Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of corn wet distillers grains fed to crossbred bulls on feeding behavior, rumen morphology, liver abscesses and blood parameters

Corn ethanol production has been growing in Brazil in the last ten years, generating by-products to feedlot diets. This study evaluates the effects of the inclusion of low-fat corn wet distillers grains (LF-WDG) on feeding behavior, ruminal health, liver abscesses and blood parameters of F1 Angus-Nellore bulls feedlot finished. Our hypothesis is that evaluation of data from feeding behavior, rumen and liver health would help to explain animal performance. In this trail, one-hundred animals were fed for 129 days with diets containing amounts of 0 (control), 15, 30 and 45% of LF-WDG replacing corn grain and soybean meal. Evaluations of fluctuation of dry matter intake (DMI) were carried out. Additionally, feeding behavior data were assessed by monitoring (24-h period) the feeding, rumination, time spent eating (TSE), and time expended on other activities (resting and number of meals per day). Blood variables such as pH, bicarbonate, total CO2 content, and base excess in extracellular fluid (Beecf) were determined. After slaughter, rumen epithelium was classified according to the incidence of lesions (rumenitis) and abnormalities (papillae clumped), and samples were collected for morphology and histology evaluations. Moreover, livers were scored for severity of abscesses as follow: as unabscessed (0), one or two small abscesses (A−), two to four small active abscesses (A) or one or more large, active abscesses (A+). The DMI (kg/day) differed (P = 0.03) among treatments and there is a tendency of 15 and 30 LF-WDG (% DM) had lower %DMI fluctuation compared to 0 or 45%. The TSE increased linearly (P < 0.01) as the amounts of inclusion of LF-WDG increased. Moreover, neutral detergent fiber (NDF) intake, NDF consumption rate and NDF rumination efficiency increased linearly (P < 0.01) in response to LF-WDG feeding. The incidence of rumenitis tended (P = 0.08) to be greater at 45% LF-WDG, while keratin thickness decreased linearly in bulls fed LF-WDG (P < 0.01). The severity of liver abscesses (score A+) increased linearly (P = 0.02). Regarding blood parameters, only Beecf decreased linearly (P < 0.01) in response to LF-WDG feeding. Therefore, the hypothesis of the current study was confirmed. We previous reported that F1 Angus-Nellore bulls fed LF-WDG show greater weight gain (1.94 ± 0.09 kg/day) and final body weight (620 ± 18.8 kg) when compare to control (1.8 ± 0.09 kg/day and 602 ± 18.8 kg, respectively). Here, we conclude that inclusion of 15 to 30% LF-WDG in feedlot diets improved feeding behavior without impairing ruminal health and blood parameters, driving performance and weigh gain of crossbred bulls. However, bulls fed 45% LF-WDG had greater severity of liver abscesses.
Advanced bioengineering of female germ cells to preserve fertility

Abstract Oogenesis and folliculogenesis are considered as complex and species-specific cellular differentiation processes, which depend on the in vivo ovarian follicular environment and endocrine cues. Considerable efforts have been devoted to driving the differentiation of female primordial germ cells toward mature oocytes outside of the body. The recent experimental attempts have laid stress on offering a suitable microenvironment to assist the in vitro folliculogenesis and oogenesis. Despite developing a variety of bioengineering techniques and generating functional mature gametes through in vitro oogenesis in earlier studies, we still lack knowledge of appropriate microenvironment conditions for building biomimetic culture systems for female fertility preservation. Therefore, this review paper can provide a source for a large body of scientists developing cutting-edge in vitro culture systems for female germ cells or setting up the next generation of reproductive medicine as feasible options for female infertility treatment. The focal point of this review outlines advanced bioengineering technologies such as 3D biofabricated hydrogels/scaffolds and microfluidic systems utilized with female germlines for fertility preservation through in vitro folliculogenesis and oogenesis. Graphical Abstract Schematic representation of species-specific differences in folliculogenesis between rodents and humans (A) plus estimates of the number of ovarian follicles in various species (B). The current and specific future applications of advanced technologies in female fertility preservation and in vitro folliculogenesis, utilizing 3D organ culture techniques, hydrogels, scaffolds, microfluidic systems, and bioprinters are illustrated and compared with the conventional culture systems (A and C). Some items created with BioRender.com Summary Sentence Utilizing cutting-edge bioengineered culture microenvironments, it is possible to achieve successful in vitro folliculogenesis and oogenesis for therapeutic purposes.
The proportion of loss to follow-up from antiretroviral therapy (ART) and its association with age among adolescents living with HIV in sub-Saharan Africa: A systematic review and meta-analysis

Background Human immunodeficiency virus (HIV) remains a global health threat, especially in developing countries. The successful scale-up of antiretroviral therapy (ART) programs to address this threat is hindered by a high proportion of patient loss to follow-up (LTFU). LTFU is associated with poor viral suppression and increased mortality. It is particularly acute among adolescents, who face unique adherence challenges. Although LTFU is a critical obstacle on the continuum of care for adolescents, few regional-level studies report the proportion of LTFU among adolescents receiving ART. Therefore, a systematic review and meta-analysis were conducted to estimate the pooled LTFU in ART programs among adolescents living with HIV in sub-Saharan Africa (SSA). Methods We searched five databases (PubMed, Embase (Elsevier), PsycINFO, CINAHL, and Scopus) for articles published between 2005 and 2020 and reference lists of included articles. The PRISMA guidelines for systematic reviews were followed. A standardised checklist to extract data was used. Descriptive summaries were presented using narrative tables and figures. Heterogeneity within the included studies was examined using the Cochrane Q test statistics and I2 test. Random effect models were used to estimate the pooled prevalence of LTFU among ALHIV. We used Stata version 16 statistical software for our analysis. Results Twenty-nine eligible studies (n = 285,564) were included. An estimated 15.07% (95% CI: 11.07, 19.07) of ALHIV were LTFU. Older adolescents (15–19 years old) were 43% (AOR = 0.57, 95% CI: 0.37, 0.87) more likely to be LTFU than younger (10–14 years old) adolescents. We find an insignificant relationship between gender and LTFU (AOR = 0.95, 95% CI: 0.87, 1.03). A subgroup analysis found that regional differences in the proportion of adolescent LTFU were not statistically significant. The trend analysis indicates an increasing proportion of adolescent LTFU over time. Conclusions and recommendations The proportion of LTFU among HIV-positive adolescents in SSA seems higher than those reported in other regions. Older adolescents in the region are at an increased risk for LTFU than younger adolescents. These findings may help policymakers develop appropriate strategies to retain ALHIV in ART services. Such strategies could include community ART distribution points, appointment spacing, adherence clubs, continuous free access to ART, and community-based adherence support.
"Magic" Molecules and a New Look at Chemical Diversity of Hydrocarbons.

We address the question why among the multitude of imaginable CnHm compositions some are easily synthesizable and abundant in nature, while others are not. To shed light on this problem we borrow approaches from nanocluster study, where stability with respect to neighboring compositions is used as a criterion of "magic" (particularly stable) clusters. By merging this criterion with predictions of lowest-energy structures of all CnHm molecules in a wide range of compositions (n ≤ 20, m ≤ 42) we provide guidelines for predicting the presence or absence of certain hydrocarbon molecules in various environments, their relative abundance and reactivity/inertness. The resulting maps of stability show the increased stability of C2nH2 compounds, polyaromatic hydrocarbons, and diamondoids, which is supported by experimental studies of the interstellar medium, flames, and petroleum fractions. This approach can be applied to any other molecular system, rationalizing the diversity of known compounds and predicting new potentially synthesizable molecules.
Host genotype controls ecological change in the leaf fungal microbiome

Leaf fungal microbiomes can be fundamental drivers of host plant success, as they contain pathogens that devastate crop plants and taxa that enhance nutrient uptake, discourage herbivory, and antagonize pathogens. We measured leaf fungal diversity with amplicon sequencing across an entire growing season in a diversity panel of switchgrass (Panicum virgatum). We also sampled a replicated subset of genotypes across 3 additional sites to compare the importance of time, space, ecology, and genetics. We found a strong successional pattern in the microbiome shaped both by host genetics and environmental factors. Further, we used genome-wide association (GWA) mapping and RNA sequencing to show that 3 cysteine-rich receptor-like kinases (crRLKs) were linked to a genetic locus associated with microbiome structure. We confirmed GWAS results in an independent set of genotypes for both the internal transcribed spacer (ITS) and large subunit (LSU) ribosomal DNA markers. Fungal pathogens were central to microbial covariance networks, and genotypes susceptible to pathogens differed in their expression of the 3 crRLKs, suggesting that host immune genes are a principal means of controlling the entire leaf microbiome.
Children's anxiety and parenting self‐efficacy during the COVID‐19‐related home confinement

Abstract Background The COVID‐19 crisis influenced the lives of families and preschoolers, worldwide. School closures and restriction measures introduced distance learning for preschoolers and remote working for parents. Social distancing narrowed opportunities to meet with peers and enjoy leisure activities. Additionally, social and mental services closures limited young children's accessibility to mental, speech and occupational health services. The aim of the current study was to investigate how home confinement during the third wave of the COVID‐19 pandemic affected parenting self‐efficacy and preschoolers' anxiety. Method An online survey based on a convenience sample took place on April 2021 to evaluate how home confinement to halt the third wave of COVID‐19 pandemic influenced children's anxiety and parenting self‐efficacy (PSE). Parents of 146 children (65 girls [44.5%] and 81 boys [55.5%]; aged 2–6 years old) were enrolled and completed a demographics form, the Preschool Anxiety Scale (PAS) and the Tool to Measure Parenting Self‐efficacy (TOPSE). Results Most of the participants reported that the relationship with their child was positively affected from staying at home. TOPSE mean scores reflected average parenting self‐efficacy. PSE was negatively correlated with children's anxiety. COVID‐19‐related variables ‘Parent's vaccine hesitancy’ and ‘Death of a loved one’ had a clear effect on preschoolers' anxiety, whereas the latter also on PSE. Conclusion Findings highlight the necessity of implementing public health strategies to strengthen families and support parents and their children during the ongoing health crisis.
Mycotoxin ingestion during late gestation alters placentome structure, cotyledon transcriptome, and fetal development in pregnant sheep

Ergot alkaloids, a class of mycotoxins, induce vasoconstriction when consumed by animals and humans. Pregnant ewes (n = 16; 81.2 kg ± 7.7) were assigned fed endophyte-infected tall fescue seed (E+; 4.14 μg ergovaline + ergovalinine/g seed) or a control diet (CON; 0 μg ergovaline + ergovalinine) for increasing duration during late gestation (from gd86 to gd110 or gd133) to examine changes in placentome morphology and mRNA transcriptome, and fetal development. Exposure to E+ fescue reduced serum prolactin concentrations at gd110 and gd133 demonstrating treatment efficacy. For control ewes, cotyledon and total placentome weights decreased with advancing gestation due to remodeling of placental tissues; however, cotyledon and placentome weight did not change with advancing gestation in E+ fed ewes. Fetal brain sparing was evident in E+ exposed fetuses at gd110 and gd133 compared to CON, which demonstrates asymmetrical growth and intrauterine growth restriction. Mycotoxin exposure (E+) resulted in differential expression of 22 genes in the cotyledon tissue at gd110 but only one gene at gd133 compared to CON. These results suggest that the response to mycotoxin exposure in the pregnant sheep model has an immediate impact on placental remodeling and fetal development that persists throughout the duration of the exposure period.
Bisection Neural Network Toward Reconfigurable Hardware Implementation

A hardware-friendly bisection neural network (BNN) topology is proposed in this work for approximately implementing massive pieces of complex functions in arbitrary on-chip configurations. Instead of the conventional reconfigurable fully connected neural network (FC-NN) circuit topology, the proposed hardware-friendly topology performs NN behaviors in a bisection structure, in which each neuron includes two constant synapse connections for both inputs and outputs. Compared with the FC-NN one, the reconfiguration of the BNN circuit topology eliminates the remarkable amount of dummy synapse connections in hardware. As the main target application, this work aims at building a general-purpose BNN circuit topology that offers a great amount of NN regressions. To achieve this target, we prove that the NN behaviors of the FC-NN circuit topologies can be migrated to the BNN circuit topologies equivalently. We introduce two approaches including the refining training algorithm and the inverted-pyramidal strategy to further reduce the number of neurons and synapses. Finally, we conduct the inaccuracy tolerance analysis to suggest the guideline for ultra-efficient hardware implementations. Compared with the state-of-the-art FC-NN circuit topology-based TrueNorth baseline, the proposed design can achieve 17.8– $22.2\times $ hardware reduction and less than 1% inaccuracy.
An inception network for positron emission tomography based dose estimation in carbon ion therapy

Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of 12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image. Approach. A set of dose deposition and positron annihilation profiles for monoenergetic 12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated 12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a 12C ion beam at QST’s Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental 12C SOBP profiles. Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental 12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm. Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.
Use of Area Under the Curve (AUC) from Propensity Model to Estimate Accuracy of the Estimated Effect of Exposure

Objective: To investigate the relationship between the area under the Receiver Operating Characteristic curve (AUC) of the propensity model for exposure and the accuracy of the estimated effect of the exposure on the outcome of interest.Methods: A Monte Carlo simulation study was performed where multiple realizations of three binary variables: outcome, exposure of interest and a covariate were repeatedly generated from the distribution determined by the parameters of the "propensity" and "main" models and the prevalence of the exposure. "Propensity" model was a logistic regression with the exposure of interest as a dependent variable and a single covariate as an "independent" variable. "Main" model was a logistic regression with outcome as a dependent variable, exposure of interest and covariate as "independent" variables. A total of 500 simulations were performed for each considered combination of the model parameters and the prevalence of the exposure. AUC was estimated from the probabilities predicted by the propensity score model. The accuracy of the estimated effect of exposure was primarily assessed with the square root of Mean Square Error (RMSE); the fifth and ninety-fifth percentile of the empirical distribution of the estimator were used to illustrate a range of not unlikely deviations from the true value.Results: The square root of Mean Square Error of the estimated effect of exposure increases as AUC increases from 0.6 to 0.9. Varying values for parameters of the propensity score model or the main effect model does not change the direction of this trend. As the proportion of exposed subjects changes away from 0.5 the RMSE increases, but the effect of AUC on RMSE remains approximately the same. Similarly, as sample size changes from 50 to 100 or 200, the RMSE of effect estimate decreases on average, but the effect of AUC on RMSE remains approximately the same. Also, the rate of change in RMSE increases with increasing AUC; the rate is the lowest when AUC changes from 0.6 to 0.7 and is highest when AUC changes from 0.8 to 0.9. Conclusions: The AUC of the propensity score model for exposure provides a single, relatively easy to compute, and suitable for various kind of data statistic, which can be used as an important indicator of the accuracy of the estimated effect of exposure on the outcome of interest. The public health importance is that it can be considered as an alternative to the previously suggested (Rubin, 2001) simultaneous consideration of the conditions of closeness of means and variances of the propensity scores in the different exposure groups. Our simulations indicate that the estimated effect of exposure is highly unreliable if AUC of the propensity model is larger than 0.8; at the same time AUCs of less than 0.7 are not associated with any substantial increase of inaccuracy of the estimated effect of exposure.
A Popular Approach, but Do They Work? A Systematic Review of Social Marketing Campaigns to Prevent Sexual Violence on College Campuses

College campuses continue to face high rates of sexual violence and social marketing campaigns have emerged as a common prevention strategy. However, there exists no summative research examining the effectiveness of this approach. A systematic search yielded 15 evaluations of eight unique prevention campaigns, which contributed to 38 individual outcome measures across four outcome categories (i.e., knowledge, attitudes, intentions/efficacy, and behavior). Summative results are mixed, but show promising campaign effects for increasing knowledge, modification of some attitudes toward sexual violence, intentions to participate, and actual participation in prevention activities. More evaluative research is needed for a comprehensive understanding of campaign effectiveness.
Leisure Activities and the Risk of Dementia

Background and Objectives Leisure activities are major components of modifiable and healthy lifestyles and are proposed to help prevent the development of dementia. This study aimed to assess the effects of different types of leisure activities, including cognitive, physical, and social activities, on the incidence of all-cause dementia (ACD), Alzheimer disease (AD), and vascular dementia (VD). Methods We performed a systematic review and meta-analysis of the Cochrane, PubMed, Embase, and Web of Science databases to identify longitudinal studies that examined associations between leisure activities and dementia. Relative risks (RRs) and 95% CIs were pooled using random-effects meta-analysis. Subgroup analyses were used to estimate potential effect modifiers. The study was registered with PROSPERO (CRD42019116857). Results A total of 38 longitudinal studies, with 2,154,818 participants at baseline, 74,700 ACD cases, 2,848 AD cases, and 1,423 VD cases during follow-up, were included in the meta-analysis. The subgroup analyses showed that physical (RR 0.83, 95% CI 0.78–0.88), cognitive (RR 0.77; 95% CI 0.68–0.87), and social (RR 0.93; 95% CI 0.87–0.99) activities were associated with a decreased incidence of ACD. In addition, physical (RR 0.87; 95% CI 0.78–0.96) and cognitive (RR 0.66; 95% CI 0.52–0.85) activities were related to a reduced risk of AD. Physical activity (RR 0.67; 95% CI 0.53–0.85) was associated with a lower incidence of VD. Discussion Our findings suggest that leisure activities are inversely associated with a risk of ACD, AD, and VD.
TopEx: topic exploration of COVID-19 corpora - Results from the BioCreative VII Challenge Track 4

Abstract TopEx is a natural language processing application developed to facilitate the exploration of topics and key words in a set of texts through a user interface that requires no programming or natural language processing knowledge, thus enhancing the ability of nontechnical researchers to explore and analyze textual data. The underlying algorithm groups semantically similar sentences together followed by a topic analysis on each group to identify the key topics discussed in a collection of texts. Implementation is achieved via a Python library back end and a web application front end built with React and D3.js for visualizations. TopEx has been successfully used to identify themes, topics and key words in a variety of corpora, including Coronavirus disease 2019 (COVID-19) discharge summaries and tweets. Feedback from the BioCreative VII Challenge Track 4 concludes that TopEx is a useful tool for text exploration for a variety of users and tasks. Databse URL http://topex.cctr. vcu.edu