Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Polymorphisms in miRNA Processing Genes With Type 2 Diabetes Mellitus and Its Vascular Complications in a Southern Chinese Population

Objective: To evaluate the potential association between the genetic variants in miRNA processing genes (RAN, XPO5, DICER1, and TARBP2) and susceptibility to type 2 diabetes mellitus (T2DM) and its vascular complications, as well as to further investigate their interaction with environmental factors in type 2 diabetes. Methods: We conducted a case-control study in genotyping of five polymorphic loci, including RAN rs14035, XPO5 rs11077, DICER1 rs13078, DICER1 rs3742330, and TARBP2 rs784567, in miRNA processing genes to explore the risk factors for T2DM and diabetic vascular complications. Haplotype analyses, interactions of gene-gene and interactions of gene-environment were performed too. Results: We identified a 36% decreased risk of developing T2DM in individuals with the minor A allele in DICER1 rs13078 (OR: 0.64; 95%CI: 0.42–0.95; P: 0.026). The AA haplotype in DICER1 was also associated with a protective effect on T2DM compared with the AT haplotype (OR: 0.63; 95%CI: 0.42–0.94; P-value: 0.023). T2DM patients with the TT+TC genotype at RAN rs14035 had a 1.89-fold higher risk of developing macrovascular complications than patients with the CC genotype (OR: 1.89; 95%CI: 1.04–3.45; P-value: 0.037). We also identified two three-factor interaction models. One is a three-factor [DICER1 rs13078, body mass index (BMI), and triglyceride (TG)] interaction model for T2DM (OR: 5.93; 95%CI: 1.25–28.26; P = 0.025). Another three-factor [RAN rs14035, hypertension (HP), and duration of T2DM (DOD)] interaction model was found for macrovascular complications of T2DM (OR = 41.60, 95%CI = 11.75–147.35, P < 0.001). Conclusion: Our study provides new evidence that two single nucleotide polymorphisms (SNPs) of the miRNA processing genes, DICER1 and RAN, and their interactions with certain environmental factors might contribute to the risk of T2DM and its vascular complications in the southern Chinese population.
Relationship Between White Matter Integrity and Plasma Leptin Levels in Drug-Naïve and Medicated Patients With Major Depressive Disorder

Many previous studies have noticed obvious alterations in different white matter tracts among patients with major depressive disorder (MDD). Growing evidence also strongly suggest a role of leptin in the pathogenesis of MDD, but with conflicting results of leptin levels. However, no previous studies have examined the relationship between leptin and white matter integrity of patients with MDD. Therefore, we aimed in this study to investigate the relationship between white matter alterations and plasma leptin levels in both drug-naïve and medicated MDD patients. We measured plasma leptin levels and white matter integrity using diffusion tensor imaging (DTI) and voxel-based analysis (VBA) in 140 participants (40 drug-naïve MDD patients; 40 medicated MDD patients; 60 healthy controls) aged between 18 and 49 years old. A significant reduced fractional anisotropy (FA) value in the dorsomedial thalamus was found for both drug-naïve and medicated MDD patients compared to the healthy non-depressed participants (p < 0.01, corrected). In addition, leptin levels were significantly higher in the drug-naïve MDD patients and were negatively correlated with the detected white matter alteration. Our results suggest that the elevated plasma leptin levels in the drug-naïve MDD group might be associated with the changes of the white matter integrity in the dorsomedial thalamus region.
Docking, Interaction Fingerprint, and Three-Dimensional Quantitative Structure–Activity Relationship (3D-QSAR) of Sigma1 Receptor Ligands, Analogs of the Neuroprotective Agent RC-33

The human Sigma1 receptor (S1R), which has been identified as a target with an important role in neuropsychological disorders, was first crystallized 3 years ago. Since S1R structure has no relation with another previous crystallized structures, the presence of the new crystal is an important hallmark for the design of agonists and antagonists against this important target. Some years ago, our group identified RC-33, a potent and selective S1R agonist, endowed with neuroprotective properties. In this work, drawing on new structural information, we studied the interactions of RC-33 and its analogs with the S1R binding site by using computational methods such as docking, interaction fingerprints, and receptor-guided alignment three dimensional quantitative structure–activity relationship (3D-QSAR). We found that RC-33 and its analogs adopted similar orientations within S1R binding site, with high similitude with orientations of the crystallized ligands; such information was used for identifying the residues involved in chemical interactions with ligands. Furthermore, the structure-activity relationship of the studied ligands was adequately described considering classical QSAR tests. All relevant aspects of the interactions between the studied compounds and S1R were covered here, through descriptions of orientations, binding interactions, and features that influence differential affinities. In this sense, the present results could be useful in the future design of novel S1R modulators.
Aphids Influence Soil Fungal Communities in Conventional Agricultural Systems

Arbuscular mycorrhizal fungi (AMF) form symbioses with the roots of most plant species, including cereals. AMF can increase the uptake of nutrients including nitrogen (N) and phosphorus (P), and of silicon (Si) as well as increase host resistance to various stresses. Plants can simultaneously interact with above-ground insect herbivores such as aphids, which can alter the proportion of plant roots colonized by AMF. However, it is unknown if aphids impact the structure of AMF communities colonizing plants or the extent of the extraradical mycelium produced in the soil, both of which can influence the defensive and nutritional benefit a plant derives from the symbiosis. This study investigated the effect of aphids on the plant-AMF interaction in a conventionally managed agricultural system. As plants also interact with other soil fungi, the non-AMF fungal community was also investigated. We hypothesized that aphids would depress plant growth, and reduce intraradical AMF colonization, soil fungal hyphal density and the diversity of AM and non-AM fungal communities. To test the effects of aphids, field plots of barley enclosed with insect proof cages were inoculated with Sitobion avenae or remained uninoculated. AMF specific and total fungal amplicon sequencing assessed root fungal communities 46 days after aphid addition. Aphids did not impact above-ground plant biomass, but did increase the grain N:P ratio. Whilst aphid presence had no impact on AMF intraradical colonization, soil fungal hyphal length density, or AMF community characteristics, there was a trend for the aphid treatment to increase vesicle numbers and the relative abundance of the AMF family Gigasporaceae. Contrary to expectations, the aphid treatment also increased the evenness of the total fungal community. This suggests that aphids can influence soil communities in conventional arable systems, a result that could have implications for multitrophic feedback loops between crop pests and soil organisms across the above-below-ground interface.
Psychometric Properties of a Measure of Borderline Personality Organization in a Spanish Court-Referred Partner-Violent Male Sample

Borderline personality organization (BPO) is a key personality component of some but not all partner-violent men. The study described in this paper examines the psychometric properties of the borderline personality organization scale (BPO Scale; Oldham et al., 1985) in a Spanish sample of 643 men undergoing court-mandated psychological treatment after conviction for episodes of intimate-partner violence. Three confirmatory factor analyses were carried out first, and the three-factor structure of the BPO scale was then tested. Results for concurrent validity show positive and significant correlations between the subscales and the overall BPO scale, and with other instruments that measure borderline and antisocial personality disorders (ASPDs), and impulsivity. The BPO scale also presents evidence of known-groups validity, since BPO scores decrease with age, and of discriminant validity, as the scale discriminates between participants who do and do not exceed the cutoff point on a borderline personality scale. The BPO Scale is a suitable instrument for evaluating BPO in partner-violent men.
Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity

Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.
Refinement and Rescoring of Virtual Screening Results

High-throughput docking is an established computational screening approach in drug design. This methodology enables a rapid identification of biologically active hit compounds, providing an efficient and cost-effective complement or alternative to experimental high-throughput screenings. However, limitations inherent to the methodology make docking results inevitably approximate. Two major Achille's heels include the use of approximated scoring functions and the limited sampling of the ligand-target complexes. Therefore, docking results require careful evaluation and further post-docking analyses. In this article, we will overview our approach to post-docking analysis in virtual screenings. BEAR (Binding Estimation After Refinement) was developed as a post-docking processing tool that refines docking poses by means of molecular dynamics (MD) and then rescores the ligands based on more accurate scoring functions (MM-PB(GB)SA). The tool has been validated and used prospectively in drug discovery applications. Future directions regarding refinement and rescoring in virtual screening are discussed.
Psychological Distress and Problematic Mobile Phone Use Among Adolescents: The Mediating Role of Maladaptive Cognitions and the Moderating Role of Effortful Control

Previous studies have documented that psychological distress is related to problematic mobile phone use (PMPU), and sporadic research has investigated the potential mechanisms underlying the association. Based on the cognitive-behavioral model of pathological Internet use (PIU), the self-control theory, and the problem-behavior theory, this study aimed to examine the mediating role of maladaptive cognitions toward mobile phones and the moderating role of effortful control between psychological distress and PMPU. Data were collected from 1,799 secondary school students (45.1% male; Mage = 14.07, SD = 1.69) using four self-reported questionnaires. The results revealed that maladaptive cognitions toward mobile phones partially mediated the relationship between psychological distress and PMPU. In addition, effortful control as a protective factor attenuated the indirect effect from psychological distress to PMPU. These findings advanced the understanding of the etiology of PMPU and the need to develop effective strategies for prevention, suggesting that schools and families should pay additional attention to students with psychological distress. Targeted interventions for integrating online and offline worlds and effortful control training programs may help to prevent adolescents from engaging in PMPU.
Patterns of Geographical and Potential Adaptive Divergence in the Genome of the Common Carp (Cyprinus carpio)

The common carp, Cyprinus carpio, is a cyprinid fish species cultured in Europe and Asia. It accounts for >70% of freshwater aquaculture production worldwide. We conducted a population genomics analysis on C. carpio using high-throughput SNP genotyping of 2,198 individuals from 14 populations worldwide to determine the genetic architecture of common carp populations and the genetic bases for environmental adaptation. Structure analyses including phylogeny and principal component analysis were also conducted, showing distinct geographical patterns in European and Asian populations. The linkage disequilibrium block average lengths of the 14 populations ranged from 3.94 kb to 36.67 kb. Genes within selective sweep regions were identified by genome scanning among the different populations, including gdf6a, bmpr1b, and opsin5. Gene Ontology and KEGG enrichment analyses revealed potential trait-related loci and genes associated with body shape, scaling patterns, and skin color. This population genomics analysis may provide valuable clues for future genome-assisted breeding of C. carpio.
Personality Traits and Postnatal Depression: The Mediated Role of Postnatal Anxiety and Moderated Role of Type of Birth

This study investigated how personality traits are related to postnatal depression 2 weeks after giving birth and whether these relations are mediated by postnatal anxiety, measured after 3–4 days after giving birth and moderated by the type of birth. New mothers (N = 672, Mage = 29.33) completed scales assessing their personality traits, postnatal anxiety, and postnatal depression 3 or 4 days after giving birth (T1). They also reported postnatal depression 2 weeks after giving birth (T2). Path analysis indicated that postnatal anxiety explained the link between personality traits (i.e., neuroticism) and postnatal depression 2 weeks after childbirth. The type of birth moderated the relation among, personality traits, postnatal anxiety and depression. Neuroticism and consciousness, in the natural birth’s group, and neuroticism and agreeableness, in the cesarean birth’s group, were associated with postnatal depression. Further, anxiety explained the relation between neuroticism and postnatal depression in both natural and cesarean birth groups. In addition, postnatal anxiety mediated the relation between extraversion and postnatal depression in the cesarean birth group. Our findings highlight that postnatal anxiety is a potential mechanism explaining how personality traits (i.e., neuroticism, extraversion) are related to postnatal depression, and that these relations may depend on the type of childbirth.
Hybrid techniques for detecting changes in less detectable dynamic multiobjective optimization problems

Detecting the environmental changes in dynamic optimization problems is an essential phase for a dynamic evolutionary algorithm. By determining the time points of change in the problem, the evolutionary algorithm is capable of adapting and responding to these changes efficiently. It might be more crucial for multiobjective optimization problems, since lack of efficient change detectors may not prevent evolutionary process utilizing invalid nondominated solutions due to the occurrence of changes. The change detection becomes a challenge when dealing with problems that expose less detectable environmental changes, which is a common characteristic of some real-world problems. In this paper, we investigate the performance of sensor-based and population-based change detection schemes on less detectable environmental changes. Additionally, a hybrid scheme is proposed that incorporates sensor-based schemes with the population-based ones. We validate the performance of all three schemes on four different less detectable environment problems by considering different characteristics of dynamism, where hybrid techniques significantly outperform the other alternatives.
Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper

Benchmarking aims to investigate the performance of one or several algorithms for a set of reference problems by empirical means. An important motivation for benchmarking is the generation of insight that can be leveraged for designing more efficient solvers, for selecting a best algorithm, and/or for choosing a suitable instantiation of a parametrized algorithm. An important component of benchmarking is its design of experiment (DoE), which comprises the selection of the problems, the algorithms, the computational budget, etc., but also the performance indicators by which the data is evaluated. The DoE very strongly depends on the question that the user aims to answer. Flexible benchmarking environments that can easily adopt to users' needs are therefore in high demand. With the objective to provide such a flexible benchmarking environment, the recently released IOHprofiler not only allows the user to choose the sets of benchmark problems and reference algorithms, but provides in addition a highly interactive, versatile performance evaluation. However, it still lacks a few important performance indicators that are relevant to practitioners and/or theoreticians. In this discussion paper we focus on one particular aspect, the probability that a considered algorithm reaches a certain target value within a given time budget. We thereby suggest to extend the classically regarded fixed-target and fixed-budget analyses by a fixed-probability measure. Fixed-probability curves are estimated using Pareto layers of (target, budget) pairs that can be realized by the algorithm with the required certainty. We also provide a first implementation towards a fixed-probability module within the IOHprofiler environment.
Motivations for the IT Professional Turnaway Intention: A Delphi Approach

ABSTRACT In this paper, we use the Delphi method to identify the main motivations that have led IT professionals to intend to move to another area. We found that the pursuit of career growth and the quest for acquiring new experiences and abilities have a marked impact on the IT professional turnaway intention. Moreover, female IT professionals and IT professionals oriented by the career advancement paradigm have a higher propensity to abandon the IT area.
A Non-Stationary Geometry-Based Cooperative Scattering Channel Model for MIMO Vehicle-to-Vehicle Communication Systems

Traditional channel models for vehicle-to-vehicle (V2V) communication usually assume fixed velocity in static scattering environment. In the realistic scenarios, however, time-variant velocity for V2V results in non-stationary statistical properties of wireless channels. Dynamic scatterers with random velocities and directions have been always utilized to depict the non-stationary statistical properties of the channel. In this paper, a non-stationary geometry-based cooperative scattering channel model is proposed for multiple-input multiple-output (MIMO) V2V communication systems, where a birth-death process is used to capture the appearance and disappearance dynamic properties of moving scatterers that reflect the time-variant time correlation and Doppler spectrum characteristics. Moreover, our model has more straight and concise to study the impact of the vehicular traffic density on channel characteristics and thus avoid complicated procedure in deriving the analytical expressions of the channel parameters and functions. The numerical results validate our analysis and demonstrate that setting important parameters of our model can appropriately build up more purposeful measurement campaigns in the future.
Applying and Evaluating Visualization Design Guidelines for a MOOC Dashboard to Facilitate Self-Regulated Learning Based on Learning Analytics

With the help of learning analytics, MOOCs have wider potential to succeed in learning through promoting self-regulated learning (SRL). The current study aims to apply and validate visualization design guidelines for a MOOC dashboard to enhance such SRL capabilities based on learning analytics. To achieve the research objective, a MOOC dashboard prototype, LM-Dashboard, was designed and developed, reflecting the visualization design guidelines to promote SRL. Then, both expert and learner participants evaluated LM-Dashboard through iterations to validate the visualization design guidelines and perceived SRL effectiveness. The results of expert and learner evaluations indicated that most of the visualization design guidelines on LM-Dashboard were valid and some perceived SRL aspects such as monitoring a student’s learning progress and assessing their achievements with time management were beneficial. However, some features on LM-Dashboard should be improved to enhance SRL aspects related to achieving their learning goals with persistence. The findings suggest that it is necessary to offer appropriate feedback or tips as well as to visualize learner behaviors and activities in an intuitive and efficient way for the successful cycle of SRL. Consequently, this study contributes to establishing a basis for the visual design of a MOOC dashboard for optimizing each learner’s SRL.
Approaching the quadratic assignment problem with kernels of mallows models under the hamming distance

The Quadratic Assignment Problem (QAP) is a specially challenging permutation-based np-hard combinatorial optimization problem, since instances of size n > 40 are seldom solved using exact methods. In this sense, many approximate methods have been published to tackle this problem, including Estimation of Distribution Algorithms (EDAs). In particular, EDAs have been used to solve permutation problems by introducing distance based exponential models, such as the Mallows Models. In this paper we approximate the QAP with a Hamming distance based kernels of Mallows Models. Based on the benchmark instances, we have observed that our approach is competitive, reaching the best-known solution in 71% of the tested instances, especially on large instances (n > 125), where it is able to outperform state of the art results in 43 out of 288 instances.
Surrgate Text Representation of Visual Features for Fast Image Retrieval

We propose a simple and effective methodology to index and retrieve image features without the need for a time-consuming codebook learning step. We employ a scalar quantization approach combined with Surrogate Text Representation (STR) to perform large-scale image retrieval relying on the latest text search engine technologies. Experiments on large-scale image retrieval benchmarks show that we improve the effectiveness-efficiency trade-off of current STR approaches while performing comparably to state-of-the-art main-memory methods without requiring a codebook learning procedure.