Miracle-dz/UniFAR-FTUs huggingface dataset:
Serotype and Genotype (Multilocus Sequence Type) of Streptococcus suis Isolates from the United States Serve as Predictors of Pathotype

Streptococcus suis is a significant cause of mortality in piglets and growing pigs worldwide. The species contains pathogenic and commensal strains, with pathogenic strains causing meningitis, arthritis, endocarditis, polyserositis, and septicemia. Serotyping and multilocus sequence typing (MLST) are primary methods to differentiate strains, but the information is limited for strains found in the United States. ABSTRACT Streptococcus suis is a significant cause of mortality in piglets and growing pigs worldwide. The species contains pathogenic and commensal strains, with pathogenic strains causing meningitis, arthritis, endocarditis, polyserositis, and septicemia. Serotyping and multilocus sequence typing (MLST) are primary methods to differentiate strains, but the information is limited for strains found in the United States. The objective of this study was to characterize the diversity of 208 S. suis isolates collected between 2014 and 2017 across North America (mainly the United States) by serotyping and MLST and to investigate associations between subtype and pathotype classifications (pathogenic, possibly opportunistic, and commensal), based on clinical information and site of isolation. Twenty serotypes were identified, and the predominant serotypes were 1/2 and 7. Fifty-eight sequence types (STs) were identified, and the predominant ST was ST28. Associations among serotypes, STs, and pathotypes were investigated using odds ratio and clustering analyses. Evaluation of serotype and ST with pathotype identified a majority of isolates of serotypes 1, 1/2, 2, 7, 14, and 23 and ST1, ST13, ST25, ST28, ST29, ST94, ST108, ST117, ST225, ST373, ST961, and ST977 as associated with the pathogenic pathotype. Serotypes 21 and 31, ST750, and ST821 were associated with the commensal pathotype, which is composed of isolates from farms with no known history of S. suis-associated disease. Our study demonstrates the use of serotyping and MLST to differentiate pathogenic from commensal isolates and establish links between pathotype and subtype, thus increasing the knowledge about S. suis strains circulating in the United States.
The solid solution Co4.32Mn2.68(HPO4)4(PO4)2

Single crystals of the solid solution cobalt manganese tetra­kis(hydrogen phosphate) bis­(phosphate), Co4.32Mn2. 68(HPO4)4(PO4)2, have been prepared under hydro­thermal conditions. The compound crystallizes in the Fe7(PO4)6 structure type and is isotypic with the Co and Mn end members of the solid solution Co7−xMnx(HPO4)4(PO4)2. The structure is based on a three-dimensional framework of distorted edge-sharing MO6 and MO5 polyhedra (M = Co or Mn) which are inter­linked by corner-sharing with PO4 tetra­hedra. The four metal positions are statistically occupied by Co and Mn. Strong hydrogen bonds between the OH groups of the HPO4 tetra­hedra and the O atoms help to consolidate the crystal structure. Except for one metal site located on a position with \overline{1} symmetry, all atoms are on general positions.
Approaches to CNS Drug Delivery with a Focus on Transporter-Mediated Transcytosis

Drug delivery to the central nervous system (CNS) conferred by brain barriers is a major obstacle in the development of effective neurotherapeutics. In this review, a classification of current approaches of clinical or investigational importance for the delivery of therapeutics to the CNS is presented. This classification includes the use of formulations administered systemically that can elicit transcytosis-mediated transport by interacting with transporters expressed by transvascular endothelial cells. Neurotherapeutics can also be delivered to the CNS by means of surgical intervention using specialized catheters or implantable reservoirs. Strategies for delivering drugs to the CNS have evolved tremendously during the last two decades, yet, some factors can affect the quality of data generated in preclinical investigation, which can hamper the extension of the applications of these strategies into clinically useful tools. Here, we disclose some of these factors and propose some solutions that may prove valuable at bridging the gap between preclinical findings and clinical trials.
artMAP: A user‐friendly tool for mapping ethyl methanesulfonate‐induced mutations in Arabidopsis

Abstract Mapping‐by‐sequencing is a rapid method for identifying both natural as well as induced variations in the genome. However, it requires extensive bioinformatics expertise along with the computational infrastructure to analyze the sequencing data and these requirements have limited its widespread adoption. In the current study, we develop an easy to use tool, artMAP, to discover ethyl methanesulfonate (EMS) induced mutations in the Arabidopsis genome. The artMAP pipeline consists of well‐established tools including TrimGalore, BWA, BEDTools, SAMtools, and SnpEff which were integrated in a Docker container. artMAP provides a graphical user interface and can be run on a regular laptop and desktop, thereby limiting the bioinformatics expertise required. artMAP can process input sequencing files generated from single or paired‐end sequencing. The results of the analysis are presented in interactive graphs which display the annotation details of each mutation. Due to its ease of use, artMAP makes the identification of EMS‐induced mutations in Arabidopsis possible with only a few mouse click. The source code of artMAP is available on Github (https://github.com/RihaLab/artMAP).
Age-Associated mRNA and miRNA Expression Changes in the Blood-Brain Barrier

Functional and structural age-associated changes in the blood-brain barrier (BBB) may affect the neurovascular unit and contribute to the onset and progression of age-associated neurodegenerative pathologies, including Alzheimer’s disease. The current study interrogated the RNA profile of the BBB in an ageing human autopsy brain cohort and an ageing mouse model using combined laser capture microdissection and expression profiling. Only 12 overlapping genes were altered in the same direction in the BBB of both ageing human and mouse cohorts. These included genes with roles in regulating vascular tone, tight junction protein expression and cell adhesion, all processes prone to dysregulation with advancing age. Integrated mRNA and miRNA network and pathway enrichment analysis of the datasets identified 15 overlapping miRNAs that showed altered expression. In addition to targeting genes related to DNA binding and/or autophagy, many of the miRNAs identified play a role in age-relevant processes, including BBB dysfunction and regulating the neuroinflammatory response. Future studies have the potential to develop targeted therapeutic approaches against these candidates to prevent vascular dysfunction in the ageing brain.
End-of-Life Activities Among Community-Dwelling Older Adults in Japan

This study explored end-of-life (EOL) activities among community-dwelling Japanese older adults and the relationships between EOL activities and related variables. One hundred twenty-three older adults (38 men, 87 women; mean age = 72.54 years) who attended EOL seminars were surveyed regarding EOL activities, attitudes toward death, and mental health status. Cluster analysis of EOL activities revealed three clusters: Planning (e.g., had planned own funeral arrangements), Preference (e.g., had talked about EOL care with their family), and Preparation (e.g., already written their will). The number of EOL-related events attended was positively correlated with Preparation, while fear of death was negatively associated with Preference. Older adults with bereavement experience had higher Planning and Preparation scores than those without such experience.
A Radiomic-feature based Nipple Detection Algorithm on Digital Mammography.

PURPOSE In the diagnosis and detection of breast lesions, the nipple is an important anatomical landmark which can be used for registration on multi-view mammograms. In this study, we propose a new detection algorithm for nipples on digital mammography (DM) by applying pixel classification based on geometric and radiomic features extracted from breast boundary regions. METHODS The imaging characteristics of nipples are closely related to the visibility on mammograms. To locate the nipple on mammogram, a searching area is first determined based on the breast boundary and chest wall orientation. Two different approaches are developed for obvious and subtle nipples, respectively. For obvious nipples, top hat transformation is employed to detect the nipple region, whose geometric center is regarded as the nipple position. For subtle nipples, the curved searching area near the breast boundary is mapped onto a Cartesian plane through a revised rubber band straightening transformation. On the straightened searching area, the geometric and radiomic features are calculated along the normal direction of the breast boundary, and a random forest classifier is trained for subtle nipple localization. RESULTS 721 DMs were collected for the evaluation of the proposed algorithm. The locations of nipples are manually identified by an experienced radiologist as the reference standard. The average Euclidean distance between the computed nipple position and the reference standard was 2.69 mm (obvious) and 7.81 mm (subtle), respectively. A total of 97.61% of the obvious nipples (613/628) and 88.17% of the subtle nipples (82/93) were detected within a 10 mm radius centered from the reference standard. CONCLUSIONS The evaluation results show that the proposed method is effective for nipple detection on DM, especially for subtle nipple detection. This article is protected by copyright. All rights reserved.
Chemotherapeutic Drugs Inhibiting Topoisomerase 1 Activity Impede Cytokine-Induced and NF-κB p65-Regulated Gene Expression

Inhibitors of DNA topoisomerase I (TOP1), an enzyme relieving torsional stress of DNA by generating transient single-strand breaks, are clinically used to treat ovarian, small cell lung and cervical cancer. As torsional stress is generated during transcription by progression of RNA polymerase II through the transcribed gene, we tested the effects of camptothecin and of the approved TOP1 inhibitors Topotecan and SN-38 on TNFα-induced gene expression. RNA-seq experiments showed that inhibition of TOP1 but not of TOP2 activity suppressed the vast majority of TNFα-triggered genes. The TOP1 effects were fully reversible and preferentially affected long genes. TNFα stimulation led to inducible recruitment of TOP1 to the gene body of IL8, where its inhibition by camptothecin reduced transcription elongation and also led to altered histone H3 acetylation. Together, these data show that TOP1 inhibitors potently suppress expression of proinflammatory cytokines, a feature that may contribute to the increased infection risk occurring in tumor patients treated with these agents. On the other hand, TOP1 inhibitors could also be considered as a therapeutic option in order to interfere with exaggerated cytokine expression seen in several inflammatory diseases.
Advances in treating bronchopulmonary dysplasia

ABSTRACT Introduction: Bronchopulmonary dysplasia (BPD) is a common long-term adverse complication of very premature delivery. Affected infants can suffer chronic respiratory morbidities including lung function abnormalities and reduced exercise capacity even as young adults. Many studies have investigated possible preventative strategies; however, it is equally important to identify optimum management strategies for infants with evolving or established BPD. Areas covered: Respiratory support modalities and established and novel pharmacological treatments. Expert opinion: Respiratory support modalities including proportional assist ventilation and neurally adjusted ventilatory assist are associated with short term improvements in oxygenation indices. Such modalities need to be investigated in appropriate RCTs. Many pharmacological treatments are routinely used with a limited evidence base, for example diuretics. Stem cell therapies in small case series are associated with promising results. More research is required before it is possible to determine if such therapies should be investigated in large RCTs with long-term outcomes.
Repurposing of FDA-approved drugs to target MurB and MurE enzymes in Mycobacterium tuberculosis

Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) is one amongst the top 10 causes of death worldwide. The growing rise in antibiotic resistance compounded with slow and expensive drug discovery has further aggravated the situation. ‘Drug repurposing’ is a promising approach where known drugs are examined for a new indication. In the present study, we have attempted to identify drugs that could target MurB and MurE enzymes involved in the muramic acid synthesis pathway (Mur Pathway) in Mtb. FDA-approved drugs from two repositories i.e. Drug Bank (1932 drugs) and e-LEA3D (1852 drugs) were screened against these proteins. Several criteria were applied to study the protein-drug interactions and the consensus drugs were further studied by molecular dynamics (MD) simulation. Our study found Sulfadoxine (–7.3 kcal/mol) and Pyrimethamine (–7.8 kcal/mol) to show stable interaction with MurB while Lifitegrast (–10.5 kcal/mol) and Sildenafil (–9.1 kcal/mol) showed most reliable interaction with MurE. Furthermore, binding free energy (ΔGbind), RMSD and RMSF data and the number of hydrogen bonds corroborated the stability of interactions and hence these drugs for repurposing should be explored further. Communicated by Ramaswamy H. Sarma
Adaptive Robust Attitude Controller Design for a Quadrotor Platform

This paper includes attitude controller design ideas for a quadrotor platform which can be regarded as an exceptionally agile flying robot with highly non-linear and unstable features in flight dynamics. The quadrotor poses severe problems in characterizing the dynamics especially when performing high-speed manoeuvres. These facts cause the quadrotor not to lose its popularity as a compelling tool among avid researchers who endeavour to realize various controller ideas. The procedure in this paper is initiated with the construction of the system model and the verification of this phase relying on the characteristics of the test bed. With the aid of sensors on the off-the-shelf platform, the controllers are designed to enact tracking of the reference commands that contain the desired trajectories and attitudes. The controller methods highlighted in this research are non-linear dynamic inversion, model reference adaptive control and integral back-stepping technique. The trade-off between performance and robustness is investigated as well. The responses of the system to the impacts of the existence of uncertain parameters, unmatched uncertainties or disturbances are exceptional means to judge how robust the controller is. An overview of the cases with parametric uncertainty and the existence of noise, therefore, finds its place as a section within this work. This sketch grades the controller options while putting forward the advantage of adaptation. Besides, by employing correction approaches, the advancement of the adaptive controller in terms of robustness is examined where dead zone implementation, e-, and σ-modifications are exploited. The motivation behind this research is to produce persistent state controllers to lay the first stone for more complex algorithm structures such as autonomous flight phases, obstacle avoidance and way-point targeting. The future work of this study is the justification of the reliability of the methodologies used and the results attained from the simulations through experiments.
Fishing for vaccines against Vibrio cholerae using in silico pan-proteomic reverse vaccinology approach

Background Cholera, an acute enteric infection, is a serious health challenge in both the underdeveloped and the developing world. It is caused by Vibrio cholerae after ingestion of fecal contaminated food or water. Cholera outbreaks have recently been observed in regions facing natural calamities (i.e., earthquake in Haiti 2010) or war (i.e., ongoing civil war in Yemen 2016) where healthcare and sanitary setups have been disrupted as a consequence. Whole-cell oral cholera vaccines (OCVs) have been in market but their regimen efficacy has been questioned. A reverse vaccinology (RV) approach has been applied as a successful anti-microbial measure for many infectious diseases. Methodology With the aim of finding new protective antigens for vaccine development, the V. cholerae O1 (biovar eltr str. N16961) proteome was computationally screened in a sequential prioritization approach that focused on determining the antigenicity of potential vaccine candidates. Essential, accessible, virulent and immunogenic proteins were selected as potential candidates. The predicted epitopes were filtered for effective binding with MHC alleles and epitopes binding with greater MHC alleles were selected. Results In this study, we report lipoprotein NlpD, outer membrane protein OmpU, accessory colonization factor AcfA, Porin, putative and outer membrane protein OmpW as potential candidates qualifying all the set criteria. These predicted epitopes can offer a potential for development of a reliable peptide or subunit vaccine for V. cholerae.
Semantic Mapping using Extreme Learning Machine

The tremendous growth of technologies such as the World Wide Web, Content Management Systems (CMS), and the emerging Semantic Web has initiated the problem of Ontology Mapping. Ontology specifies a conceptualization of a domain in terms of concepts, attributes, and relations. It involves concepts and relationships, which exist between the concepts. Ontology Mapping is done to find the relevance between the heterogeneous Ontological representations. Ontology matching was based on manual mapping or semistructured mapping process. To automate the mapping process without human intervention, machine learning algorithms are used. The proposed work focuses on Extreme Learning Machine (ELM) algorithm to automate the Ontology Mapping process. General Terms Machine Learning algorithm, Natural Language Processing
Global ecosystem overfishing: Clear delineation within real limits to production

Newly derived thresholds show that about half the world’s marine ecosystems are experiencing “ecosystem” overfishing. The well-documented value of marine fisheries is threatened by overfishing. Management typically focuses on target populations but lacks effective tools to document or restrain overexploitation of marine ecosystems. Here, we present three indices and accompanying thresholds to detect and delineate ecosystem overfishing (EOF): the Fogarty, Friedland, and Ryther indices. These are based on widely available and readily interpreted catch and satellite data that link fisheries landings to primary production using known limits of trophic transfer efficiency. We propose theoretically and empirically based thresholds for each of those indices; with these criteria, several ecosystems are fished sustainably, but nearly 40 to 50% of tropical and temperate ecosystems exceed even extreme thresholds. Applying these criteria to global fisheries data results in strong evidence for two specific instances of EOF, increases in both pressure on tropical fish and a climate-mediated polar shift. Here, we show that these two patterns represent evidence for global EOF.
Motion Velocity, Acceleration and Energy Expenditure Estimation Using Micro Flow Sensor

Motion velocity, acceleration, and energy expenditure estimations are important in quantitative assessments for physical recovery and exercise-based interventions for post-stroke patients with partial losses of neurological functions. This paper proposes a novel wearable motion estimation device using a micro flow sensor, which realizes motion velocity, acceleration detection, and energy expenditure estimation for human limb motion. A homemade micro thermal flow sensor is used to detect motion velocity. Jerk–Kalman based algorithm is proposed to extract motion acceleration from the flow sensor outputs. Motion velocity and acceleration are used to estimate energy expenditure of limb motion. Calibration experiments and application cases are conducted to validate the effectiveness of the methodology. The micro flow sensor based motion estimation method is free of accumulated error, robust for dynamic motion measurement, and provides a promising auxiliary approach for evaluating energy expenditures of human limbs in rehabilitation training.
Toward a Way to Benchmark Multilevel Inverter Topologies Based on Level to Components Ratio

This paper introduces a generalized platform for the design selection of multilevel inverters (MLIs) topologies for any industry, especially in low- and medium-power applications. This platform is novel as it combines the component count and stress in any MLI in a normalized unique score. Each MLI topology is designed to match specific criteria to meet a specific application, which introduces diversified sets of merits and demerits in each case. Therefore, choosing a suitable MLI topology for the specific application is rather a difficult, time-consuming, and complex process. Moreover, the comparison can only be conducted between MLI topologies that fall under the same category. This paper introduces a comprehensive study to propose a new benchmark (BM) which can be used to compare MLI topologies regardless of their constructions or oriented applications. Each MLI topology gets a BM score based on comparative factors that evaluate its components quantitatively and qualitatively. Thus, comparing different types of MLI topologies is a simple process of comparing their calculated BM scores leading to better well-informed choice. First, the proposed BM-derived forms are discussed. Then, the proposed methodology is illustrated by applying to various types of MLI topologies including conventional and recently introduced ones.
UHF RFID Indoor Positioning System With Phase Interference Model Based on Double Tag Array

A UHF radio-frequency identification (RFID) indoor positioning system based on phase difference is presented in this paper. An additional auxiliary tag and the target tag make up a double tag array to eliminate the phase ambiguity. To quantify the phase offset caused by the interference between tags, a mathematical model is built. Based on the double tag array and the interference model, a hyperbolic positioning algorithm, combining the genetic algorithm, is implemented to improve the positioning accuracy. Compared with other RFID positioning systems, the proposed system achieves a better positioning accuracy of 0.2217 m.
Solution for the Continuous-Time Infinite-Horizon Linear Quadratic Regulator Subject to Scalar State Constraints

This letter provides a solution for the continuous-time linear quadratic regulator (LQR) subject to a scalar state constraint. Using a dichotomy transformation, novel properties for the finite-horizon LQR are derived; the unknown boundary conditions are explicitly expressed as a function of the horizon length, the initial state, and the final state or cost of the final state. Practical relevance of these novel properties are demonstrated with an algorithm to compute the continuous-time LQR subject to a scalar state constraint. The proposed algorithm uses the analytical conditions for optimality, without a priori discretization, to find only those sampling time instances that mark the start and end of a constrained interval. Each subinterval consists of a finite-horizon LQR, hence, a solution can be efficiently computed and the computational complexity does not grow with the horizon length. In fact, an infinite horizon can be handled. The algorithm is demonstrated with a simulation example.