Miracle-dz/UniFAR-FTUs huggingface dataset:
Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.
Classification of Infected Necrotizing Pancreatitis for Surgery Within or Beyond 4 Weeks Using Machine Learning

Background: The timing of surgery for necrotizing pancreatitis remains a matter of controversial debate, which has not been resolved by randomized controlled trial (RCT). This study aims to classify surgical timing within or beyond 4 weeks for patients with infected necrotizing pancreatitis by using machine learning methods. Methods: This study analyzed 223 patients who underwent surgery for infected pancreatic necrosis at West China Hospital of Sichuan University. We used logistic regression, support vector machine, and random forest with/without the simulation of generative adversarial networks to classify the surgical intervention within or beyond 4 weeks in the patients with infected necrotizing pancreatitis. Results: Our analyses showed that interleukin 6, infected necrosis, the onset of fever and C-reactive protein were important factors in determining the timing of surgical intervention (< 4 or ≥ 4 weeks) for the patients with infected necrotizing pancreatitis. The main factors associated with postoperative mortality in patients who underwent early surgery (< 4 weeks) included modified Marshall score on admission and preoperational modified Marshall score. Preoperational modified Marshall score, time of surgery, duration of organ failure and onset of renal failure were important predictive factors for the postoperative mortality of patients who underwent delayed surgery (≥ 4 weeks). Conclusions: Machine learning models can be used to predict timing of surgical intervention effectively and key factors associated with surgical timing and postoperative survival are identified for infected necrotizing pancreatitis.
A Rice Autophagy Gene OsATG8b Is Involved in Nitrogen Remobilization and Control of Grain Quality

Enhancing nitrogen (N) use efficiency is a potential way to reduce excessive nitrogen application and increase yield. Autophagy is a conserved degradation system in the evolution of eukaryotic cells and plays an important role in plant development and stress response. Autophagic cores have two conjugation pathways that attach the product of autophagy-related gene 8 (ATG8) to phosphatidylethanolamine (PE) and ATG5 to ATG12, respectively, which then help with vesicle elongation and enclosure. Rice has six ATG8 genes, which have not been functionally confirmed so far. We identified the rice gene OsATG8b and characterized its role in N remobilization to affect grain quality by generating transgenic plants with its over-expression and knockdown. Our study confirmed the autophagy activity of OsATG8b through the complementation of the yeast autophagy-defective mutant scatg8 and by observation of autophagosome formation in rice. The autophagy activity is higher in OsATG8b-OE lines and lower in OsATG8b-RNAi than that in wild type (ZH11). 15N pulse-chase analysis revealed that OsATG8b-OE plants conferred higher N recycling efficiency to grains, while OsATG8b-RNAi transgenic plants exhibited lower N recycling efficiency and poorer grain quality. The autophagic role of OsATG8b was experimentally confirmed, and it was concluded that OsATG8b-mediated autophagy is involved in N recycling to grains and contributes to the grain quality, indicating that OsATG8b may be a potential gene for molecular breeding and cultivation of rice.
Plant Images Recognition based on Transfer Learning

With the fruitful achievement of deep learning in computer vision, transfer learning is becoming a profoundly developing and potential research field to overcome its shortcomings because transfer learning can reach desired goal with fewer training data and less running time. Tree identification is meaningful and important for many fields, such as phytology, ecology, traditional Chinese medicine and so on. In this paper, transfer learning is employed in the proposed tree image recognition method which is prepared by the per-trained networks: Inception-V3 and Inception-ResNet-v2 networks; and 22 ornamental tree species with more than 22,000 images from ImageNet database are collected for retraining. After 10,000 rounds of training for these networks, the cross-accuracy of Inception-V3 and Inception-ResNet-v2 networks is reach 87.8 and 91.2%, respectively. To test the performance of the proposed method, it is compared with conventional neural network and convolutional neural network (CNN) using the same data. Our work mainly includes to analyze the recognition effect of "bad image" for the proposed inception networks, such as easier confusing or bad shooting images and so on; besides, we also collect another easily confused tree images for testing the performance of the proposed method. The experiments show that the proposed method is effective than the common methods.
COVID-19 Confinement and Health Risk Behaviors in Spain

The World Health Organization (WHO) has declared a world pandemic due to COVID-19. In response, most affected countries have enacted measures involving compulsory confinement and restrictions on free movement, which likely influence citizens' lifestyles. This study investigates changes in health risk behaviors (HRBs) with duration of confinement. An online cross-sectional survey served to collect data about the Spanish adult population regarding health behaviors during the first 3 weeks of confinement. A large sample of participants (N = 2,741) (51.8% women; mean age 34.2 years [SD 13.0]) from all Spanish regions completed the survey. Binomial logistic regressions adjusted for socioeconomic characteristics (i.e., gender, age, civil status, education, and occupation), body mass index (BMI), previous HRBs, and confinement context (i.e., solitude and exposure to COVID-19) were conducted to investigate associations between the number of weeks confined and a set of six HRBs (physical activity, alcohol consumption, fresh fruit and vegetable consumption, smoking, screen exposure, and sleep hours). When adjusted, we observed significantly lower odds of experiencing a higher number of HRBs than before confinement overall in a time-dependent fashion: OR 0.63; 95% CI: 0.49–0.81 for the second and OR 0.47; 95% CI: 0.36–0.61 for the third week of confinement. These results were equally consistent in all age and gender subgroup analyses. The present study indicates that changes toward a higher number of HRBs than before confinement, as well as the prevalence of each HRB except screen exposure, decreased during the first 3 weeks of COVID-19 confinement, and thus the Spanish adult population may have adapted to the new situational context by gradually improving their health behaviors.
SKELETAL CARBONATE MINERALOGY OF BRYOZOANS FROM CHILE: AN INDEPENDENT CHECK OF PHYLOGENETIC PATTERNS

Abstract Bryozoa exhibit some broad phylogenetic patterns in skeletal carbonate mineralogy that have previously been elucidated based on material from Australasia, Europe, North America, South Africa, and Antarctica. A new dataset from 19 locations in the Patagonian fiord region of Chile adds 93 specimens and 23 species to the mineralogical information on this highly variable phylum, as well as providing a comparison with generalizations made to date. Most species, genera, and families from Chile are of similar mineralogy to their worldwide counterparts, but a few are surprising. Chilean Membranipora isabellana and Diastopora sp. are both 100% aragonite despite belonging to taxa that are dominantly calcitic. Adeonella patagonica and Adeonella sp. are the only species exhibiting bimineral skeletons, from 6 to 100% calcite, a much greater range than was previously known for this genus and the Adeonellidae. Skeletal mineralogy has been tested in only 95 of the 323 families in the Bryozoa. We are, nevertheless, able to make some generalizations. For example, stenolaemates are almost always low-Mg calcite, and ascophoran cheilostomes are the most variable and mineralogically complex group. The capacity to generalize about bryozoan mineralogy is necessary in the face of increasing pressure on biomineralization from ocean acidification.
AITI: An Automatic Identification Model of Threat Intelligence Based on Convolutional Neural Network

Cyberspace security issues are becoming more and more important, but traditional methods cannot cope with changing cyber-attack methods, which often leads to severe network paralysis and economic losses. Therefore, we propose an automatic identification model of threat intelligence (TI) based on convolutional neural network (CNN) called AITI. At first, the cyber crawler technology is used to obtain unstructured semantic text data from platforms such as security forums and blogs. Next, the semantic text is preprocessed and input into the word embedding model to extract feature vectors. Then, we build a classification model based on CNN and train it on the collected dataset. Finally, the trained CNN model is used to automatically identify TI from unstructured semantic text such as security articles. According to the experiment results, AITI have obtained the accuracy of 90.38% and the F1 Score of 91.16%. The experiments verified that AITI outperforms other models on multiple core metrics. AITI provides a practical solution for TI identification to a certain extent, which can improve the efficiency and accuracy of TI identification.
The influence of habitat, prey abundance, sex, and breeding success on the ranging behavior of Prairie Falcons

We studied the ranging behavior and habitat selection of radio-tagged Prairie Falcons (Falco mexicanus) during the breeding season in southwestern Idaho. The distribution and numbers of Townsend's ground squirrels (Spermophilus townsendii), the primary prey of Prairie Falcons in our study area, varied in response to drought during the study period. Prairie Falcons ranged over large areas (ca. 300 km 2 ) and increased their foraging ranges in response to declining ground squirrels. Reptiles and birds were preyed upon most frequently when squirrels were rare. Males and females differed little in their use of space. Successful pairs ranged over smaller areas than non-nesters and unsuccessful pairs. Falcons nesting near habitat most suitable for ground squirrels ranged over smaller areas than those nesting farther from such habitat. Home ranges contained significantly more winterfat (Ceratoides lanata) and native perennial grasses (especially Poa secunda), and significantly less salt desert shrubs and exotic annual grasses than expected based on availability. Salt desert shrubs were found less than expected, based on availability in core areas within home ranges. Selection for winterfat and bluegrass in core areas was contingent upon selection at the larger scale of the home range; falcons with-home ranges containing more winterfat and bluegrass than expected based on availability were less selective in their placement of core areas with respect to these habitats. We believe salient features of Prairie Falcon home ranges result largely from patchy distribution of landscape features associated with different densities and availabilities of Townsend's ground squirrels.
Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis

Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) (R2 = 0.96) and paced auditory serial addition test (PASAT) (R2 = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.
Temporal Changes in Size at Maturity and Their Implications for Fisheries Management for Eastern Bering Sea Tanner Crab

Tanner crab (Chionoecetes bairdi) in the eastern Bering Sea are primarily distributed in Bristol Bay and around the Pribilof Islands. Summer trawl survey data in these two areas were used to estimate mean sizes at maturity for female Tanner crab from 1975 to 2006 and sizes at 50% morphometric maturity for male Tanner crab from 1990 to 2006. Estimated mean sizes at maturity for females showed a statistically significant downward trend in both areas. Sizes at 50% morphometric maturity for males have declined significantly since 1990, in Bristol Bay only. In Bristol Bay, the distribution centers of female Tanner crab have shifted southwest over time and the decrease in female mean size at maturity was significantly related to changes in longitude and bottom depths. Because of terminal molt at maturity, the decrease in size at maturity has important implications for fisheries management: under the current size limit, a smaller proportion of males grow to legal size and therefore a higher proportion of large-growing males are removed by the fishery before they have a chance to participate in reproduction. With the recent maturity at a small size, reduction of the current harvest rates and size limit while maintaining current fishing gear requirements will result in higher yield and higher male spawning biomass per recruit than those under the current harvest strategy.
Use of Existing and Reconnected Backwater Habitats by Hatchery-Reared Adult Razorback Suckers: A Predictive Model for the Imperial Division, Lower Colorado River

Abstract Information regarding the life history and biological requirements and preferences for the razorback sucker Xyrauchen texanus is limited. Current recovery efforts involve rearing fish to juvenile or adult stages in hatcheries before they are released into areas of critical habitat that increase their survival. Our objectives were to develop a model based on habitat use by hatchery-reared razorback suckers in the lower Colorado River of Arizona and California for predicting preferred habitat and to determine whether fish would use reconnected off-channel habitats. To this end, we monitored the use of existing and reconnected habitats by hatchery-reared razorback suckers implanted with sonic transmitters. Off-channel (backwater) habitats were preferred over main-channel or side-channel habitats. We constructed a model using logistic regression to predict which types of backwaters (based on morphology and water quality) were most suitable for use by razorback suckers. The model works well for predic.
Diet of Tawny Owl (Strix aluco) and Long-Eared Owl (Asio otus) in Lithuania as Found from Pellets

Diet composition and food niches of two common and widespread in Lithuania owl species, Tawny Owl (Strix aluco) and Long-eared Owl (Asio otus), were analysed from irregularly collected pellets. S. aluco was characterised by a more diverse diet and a wider food niche: 14 small mammal (93.1% of the recovered items) and two amphibian (5.2%) species, a few passerine birds (1.1%) and representatives of three Coleoptera groups (0.6%) were recovered, whereas for A. otus – nine small mammal and two Carabidea species. By numbers, primary food resources of S. aluco were C. glareolus (31.4%), M. arvalis (27.9%) and A. flavicollis (14.3%), whereas of A. otus - M. arvalis (70.8%), all Microtus voles constituting 95.2%. Diet diversity of S. aluco was more than twofold higher (Shannon’s H = 2.62 vs. 1.16). According to biomass, main foods consumed by S. aluco were C. glareolus, M. arvalis and A. flavicollis (27.6, 25.0 and 22.4%, respectively). For A. otus, Microtus voles represented 95.8% of biomass consumed (M. arvali.
Activation of the VPAC2 Receptor Impairs Axon Outgrowth and Decreases Dendritic Arborization in Mouse Cortical Neurons by a PKA-Dependent Mechanism

Clinical studies have shown that microduplications at 7q36.3, containing VIPR2, confer significant risk for schizophrenia and autism spectrum disorder (ASD). VIPR2 gene encodes the VPAC2 receptor for vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP). Lymphocytes from patients with these mutations exhibited higher VIPR2 gene expression and VIP-induced cAMP responsiveness, but mechanisms by which overactive VPAC2 signaling may lead to these psychiatric disorders are unknown. We have previously found that repeated administration of a selective VPAC2 receptor agonist Ro25-1553 in the mouse during early postnatal development caused synaptic alterations in the prefrontal cortex and sensorimotor gating deficits. In this study, we aimed to clarify the effects of VPAC2 receptor activation on neurite outgrowth in cultured primary mouse cortical neurons. Ro25-1553 and VIP caused reductions in total numbers and lengths of both neuronal dendrites and axons, while PACAP38 facilitated elongation of dendrites, but not axons. These effects of Ro25-1553 and VIP were blocked by a VPAC2 receptor antagonist PG99-465 and abolished in VPAC2 receptor-deficient mice. Additionally, Ro25-1553-induced decreases in axon and dendritic outgrowth in wild-type mice were blocked by a protein kinase A (PKA) inhibitor H89, but not by a PKC inhibitor GF109203X or a mitogen-activated protein kinase (MAPK) kinase (MEK) inhibitor U0126. PACAP38- induced facilitation of dendritic outgrowth was blocked by U0126. These results suggest that activation of the VPAC2 receptor impairs neurite outgrowth and decreases branching of cortical neurons by a PKA-dependent mechanism. These findings also imply that the VIPR2-linkage to mental health disorders may be due in part to deficits in neuronal maturation induced by VPAC2 receptor overactivation.
Human Monocyte Subset Distinctions and Function: Insights From Gene Expression Analysis

Monocytes are a highly plastic innate immune cell population that displays significant heterogeneity within the circulation. Distinct patterns of surface marker expression have become accepted as a basis for distinguishing three monocyte subsets in humans. These phenotypic subsets, termed classical, intermediate and nonclassical, have also been demonstrated to differ in regard to their functional properties and disease associations when studied in vitro and in vivo. Nonetheless, for the intermediate monocyte subset in particular, functional experiments have yielded conflicting results and some studies point to further levels of heterogeneity. Developments in genetic sequencing technology have provided opportunities to more comprehensively explore the phenotypic and functional differences among conventionally-recognized immune cell subtypes as well as the potential to identify novel subpopulations. In this review, we summarize the transcriptomic evidence in support of the existence of three separate monocyte subsets. We also critically evaluate the insights into subset functional distinctions that have been garnered from monocyte gene expression analysis and the potential utility of such studies to unravel subset-specific functional changes which arise in disease states.
BROAD

Keyword search in databases has received a lot of attention in the database community as it is an effective approach for querying a database without knowing its underlying schema. However, keyword search queries often return too many results. One standard solution is to rank results such that the "best" results appear first. Still, this approach can suffer from redundancy problem where many high ranking results are in fact coming from the same part of the database and results in other parts of the database are missed completely. In this demo, we propose the BROAD system which allows users to perform diverse, hierarchical browsing on keyword search results. Our system partitions the answer trees in the keyword search results by selecting k diverse representatives from the trees, separating the answer trees into k groups based on their similarity to the representatives and then recursively applying the partitioning for each group. By constructing summarized result for the answer trees in each of the k groups, we provide a way for users to quickly locate the results that they desire.