Miracle-dz/UniFAR-FTUs huggingface dataset:
Studies on Egg Yolk Cholesterol 1. Genetic Variation and Some Phenotypic Correlations in a Random Bred Population

Abstract MIYAMORI (1934) has reported the cholesterol content of egg yolk to be relatively constant among the eggs of different species of birds. However, the reports of Gaujoux and Krijanowsky (1932) and Achard et al. (1934) indicate that the duck’s egg is markedly richer in yolk cholesterol than the hen’s egg. There is little comparative information on the variation of yolk cholesterol among hens’ eggs. Edwards et al. (1960) have reported significant yolk cholesterol differences among eight strains of hens. In this study the yolk cholesterol of a random-bred strain of hens is reported together with a number of phenotypic correlations between yolk cholesterol and other physiological traits. EXPERIMENTAL S. C. White Leghorns, obtained as hatching eggs from the randombred flock maintained at Cornell University, were housed in a single floor pen. In November, 1957, and March, 1958, two consecutively-laid eggs were gathered from all birds in production. A total of …
Not so fast! Limitations of processing speed and working memory indices as embedded performance validity tests in a mixed neuropsychiatric sample

ABSTRACT Introduction Validity indicators embedded within standard neuropsychological tests have received increasing attention as more efficient measures for sampling performance validity throughout an evaluation. This cross-sectional study examined multiple performance validity tests (PVTs) embedded in the Wechsler Adult Intelligence Scale-IV (WAIS-IV) Working Memory (WMI) and Processing Speed (PSI) Indices for detecting invalid test performance. Method This cross-sectional study examined data from a mixed clinical neuropsychiatric sample of 110 patients referred for outpatient evaluation. The sample was composed of 85 patients with valid neuropsychological performance and 25 with invalid performance based on multiple independent criterion PVTs. Among the patients with valid performance, 54% were cognitively impaired, whereas 46% were cognitively unimpaired. Results Among the overall sample, performance on WMI, PSI, and 3/4 constituent subtests (i.e., Digit Span, Symbol Search, Coding) was significantly worse among the invalid group compared to the valid group (ηp 2 =.06–.16) with areas under the curve (AUCs) of.67–. 76 and 24–32% sensitivity (≥88% specificity) for identifying invalid performance at cut-scores that maximized accuracy. When the sample was subdivided by cognitive impairment status, AUCs of.68–. 87 and 36–56% sensitivity (≥87% specificity) for detecting invalidity at cut-scores that maximized accuracy were found among those without cognitive impairment. In contrast, for patients with cognitive impairment, Digit Span, Arithmetic, WMI, and Coding were nonsignificant, and AUCs of.66–. 67. Further, notably reduced sensitivities of 16–28% (≥91% specificity) were found for the remaining significant indices. Conclusion Overall, results indicated that embedded WAIS-IV WMI and PSI are useful embedded PVTs in conditions in which cognitive impairment is not expected; however, these embedded PVTs demonstrated questionable utility among patients with cognitive impairment due to poor sensitivity, if adequate specificity is maintained, suggesting limited efficacy among patients with cognitive impairment due to risk of false-positive classification.
Methanolic Extracts from Cultivated Mushrooms Affect the Production of Fumonisins B and Fusaric Acid by Fusarium verticillioides

The maize pathogen Fusarium verticillioides and their mycotoxins cause damage to plants, animals, and human health. This work aimed to evaluate the effect of crude extracts (CEs) from Agaricus subrufescens, Lentinula edodes, and Pleurotus ostreatus fruiting bodies on in vitro production of biomass and mycotoxins by two strains of F. verticillioides. Stipes and pilei were separated before extraction for A. subrufescens and L. edodes. Comparative metabolomics and dereplication of phenolic compounds were used to analyze all CEs. Mushroom CEs did not significantly inhibit the production of mycelial biomass at concentrations of 2 mg mL−1. CEs from A. subrufescens (stipes and pilei) and L. edodes pilei inhibited the production of fumonisins B1 + B2 + B3 by 54% to 80%, whereas CE from P. ostreatus had no effect. In contrast, CE from L. edodes stipes dramatically increased the concentration of fumonisins in culture media. Fusaric acid concentration was decreased in cultures by all CEs except L. edodes stipes. Differences in phenolic composition of the extracts may explain the different effects of the CE treatments on the production of mycotoxins. The opposing activities of stipes and pilei from L. edodes offer an opportunity to search for active compounds to control the mycotoxin production by F. verticillioides.
Nitrate Promotes Germination Under Inhibition by NaCl or High Concentration of Glucose

Seed germination, one of the most important stages in a plant’s life cycle, can be affected by abiotic stresses, such as salinity. The plant hormone abscisic acid (ABA) and high concentrations of glucose are also known to inhibit germination. In contrast, nitrate is known to stimulate germination in many plants. However, this stimulatory effect has not yet been investigated in the presence of inhibitory effects caused by abiotic stresses, ABA, and glucose. In this study, we show that nitrate can alleviate the inhibitory effects of sodium chloride (NaCl) or high concentrations of glucose on seed germination in Arabidopsis, while it was not able to promote germination that was inhibited by exogenous ABA and mannitol (an inducer of osmotic stress). An analysis of the gene expression involved in the regulation of germination showed that GA20ox1, encoding the gibberellin (GA) synthesis enzyme, SPATULA (SPT), encoding a bHLH transcription factor, and CYP707A2, encoding an ABA catabolic enzyme, were significantly upregulated by the addition of KNO3 in the presence of NaCl or glucose. Our results suggest the possibility that these genes are involved in the nitrate-mediated control of seed germination in the presence of NaCl or glucose.
Gallstone Disease and Microbiome

Gallstone disease (GSD) has, for many years, remained a high-cost, socially significant public health problem. Over the past decade, a number of studies have been carried out—both in humans and in animal models—confirming the role of the microbiota in various sections of the gastrointestinal tract as a new link in the etiopathogenesis of GSD. The microbiome of bile correlates with the bacterial composition of saliva, and the microbiome of the biliary tract has a high similarity with the microbiota of the duodenum. Pathogenic microflora of the oral cavity, through mechanisms of immunomodulation, can affect the motility of the gallbladder and the expression of mucin genes (MUC1, Muc3, MUC4), and represent one of the promoters of stone formation in the gallbladder. The presence of H. pylori infection contributes to the formation of gallstones and affects the occurrence of complications of GSD, including acute and chronic cholecystitis, cholangitis, pancreatitis. Intestinal bacteria (Clostridium, Bifidobacterium, Peptostreptococcus, Bacteroides, Eubacterium, and Escherichia coli) participating in the oxidation and epimerization of bile acids can disrupt enterohepatic circulation and lead to the formation of gallstones. At the same time, cholecystectomy due to GSD leads to the further transformation of the composition of the microbiota in various parts of the gastrointestinal tract, increasing the risk of developing stomach cancer and colorectal cancer. Further research is required to determine the possibility of using the evaluation of the composition of the microbiota of the gastrointestinal and biliary tracts as an early diagnostic marker of various gastroenterological diseases.
Complexity of Election Evaluation and Probabilistic Robustness: Extended Abstract

When dealing with election data it is reasonable to assume that the votes are incomplete or noisy. The reasons are manifold and range from cost-intensive elicitation to manipulation. We study the important questions of evaluating elections with incomplete data and the robustness of elections with noisy data from a computational point of view. To capture different motivations, we consider three models for the distribution of preferences: the uniform distribution over the completions of incomplete preferences inspired by the possible winner problem, the dispersion around complete preferences, also called Mallows noise model, and a model in which the distribution over the votes of each voter is explicitly given. We consider both approval vector preferences and linear order preferences and show that the complexity of the problem can vary greatly depending on the voting rule, the distribution model, and the parameterization.
An Update on Mitochondrial Reactive Oxygen Species Production

Mitochondria are quantifiably the most important sources of superoxide (O2●−) and hydrogen peroxide (H2O2) in mammalian cells. The overproduction of these molecules has been studied mostly in the contexts of the pathogenesis of human diseases and aging. However, controlled bursts in mitochondrial ROS production, most notably H2O2, also plays a vital role in the transmission of cellular information. Striking a balance between utilizing H2O2 in second messaging whilst avoiding its deleterious effects requires the use of sophisticated feedback control and H2O2 degrading mechanisms. Mitochondria are enriched with H2O2 degrading enzymes to desensitize redox signals. These organelles also use a series of negative feedback loops, such as proton leaks or protein S-glutathionylation, to inhibit H2O2 production. Understanding how mitochondria produce ROS is also important for comprehending how these organelles use H2O2 in eustress signaling. Indeed, twelve different enzymes associated with nutrient metabolism and oxidative phosphorylation (OXPHOS) can serve as important ROS sources. This includes several flavoproteins and respiratory complexes I-III. Progress in understanding how mitochondria generate H2O2 for signaling must also account for critical physiological factors that strongly influence ROS production, such as sex differences and genetic variances in genes encoding antioxidants and proteins involved in mitochondrial bioenergetics. In the present review, I provide an updated view on how mitochondria budget cellular H2O2 production. These discussions will focus on the potential addition of two acyl-CoA dehydrogenases to the list of ROS generators and the impact of important phenotypic and physiological factors such as tissue type, mouse strain, and sex on production by these individual sites.
Optical Coherence Tomography Angiography in Neurodegenerative Disorders †

Retinal microcirculation shares similar features with cerebral small blood vessels. Thus, the retina may be considered an accessible ‘window’ to detect the microvascular damage occurring in the setting of neurodegenerative disorders. Optical coherence tomography angiography (OCT-A) is a non-invasive imaging modality providing depth resolved images of blood flow in the retina, choroid, and optic nerve. In this review, we summarize the current literature on the application of OCT-A in glaucoma and central nervous system conditions such as Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. Future directions aiming at evaluating whether OCT-A can be an additional biomarker for the early diagnosis and monitoring of neurodegenerative disorders are also discussed.
Big data analytics in medical engineering and healthcare: methods, advances and challenges

Abstract Big data analytics are gaining popularity in medical engineering and healthcare use cases. Stakeholders are finding big data analytics reduce medical costs and personalise medical services for each individual patient. Big data analytics can be used in large-scale genetics studies, public health, personalised and precision medicine, new drug development, etc. The introduction of the types, sources, and features of big data in healthcare as well as the applications and benefits of big data and big data analytics in healthcare is key to understanding healthcare big data and will be discussed in this article. Major methods, platforms and tools of big data analytics in medical engineering and healthcare are also presented. Advances and technology progress of big data analytics in healthcare are introduced, which includes artificial intelligence (AI) with big data, infrastructure and cloud computing, advanced computation and data processing, privacy and cybersecurity, health economic outcomes and technology management, and smart healthcare with sensing, wearable devices and Internet of things (IoT). Current challenges of dealing with big data and big data analytics in medical engineering and healthcare as well as future work are also presented.
Relationship between Evaluations of Tracheal Tube Position Using Ultrasound and Fluoroscopy in an Infant and Pediatric Population

Introduction: A non-radiographic technique to measure the location of the tracheal tube (TT) in children is of value given the risk of inappropriate TT placement along with concerns about radiation exposure. Airway point-of-care ultrasound (POCUS) has demonstrated utility in children, but the examinations vary by age and may require non-traditional techniques or utilize less common probes. This study evaluated the performance of measuring the tracheal location of the cuffed TT using a novel, linear probe-based POCUS examination over a wide age range of children. After adjusting for the subjects’ height and TT size, ultrasound measurements of the TT cuff location were compared with fluoroscopy measurements of the TT tip location. Methods: Perioperative pediatric patients (<10 years) requiring a cuffed TT were enrolled. After routine TT placement, ultrasound and fluoroscopy images were obtained. Measurements from the TT cuff to the cricoid cartilage were obtained from the POCUS examination. Chest fluoroscopy was reviewed to measure the TT’s distance from the carina. Both measurements were then compared after scaling for patient height. The duration of the ultrasound examination and image quality scores were also recorded. Results: Forty-one patients were enrolled, with a median age of 3 (25th/75th percentile: 1.50/7.00) years. The POCUS examination identified the TT cuff in all cases with the highest image quality score. The median POCUS exam time was 112 (25th/75th percentile: 80.00/156.00) seconds. There was a strong correlation between the POCUS measurements and the fluoroscopy measurements, r = −0.7575, 95% CI [−0.8638, −0.5866 ], p < 0.001). Conclusions: Our results demonstrate a strong correlation between POCUS TT localization measurements and traditional measurements via fluoroscopy. This study further supports the utility of POCUS for pediatric care.
Evaluation of the phenolic profile and immunoreactivity of Mal d 3 allergen in ancient apple cultivars from Italy.

BACKGROUND Since the second half of the last century, the cultivation of ancient and local apple cultivars has almost disappeared from orchards in Italy. Some of these ancient apple cultivars often possess high nutraceutical values, and display lower allergenicity when compared to the modern ones, supporting the so-called 'green revolution' theory. RESULTS In this study, the phenolic composition and the antioxidant activity of five ancient apple cultivars (Belfiore, Pomella Genovese, Gravenstein, Bella del Bosco and Piatlin) were compared to a Golden Delicious commercial cultivar. Additionally, apples were tested for their potential allergenicity by detecting the presence of Mal d 3, a non-specific lipid transfer protein (nsLTP) that represent the main apples' allergen. All apples came from Northern Italy (Trentino Region) and were organically produced. Results showed that, for all cultivars, the skins contained more polyphenols than the pulps. Bella del Bosco had the highest amount of polyphenols as well as antioxidant activity, while Piatlin had the lowest phenolic content. All ancient cultivars presented a higher amount of pulp phenolic compounds than Golden Delicious. Immunoblotting techniques showed that Bella del Bosco and Piatlin had very low quantities of Mal d 3 allergen, hence they can be considered hypoallergenic cultivars. CONCLUSIONS The preservation of ancient apple cultivars would be of great importance, not only to maintain the biodiversity but also for their nutritional properties. The hypoallergenic activity of some of these cultivars could be of interest also for the preparation of different apple-based products. This article is protected by copyright. All rights reserved.
Light microscopy of the endoplasmic reticulum–membrane contact sites in plants

The existence of membrane contact sites (MCS) has been reported in different systems in the past decade, and their importance has been recognised by the cell biology community. Amongst all endomembrane structures, the endoplasmic reticulum (ER) plays vital roles in organising the organelle interaction network with the plasma membrane (PM), Golgi bodies, mitochondria, plastids, endosomes and autophagosomes. A number of methods have been used to study the establishment and functions of these interactions, among them, light microscopy appears to be one of the most effective approaches. Here, we present an overview of the discovery of ER–PM contact sites, and highlight the latest developments in light microscopical‐based techniques that can be used for their study.
Serum nesfatin-1, ghrelin, and lipid levels in adolescents with first episode drug naïve unipolar depression

Abstract Background: Major depressive disorder (MDD) is a mental health and emotional disorder that affects children and adolescents worldwide. This study aimed to evaluate serum nesfatin-1, ghrelin, and lipid levels as biological markers of adolescent MDD and their relationship with the severity of depression-anxiety and suicide risk in MDD. Methods:This study included 37 drug naïve adolescents between the ages of 12 and 18 who were diagnosed with a first episode MDD according to the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL) and DSM-V diagnostic criteria. Thirty-three healthy adolescents between the ages of 12 and 18 were included as the control group. The Children’s Depression Inventory (CDI), Screen for Child Anxiety Related Disorders (SCARED), and Suicide Probability Scale (SPS) were used to evaluate the subjects in the MDD and control groups. In the first stage, serum nesfatin-1, ghrelin, and lipid levels were compared between the adolescents diagnosed with MDD and the control group. Next, the correlations between these levels and the CDI, SCARED, and SPS scores were evaluated. Results: Nesfatin-1 levels were significantly lower in the MDD group than the control group (p < 0.001) A positive correlation was found between the nesfatin-1 levels and the SPS scores. Conclusions: This is the first study to evaluate nesfatin-1 levels in adolescent depression, suggesting that nesfatin-1, ghrelin, total cholesterol, and low-density lipoprotein cholesterol (LDL) levels can be used as biomarkers in child-adolescent MDD. However, it is evident that further studies with larger samples and post-treatment measurements are needed.
The association of polymorphisms in the ovine PPARGC1B and ZEB2 genes with body weight in Hu sheep

Abstract The aims of this study were to analyze the effects of PPARGC1B and ZEB2 polymorphisms on the body weight of Hu sheep. DNA sequencing and KASPar technologies were used to detect single nucleotide polymorphisms (SNPs) within the PPARGC1B and ZEB2 genes of Hu sheep (n = 207). Two synonymous mutations, g.300 G > A and g.645 C > T, were detected in PPARGC1B and ZEB2, respectively. The body weights of sheep were recorded at 80, 100, 120, 140, 160 and 180-days, and associations between these polymorphisms and body weight changes were analyzed. Association analysis demonstrated that the polymorphisms in PPARGC1B and ZEB2 significantly associated with body weight (p < 0.05). At the g.300 G > A locus, individuals with the GG genotype had significantly higher body weight than those with the AA genotype, and at the g.645 C > T locus, individuals with the TT genotype had significantly higher body weight than those with the TC genotype. Individuals with both polymorphisms exhibited significantly different growth (p < 0.05). These data suggest that polymorphisms in the PPARGC1B and ZEB2 genes can be used as candidate molecular markers for the breeding of desirable growth traits in Hu sheep.
Skeleton-based Action Recognition for Industrial Packing Process

: The applications of action recognition in real-world scenarios are challenging. Although state-of-the-art methods have demonstrated good performance on large scale datasets, we still face complex practical problems and inappropriate models. In this work, we propose a novel local image directed graph neural network (LI-DGNN) to solve a real-world production scenario problem which is the completeness identification of accessories during the range hood packing process in a kitchen appliance manufacturing workshop. LI-DGNN integrates skeleton-based action recognition and local image classification to make good use of both human skeleton data and appearance information for action recognition. The experimental results demonstrate the high recognition accuracy and good generalization ability on the range hood packing dataset (RHPD) which is generated in the industrial packing process. The results can meet the recognition requirements in the actual industrial production process.
Energy Optimisation of Cascading Neural-network Classifiers

Artificial Intelligence is increasingly being used to improve different facets of society such as healthcare, education, transport, security, etc. One of the popular building blocks for such AI systems are Neural Networks, which allow us to recognise complex patterns in large amounts of data. With the exponential growth of data, Neural Networks have become increasingly crucial to solve more and more challenging problems. As a result of this, the computational and energy requirements for these algorithms have grown immensely, which going forward will be a major contributor to climate change. In this paper, we present techniques to reduce the energy use of Neural Networks without significantly reducing their accuracy or requiring any specialised hardware. In particular, our work focuses on Cascading Neural Networks and reducing the dimensions of the input space which in turn allows us to create simpler classifiers which are more energy-efficient. We reduce the input complexity by using semantic data (Colour, Edges, etc.) from the input images and systematic techniques such as LDA. We also introduce an algorithm to efficiently arrange these classifiers to optimise gain in energy efficiency. Our results show a 13% reduction in energy usage over the popular Scalable effort classifier and a 35% reduction when compared to Keras CNN for Cifar10. Finally, we also reduced energy usage of the full input neural network (often used as the last stage in the cascading technique) by using Bayesian optimisation with adjustable parameters and minimal assumptions to search for the best model under given energy constraints. Using this technique we achieve significant energy savings of 29% and 34% for MNIST and Cifar10 respectively.