Miracle-dz/UniFAR-FTUs huggingface dataset:
IN VITRO AND IN VIVO IMPACT OF SOME PSEUDOMONAS SPP. ON GROWTH AND YIELD OF CULTIVATED MUSHROOM (AGARICUS BISPORUS)

The aim of this study was to determine the in vitro and in vivo actions of isolated Pseudomonas spp. from casing soil on the hyphal growth and yield of Agaricus bisporus. It was found that only Pseudomonas putida increased the hyphae extension rate and also mushroom yield up to 26.6% when compared to the non-inoculated control. Pseudomonas tolaasii markedly inhibited growth, lysis of A. bisporus mycelium, and there were also significant reduction in mushroom yield (-72.5%). Mycelial growth was also inhibited by Pseudomonas aeruginosa, but the inhibition only occurred when the fungus hypha contact with the bacterial colony, this inhibition reduced the mushroom yield by 70.5%. Furthermore, Pseudomonas fluorescens had no statistically positive effects on mushroom mycelium growth and yield compared to control treatments. Until now, most research and applications of Pseudomonas aeruginosa have been conducted with animal disease. Findings of this research showed that this bacterium inhibits the mushroom hyphal growth and significantly reduces the harvested mushroom.
A Highly Pathogenic H5N1 Influenza A Virus Isolated from a Flamingo on the Caspian Sea Shore

In 2015, in the Kazakh part of the northern Caspian Sea region, during the monitoring of wild birds for avian influenza viruses, a highly pathogenic A/flamingo/Mangistau/6570/2015(H5N1) influenza virus was isolated from a dead flamingo. This study aimed to obtain the complete genome sequence of the isolate. ABSTRACT In 2015, in the Kazakh part of the northern Caspian Sea region, during the monitoring of wild birds for avian influenza viruses, a highly pathogenic A/flamingo/Mangistau/6570/2015(H5N1) influenza virus was isolated from a dead flamingo. This study aimed to obtain the complete genome sequence of the isolate.
Shotgun Metagenomic Survey of Maize Soil Rhizobiome

The plant soil rhizobiome induces critical functions in the plant proximal environment. Linkages between soil microbiota and primary functional attributes are underexplored. Here, we present the metagenomes of maize soil rhizosphere organisms with functional diversity associated with farms at two different municipalities in North West and Gauteng provinces of South Africa. We describe a plenteous and diverse microbial community. ABSTRACT The plant soil rhizobiome induces critical functions in the plant proximal environment. Linkages between soil microbiota and primary functional attributes are underexplored. Here, we present the metagenomes of maize soil rhizosphere organisms with functional diversity associated with farms at two different municipalities in North West and Gauteng provinces of South Africa. We describe a plenteous and diverse microbial community.
Genome Sequences of Two Microcystis aeruginosa (Chroococcales, Cyanobacteria) Strains from Florida (United States) with Disparate Toxigenic Potentials

Here, we report the draft genomes of two Microcystis aeruginosa strains, i.e., M. aeruginosa BLCC-F108, which was isolated from a toxic bloom in eutrophic waters in Lake Okeechobee (Florida, USA), and M. aeruginosa BLCC-F158, which was isolated from mesotrophic waters in Lake Tohopekaliga (Florida, USA). Genomic analyses show disparate toxin potentials for these two strains. ABSTRACT Here, we report the draft genomes of two Microcystis aeruginosa strains, i.e., M. aeruginosa BLCC-F108, which was isolated from a toxic bloom in eutrophic waters in Lake Okeechobee (Florida, USA), and M. aeruginosa BLCC-F158, which was isolated from mesotrophic waters in Lake Tohopekaliga (Florida, USA). Genomic analyses show disparate toxin potentials for these two strains.
Detecting Illicit Entities in Bitcoin using Supervised Learning of Ensemble Decision Trees

Since its inception in 2009, Bitcoin has been mired in controversies for providing a haven for illegal activities. Several types of illicit users hide behind the blanket of anonymity. Uncovering these entities is key for forensic investigations. Current methods utilize machine learning for identifying these illicit entities. However, the existing approaches only focus on a limited category of illicit users. The current paper proposes to address the issue by implementing an ensemble of decision trees for supervised learning. More parameters allow the ensemble model to learn discriminating features that can categorize multiple groups of illicit users from licit users. To evaluate the model, a dataset of 2059 real-life entities on Bitcoin was extracted from the Blockchain. Nine features were engineered to train the model for segregating 28 different licit-illicit categories of users. The proposed model provided a reliable tool for forensic study. Empirical evaluation of the proposed model vis-a-vis three existing benchmark models was performed to highlight its efficacy. Experiments showed that the specificity and sensitivity of the proposed model were comparable to other models.
HTM Based Anomaly Detecting Model for Traffic Congestion

Traffic congestion has become one of the most critical issues that have to be addressed in road transport. There were many attempts to address this problem. However, there is a demand for innovative solutions developments, as the roads infrastructure are changing rapidly, and more intelligent solutions are desired. Smart transport is a growing area that offers potential solutions to make roads less congested and better to use. Many Machine Learning (ML) based applications were proposed to control traffic congestion on the roads. Even though the foreseeing benefits of machine learning based solutions, the number of publications, in this research area, is still limited and needs to be thoroughly investigated, especially, bio-inspired approaches such as the Hierarchical Temporal Memory (HTM). Cortical Learning Algorithms (CLAs) are the implementation of the HTM's computational models for the pyramidal neurons in the neocortex in the mammalian brain, which are, based on neuroscience's findings. This paper applies HTM cortical learning algorithm anomaly detection to detect traffic congestion. The proposed work shows an improvement in detecting traffic congestion by 7.40% compared to state-of-the-art anomaly detection techniques with an average score of 98.83% F-measure.
A Machine Learning Approach for Predicting Antibody Properties

This paper used an amino acid location-based sequence encoding as a feature extraction techniques to identify single chains antibody molecules that bind to B-lymphocyte stimulator (BLyS) antigen. The data were manually derived from the European patent (EP2275449B1) text. The dataset was cleaned and made suitable for the machine learning models. The accuracy, precision and recall achieved across individual descriptors (Membrane and Soluble) for Logistic regression, KNN, KSVM, and Random Forest Tree was above 80%. However, it was much lower for the Naïve Bayes except for the precision score. The promising accuracy value achieved from such a minimal dataset has significant implications for the drug discovery process - this includes considerable savings in time and resources.
Understanding and Improving Word Embeddings through a Neuroscientific Lens

Despite the success of models making use of word embeddings on many natural language tasks, these models often perform significantly worse than humans on several natural language understanding tasks. This difference in performance motivates us to ask: (1) if existing word vector representations have any basis in the brain’s representational structure for individual words, and (2) whether features from the brain can be used to improve word embedding model performance, defined as their correlation with human semantic judgements. To answer the first question, we compare the representational spaces of existing word embedding models with that of brain imaging data through representational similarity analysis. We answer the second question by using regression-based learning to constrain word vectors to the features of the brain imaging data, thereby determining if these modified word vectors exhibit increased performance over their unmodified counterparts. To collect semantic judgements as a measure of performance, we employed a novel multi-arrangement method. Our results show that there is variance in the representational space of the brain imaging data that remains uncaptured by word embedding models, and that brain imaging data can be used to increase their coherence with human performance.
MetaFusion: A high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates

Motivation Gene fusions are often associated with cancer, yet current fusion detection tools vary in their calling approaches, making selecting the right tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function. Results MetaFusion is a flexible meta-calling tool that amalgamates the outputs from any number of fusion callers. Results from individual callers are converted into Common Fusion Format, a new file type that standardizes outputs from callers. Calls are then annotated, merged using graph clustering, filtered and ranked to provide a final output of high confidence candidates. MetaFusion consistently outperformed individual callers with respect to recall and precision on real and simulated datasets, achieving up to 100% precision. Thus, an ensemble calling approach is imperative for high confidence results. MetaFusion also labels fusions found in databases using the FusionAnnotator package, and is provided with a benchmarking toolkit to calibrate new callers. Availability MetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion Contact arun.ramani@sickkids.ca
Trends in scientific research on Environmental Education: A scientometric review

Given the need to understand the current approaches to Environmental Education (EE) in the world, we answer the following questions: (i) Have the studies directed to EE received attention from the scientific community? (ii) what are the trends in EE publications? In the past years, there has been an increase in the number of publications on EE. Brazil stood out in the number of publications, reflecting the concern of Brazilian researchers to promote sustainability and biodiversity maintenance. As for the approaches, the studies are broad, ranging from the influence of policies on environmental protection to the importance of reflection at a global level, proposing international agreements. However, regarding the EE application, given the multiple existing currents, it is worth emphasizing the importance of the teaching-learning process to take place critically so that there is no favoring of the contents promoted and supported by a hegemonic class.
A plausible mechanism for Drosophila larva intermittent behavior

The behavior of many living organisms is not continuous. Rather, activity emerges in bouts that are separated by epochs of rest, a phenomenon known as intermittent behavior. Although intermittency is ubiquitous across phyla, empirical studies are scarce and the underlying neural mechanisms remain unknown. Here we reproduce empirical evidence of intermittency during Drosophila larva free exploration. Our findings are in line with previously reported power-law distributed rest-bout durations while we report log-normal distributed activity-bout durations. We show that a stochastic network model can transition between power-law and non-power-law distributed states and we suggest a plausible neural mechanism for the alternating rest and activity in the larva. Finally, we discuss possible implementations in behavioral simulations extending spatial Levy-walk or coupled-oscillator models with temporal intermittency.
Plant self-thinning and leaf area dynamics in experimental and natural monocultures

The gradient of the relationship between mean plant weight and density for many species in self-thinning monocultures is known to be -3/2. There is evidence in the literature that this gradient may decline as light intensity falls. A recent controversy has centred upon whether or not the -3/2 gradient can be restored at low light intensities by graphing mean leaf area per plant against density. An experiment was conducted, using Trifolium pratense L. grown at three light intensities, to establish the gradient of this relationship. Whereas the mean weight vs. density gradient remained near -3/2 at all light intensities, the mean leaf area vs. density gradient approximated to -1.0, indicating that leaf area index stays constant as thinning proceeds. Thus, the results do not support the proposal that alterations in leaf area ratio act to restore the -3/2 gradient to the mean leaf area vs. density graph at low light intensities. Support for these findings is discussed, including data from field monocultures of Mercurialis perennis L.
Constructing A Learning Style Model in an Adaptive Learning System

Most of the adaptive learning systems adopt the classical learning style theory, without considering the characteristics of online learning. Based on learning theories, the study analyses psychological activities in e-learning and the requirements of knowledge characteristics for students' learning activities, systematically determine learning style's elements of e-learning and design a new learning style model in an adaptive learning system. Furthermore, we design a scale which reliability and validity are measured by a reasonable experiment.
CD8+ T cell priming in oral mucosa-draining lymph nodes supports systemic immunity

The gastrointestinal (GI) tract constitutes an essential barrier against ingested pathogens. While immune reactions are well-studied in the lower GI tract, it remains unclear how adaptive immune responses are initiated during microbial challenge of the oral mucosa, the primary site of pathogen encounter in the upper GI tract. Here, we identify mandibular lymph nodes (mandLN) as sentinel lymphoid organs that collect orally administered Listeria monocytogenes (Lm), leading to local CD8+ T cell activation. In contrast to CD8+ T effector cells (TEFF) generated in mesenteric lymph nodes, mandLN CD8+ TEFF lacked a gut-seeking phenotype but contributed to systemic host protection. Accordingly, mandLN stromal and dendritic cells expressed low levels of enzymes required for gut homing imprinting. Our findings extend the concept of regional specialization of immune responses along the length of the GI tract, with mandLN acting as oral lymph-draining counterparts of intestinal lymph-draining LN of the lower GI tract. Summary Listeria monocytogenes ingestion leads to priming of cytotoxic T cells in oral mucosa draining mandibular lymph nodes, which contribute to systemic host protection.
Is there a need for preoperative α-blocker in patients missed preoperative diagnosis of extra-adrenal retroperitoneal paraganglioma undergoing paraganglioma resection? A retrospective study of 167 cases at a single center

Background Preoperative α-adrenergic blockade is believed to decrease perioperative risks and mortality in adrenal pheochromocytoma surgeries. The aim of this study is to evaluate the effects of the preoperative α-adrenergic blockade on patients’ outcomes in extra-adrenal retroperitoneal paraganglioma surgeries. Methods We searched our clinical database for the diagnosis extra-adrenal retroperitoneal paraganglioma by postoperative histopathology in the General Hospital of People’s Liberation Army from 2000 till 2017. And we recorded preoperative status of patients, preoperative medication preparation, intraoperative and postoperative cardiovascular events, intake and output, length of stay in ICU, length of hospital stay, and short time outcomes. Results The intraoperative morbidity of heart rate elevation and highest heart rate were higher in patients undergoing tumor manipulation with preoperative α-adrenergic blockade than those without (P<0.05), while there were no significant differences in intraoperative morbidity of blood pressure elevation and SAP decreased following tumorectomy in these two groups (P>0.05). There were no significant differences in postoperative complications and outcomes (P>0.05). Conclusion Under the current medical techniques, either with or without preoperative medicine, resection of extra-adrenal retroperitoneal paraganglioma could be carried out successfully.
Feasibility of Prehabilitation Prior to Breast Cancer Surgery: A Mixed-Methods Study

Background Breast cancer surgery results in numerous acute and long-term adverse outcomes; the degree to which these can be mitigated or prevented through prehabilitation is unknown. Methods We conducted a longitudinal, single-arm, mixed-methods study to examine the feasibility of prehabilitation in 22 women undergoing breast cancer surgery. All participants received an individualized exercise prescription including upper quadrant-specific resistance and mobility training and aerobic exercise for the duration of their surgical wait time. Feasibility was assessed by recruitment, adherence, attrition, and intervention-related adverse event rates. An exploratory investigation of intervention efficacy was conducted via a 6-min walk test, upper-quadrant strength and range of motion, volumetric chances associated with lymphedema, and participant-reported quality of life, fatigue, pain, and disability. Outcome assessments were conducted at baseline, prior to surgery, and at six and 12 weeks after surgery. Semi-structured interviews with a subset of participants (n = 5) and health-care providers (H; n = 2) were conducted to provide further insights about intervention feasibility. Qualitative data were analyzed using a hybrid inductive and deductive thematic analysis approach. Results Recruitment and attrition rates were 62 and 36%, respectively. Average prehabilitation duration was 31 days (range = 7–69 days). Seventy six percent of participants complied with at least 70% of their prehabilitation prescription. There was a clinically significant increase in the 6-min walk distance from baseline to the preoperative assessment (57 m, 95% CI = −7.52, 121.7). The interviews revealed that the intervention was favorably received by participants and HCPs and included suggestions that prehabilitation (i) should be offered to all surgical candidates, (ii) is an avenue to regain control in the preoperative period, (iii) is a facilitator of postoperative recovery, and (iv) is an opportunity to provide education regarding postoperative rehabilitation protocols. A preference for multimodal prehabilitation (including dietetic and psychological counseling) was also highlighted. Conclusion Our findings suggest that surgical prehabilitation in women with breast cancer is feasible. Data are hampered by study sample size and lack of a control group. Thus, randomized controlled trials to examine prehabilitation efficacy in people with breast cancer, especially interventions employing a multimodal strategy, are warranted.
Calsyntenin 3β Is Dynamically Regulated by Temperature in Murine Brown Adipose and Marks Human Multilocular Fat

Activation of thermogenic adipose tissue is linked to improved metabolic outcomes in mice and humans. Dissipation of energy as heat during thermogenesis relies on sufficient innervation of fat by sympathetic nerve fibers, a process recently proposed to be regulated by the adipose-specific calsyntenin3β (Clstn3β)-S100b axis. Here we aimed 1) to assess enrichment patterns of CLSTN3β, S100b as well as the previously annotated neuronal CLSTN3α in perirenal brown and subcutaneous white human fat specimens, and 2) to investigate if the novel Clstn3β is dynamically regulated by changes in environmental temperatures and nutritional stress in thermogenic adipose tissues in mice. We provide evidence for CLSTN3β enrichment in multilocular perirenal fat located anatomically in the proximity to both the adrenal gland and sympathetic nerve bundles innervating the kidney in humans. Moreover, transcript levels of CLSTN3β, but not S100b or CLSTN3α, positively correlate with uncoupling protein 1 (UCP1) expression in human adipose tissue. Our results further show that Clsnt3β is preferentially expressed in brown adipocytes and is highly responsive to changes in environmental temperature and obesity state in mice. Collectively, this brief communication highlights CLSTN3β as a hallmark of thermogenic adipose depots in mice and humans.
Immunocytochemical Localization of the Kinetochore Protein Nuf2p on the Gametophyte Chromosomes of a Cultivar of Saccharina (Phaeophyta)

Nuclear filament-containing protein 2 (Nuf2p), a centromere-associated protein, is an indispensable component of Ndc80 complex, which is important for stable microtubule–kinetochore attachment, chromosome pairing, and spindle assembly in mitosis. Based upon contig sequences coding for Nuf2p from a pyrosequencing transcriptome of Saccharina japonica, primers were designed for molecular cloning of this kinetochore protein. The open reading frame (ORF) of this gene SjNuf2 was 1,452 bp long, encoding a putative protein consisting of 483 amino acids. Multi-sequence alignment showed SjNuf2p possessed several conserved domains of Nuf2, Spc7, SPT2, and MIT. To illustrate the location of SjNuf2p using immunocytochemistry, its ORF was inserted into a prokaryotic expression vector pET-28a. Then, the recombinant SjNuf2p (rSjNuf2p) was induced to be expressed in Escherichia coli. The rSjNuf2p was verified by Western blotting with the commercial anti-6 × His-tag antibody and then purified using affinity chromatography. The polyclonal antibody of anti-SjNuf2p was raised against the purified rSjNuf2p. Western blotting with this prepared antibody showed the presence of SjNuf2p in the gametophytes of a Saccharina cultivar. SjNuf2p and α/β-tubulin were subsequently co-localized to the paraffin sections of kelp chromosomes with their corresponding antibodies, thus illustrating that SjNuf2p could reside at the kelp centromeres. This study laid a solid foundation for kelp centromere and karyotype analyses.
Recent Advances of Magnetic Nanomaterials in Bone Tissue Repair

The magnetic field has been proven to enhance bone tissue repair by affecting cell metabolic behavior. Magnetic nanoparticles are used as biomaterials due to their unique magnetic properties and good biocompatibility. Through endocytosis, entering the cell makes it easier to affect the physiological function of the cell. Once the magnetic particles are exposed to an external magnetic field, they will be rapidly magnetized. The magnetic particles and the magnetic field work together to enhance the effectiveness of their bone tissue repair treatment. This article reviews the common synthesis methods, the mechanism, and application of magnetic nanomaterials in the field of bone tissue repair.
How to Understand “Herd Immunity” in COVID-19 Pandemic

The COVID-19 pandemic has been a global threat. Through rapid and effective surveillance and control, the newly confirmed patients have been fluctuated at a very low level and imported case explained most of them through March, 2020 to the present, indicating China’s response has achieved a stage victory. By contrast, the epidemic of COVID-19 in other countries out of China is bursting. Different countries are adopting varied response strategy in terms of their public health system to prevent the spread. Herd immunity has been a hot topic since the outbreak of COVID-19 pandemic. Can it be a possible strategy to combat COVID-19? To fully interpret the knowledge regarding the term upon the background of COVID-19-related health crisis, we aim to systematically review the definition, describe the effective measures of acquiring herd immunity, and discuss its feasibility in COVID-19 prevention. Findings from this review would promote and strengthen the international cooperation and joint efforts when confronting with COVID-19.