Miracle-dz/UniFAR-FTUs huggingface dataset:
5-(Hydroxyphenyl)-γ-Valerolactone-Sulfate, a Key Microbial Metabolite of Flavan-3-ols, Is Able to Reach the Brain: Evidence from Different in Silico, In Vitro and In Vivo Experimental Models

Phenolic compounds have been recognized as promising compounds for the prevention of chronic diseases, including neurodegenerative ones. However, phenolics like flavan-3-ols (F3O) are poorly absorbed along the gastrointestinal tract and structurally rearranged by gut microbiota, yielding smaller and more polar metabolites like phenyl-γ-valerolactones, phenylvaleric acids and their conjugates. The present work investigated the ability of F3O-derived metabolites to cross the blood-brain barrier (BBB), by linking five experimental models with increasing realism. First, an in silico study examined the physical-chemical characteristics of F3O metabolites to predict those most likely to cross the BBB. Some of these metabolites were then tested at physiological concentrations to cross the luminal and abluminal membranes of brain microvascular endothelial cells, cultured in vitro. Finally, three different in vivo studies in rats injected with pure 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone, and rats and pigs fed grapes or a F3O-rich cocoa extract, respectively, confirmed the presence of 5-(hydroxyphenyl)-γ-valerolactone-sulfate (3′,4′ isomer) in the brain. This work highlighted, with different experimental models, the BBB permeability of one of the main F3O-derived metabolites. It may support the neuroprotective effects of phenolic-rich foods in the frame of the “gut-brain axis”.
Systematic collection of patient-reported outcomes in atrial fibrillation: feasibility and initial results of the Utah mEVAL AF programme.

AIMS Incorporating patient-reported outcomes (PROs) into routine care of atrial fibrillation (AF) enables direct integration of symptoms, function, and health-related quality of life (HRQoL) into practice. We report our initial experience with a system-wide PRO initiative among AF patients. METHODS AND RESULTS All patients with AF in our practice undergo PRO assessment with the Toronto AF Severity Scale (AFSS), and generic PROs, prior to electrophysiology clinic visits. We describe the implementation, feasibility, and results of clinic-based, electronic AF PRO collection, and compare AF-specific and generic HRQoL assessments. From October 2016 to February 2019, 1586 unique AF patients initiated 2379 PRO assessments, 2145 of which had all PRO measures completed (90%). The median completion time for all PRO measures per visit was 7.3 min (1st, 3rd quartiles: 6, 10). Overall, 38% of patients were female (n = 589), mean age was 68 (SD 12) years, and mean CHA2DS2-VASc score was 3.8 (SD 2.0). The mean AFSS symptom score was 8.6 (SD 6.6, 1st, 3rd quartiles: 3, 13), and the full range of values was observed (0, 35). Generic PROs of physical function, general health, and depression were impacted at the most severe quartiles of AF symptom score (P < 0.0001 for each vs. AFSS quartile). CONCLUSION Routine clinic-based, PRO collection for AF is feasible in clinical practice and patient time investment was acceptable. Disease-specific AF PROs add value to generic HRQoL instruments. Further research into the relationship between PROs, heart rhythm, and AF burden, as well as PRO-guided management, is necessary to optimize PRO utilization.
Removal of ECG Artifacts From EEG Using an Effective Recursive Least Square Notch Filter

Electroencephalogram (EEG) is a common tool for medical diagnosis, cognitive research, and managing neurological disorders. However, EEG is usually contaminated with various artifacts, making it difficult to interpret EEG data. In this study, a recursive least square (RLS) notch filter was developed to effectively suppress electrocardiogram (ECG) artifacts from EEG recordings. ECG artifacts were estimated and modeled using the instantaneous frequency of the cardiac cycle. Then it was adaptively estimated using a RLS filter and directly subtracted from contaminated EEG data. Based on the validation measures of improvement of normalized power spectrum (INPS), mean square error (MSE) and information quantity (IQ), the performance of ECG artifacts suppression was compared among the proposed RLS approach, independent component analysis (ICA) and blind deconvolution method under information maximization (Infomax) on simulated and animal experimental data. Simulation data demonstrated that INPS of RLS method (19.75(18.37,20.95) dB) was significantly higher than that of ICA (4.35(3.35,5.41) dB) and Infomax (5.76(4.60,6.88) dB). Meanwhile, MSE of RLS method (0.20(0.08,0.53) <inline-formula> <tex-math notation="LaTeX">$\mu \text{V}^{2}$ </tex-math></inline-formula>) was considerably lower than that of ICA (5.59(2.35,19.79) <inline-formula> <tex-math notation="LaTeX">$\mu \text{V}^{2}$ </tex-math></inline-formula>) and Infomax (3.21(1.01,10.69) <inline-formula> <tex-math notation="LaTeX">$\mu \text{V}^{2}$ </tex-math></inline-formula>). Animal experimental data showed that INPS was 1.76(0.42,9.40) dB for RLS method, which was dramatically higher than that of ICA (0.02(0.00,0.14) dB) and Infomax (0.57(0.08,2.45) dB). The calculated IQ for RLS method (0.331(0.021,0.584)) was relatively lower than that of raw EEG (0.350(0.070,0.586)), ICA (0.350(0.069,0.581)) and Infomax (0.341(0.050,0.585)). The RLS notch filter can effectively eliminate ECG artifacts from EEG and preserve the majority of EEG information with little loss.
Variational Bayesian Point Set Registration

Point set registration presents unique significance in Lidar-based intelligent vehicle localization and mapping. It involves registering point sets of the same scene observed from different positions by determining their relative spatial transformation. However, due to the noise and outliers in the point sets and initial misalignment, existing methods suffer from the issues of low accuracy or large computational cost. In this paper, we propose a novel Bayesian state space model to describe the sequential point registration problem. Specifically, we specify the transformations to be the latent states and further assume that they vary smoothly across time. The point clouds are then represented as Gaussian mixture models that change accordingly with the transformation. We then develop a stochastic variational Bayesian inference algorithm to learning the distributions of the transformation, which automatically strike a balance between mapping every two consecutive point clouds and the temporal smoothness of the transformation. Experimental results based simulated data show that the proposed variational Bayesian point set registration (VB-PSR) algorithm achieves higher accuracy with comparable or less time and resources, in comparison with the state- of-the-art methods.
Outcome of acute psychiatric in-patient care where there are no crisis or home treatment teams

AIMS AND METHOD To examine the pathways and outcomes of in-patient care in our locality before crisis teams were introduced details of all emergency referrals to psychiatry were recorded and all admissions to hospital were assessed within 24 h of admission and discharge. RESULTS Over a 6-month period, 88% ( n =1852) of calls to the duty psychiatrist occurred between 09.00 and 01.00 h. Referrals from accident and emergency and general practice represented the majority of calls (80%); 40% of patients were admitted. Highest admission rates were for patients who were psychotic, suicidal or depressed. Admission led to improvement in all symptoms. CLINICAL IMPLICATIONS In-patient care is a valuable resource for stabilising patients who are acutely ill. Routine monitoring of unscheduled activity can inform service delivery.
Subtypes of COPD Have Unique Distributions and Differential Risk of Mortality.

Background Previous attempts to explore the heterogeneity of chronic obstructive pulmonary disease (COPD) clustered individual patients using clinical, demographic, and disease features. We developed continuous multidimensional disease axes based on radiographic and spirometric variables that split into an airway-predominant axis and an emphysema-predominant axis. Methods The COPD Genetic Epidemiology study (COPDGene®) is a cohort of current and former smokers, > 45 years, with at least 10 pack years of smoking history. Spirometry measures, blood pressure and body mass were directly measured. Mortality was assessed through continuing longitudinal follow-up and cause of death was adjudicated. Among 8157 COPDGene® participants with complete spirometry and computed tomography (CT) measures, the top 2 deciles of the airway-predominant and emphysema-predominant axes previously identified were used to categorize individuals into 3 groups having the highest risk for mortality using Cox proportional hazard ratios. These groups were also assessed for causal mortality. Biomarkers of COPD (fibrinogen, soluble receptor for advanced glycation end products [sRAGE], C-reactive protein [CRP], clara cell secretory protein [CC16], surfactant-D [SP-D]) were compared by group. Findings High-risk subtype classification was defined for 2638 COPDGene® participants who were in the highest 2 deciles of either the airway-predominant and/or emphysema-predominant axis (32% of the cohort). These high-risk participants fell into 3 groups: airway-predominant disease only (APD-only), emphysema-predominant disease only (EPD-only) and combined APD-EPD. There was 26% mortality for the APD-only group, 21% mortality for the EPD-only group, and 54% mortality for the combined APD-EPD group. The APD-only group (n=1007) was younger, had a lower forced expiratory volume in 1 second (FEV1) percent (%) predicted and a strong association with the preserved ratio-impaired spirometry (PRISm) quadrant. The EPD-only group (n=1006) showed a relatively higher FEV1 % predicted and included largely GOLD stage 0, 1 and 2 partipants. Individuals in each of the 3 high-risk groups were at greater risk for respiratory mortality, while those in the APD-only group were additionally at greater risk for cardiovascular mortality. Biomarker analysis demonstrated a significant association of the APD-only group with CRP, and sRAGE demonstrated greatest significance with both the EPD-only and the combined APD-EPD groups. Interpretation Among current and former smokers, individuals in the highest 2 deciles for mortality risk on the airway-predominant axis and the emphysema-predominant axis have unique associations to spirometric patterns, different imaging characteristics, biomarkers and causal mortality.
Blocks: Redesigning Coarse Grained Reconfigurable Architectures for Energy Efficiency

Demand for coarse grain reconfigurable architectures has significantly increased as architectures need to be both energy efficient and flexible. However, most CGRAs are optimized for performance instead of energy efficiency. In this work Blocks is presented. Blocks uses two separate circuit-switched networks, one for control and one for the data-path. The unique structure of these networks enables run-time construction of energy-efficient application-specific VLIW-SIMD processors. Energy efficiency is demonstrated by comparing Blocks to a traditional CGRA on 40nm layout. Results show an energy overhead reduction between 46% and 76% and total energy reduction between 9% and 29%, depending on the benchmark. Demonstrating that the cost of flexibility can be lower than might be expected.
Autism and depression are connected: A report of two complimentary network studies

Autism and depression often co-occur. Through network analysis, we seek to gain a better understanding of this co-occurrence by investigating whether (1) autism and depression share overlapping groups of symptoms and/or (2) are connected through a bridge of mastery or worry symptoms. This is addressed in two complimentary studies: (1) Study 1 focusing on depressed (N = 258) and non-depressed adults (N = 117), aged 60–90 years; (2) Study 2 focusing on autistic (N = 173) and non-autistic adults (N = 70), aged 31–89 years. Self-report questionnaire data were collected on autistic traits (AQ-28), depression symptoms (Study 1: Inventory of Depressive Symptomatology Self Report; Study 2: Symptom Checklist 90–Revised depression subscale), worry (Worry Scale-R) and mastery (the Pearlin Mastery Scale). For both studies, data were analysed by creating glasso networks and subsequent centrality analyses to identify the most influential variables in the respective networks. Both depressed and autistic adults are highly similar in the perceived amount of worries and lack of control. While caution is needed when interpreting the pattern of findings given the bootstrapping results, findings from both studies indicate that overlapping symptoms do not fully explain the co-occurrence of autism and depression and the perception of having control over your life, that is, mastery seems a relevant factor in connecting autism and depression.
Experiences of Living With Primary Progressive Aphasia: A Scoping Review of Qualitative Studies

Introduction: Understanding the experiences of people who live with primary progressive aphasia (PPA) can inform the development of appropriate speech-language pathology services for this population. This review aimed to summarize the qualitative research on the experience of living with PPA from the perspective of the individuals with the disorder and their families. Methods: A scoping review was conducted. Results: Eight studies met the inclusion criteria. Themes in the 3 investigations that focused on the individual’s perspective included adapting to overcome language difficulties and dealing with increased dependency. Themes identified in the 5 studies that highlighted the family’s perspective included observing and adapting to language, behavioral, and social communication changes; lack of awareness of PPA; control; and the impact of the historical relationship. Discussion: Experiences from the 2 perspectives differed. Further research is needed, particularly in relation to identifying the general experience of PPA from the perspective of individuals with the disorder.
Brain N-Acetyl Aspartate and associations with cognitive impairment in alcohol dependent patients

ABSTRACT Introduction: Chronic alcohol consumption has been observed to be associated with a range of cognitive impairments that impact on treatment management. In this spectroscopy study, we examined the association of N-Acetyl Aspartate (NAA), a marker of neuronal integrity, and cognitive impairment in alcohol dependent patients. Method: Using in vivo proton magnetic resonance spectroscopy (1H-MRS), we examined brain metabolite levels in 31 alcohol dependent individuals. 1H-MRS from the parietal lobe were analyzed to yield absolute concentrations of NAA. Alcohol history, neurocognitive function including Clock Drawing Test (CDT), Mini Mental State Exam (MMSE), Trial Making Test (TMT) and Balloon Analogue Risk Task (BART) were also assessed. Covariates included concurrent medication, age and recent alcohol consumption. Results: There were statistically significant bivariate associations between NAA and the variables age, CDT and BART (r = −.45, P = 01; r = −.53, P = .01; r = .49, P = .02) respectively) but there were no statistically significant associations with other measures of cognitive function. Controlling for age, concurrent medication and recent alcohol consumption, multiple linear regression revealed a negative association between parietal NAA (Model: F = 6.96, R2 = .66, P = .001) and CDT scores (B = −.35, P = .03), a positive association with BART scores (B = .47, P = .02). Conclusion: These results demonstrate that in alcohol dependent patients lower NAA/Cr is associated with reduced cognitive functioning and increased risk-taking.
Machine Learning Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homo- and Co-polymers.

Polyhydroxyalkanoate-based polymers-being eco-friendly, bio-synthesizable, economically-viable and possessing a broad range of tunable properties-are currently being actively pursued as promising alternatives for petroleum-based plastics. The vast chemical complexity accessible within this class of polymers gives rise to challenges in the rational discovery of novel polymer chemistries for specific applications. The burgeoning field of polymer informatics addresses this challenge via providing tools and strategies for accelerated property prediction and materials design via surrogate machine learning models built on reliable past data. In this contribution, we use glass transition temperature Tg as an example target property to demonstrate promise of the data-enabled route to accelerated learning of accurate structure-property mappings in PHA-based polymers. Our analysis uses a data set of experimentally measured Tg values, polymer molecular weights and polydispersity index for PHA-based homo- and co-polymers that was carefully assembled from the literature. A fingerprinting scheme that captures key properties based on topology, shape, and charge/polarity of specific chemical units or motifs forming the polymer backbone was devised to numerically represent the polymers. A validated statistical learning model is then developed to allow for a mapping of the polymer fingerprints onto the property space in a physically-meaningful and reliable manner. Once developed, the model can not only rapidly predict the property of new PHA polymers, but also provides uncertainties underlying the predictions. The model is further combined with an evolutionary algorithm-based search strategy to efficiently identify multi-component polymer compositions with a pre-specified Tg. While the present contribution is focused specifically on Tg, the surrogate model development approach put forward here is general and can, in principle, be extended to a range of other properties.
A Vaccination for Education - The ICDS and the Education of Older Girls in Rural India

Girls lag behind boys in education in India. They also appear to provide significant amount of childcare at home. In this paper I investigate if provision of childcare services by India’s largest child development program - Integrated Child Development Scheme (ICDS) - helps to reduce gender education gap byreleasing girls from home responsibilities. There are several mechanisms by which the ICDS provides childcare directly and could reduce its cost. Using logit, covariate matching and conditional logit (villageand mother fixed-effects), I find that in rural India the girls 6-14 years, whose younger sibling below 5 years is receiving any of the ICDS services intensely, have 44% higher odds of schooling, than thosewhose sibling is either receiving no ICDS service or none intensely. The effect on boys 6-14 years is positive, but not robust. Further evidence suggests that younger age girls seem to be benefiting relativelymore, and the effect is driven mainly by positive health benefits of vaccinations of younger children, and perhaps of supplementary feeding. The bigger and more robust effect on girls seems to be consistent with evidence from time-use of children 6-14. In comparison to boys, relatively many more girls spendtime on childcare, especially those with very young siblings of ages 0-23 months, and significantly lesser number combine childcare and education.
Sexual risk among men who have sex with men with online sex partners in New York City: Insight using the Centers for Disease Control and Prevention's Web-based HIV Behavioral Surveillance and National HIV Behavioral Surveillance

Sexual risk among men who have sex with men with online sex partners in New York City: Insight using the Centers for Disease Control and Prevention‟s Web-based HIV Behavioral Surveillance and National HIV Behavioral Surveillance Michael Navejas Increasingly the Internet has been used by men who have sex with men (MSM)to facilitate social and sexual relationships. Finding from studies investigating the relationship between sexual risk and MSM who meet sex partners on the Internet in either venue-based (offline) and Internet-based (online) settings have been mixed. In an effort to contribute to the knowledge base on this topic, this study analyzed data from two samples of MSM recruited in New York City: Web-based HIV Behavioral Surveillance (WHBS) and National HIV Behavioral Surveillance (NHBS). The relationship between sexual risk behaviors including unprotected anal intercourse (UAI), drug use, number of sexual partners, use of performance enhancing drugs (also known as erectile dysfunction drugs or PDE5 inhibitors), and group sex participation and mode of sex partner recruitment are examined. Univariate, bivariate, and multivariate analysis were used to examine the research questions and hypothesis.
Does passive smoking at home lead to depression among older people in China?

BACKGROUND This paper was carried out based on two motivations: (a) prior studies achieved mixed results regarding the effect of passive smoking on depression; and (b) studies on the impacts of passive smoking usually neglect effects on older people. In our paper, we studied the causal effect of passive smoking at home on depression among older people aged 60 years and older in China with a longitudinal study. METHODS In assessing the causal relationship, we developed a fixed-effects instrumental variable method using an exogenous variable-health consciousness and the smoking status of parents-as instruments of smoking status. We used data from the China Health and Retirement Longitudinal Study (CHARLS), which provides a national, high-quality, and longitudinal household survey of people aged 45 years and older. RESULTS Our empirical results reveal that passive smoking at home increased the depressive symptoms of older people, regardless of their smoking status. Moreover, the impact of passive smoking on depression is larger for nonsmokers than smokers. Additionally, the health consciousness and smoking status of parents are effective instrumental variables. CONCLUSIONS This paper calls for governments and medical institutions to pay more attention to the health of older people and their need for healthy living environments.
Revealing the Grain Boundary Formation Mechanism and Kinetics during Polycrystalline MoS2 Growth.

Controllable synthesis of MoS2 with desired grain morphology via chemical vapor deposition (CVD) or physical vapor deposition (PVD) remains a challenge. Hence, it is important to understand polycrystalline growth of MoS2 and further provide guidelines for its CVD/PVD growth. Here, we formulate a kinetic Monte Carlo (kMC) model aiming at predicting the grain boundary (GB) formation in the CVD/PVD growth of polycrystalline MoS2. In the kMC model, the grain growth is via kink nucleation and propagation, whose energetic parameters and initial nucleus details are either from first-principles calculations or from experiments. Using the kMC model, we perform extensive simulations to predict the GB formation by using two, three, four and five initial nuclei, and compare the simulation results with previous experimental results. The obtained GB morphologies are in an excellent agreement with those experimental results. These agreements suggest that the proposed kMC model can correctly capture the mechanism and kinetics of GB formation. In particular, we reveal that the formation of smooth/rough GB is dictated by the two growth vectors for the kink propagation at the two associated grain edges, which is validated by our high-resolution scanning transmission electron microscopy images for PVD growth of MoS2 grains. Besides, we have made predictions beyond reproducing experimental observations, including the growth with artificially designed nuclei, the morphology transformation by tuning the Mo and S sources, and the formation of high-quality single-crystalline monolayer MoS2 by using single-crystalline substrate with vicinal steps. Our kMC model may serve as a powerful predictive tool for the CVD/PVD growth of monolayer MoS2 with desired GB configurations.