Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters

Introduction Replicability has become an increasing focus within the scientific communities with the ongoing “replication crisis. ” One area that appears to struggle with unreliable results is resting-state functional magnetic resonance imaging (rs-fMRI). Therefore, the current study aimed at improving the knowledge of endogenous factors that contribute to inter-individual variability. Methods Arterial blood pressure (BP), body mass, hematocrit, and glycated hemoglobin were investigated as potential sources of between-subject variability in rs-fMRI, in healthy individuals. Whether changes in resting-state networks (rs-networks) could be attributed to variability in the blood-oxygen-level-dependent (BOLD)-signal, changes in neuronal activity, or both was of special interest. Within-subject parameters were estimated by utilizing dynamic-causal modeling, as it allows to make inferences on the estimated hemodynamic (BOLD-signal dynamics) and neuronal parameters (effective connectivity) separately. Results The results of the analyses imply that BP and body mass can cause between-subject and between-group variability in the BOLD-signal and that all the included factors can affect the underlying connectivity. Discussion Given the results of the current and previous studies, rs-fMRI results appear to be susceptible to a range of factors, which is likely to contribute to the low degree of replicability of these studies. Interestingly, the highest degree of variability seems to appear within the much-studied default mode network and its connections to other networks. Impact statement We believe that thanks to the evidence that we have collected by analyzing the well-controlled data of the Human Connectome Project with dynamic-causal modeling (DCM) and by focusing not only on the effective connectivity, which is the typical way of using DCM, but also by analyzing the underlying hemodynamic parameters, we were able to explore the underlying vascular dependencies in a much broader perspective. Our results challenge the premise for studying changes in the default mode network as a clinical marker of disease, and we add to the growing list of factors that contribute to resting-state network variability.
The effects of curcumin on anthropometric and cardiometabolic parameters of patients with metabolic related diseases: a systematic review and dose-effect meta-analysis of randomized controlled trials

Abstract Objective:To perform a meta-analysis of published randomized controlled trials (RCTs) to assess the effects of curcumin supplementation with different formulations on anthropometric and cardiometabolic indices in patients with metabolism-related diseases (MRDs). Methods: Six databases, including PubMed, Embase, Web of Science, China national knowledge internet (CNKI), Wanfang and China Biology Medicine (CBM), were systematically searched to find relevant articles from 2011 to July 2021. The effect sizes were expressed as weighted mean difference (WMD) with 95% confidence intervals (CI). Between-study heterogeneity was assessed using I2. Subgroup analysis was conducted to find possible sources of heterogeneity. Curcumin formulations in this study were divided as low bioavailability, high bioavailability and nanocurcumin. Results: Of the retrieved 1585 articles, 31 were included in the final analysis. Combined effect sizes suggested a significant effect of curcumin supplementation on reduced body weight (BW) (WMD: −0.94 kg, 95% CI: −1.40, −0.47) and body mass index (BMI) (WMD: −0.40 kg/m2, 95% CI: −0.60, −0.19), respectively. The results also showed significant improvements of fasting plasma glucose (FPG) (WMD: −0.50 mg/dL, 95% CI: −0.72, −0.28), glycosylated hemoglobin (Hb1Ac) (WMD: −0.42%, 95% CI: −0.57, −0.26), insulin (INS) (WMD: −1.70 μIU/mL, 95%CI: −2.03, −1.38), homeostasis model assessment-insulin resistance (HOMA-IR) (WMD: −0.71, 95%CI: −1.11, −0.31), high-density lipoprotein cholesterol (HDL-C) (WMD: 1.73 mg/dL, 95%CI: 0.78, 2.68) and high sensitivity C-reactive protein (Hs-CRP) (WMD: −1.11, 95%CI: −2.16, −0.05). Nanocurcumin showed a greater reduction in FPG (WMD: −1.78 mg/dL, 95% CI: −2.49, −1.07), INS (WMD: −1.66 μIU/mL, 95% CI: −3.21, −0.11), TC (WMD: −12.64 mg/dL (95% CI: −23.72, −1.57) and LDL-C (WMD: −8.95 mg/dL, 95% CI: −16.51, −1.38). The dose-effect analysis showed that there were trends of first rising and then falling between the supplemented curcumin dose and BW, BMI, LDL-C, Hb1Ac, which were clearly distinguished at 80 mg/d due to the strong effect of nanocurcumin on outcomes. A slow upward trend between the dose of curcumin supplementation and HDL-C. No relationships between dose and outcomes were found for FPG and insulin, except for nanocurcumin at 80 mg/d. Conclusions: Our study showed some significant beneficial effects of curcumin supplementation on improving BW, BMI, and the levels of FPG, Hb1Ac, HOMA-IR, HDL-C and Hs-CRP in patients with MRDs. Nanocurcumin may have a greater effect on the reduction of FPG, INS, TC and LDL-C than other curcumin formulations. Considering the potential bias and limitations of studies included, further quality studies with larger sample sizes are needed to confirm these results.
Study of the dynamic behavior of the cruzain enzyme in free and complexed forms with competitive and noncovalent benzimidazole inhibitors

Abstract There are only two drugs for the treatment of Chagas disease, namely, nifurtimox and benznidazole, that can cause several adverse effects. Despite the effectiveness of these drugs in the disease's acute phase, they are not recognized as curative in the chronic phase, establishing the need for more effective treatment in all stages of the disease. Cruzain is an enzyme that plays a vital role in the life cycle of the etiologic agent, the protozoan Trypanosoma cruzi, being relevant as a therapeutic target in the planning of new drugs. Using molecular docking and dynamics simulations, we have investigated the structural and dynamic factors that can be involved in the enzyme inhibition process at the atomic-molecular level by benzimidazole compounds that are potent cruzain inhibitors with in vitro trypanocidal activity. The study suggests that these inhibitors bind cruzain through steric and hydrogen bonding interactions without altering its secondary structure content and protein compaction. Besides, we observed that these inhibitors decrease the correlation of movements between Cα-atoms of cruzain, increasing the number of atomic communities, mainly in the α-helix that presents the catalytic Cys25 residue. As expected, we also observed a correlation between the inhibitory activity of each inhibitor and their respective binding-free energies, reinforcing that the affinity of the complexes seems to be a relevant factor for enzymatic inhibition. Hence, the results presented in this work contribute to a better understanding of the cruzain enzyme inhibition mechanism through competitive and non-covalent inhibitors. Communicated by Ramaswamy H. Sarma
Decoupling representation learning for imbalanced electroencephalography classification in rapid serial visual presentation task

Objective. The class imbalance problem considerably restricts the performance of electroencephalography (EEG) classification in the rapid serial visual presentation (RSVP) task. Existing solutions typically employ re-balancing strategies (e.g. re-weighting and re-sampling) to alleviate the impact of class imbalance, which enhances the classifier learning of deep networks but unexpectedly damages the representative ability of the learned deep features as original distributions become distorted. Approach. In this study, a novel decoupling representation learning (DRL) model, has been proposed that separates the representation learning and classification processes to capture the discriminative feature of imbalanced RSVP EEG data while classifying it accurately. The representation learning process is responsible for learning universal patterns for the classification of all samples, while the classifier determines a better bounding for the target and non-target classes. Specifically, the representation learning process adopts a dual-branch architecture, which minimizes the contrastive loss to regularize the representation space. In addition, to learn more discriminative information from RSVP EEG data, a novel multi-granular information based extractor is designed to extract spatial-temporal information. Considering the class re-balancing strategies can significantly promote classifier learning, the classifier was trained with re-balanced EEG data while freezing the parameters of the representation learning process. Main results. To evaluate the proposed method, experiments were conducted on two public datasets and one self-conducted dataset. The results demonstrate that the proposed DRL can achieve state-of-the-art performance for EEG classification in the RSVP task. Significance. This is the first study to focus on the class imbalance problem and propose a generic solution in the RSVP task. Furthermore, multi-granular data was explored to extract more complementary spatial-temporal information. The code is open-source and available at https://github.com/Tammie-Li/DRL.
The use of Latent Profile Analyses to examine social dominance orientation as a predictor of peer-to-peer aggression among adolescents

Peer-to-peer aggression and bullying is a social phenomenon and is related to social structures in the school. In-group membership as well as construction of the other and differentiation from other potential groups is an important predictor of one’s social identity. Social Dominance Orientation is an important addition to social identity theory as it examines both issues of social dominance and social egalitarianism and is related to out-group denigration. In this study, we examined whether social dominance theory (both the dominance and egalitarian forms) will add to the prediction of physical and relational aggression among adolescents. Using a bias-corrected 3-step approach, we used Latent Profile Analyses to examine the responses of 1617 Israeli adolescents on measures of social dominance and egalitarian orientation, salience of their social groups and moral disengagement. Based on the analysis, we identified four classes of respondents, which can be broken down into two distinct categories: high social dominance and moral disengagement and high social egalitarianism. We compared male and female adolescent respondents and group salience. We then compared the four latent profiles on the two distal variables of physical and relational peer-to-peer aggression. Findings have theoretical and applied relevance to further investigating issues of group dynamics and construction of the other as potential predictive factors in understanding peer-to-peer aggression and bullying.
Predicting Actions of Users Using Heterogeneous Online Signals

Advertising platforms have a growing need for improving prediction quality, as missing out on ad opportunities can have a negative effect on their performance. To that end, prediction tasks such as conversion prediction need to be continuously advanced through the inclusion of data from new sources or through algorithmic development that tackles existing challenges. The introduction of different data sources naturally brings unwanted noise, whereas underexplored areas still exist in modeling approaches, such as temporal information of events in sequences. In this study, we propose extensions for modeling online user activity trails that address two very important aspects of activities-time and noise, through dedicated layers that can be used in existing deep sequence-learning approaches. Our proposed method exhibited area under the receiver operating characteristic curve improvement of up to 3% and 1.75% compared with production and best baseline approaches, respectively, across two major advertiser data sets and several predictive tasks.
Joint Effects of Fragmentation and Mercury Contamination on Marsh Periwinkle (Littoraria irrorata) Movement

There are different ways contaminants can interact and enhance the effects of habitat fragmentation, such as modifying the movement of organisms. The present study tested the hypothesis that mercury exacerbates the effects of fragmentation by affecting the movement of the marsh periwinkle Littoraria irrorata and reducing the probability of snails crossing fragmented microlandscape experimental systems. How these changes could affect the search efficiency of organisms in the long term was assessed using hidden Markov models and random walks simulations. Bayesian nonlinear models were used to analyze the effects of fragmentation and contamination on the mean speed and mean directional change of organisms. Snail movement for control and two mercury‐exposure treatments were recorded in microlandscapes with six different levels of habitat cover and three landscape replicates. The results indicated that exposed organisms had lower probabilities of crossing the landscape, reduced speed, and shifts in step length distributions. Both mercury exposure and habitat fragmentation affected the movement of the marsh periwinkle. Mercury exacerbated the effects of habitat fragmentation by affecting the cognition (e.g., route planning, orientation, and spatial learning) and movement of L. irrorata. Hence, the interaction of these stressors could further reduce the functional connectivity of landscapes and reduce the search efficiency of organisms. Environ Toxicol Chem 2022;41:1742–1753. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Prostate Cancer Genomics Research Disparities in Africa: Advancing Knowledge in Resource Constrained Settings

Prostate cancer disproportionately affects men of African descent and it is estimated that Africa will bear the highest disease burden in the next decade. Underlying genomic factors may contribute to prostate cancer disparities; however, it is unclear whether Africa has prioritised genomics research toward addressing these disparities. A Pubmed review was performed of publications spanning a 15-year period, with specific focus on prostate cancer genomics research that included samples from Africa and investigators in Africa. Data are presented on research publications from Africa relative to similar publications from different geographical regions, and more specifically, the extent of disparities and the contributions to prostate cancer knowledge as a result of genomics research that included African samples and African institutions. Limited publication output may reflect the infrastructure and funding challenges in Africa. Widespread cooperation should be fostered by sharing capacity and leveraging existing expertise to address the growing cancer burden facing the continent.
Cortical complexity and connectivity during isoflurane-induced general anesthesia: a rat study

Objective. The investigation of neurophysiologic mechanisms of anesthetic drug-induced loss of consciousness (LOC) by using the entropy, complexity, and information integration theories at the mesoscopic level has been a hot topic in recent years. However, systematic research is still lacking. Approach. We analyzed electrocorticography (ECoG) data recorded from nine rats during isoflurane-induced unconsciousness. To characterize the complexity and connectivity changes, we investigated ECoG power, symbolic dynamic-based entropy (i.e. permutation entropy (PE)), complexity (i.e. permutation Lempel-Ziv complexity (PLZC)), information integration (i.e. permutation cross mutual information (PCMI)), and PCMI-based cortical brain networks in the frontal, parietal, and occipital cortical regions. Main results. Firstly, LOC was accompanied by a raised power in the ECoG beta (12–30 Hz) but a decreased power in the high gamma (55–95 Hz) frequency band in all three brain regions. Secondly, PE and PLZC showed similar change trends in the lower frequency band (0.1–45 Hz), declining after LOC (p < 0.05) and increasing after recovery of consciousness (p < 0.001). Thirdly, intra-frontal and inter-frontal-parietal PCMI declined after LOC, in both lower (0.1–45 Hz) and higher frequency bands (55–95 Hz) (p < 0.001). Finally, the local network parameters of the nodal clustering coefficient and nodal efficiency in the frontal region decreased after LOC, in both the lower and higher frequency bands (p < 0.05). Moreover, global network parameters of the normalized average clustering coefficient and small world index increased slightly after LOC in the lower frequency band. However, this increase was not statistically significant. Significance. The PE, PLZC, PCMI and PCMI-based brain networks are effective metrics for qualifying the effects of isoflurane.
Assumptions of Full Mission Ship Bridge Simulation Including EGNOS

This paper presents the assumptions of the Full Mission Bridge Simulation (FMBS) studies which aim to define the role of European Geostationary Navigation Overlay System (EGNOS) from a marine user perspective. The work focused on the possible benefits of Satellite Based Augmentation Systems (SBAS) integrity data presentation within the ship’s bridge environment. At the present stage of research, the MVPA (Marine Vessel Protection Area) model is under development for ships navigating in limited water areas and utilizing precise navigation by fusion of EGNOS integrity data with course/heading error estimates. The model takes into consideration several aspects, influencing protection area dimensions. These include signal coverage aspects, ship’s size, ship’s heading accuracy, position of the Global Navigation Satellite Systems (GNSS) antenna, and GNSS/EGNOS integrity data. The output from this model can be displayed graphically on the desired route within the Electronic Chart Display and Information System (ECDIS) environment as ship’s uncertainty area (MVPA in ECDIS). This ECDIS layer constitutes an EGNOS integrity display within bridge environment showing graphical representation of the ship and integrity information (protection levels in conjunction with alert limits). The plan of experiments to be conducted in the controlled environment of navigational FMBS is discussed with regard to possible benefits of proposed graphical representation of EGNOS integrity data.
An organ‐specific transcriptomic atlas of the medicinal plant Bletilla striata: Protein‐coding genes, microRNAs, and regulatory networks

As one of the important species belonging to the Bletilla genus of Orchidaceae, Bletilla striata (Thunb.) Rchb. f. , possesses both ornamental and medicinal values. Its dried tubers are used as a traditional Chinese medicine, and several secondary metabolites have been indicated to be the active ingredients. However, the molecular mechanisms related to the regulation of secondary metabolism have not been characterized in B. striata. In this study, integrated analysis of RNA sequencing (RNA‐seq), small RNA sequencing (sRNA‐seq), and degradome sequencing (degradome‐seq) data from three organs (leaf, root, and tuber) of B. striata provided us with a comprehensive view of the microRNA (miRNA)‐mediated regulatory network. Firstly, based on the RNA‐seq data, the organ‐specific expression patterns of the protein‐coding genes, especially for those related to secondary metabolism, were investigated. Secondly, 342 conserved miRNA candidates were identified from B. striata. These miRNAs were assigned to 88 families, some of which were selected for expression pattern analysis. Additionally, 31 hairpin‐structured precursors encoding 23 novel miRNAs were uncovered from the transcriptome assembly. Thirdly, based on the degradome signatures, 1,142 validated miRNA–target pairs (involving 167 conserved miRNAs and six novel miRNAs and 51 target genes) were included in the regulatory network. Organ‐specific expression level comparison between the miRNAs and their targets revealed some interesting miRNA–target pairs. Fourthly, some valuable subnetworks were extracted for further functional studies. Additionally, some regulatory pathways were indicated to be monocot specific. Summarily, our results lay a solid basis for in‐depth studies on the regulatory mechanisms underlying the production of the medicinal ingredients in B. striata.
CD55 is upregulated by cAMP/PKA/AKT and modulates human decidualization via Src and ERK pathway and decidualization‐related genes

Decidualization is an essential process for embryo implantation and maintenance of pregnancy, and abnormal decidualization contributed to several pregnancy disorders like a miscarriage. The objective of this study was to explore the regulation and function of CD55 in human decidualization. By immunohistochemical staining, it was found that CD55 expression was higher in first‐trimester decidua than in the endometrium. In both primary endometrial stromal cells and immortalized cell line T‐hESCs, CD55 was upregulated by induction of in vitro decidualization with medroxyprogesterone acetate (MPA) and 8‐Br‐cAMP. During decidualization in vitro, CD55 was stimulated by 8‐Br‐cAMP in a time‐ and concentration‐dependent manner, which was reversed by a PKA inhibitor H89 and partially by an AKT activator SC79. Knocking down CD55 expression diminished the expression of decidualization markers prolactin (PRL) and insulin‐like growth factor‐binding protein 1 (IGFBP1), accompanied by inhibition of Src, aberrant activation of ERK and decreased expression of several decidualization‐related genes, including FOXO1, EGFR, and STAT3. Furthermore, the decidua of unexplained miscarriage women and the endometrium of unexplained infertile women both exhibited decreased CD55 expression. Collectively, these findings revealed that 8‐Br‐cAMP promotes CD55 expression via PKA activation and AKT dephosphorylation, and decreased CD55 impairs decidualization by inactivation of Src, aberrant activation of ERK pathway, and compromised expression of decidualization‐related genes, indicating that CD55 deficiency may contribute to the pathogenesis of spontaneous miscarriage and infertility.
The Impact of Limb Velocity Variability on Mallet Accuracy in Marimba Performance

Abstract The present study examined spatial accuracy of mallet endpoints in a marimba performance context. Trained percussionists performed two- (i.e., Experiment 1) and four-mallet (i.e., Experiment 2) excerpts in three tempo conditions including slow, intermediate, and fast. Motion capture was utilized to gather data of upper-limb and mallet movements, as well as to compute velocities of the upper-limb joints. Mallet spatial accuracy was assessed by comparing mallet endpoints to a visual target positioned on the marimba. It was hypothesized that mallet spatial accuracy would be reduced as tempo condition increased, with effects on joint kinematics potentially revealing sensorimotor mechanisms underlying optimal sound production in marimba. Across both experiments, mallet accuracy was reduced as tempo condition increased. Interestingly, velocity variability in the elbows, wrists, and hands increased as mallet accuracy decreased. Such a pattern of effects suggested that sound production in marimba is suboptimal at fast relative to slow tempi. In addition, the velocity variability effects highlight the impact of motor planning mechanisms on sound production. Overall, the results shed new light on sensorimotor control in percussion which can be leveraged to enhance the training of percussionists.