Miracle-dz/UniFAR-FTUs huggingface dataset:
Species Composition and Abundance of the Natural Enemies of Sugarcane Aphid, Melanaphis sacchari (Zehnter) (Hemiptera: Aphididae), on Sorghum in Texas

Abstract. The sugarcane aphid, Melanaphis sacchari (Zehntner), is an emergent sorghum pest in the United States. This study was designed to identify which natural enemy species are present in aphid populations in sorghum in Texas, and to track the seasonal population trends of the aphid and its natural enemies on sorghum hybrids that differ in susceptibility to the aphid. From 2015 through 2016, sugarcane aphid and its natural enemies were sampled weekly in plots of aphid-susceptible and partially aphid-resistant sorghum hybrids at two field sites in Nueces County and Burleson County, Texas. In 2015, aphids and natural enemies had greater peak abundance on the susceptible hybrid than on the resistant hybrid. Peak abundance of most natural enemies tended to lag behind that of aphids by one to two weeks. Natural enemy taxa observed at both field sites included two primary parasitoid wasp species (Hymenoptera: Aphelinidae: Aphelinus nigritus Howard stat. rev.; Braconidae: Lysiphlebus testaceipes (Cresson)), one species of hyperparasitoid (Hymenoptera: Encyrtidae), ten lady beetle species (Coleoptera: Coccinellidae) and three morphospecies of dusky lady beetle (Coccinellidae: Scymninae), three hoverfly species (Diptera: Syrphidae), five green lacewing species (Neuroptera: Chrysopidae), brown lacewings (Neuroptera: Hemerobiidae: Hemerobius), and minute pirate bugs (Hemiptera: Anthocoridae: Orius insidiosus (Say)). Aphelinus and Coccinellidae were the numerically dominant natural enemy groups in all sorghum hybrids, followed by Chrysopidae and Syrphidae. Aphids mummified by Aphelinus were hyperparasitized by Syrphophagus aphidivorus at a rate of approximately 90%. Natural enemy densities were similarly proportionate to aphid densities on both aphid-susceptible and aphid-resistant plants. Overall, the continuity of natural enemy species composition and population trends supports that these natural enemies responded positively to sugarcane aphid on sorghum.
Relapsing-Remitting Multiple Sclerosis Is Associated With Regional Brain Activity Deficits in Motor- and Cognitive-Related Brain Areas

Objective: To identify the abnormal regional spontaneous brain activity associated with relapsing-remitting multiple sclerosis (RRMS) using fractional amplitude of low-frequency fluctuation (fALFF) analysis and their relationships with clinical features. Methods: A total of 26 RRMS (11 males, 15 females; age, 36.58 ± 10.82 years) and 27 status-matched healthy group (HGs; 12 males, 15 females; age, 35.85 ± 12.05 years) underwent an Expanded Disability Status Scale (EDSS) examination. fALFF was applied to evaluate the abnormal regional brain activity associated with RRMS. Pearson's correlation analysis was applied to calculate the correlations between the signal values of brain areas that exhibited abnormal fALFF values and clinical features. Receiver operating characteristic (ROC) curve was performed to evaluate the sensitivity and specificity of those altered brain areas to distinguish between RRMS and HGs. Results: Compared with HGs, RRMS exhibited higher fALFF in the right cerebellum posterior lobe, left orbitofrontal cortex, left dorsolateral prefrontal cortex, bilateral supplementary motor area, and right fusiform gyrus and lower fALFF values in the left hippocampus and right precuneus. ROC revealed that these areas showed two good and five fair AUC values (0.77 ± 0.03, 0.729~0.822). However, four combinations with more than five brain regions received the same best discriminatory power with a sensitivity of 96.3% and a specificity of 88.5%. EDSS revealed a negative correlation with supplementary motor area (r = −0.395, p = 0.046). Conclusions: RRMS is associated with abnormal regional brain activity deficits of motor- and cognitive-related areas. The fALFF parameter may serve as a potential biological marker to discriminate between the two groups.
A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.
Biological Activities of Secretory RNases: Focus on Their Oligomerization to Design Antitumor Drugs

Ribonucleases (RNases) are a large number of enzymes gathered into different bacterial or eukaryotic superfamilies. Bovine pancreatic RNase A, bovine seminal BS-RNase, human pancreatic RNase 1, angiogenin (RNase 5), and amphibian onconase belong to the pancreatic type superfamily, while binase and barnase are in the bacterial RNase N1/T1 family. In physiological conditions, most RNases secreted in the extracellular space counteract the undesired effects of extracellular RNAs and become protective against infections. Instead, if they enter the cell, RNases can digest intracellular RNAs, becoming cytotoxic and having advantageous effects against malignant cells. Their biological activities have been investigated either in vitro, toward a number of different cancer cell lines, or in some cases in vivo to test their potential therapeutic use. However, immunogenicity or other undesired effects have sometimes been associated with their action. Nevertheless, the use of RNases in therapy remains an appealing strategy against some still incurable tumors, such as mesothelioma, melanoma, or pancreatic cancer. The RNase inhibitor (RI) present inside almost all cells is the most efficacious sentry to counteract the ribonucleolytic action against intracellular RNAs because it forms a tight, irreversible and enzymatically inactive complex with many monomeric RNases. Therefore, dimerization or multimerization could represent a useful strategy for RNases to exert a remarkable cytotoxic activity by evading the interaction with RI by steric hindrance. Indeed, the majority of the mentioned RNases can hetero-dimerize with antibody derivatives, or even homo-dimerize or multimerize, spontaneously or artificially. This can occur through weak interactions or upon introducing covalent bonds. Immuno-RNases, in particular, are fusion proteins representing promising drugs by combining high target specificity with easy delivery in tumors. The results concerning the biological features of many RNases reported in the literature are described and discussed in this review. Furthermore, the activities displayed by some RNases forming oligomeric complexes, the mechanisms driving toward these supramolecular structures, and the biological rebounds connected are analyzed. These aspects are offered with the perspective to suggest possible efficacious therapeutic applications for RNases oligomeric derivatives that could contemporarily lack, or strongly reduce, immunogenicity and other undesired side-effects.
Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome

While over ten thousand genetic loci have been associated with phenotypic traits and inherited diseases in genome-wide association studies, in most cases only a relatively small proportion of the trait heritability is explained and biological mechanisms underpinning these traits have not been clearly identified. Expression quantitative trait loci (eQTL) are subsets of genomic loci shown experimentally to influence gene expression. Since gene expression is one of the primary determinants of phenotype, the identification of eQTL may reveal biologically relevant loci and provide functional links between genomic variants, gene expression and ultimately phenotype. Skeletal muscle (gluteus medius) gene expression was quantified by RNA-seq for 111 Thoroughbreds (47 male, 64 female) in race training at a single training establishment sampled at two time-points: at rest (n = 92) and four hours after high-intensity exercise (n = 77); n = 60 were sampled at both time points. Genotypes were generated from the Illumina Equine SNP70 BeadChip. Applying a False Discovery Rate (FDR) corrected P-value threshold (P FDR < 0.05), association tests identified 3,583 cis-eQTL associated with expression of 1,456 genes at rest; 4,992 cis-eQTL associated with the expression of 1,922 genes post-exercise; 1,703 trans-eQTL associated with 563 genes at rest; and 1,219 trans-eQTL associated with 425 genes post-exercise. The gene with the highest cis-eQTL association at both time-points was the endosome-associated-trafficking regulator 1 gene (ENTR1; Rest: P FDR = 3.81 × 10-27, Post-exercise: P FDR = 1.66 × 10-24), which has a potential role in the transcriptional regulation of the solute carrier family 2 member 1 glucose transporter protein (SLC2A1). Functional analysis of genes with significant eQTL revealed significant enrichment for cofactor metabolic processes. These results suggest heritable variation in genomic elements such as regulatory sequences (e.g. gene promoters, enhancers, silencers), microRNA and transcription factor genes, which are associated with metabolic function and may have roles in determining end-point muscle and athletic performance phenotypes in Thoroughbred horses. The incorporation of the eQTL identified with genome and transcriptome-wide association may reveal useful biological links between genetic variants and their impact on traits of interest, such as elite racing performance and adaptation to training.
Effect of Prior Direction Expectation on the Accuracy and Precision of Smooth Pursuit Eye Movements

The integration of sensory with top–down cognitive signals for generating appropriate sensory–motor behaviors is an important issue in understanding the brain’s information processes. Recent studies have demonstrated that the interplay between sensory and high-level signals in oculomotor behavior could be explained by Bayesian inference. Specifically, prior knowledge for motion speed introduces a bias in the speed of smooth pursuit eye movements. The other important prediction of Bayesian inference is variability reduction by prior expectation; however, there is insufficient evidence in oculomotor behaviors to support this prediction. In the present study, we trained monkeys to switch the prior expectation about motion direction and independently controlled the strength of the motion stimulus. Under identical sensory stimulus conditions, we tested if prior knowledge about the motion direction reduced the variability of open-loop smooth pursuit eye movements. We observed a significant reduction when the prior expectation was strong; this was consistent with the prediction of Bayesian inference. Taking advantage of the open-loop smooth pursuit, we investigated the temporal dynamics of the effect of the prior to the pursuit direction bias and variability. This analysis demonstrated that the strength of the sensory evidence depended not only on the strength of the sensory stimulus but also on the time required for the pursuit system to form a neural sensory representation. Finally, we demonstrated that the variability and directional bias change by prior knowledge were quantitatively explained by the Bayesian observer model.
Immunoreactive Cells After Cerebral Ischemia

The immune system is rapidly activated after ischemic stroke. As immune cells migrate and infiltrate across the blood-brain barrier into the ischemic region, a cascade of cellular and molecular biological reactions occur, involving migrated immune cells, resident glial cells, and the vascular endothelium. These events regulate infarction evolution and thus influence the outcome of ischemic stroke. Most immune cells exert dual effects on cerebral ischemia, and some crucial cells may become central targets in ischemic stroke treatment and rehabilitation.
Pervasive Inter-Individual Variation in Allele-Specific Expression in Monozygotic Twins

Despite being developed from one zygote, heterokaryotypic monozygotic (MZ) co-twins exhibit discordant karyotypes. Epigenomic studies in biological samples from heterokaryotypic MZ co-twins are of the most significant value for assessing the effects on gene- and allele-specific expression of an extranumerary chromosomal copy or structural chromosomal disparities in otherwise nearly identical germline genetic contributions. Here, we use RNA-Seq data from existing repositories to establish within-pair correlations for the breadth and magnitude of allele-specific expression (ASE) in heterokaryotypic MZ co-twins discordant for trisomy 21 and maternal 21q inheritance, as well as homokaryotypic co-twins. We show that there is a genome-wide disparity at ASE sites between the heterokaryotypic MZ co-twins. Although most of the disparity corresponds to changes in the magnitude of biallelic imbalance, ASE sites switching from either strictly monoallelic to biallelic imbalance or the reverse occur in few genes that are known or predicted to be imprinted, subject to X-chromosome inactivation or A-to-I(G) RNA edited. We also uncovered comparable ASE differences between homokaryotypic MZ twins. The extent of ASE discordance in MZ twins (2.7%) was about 10-fold lower than the expected between pairs of unrelated, non-twin males or females. The results indicate that the observed within-pair dissimilarities in breadth and magnitude of ASE sites in the heterokaryotypic MZ co-twins could not solely be attributable to the aneuploidy and the missing allelic heritability at 21q.
Fine Scale Assemblage Structure of Benthic Invertebrate Megafauna on the North Pacific Seamount Mokumanamana

Changes in benthic megafaunal assemblage structure have been found across gradients of environmental variables for many deep-sea habitats, but patterns remain under-investigated on seamounts. To assess the extent of variability in benthic communities at the scale of within a single seamount, and to assess environmental drivers of assemblage changes, Mokumanamana, also known as Necker Island, a seamount in the Papahānaumokuākea Marine National Monument with no known history of human impacts, was surveyed. Replicate 1 km transects were conducted along depth contours at 50 m depth intervals from 200 – 700 m on three sides of Mokumanamana using the AUV Sentry. Megafaunal abundance and substrate parameters were obtained from 26,119 total images. The dominant megafaunal taxa were sponges, corallimorpharians, cup corals, and benthic ctenophores. Sea pens and alcyonacean octocorals were also abundant. Overall, abundance and diversity of megafauna increased with depth. Beta-diversity through species substitution with depth was very high. Beta-diversity was also high between the sides and likewise defined almost exclusively by species substitution. Crossed ANOSIM by depth and side showed community structure differed on Mokumanamana for both factors. NMDS and cluster analyses of Mokumanamana show nine assemblages that were defined by depth and reflect differences between sides of the seamount. Environmental modeling with DISTLM indicates sediment, oxygen, substrate variability and roughness, POC, and surface currents are correlated with these assemblage differences. These results suggest that microhabitats on seamounts can promote unique assemblages along depth gradients as well as on different sides of a feature, and this diversity may be easily overlooked without fine-scale sampling. These findings have implications for management and conservation of seamounts as well as future ecological studies of seamounts, as seamounts are generally sampled on much coarser spatial scales.
Soil Inoculation Steers Plant-Soil Feedback, Suppressing Ruderal Plant Species

Plant-soil feedbacks (PSFs) are important drivers of vegetation composition in nature. Whole-soil inoculations can help to steer plant-community assembly for nature restoration success. However, it is unclear how subsequent colonization by ruderal and late-successional plant species influences PSFs. Here we test the direction and strength of the PSFs for ruderal and target plant species on differently inoculated soils. We hypothesize that inoculation with late-successional field soil promotes positive and negative PSFs for late-successional and ruderal plants respectively. We conducted a glasshouse experiment with three plant-growth phases. First, we inoculated a common nutrient-rich ex-arable soil with either a heathland, grassland or an arable soil and grew mixtures of three ruderal and three late-successional target species in all soils. Subsequently, we divided the experimental units over four new pots and planted half with mixtures of three ruderal and half with mixtures of three late-successional plant species, to simulate local colonization by these species groups. After nine weeks, we removed the plants and replanted the pots with ruderal and late-successional species mixtures in a full factorial design to quantify the induced PSFs, after a further nine weeks of growth. We found that ruderal plants developed positive PSF on soils inoculated with arable soil and neutral feedback when soils were inoculated with grassland or heathland inoculum. The positive PSF was most pronounced for Myosotis arvensis, although all ruderal species showed the most positive PSFs on arable-inoculated soils. There was no significant effect of inoculation on the PSF of late-successional species. As a result of changing PSFs, the relative performance of ruderal and late-successional target species became more similar on soils inoculated with grassland or heathland inoculum, leading to higher evenness. We conclude that soil inoculation on nutrient-rich ex-arable soils can affect PSFs. Inoculation with grassland or heathland inoculum prevented ruderal species from developing positive PSF and shifted the competitive balance in favour of late-successional plants. Future studies need to address the longer-term dynamics of soil inoculation-induced shifts in PSFs, particularly because these are expected to develop over longer timescales in the slow-growing late-successional target species, as well as the impact of competitive plant-plant interactions.
Identification of α,β-Hydrolase Domain Containing Protein 6 as a Diacylglycerol Lipase in Neuro-2a Cells

The endocannabinoid 2-arachidonoylglycerol (2-AG) is involved in neuronal differentiation. This study aimed to identify the biosynthetic enzymes responsible for 2-AG production during retinoic acid (RA)-induced neurite outgrowth of Neuro-2a cells. First, we confirmed that RA stimulation of Neuro-2a cells increases 2-AG production and neurite outgrowth. The diacylglycerol lipase (DAGL) inhibitor DH376 blocked 2-AG production and reduced neuronal differentiation. Surprisingly, CRISPR/Cas9-mediated knockdown of DAGLα and DAGLβ in Neuro-2a cells did not reduce 2-AG levels, suggesting another enzyme capable of producing 2-AG in this cell line. Chemical proteomics revealed DAGLβ and α,β-hydrolase domain containing protein (ABHD6) as the only targets of DH376 in Neuro-2a cells. Biochemical, genetic and lipidomic studies demonstrated that ABHD6 possesses DAGL activity in conjunction with its previously reported monoacylglycerol lipase activity. RA treatment of Neuro-2a cells increased by three-fold the amount of active ABHD6. Our study shows that ABHD6 exhibits significant DAG lipase activity in Neuro-2a cells in addition to its known MAG lipase activity and suggest it is involved in neuronal differentiation.
Classification of Multiple Psychological Dimensions in Computer Game Players Using Physiology, Performance, and Personality Characteristics

Human psychological (cognitive and affective) dimensions can be assessed using several methods, such as physiological or performance measurements. To date, however, few studies have compared different data modalities with regard to their ability to enable accurate classification of different psychological dimensions. This study thus compares classification accuracies for four psychological dimensions and two subjective preferences about computer game difficulty using three data modalities: physiology, performance, and personality characteristics. Thirty participants played a computer game at nine difficulty configurations that were implemented via two difficulty parameters. In each configuration, seven physiological measurements and two performance variables were recorded. A short questionnaire was filled out to assess the perceived difficulty, enjoyment, valence, arousal, and the way the participant would like to modify the two difficulty parameters. Furthermore, participants’ personality characteristics were assessed using four questionnaires. All combinations of the three data modalities (physiology, performance, and personality) were used to classify six dimensions of the short questionnaire into either two, three or many classes using four classifier types: linear discriminant analysis, support vector machine (SVM), ensemble decision tree, and multiple linear regression. The classification accuracy varied widely between the different psychological dimensions; the highest accuracies for two-class and three-class classification were 97.6 and 84.1%, respectively. Normalized physiological measurements were the most informative data modality, though current game difficulty, personality and performance also contributed to classification accuracy; the best selected features are presented and discussed in the text. The SVM and multiple linear regression were the most accurate classifiers, with regression being more effective for normalized physiological data. In the future, we will further examine the effect of different classification approaches on user experience by detecting the user’s psychological state and adapting game difficulty in real-time. This will allow us to obtain a complete picture of the performance of affect-aware systems in both an offline (classification accuracy) and real-time (effect on user experience) fashion.