Miracle-dz/UniFAR-FTUs huggingface dataset:
Purification and Evaluation of N-benzyl Cinnamamide from Red Seaweed Gracilaria fisheri as an Inhibitor of Vibrio harveyi AI-2 Quorum Sensing

Previously, we reported that the ethanol extract from red seaweed Gracilaria fisheri effectively decreased biofilm formation of Vibrio harveyi. In this study, the anti-biofilm active compounds in the ethanol extract were isolated and their structures identified. The anti-biofilm fractionation assay for minimum inhibitory concentration (MIC) produced two fractions which possessed maximal inhibitory activities toward the biofilm formation of V. harveyi strains 1114 and BAA 1116. Following chromatographic separation of the bioactive fractions, two pure compounds were isolated, and their structures were elucidated using FTIR, NMR, and HR-TOF-MS. The compounds were N-benzyl cinnamamide and α-resorcylic acid. The in vitro activity assay demonstrated that both compounds inhibited the biofilm formation of V. harveyi and possessed the anti-quorum sensing activity by interfering with the bioluminescence of the bacteria. However, the N-benzyl cinnamamide was more potent than α-resorcylic acid with a 10-fold lesser MIC. The present study reveals the beneficial property of the N-benzyl cinnamamide from the ethanol extract as a lead anti-microbial drug against V. harveyi.
Personalized community-based prehabilitation for a high-risk surgical patient opting for pylorus-preserving pancreaticoduodenectomy: a case report

ABSTRACT Introduction: Prehabilitation aims for an optimal physical functioning level before, during, and after hospitalization for major surgery. The purpose of this case report was to illustrate the care pathway of a high-risk patient who opted for pylorus-preserving pancreaticoduodenectomy, including preparation for this procedure by participating in a community-based exercise prehabilitation program. The report describes patient examination, evaluation in decision-making for surgery, the prehabilitation program, and outcomes within the context of the Hypothesis-Oriented Algorithm for Clinicians II. Case Description: The patient was a 75-year-old woman with a history of several comorbidities and a polypoid mass in the descending segment of the duodenum. Based on the preoperative assessment, the level of physical functioning was expected to be insufficient to cope adequately with the stress of hospitalization and surgery. Intervention: A 4-week prehabilitation program, including aerobic, resistance, and functional task training in a community-based physical therapy practice. Outcomes: Prehabilitation had a beneficial impact on improving functional mobility preoperatively (timed up-and-go test score improved from 19.4 to 10.0 s, five times sit-to-stand test score improved from 30.1 to 10.1 s, and two-minute walk test distance improved from 55.0 to 107.0 m). Surgery and postoperative recovery proceeded without complications. She achieved independent physical functioning on postoperative day 6 and was discharged home on postoperative day 12. Conclusion: Preoperative risk-assessment can support clinical decision-making in a high-risk patient opting for major abdominal surgery. Furthermore, a remarkable improvement in physical functioning can be achieved by community-based prehabilitation in a high-risk surgical patient.
Learning person-centredness interprofessionally: an uneasy student journey

ABSTRACT Patient- or person-centered care is a discourse embraced by most clinicians involved in interprofessional care but generally overlooks thepersons of the practitioners and students involved. This paper explores students’ developing perceptions of person-centered care during participation in an interprofessional education program where interprofessional pairs of students partner with patients living with a long-term condition or life-changing event. Weekly focus groups with students and educators over the 7 weeks of the program revealed a rich evolving understanding of person-centredness amongst participant students as they built relationships with both their patient and student partner. Students and educators identified shifts in students’ interprofessional person-centered perspectives and practices, growing awareness of patient personhood and of stories as key to creating and maintaining space for listening and dialogue, and conscious attention to thoughtful, non-judgmental listening and responses. Although initially uncomfortable, uncertain and “stuck” students came to value working in a holistic relational partnership to explore what mattered to the patient, looking beyond the diagnosis to the multi-faceted nature of living with a life-changing condition or event. Importantly, students’ growing self-awareness and participation as persons enhanced person-centredness, leading to questioning of previous healthcare practice experiences where mutual person-centredness was overlooked. Uncertainty about student capability led some educators to reassert control of the process, which students perceived as counterproductive usurping of their personhood and professional autonomy. The research findings suggest that an interprofessional program focused on person-centered relationship building develops student awareness and understanding of mutual personhood but requires high levels of reciprocal trust.
Searching for the Big Pictures

My goal in searching for the big pictures is to discover novel ways of organizing information in psychology that will have both theoretical and practical significance. The first section lists my reasons for writing each of five articles. The second section discusses an additional five articles that integrate advancements in artificial intelligence and cognitive psychology. The following two sections elaborate on my collaboration with ontologists to use formal ontologies to organize psychological knowledge, including the National Institute of Mental Health Research Domain Criteria, for formulating a biological basis for mental illness. I next discuss strategies for writing integrative articles. The following section describes the helpfulness of the integrations for making psychology relevant to a general audience. I conclude with recommendations for creating breadth in doctoral training.
Aberrant Salience? Brain Hyperactivation in Response to Pain Onset and Offset in Fibromyalgia

While much brain research on fibromyalgia (FM) focuses on the study of hyperresponsiveness to painful stimuli, some studies suggest that the increased pain‐related brain activity often reported in FM studies may be partially explained by stronger responses to salient aspects of the stimulation rather than, or in addition to, the stimulation's painfulness. Therefore, this study was undertaken to test our hypothesis that FM patients would demonstrate elevated brain responses to both pain onset and offset—2 salient sensory events of opposing valences.
Hybrid Continuous Density Hmm-Based Ensemble Neural Networks for Sensor Fault Detection and Classification in Wireless Sensor Network

Sensor devices in wireless sensor networks are vulnerable to faults during their operation in unmonitored and hazardous environments. Though various methods have been proposed by researchers to detect sensor faults, only very few research studies have reported on capturing the dynamics of the inherent states in sensor data during fault occurrence. The continuous density hidden Markov model (CDHMM) is proposed in this research to determine the dynamics of the state transitions due to fault occurrence, while neural networks are utilized to classify the faults based on the state transition probability density generated by the CDHMM. Therefore, this paper focuses on the fault detection and classification using the hybridization of CDHMM and various neural networks (NNs), namely the learning vector quantization, probabilistic neural network, adaptive probabilistic neural network, and radial basis function. The hybrid models of each NN are used for the classification of sensor faults, namely bias, drift, random, and spike. The proposed methods are evaluated using four performance metrics which includes detection accuracy, false positive rate, F1-score, and the Matthews correlation coefficient. The simulation results show that the learning vector quantization NN classifier outperforms the detection accuracy rate when compared to the other classifiers. In addition, an ensemble NN framework based on the hybrid CDHMM classifier is built with majority voting scheme for decision making and classification. The results of the hybrid CDHMM ensemble classifiers clearly indicates the efficacy of the proposed scheme in capturing the dynamics of change of statesm which is the vital aspect in determining rapidly-evolving instant faults that occur in wireless sensor networks.
SP1/TGF-β1/SMAD2 pathway is involved in angiogenesis during osteogenesis

The relationship between osteoblasts and angiogenesis is vital for bone regeneration, especially mandibular and maxillary bones. Transforming growth factor β1 (TGF-β1) and vascular endothelial growth factor (VEGF) are closely related to angiogenesis; however, the regulatory mechanism between them remains unknown. The present study aimed to reveal this mechanism to provide novel insight for development of potential therapeutic opportunities. Western blotting and reverse transcription-quantitative PCR was used to assess the protein and mRNA expression levels in MC3T3-E1 preosteoblast cells and HUVECs, ELISAs were used to detect the expression levels of secreted VEGF, MTT assays were used to assess the viability of the cells, migratory ability was assessed using Transwell assays, angiogenesis assays were used to analyze the formation of blood vessels, and TGF-β1 regulation was confirmed using a dual-luciferase reporter assay. The overexpression of specificity protein 1 (SP1) or TGF-β1 increased VEGF expression levels and secretion, and promoted angiogenesis of co-cultured HUVECs. SP1 also promoted SMAD2 phosphorylation. These effects of SP1 were all reversed by the TGF-β1 inhibitor. The VEGF inhibitor bevacizumab also reduced the SP1/TGF-β1/SMAD2 pathway-induced angiogenesis of preosteoblasts. In conclusion, it was demonstrated that SP1 promoted TGF-β1 expression, activated the SMAD2 pathway and induced VEGF secretion, which may enhance angiogenic processes in preosteoblasts.
Single-Nucleus Sequencing of an Entire Mammalian Heart: Cell Type Composition and Velocity

Analyses on the cellular level are indispensable to expand our understanding of complex tissues like the mammalian heart. Single-nucleus sequencing (snRNA-seq) allows for the exploration of cellular composition and cell features without major hurdles of single-cell sequencing. We used snRNA-seq to investigate for the first time an entire adult mammalian heart. Single-nucleus quantification and clustering led to an accurate representation of cell types, revealing 24 distinct clusters with endothelial cells (28.8%), fibroblasts (25.3%), and cardiomyocytes (22.8%) constituting the major cell populations. An additional RNA velocity analysis allowed us to study transcription kinetics and was utilized to visualize the transitions between mature and nascent cellular states of the cell types. We identified subgroups of cardiomyocytes with distinct marker profiles. For example, the expression of Hand2os1 distinguished immature cardiomyocytes from differentiated cardiomyocyte populations. Moreover, we found a cell population that comprises endothelial markers as well as markers clearly related to cardiomyocyte function. Our velocity data support the idea that this population is in a trans-differentiation process from an endothelial cell-like phenotype towards a cardiomyocyte-like phenotype. In summary, we present the first report of sequencing an entire adult mammalian heart, providing realistic cell-type distributions combined with RNA velocity kinetics hinting at interrelations.
The Toxicological Intersection between Allergen and Toxin: A Structural Comparison of the Cat Dander Allergenic Protein Fel d1 and the Slow Loris Brachial Gland Secretion Protein

Slow lorises are enigmatic animal that represent the only venomous primate lineage. Their defensive secretions have received little attention. In this study we determined the full length sequence of the protein secreted by their unique brachial glands. The full length sequences displayed homology to the main allergenic protein present in cat dander. We thus compared the molecular features of the slow loris brachial gland protein and the cat dander allergen protein, showing remarkable similarities between them. Thus we postulate that allergenic proteins play a role in the slow loris defensive arsenal. These results shed light on these neglected, novel animals.
Microglial Activation in the Retina of a Triple-Transgenic Alzheimer’s Disease Mouse Model (3xTg-AD)

Alzheimer’s disease (AD) is the most common type of dementia in the world. The main biomarkers associated with AD are protein amyloid-β (Aβ) plaques and protein tau neurofibrillary tangles, which are responsible for brain neuroinflammation mediated by microglial cells. Increasing evidence has shown that the retina can also be affected in AD, presenting some molecular and cellular changes in the brain, such as microglia activation. However, there are only a few studies assessing such changes in the retinal microglia in animal models of AD. These studies use retinal sections, which have some limitations. In this study, we performed, for the first time in a triple-transgenic AD mouse model (3xTg-AD), a quantitative morphometric analysis of microglia activation (using the anti-Iba-1 antibody) in retinal whole-mounts, allowing visualization of the entire microglial cell, as well as its localization along the extension of the retina in different layers. Compared to age-matched animals, the retina of 3xTg-AD mice presents a higher number of microglial cells and a thicker microglial cell body area. Moreover, the microglia migrate, reorient, and retract their processes, changing their localization from a parallel to a perpendicular position relative to the retinal surface. These findings demonstrate clear microglia remodeling in the retina of 3xTg-AD mice.
Gut microbiota‐derived metabolite trimethylamine N‐oxide (TMAO) potentially increases the risk of obesity in adults: An exploratory systematic review and dose‐response meta‐ analysis

It has been suggested that trimethylamine N‐oxide (TMAO) is associated with increased risk of diabetes and cardiovascular disease (CVD) morbidity and mortality. However, it is not known whether increased TMAO concentrations is associated with obesity. In the current study, we summarized the evidence related to the association of circulating TMAO with the risk of obesity measurements, including body mass index (BMI), waist circumference (WC), and waist‐to‐hip ratio (WHR) in a two‐class and dose‐response meta‐analysis of observational studies. A systematic search carried out in PubMed, SCOPUS, Cochrane, and ProQuest through September 30, 2019 resulted in 12 eligible studies which were included in the current meta‐synthesis. In these studies, BMI was reported but there were no reports of WC or WHR. Meta‐analysis of two‐class variables and dose‐response meta‐analysis of continuous variables were performed. Subgroup analysis and meta‐regression were also performed to identify the source of heterogeneity. There was a dose‐response association between circulating TMAO concentration and increased BMI in studies involving healthy individuals (P nonlinearity = .007), while no evidence of departure from linearity was observed according to study design or among patients with CVD. Results showed the highest category of TMAO was associated with 0.56 kg/m2 increase in BMI (weighted mean difference [WMD], 0.563; CI, 0.026‐1.100; P = .04). The results of the current meta‐analysis revealed a positive association between circulating TMAO and obesity as presented by increased BMI. Moreover, a dose‐dependent association between circulating TMAO and obesity was also identified in apparently healthy individuals. This is the first meta‐analysis to reveal positive dose‐dependent associations between circulating TMAO concentration and obesity.
Point Cloud Denoising via Feature Graph Laplacian Regularization

Point cloud is a collection of 3D coordinates that are discrete geometric samples of an object’s 2D surfaces. Imperfection in the acquisition process means that point clouds are often corrupted with noise. Building on recent advances in graph signal processing, we design local algorithms for 3D point cloud denoising. Specifically, we design a signal-dependent feature graph Laplacian regularizer (SDFGLR) that assumes surface normals computed from point coordinates are piecewise smooth with respect to a signal-dependent graph Laplacian matrix. Using SDFGLR as a signal prior, we formulate an optimization problem with a general <inline-formula> <tex-math notation="LaTeX">$\ell _{p}$ </tex-math></inline-formula>-norm fidelity term that can explicitly remove only two types of additive noise: small but non-sparse noise like Gaussian (using <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> fidelity term) and large but sparser noise like Laplacian (using <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> fidelity term). To establish a linear relationship between normals and 3D point coordinates, we first perform bipartite graph approximation to divide the point cloud into two disjoint node sets (red and blue). We then optimize the red and blue nodes’ coordinates alternately. For <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm fidelity term, we iteratively solve an unconstrained quadratic programming (QP) problem, efficiently computed using conjugate gradient with a bounded condition number to ensure numerical stability. For <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm fidelity term, we iteratively minimize an <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> cost function using accelerated proximal gradient (APG), where a good step size is chosen via Lipschitz continuity analysis. Finally, we propose simple mean and median filters for flat patches of a given point cloud to estimate the noise variance given the noise type, which in turn is used to compute a weight parameter trading off the fidelity term and signal prior in the problem formulation. Extensive experiments show state-of-the-art denoising performance among local methods using our proposed algorithms.
Response Dissociation in Hierarchical Cortical Circuits: a Unique Feature of Autism Spectrum Disorder

A prominent hypothesis regarding the pathophysiology of autism is that an increase in the balance between neural excitation and inhibition results in an increase in neural responses. However, previous reports of population-level response magnitude in individuals with autism have been inconsistent. Critically, network interactions have not been considered in previous neuroimaging studies of excitation and inhibition imbalance in autism. A prominent hypothesis regarding the pathophysiology of autism is that an increase in the balance between neural excitation and inhibition results in an increase in neural responses. However, previous reports of population-level response magnitude in individuals with autism have been inconsistent. Critically, network interactions have not been considered in previous neuroimaging studies of excitation and inhibition imbalance in autism. In particular, a defining characteristic of cortical organization is its hierarchical and interactive structure; sensory and cognitive systems are comprised of networks where later stages inherit and build upon the processing of earlier input stages, and also influence and shape earlier stages by top-down modulation. Here we used the well established connections of the human visual system to examine response magnitudes in a higher-order motion processing region [middle temporal area (MT+)] and its primary input region (V1). Simple visual stimuli were presented to adult individuals with autism spectrum disorders (ASD; n = 24, mean age 23 years, 8 females) and neurotypical controls (n = 24, mean age 22, 8 females) during fMRI scanning. We discovered a strong dissociation of fMRI response magnitude between region MT+ and V1 in individuals with ASD: individuals with high MT+ responses had attenuated V1 responses. The magnitude of MT+ amplification and of V1 attenuation was associated with autism severity, appeared to result from amplified suppressive feedback from MT+ to V1, and was not present in neurotypical controls. Our results reveal the potential role of altered hierarchical network interactions in the pathophysiology of ASD. SIGNIFICANCE STATEMENT An imbalance between neural excitation and inhibition, resulting in increased neural responses, has been suggested as a pathophysiological pathway to autism, but direct evidence from humans is lacking. In the current study we consider the role of interactions between stages of sensory processing when testing increased neural responses in individuals with autism. We used the well known hierarchical structure of the visual motion pathway to demonstrate dissociation in the fMRI response magnitude between adjacent stages of processing in autism: responses are attenuated in a primary visual area but amplified in a subsequent higher-order area. This response dissociation appears to rely on enhanced suppressive feedback between regions and reveals a previously unknown cortical network alteration in autism.
Characterization of the immune microenvironment in brain metastases from different solid tumors

Brain metastases are one of the most common intracranial neoplasms. Increasing evidence have indicated that systemic immunotherapy may provide long‐term benefits for brain metastases. Herein, we presented the results of an immune oncology panel RNA sequencing platform for patients with brain metastases from different primary sites.
A Longitudinal Assessment of Two Suicide Prevention Training Programs for the Construction Industry

As part of a suite of early intervention training and support services, Mates in Construction (MATES) provide two general awareness programs to promote mental health and suicide awareness and encourage help-offering and help-seeking in construction workers. General awareness training (GAT) is a one-hour session delivered to all construction workers on large to medium worksites, while MATES awareness training (MAT) maintains similar content but is of shorter duration and delivered informally to small workplaces. This study aimed to compare the effectiveness of the two programs using a before, after and follow-up design. Construction workers undertaking MAT or GAT training completed a short survey before and after their training and again at follow-up. Linear mixed-effect modelling indicated that GAT and MAT training provided similar results in improving suicide awareness and help-seeking intentions. Some variables showed a significant increase from pre-intervention to the three-month follow-up, indicating the long-term impact of some aspects of the training. The findings demonstrating the effectiveness of MAT training have important implications for MATES, as the training can be delivered to much smaller workplaces, making the program more widely available to the construction industry.