (hours/day) (−1.27, 95% CI: −2.18,−0.37 and −1.25, 95% CI: −2.22, −0.29, respectively), emotional behavior (−0.69, 95% CI: −1.18, −0.19), and depression (−4.03, 95% CI: −6.07, −1.99) in the treated group compared to the control group. Conclusion The GA-MET program could reduce the risk of social media addictive behaviors in junior high school students in Thailand by decreasing time spent on social media, emotional behaviors, and depression.
Structural and mechanistic basis for preferential deadenylation of U6 snRNA by Usb1

Abstract Post-transcriptional modification of snRNA is central to spliceosome function. Usb1 is an exoribonuclease that shortens the oligo-uridine tail of U6 snRNA, resulting in a terminal 2′,3′ cyclic phosphate group in most eukaryotes, including humans. Loss of function mutations in human Usb1 cause the rare disorder poikiloderma with neutropenia (PN), and result in U6 snRNAs with elongated 3′ ends that are aberrantly adenylated. Here, we show that human Usb1 removes 3′ adenosines with 20-fold greater efficiency than uridines, which explains the presence of adenylated U6 snRNAs in cells lacking Usb1. We determined three high-resolution co-crystal structures of Usb1: wild-type Usb1 bound to the substrate analog adenosine 5′-monophosphate, and an inactive mutant bound to RNAs with a 3′ terminal adenosine and uridine. These structures, along with QM/MM MD simulations of the catalytic mechanism, illuminate the molecular basis for preferential deadenylation of U6 snRNA. The extent of Usb1 processing is influenced by the secondary structure of U6 snRNA.
The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments

We evaluate the effect of discussion on the accuracy of collaborative judgments. In contrast to prior research, we show that discussion can either aid or impede accuracy relative to the averaging of collaborators’ independent judgments, as a systematic function of task type and interaction process. For estimation tasks with a wide range of potential estimates, discussion aided accuracy by helping participants prevent and eliminate egregious errors. For estimation tasks with a naturally bounded range, discussion following independent estimates performed on par with averaging. Importantly, if participants did not first make independent estimates, discussion greatly harmed accuracy by limiting the range of considered estimates, independent of task type. Our research shows that discussion can be a powerful tool for error reduction, but only when appropriately structured: Decision makers should form independent judgments to consider a wide range of possible answers, and then use discussion to eliminate extreme.
Genetic diversity in Astragalus argaeus, a critically endangered species from Turkey

Astragalus argaeus is critically endangered endemic species growing only on Erciyes Mountain in Kayseri. Inter simple sequence repeat (ISSR) markers were chosen to detect the genetic diversity in four populations of A. argaeus. Ten primers were used to assess the diversity among 96 genotypes collected from the four localities in Erciyes Mountain. A total of 78 bands were scored, of which 44 (55.8%) were polymorphic. The unweighted pair group method arithmetic average (UPGMA) and principle component analysis (PCoA) showed moderate genetic diversity at the species and population level. The percentages of polymorphic bands (PPB) ranged from 53.8 to 61.5 (58.01% ± 3.2) and average gene diversity (h) at the population and species level was estimated to be 0.17 and 0.23, respectively. The Shannon’s information index (SI) ranged from 0.24 to 0.29 at the population level and was 0.35 at the species level. The determined gene flow (Nm) was 1.83. The UPGMA tree indicated that the four populations were not genetically distinct obviously. In analysis of molecular variance (AMOVA), the percentage of the variance was 38.72% among populations and 61.28% within populations. The data which small population size, habitat fragmentation and moderate levels of genetic diversity demonstrate that A. argaeus possess threat of extinction if its narrow habitat is destroyed.
Unconscious Biases in Neural Populations Coding Multiple Stimuli

Throughout the nervous system, information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However, in many situations, multiple stimuli are simultaneously present; for example, multiple motion patterns might overlap. Here we find that when multiple stimuli that overlap in their neural representation are simultaneously encoded in the population, biases in the read-out emerge. Although the bias disappears in the absence of noise, the bias is remarkably persistent at low noise levels. The bias can be reduced by competitive encoding schemes or by employing complex decoders. To study the origin of the bias, we develop a novel general framework based on gaussian processes that allows an accurate calculation of the estimate distributions of maximum likelihood decoders, and reveals that the distribution of estimates is bimodal for overlapping stimuli. The results have implications for neural coding and behavioral experiments on, for instance, overlapping motion patterns.
Structural Constraints for Dynamic Operators in Abstract Argumentation

Many recent studies of dynamics in formal argumentation within AI focus on the well-known formalism of Dung’s argumentation frameworks (AFs). Despite the usefulness of AFs in many areas of argumentation, their abstract notion of arguments creates a barrier for operators that modify a given AF, e.g., in the case that dependencies between arguments have been abstracted away that are important for subsequent modifications. In this paper we aim to support development of dynamic operators on formal models in abstract argumentation by providing constraints imposed on the modification of the structure that can be used to incorporate information that has been abstracted away. Towards a broad reach, we base our results on the general formalism of abstract dialectical frameworks (ADFs) in abstract argumentation. To show applicability, we present two cases studies that adapt an existing extension enforcement operator that modifies AFs: in the first case study, we show how to utilize constraints in order to obtain an enforcement operator on ADFs that is allowed to only add support relations between arguments, and in the second case study we show how an enforcement operator on AFs can be defined that respects dependencies between arguments. We show feasibility of our approach by studying the complexity of the proposed structural constraints and the operators arising from the case studies, and by an experimental evaluation of an answer set programming (ASP) implementation of the enforcement operator based on supports.
What the doctor doesn’t know: Discarded patient knowledge of older adults with multimorbidity

Objectives Adherence to treatment has proven to require the involvement of patients in treatment and care planning. This process involves incorporating patient knowledge, or knowledge about the patients’ everyday life, into the clinical encounter. This article explores the disclosure practices of such knowledge from older adults with multimorbidity. Methods This was an 18-month qualitative study among 14 older adults with multimorbidity living in Denmark. A thematic analysis was applied, focusing on perceptions of patient knowledge and disclosure practices among the participating patients. Results Older adults with multimorbidity have various reasons for not disclosing personal knowledge. The results present three different domains of what we termed discarded patient knowledge: (1) knowledge that had no direct biomedical relevance from participants’ perspective; (2) knowledge considered too private; and (3) knowledge assumed to position one as inferior. Discussion The participants made judgments on what they believed was welcome in the clinical encounter, framing their knowledge within the purview of biomedicine. Participants’ disclosure practices showed that personal knowledge is sometimes not recognized as important for health and care by participants themselves. Knowledge that could have influenced practitioners’ understanding of the problem and provided different solutions, is argued to be discarded patient knowledge.
Enumerating Preferred Extensions Using ASP Domain Heuristics: The ASPrMin Solver

This paper brieﬂy describes the solver ASPrMin, which enu-merates preferred extensions and scored ﬁrst in the Extension Enumer-ation problem—the only one implemented—of the Preferred Semantics Track of the Second International Competition on Computational Models of Argumentation, ICCMA17.
SafeCity: Understanding Diverse Forms of Sexual Harassment Personal Stories

With the recent rise of #MeToo, an increasing number of personal stories about sexual harassment and sexual abuse have been shared online. In order to push forward the fight against such harassment and abuse, we present the task of automatically categorizing and analyzing various forms of sexual harassment, based on stories shared on the online forum SafeCity. For the labels of groping, ogling, and commenting, our single-label CNN-RNN model achieves an accuracy of 86.5%, and our multi-label model achieves a Hamming score of 82.5%. Furthermore, we present analysis using LIME, first-derivative saliency heatmaps, activation clustering, and embedding visualization to interpret neural model predictions and demonstrate how this helps extract features that can help automatically fill out incident reports, identify unsafe areas, avoid unsafe practices, and ‘pin the creeps’.