Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular cloning, characterization, and nucleotide sequence of an extracellular amylase gene from Aeromonas hydrophila

The structural gene for excreted amylase from Aeromonas hydrophila JMP636 has been cloned within a 2.1-kilobase SmaI fragment of DNA. The amylase gene is transcribed from its own promoter in Escherichia coli, producing a gene product of Mr 49,000. The amylase gene product is secreted to the periplasm of E. coli; however, it is not excreted. Nucleotide sequencing revealed an open reading frame of 1,392 base pairs corresponding to a protein of 464 amino acid residues. A potential signal peptide of 21 amino acid residues is present at the NH2 terminal of the predicted protein. Three regions of homology with other procaryotic and eucaryotic alpha-amylases were detected within the predicted amino acid sequence.
Building damage assessment after the earthquake in Haiti using two post-event satellite stereo imagery and DSMs

In this paper, a novel disaster building damage monitoring method is presented. This method combines the multispectral imagery and DSMs from stereo matching to obtain three kinds of changes. The proposed method contains three basic steps. The first step is to segment the panchromatic images to get the smallest possible homogeneous regions. In the second step, based on a rule based classification using change information from Iteratively Reweighted Multivariate Alteration Detection (IR-MAD) and height, the changes are classified to ruined buildings, new buildings, and changes without height change (mainly temporary residential area, etc. tents). In the last step, a region based grey level co-occurrence matrix texture measurement is used to refine the third change class. The method is applied to building change detection after the Haiti earthquake.
Factors affecting a face‐to‐face learning event

Pharmacy professionals have multiple opportunities to attend learning events run by a series of providers. However, there has never been a large‐scale evaluation of events. Currently, formats of learning sessions differ by provider with no optimum model identified. Pharmacy Education South London was formed in April 2014 for the provision of education and training for pharmacy professionals in South London, running sessions multiple times across various locations.
Natural history and genotype‐phenotype correlations in 72 individuals with SATB2‐associated syndrome

SATB2‐associated syndrome (SAS) is an autosomal dominant disorder characterized by significant neurodevelopmental disabilities with limited to absent speech, behavioral issues, and craniofacial anomalies. Previous studies have largely been restricted to case reports and small series without in‐depth phenotypic characterization or genotype‐phenotype correlations. Seventy two study participants were identified as part of the SAS clinical registry. Individuals with a molecularly confirmed diagnosis of SAS were referred after clinical diagnostic testing. In this series we present the most comprehensive phenotypic and genotypic characterization of SAS to date, including prevalence of each clinical feature, neurodevelopmental milestones, and when available, patient management. We confirm that the most distinctive features are neurodevelopmental delay with invariably severely limited speech, abnormalities of the palate (cleft or high‐arched), dental anomalies (crowding, macrodontia, abnormal shape), and behavioral issues with or without bone or brain anomalies. This comprehensive clinical characterization will help clinicians with the diagnosis, counseling and management of SAS and help provide families with anticipatory guidance.
Characterization of Silicon Nitride Thin Films on Glass

The influence of process parameters on amorphous reactively sputtered silicon nitride thin films is reported in this study. The films were prepared with various argon and nitrogen flows, and sputter power in in-line horizontal coater by DC magnetron reactive sputtering from Si (10% Al) target. Refractive index and mechanical properties like residual stress, hardness and elastic modulus were studied. We show that process pressure has an important influence on mechanical properties of the sputtered film. On the other hand, the nitrogen content is the key factor for the optical properties of the films.
CONTRIBUTION OF MODULUS TO THE CONTACT GUIDANCE OF ENDOTHELIAL CELLS ON MICROTEXTURED SILOXANE ELASTOMERS

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science CONTRIBUTION OF MODULUS TO THE CONTACT GUIDANCE OF ENDOTHELIAL CELLS ON MICROTEXTURED SILOXANE ELASTOMERS By Wade Richard Wilkerson December, 2001 Chairman: Dr. Anthony B. Brennan Major Department: Biomedical Engineering Program Contact guidance is a term used to describe a material’s ability to direct the alignment and growth patterns of biological cells or tissue. It has long been understood that the surface a cell grows on impacts its size, shape, and metabolism. Typically, when cells are exposed to mechanical features such as ridges and grooves, the cells align and travel along the length. Surface chemistry plays a significant role in the attachment of cells to a substrate and in their movement on that surface. The objective of this study was to study the effect of modulus as well as surface texture dimensions on vascular endothelial cells (ECs). To examine the effects of contact guidance on silicone elastomers, microtextured substrates were produced with reproducible and well-defined surfaces. Ridges of 10,000 μm length were fabricated at 3 different widths: 5 μm, 10 μm, and 20 μm, separated by 5 μm wide grooves to determine the effect of separation of features on the alignment of porcine vascular endothelial cells (PVECs). Two depths were examined: 5 μm and 1.5 μm.
Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an in silico approach

Alzheimer’s disease (AD) is a multi-factorial disease, which can be simply outlined as an irreversible and progressive neurodegenerative disorder with an unclear root cause. It is a major cause of dementia in old aged people. In the present study, utilizing the structural and biological activity information of ligands for five important and mostly studied vital targets (i.e. cyclin-dependant kinase 5, β-secretase, monoamine oxidase B, glycogen synthase kinase 3β, acetylcholinesterase) that are believed to be effective against AD, we have developed five classification models using linear discriminant analysis (LDA) technique. Considering the importance of data curation, we have given more attention towards the chemical and biological data curation, which is a difficult task especially in case of big data-sets. Thus, to ease the curation process we have designed Konstanz Information Miner (KNIME) workflows, which are made available at http://teqip.jdvu. ac.in/QSAR_Tools/. The developed models were appropriately validated based on the predictions for experiment derived data from test sets, as well as true external set compounds including known multi-target compounds. The domain of applicability for each classification model was checked based on a confidence estimation approach. Further, these validated models were employed for screening of natural compounds collected from the InterBioScreen natural database (https://www.ibscreen.com/natural-compounds). Further, the natural compounds that were categorized as ‘actives’ in at least two classification models out of five developed models were considered as multi-target leads, and these compounds were further screened using the drug-like filter, molecular docking technique and then thoroughly analyzed using molecular dynamics studies. Finally, the most potential multi-target natural compounds against AD are suggested.
NAFLD and Atherosclerosis Are Prevented by a Natural Dietary Supplement Containing Curcumin, Silymarin, Guggul, Chlorogenic Acid and Inulin in Mice Fed a High-Fat Diet

Non-alcoholic fatty liver disease (NAFLD) confers an increased risk of cardiovascular diseases. NAFDL is associated with atherogenic dyslipidemia, inflammation and renin-angiotensin system (RAS) imbalance, which in turn lead to atherosclerotic lesions. In the present study, the impact of a natural dietary supplement (NDS) containing Curcuma longa, silymarin, guggul, chlorogenic acid and inulin on NAFLD and atherosclerosis was evaluated, and the mechanism of action was examined. C57BL/6 mice were fed an HFD for 16 weeks; half of the mice were simultaneously treated with a daily oral administration (os) of the NDS. NAFLD and atherogenic lesions in aorta and carotid artery (histological analysis), hepatic expression of genes involved in the NAFLD (PCR array), hepatic angiotensinogen (AGT) and AT1R mRNA expression (real-time PCR) and plasma angiotensin (ANG)-II levels (ELISA) were evaluated. In the NDS group, steatosis, aortic lesions or carotid artery thickening was not observed. PCR array showed upregulation of some genes involved in lipid metabolism and anti-inflammatory activity (Cpt2, Ifng) and downregulation of some genes involved in pro-inflammatory response and in free fatty acid up-take (Fabp5, Socs3). Hepatic AGT, AT1R mRNA and ANG II plasma levels were significantly lower with respect to the untreated-group. Furthermore, NDS inhibited the dyslipidemia observed in the untreated animals. Altogether, these results suggest that NDS prevents NAFLD and atherogenesis by modulating the expression of different genes involved in NAFLD and avoiding RAS imbalance.
SignFi

We propose SignFi to recognize sign language gestures using WiFi. SignFi uses Channel State Information (CSI) measured by WiFi packets as the input and a Convolutional Neural Network (CNN) as the classification algorithm. Existing WiFi-based sign gesture recognition technologies are tested on no more than 25 gestures that only involve hand and/or finger gestures. SignFi is able to recognize 276 sign gestures, which involve the head, arm, hand, and finger gestures, with high accuracy. SignFi collects CSI measurements to capture wireless signal characteristics of sign gestures. Raw CSI measurements are pre-processed to remove noises and recover CSI changes over sub-carriers and sampling time. Pre-processed CSI measurements are fed to a 9-layer CNN for sign gesture classification. We collect CSI traces and evaluate SignFi in the lab and home environments. There are 8,280 gesture instances, 5,520 from the lab and 2,760 from the home, for 276 sign gestures in total. For 5-fold cross validation using CSI traces of one user, the average recognition accuracy of SignFi is 98.01%, 98.91%, and 94.81% for the lab, home, and lab+home environment, respectively. We also run tests using CSI traces from 5 different users in the lab environment. The average recognition accuracy of SignFi is 86.66% for 7,500 instances of 150 sign gestures performed by 5 different users.
Learning Deep Context-Network Architectures for Image Annotation

Context plays an important role in visual pattern recognition as it provides complementary clues for different learning tasks including image classification and annotation. In the particular scenario of kernel learning, the general recipe of context-based kernel design consists in learning positive semi-definite similarity functions that return high values not only when data share similar content but also similar context. However, in spite of having a positive impact on performance, the use of context in these kernel design methods has not been fully explored; indeed, context has been handcrafted instead of being learned. In this paper, we introduce a novel context-aware kernel design framework based on deep learning. Our method discriminatively learns spatial geometric context as the weights of a deep network (DN). The architecture of this network is fully determined by the solution of an objective function that mixes content, context and regularization, while the parameters of this network determine the most relevant (discriminant) parts of the learned context. We apply this context and kernel learning framework to image classification using the challenging ImageCLEF Photo Annotation benchmark; the latter shows that our deep context learning provides highly effective kernels for image classification as corroborated through extensive experiments.
Cost-effectiveness Analysis for Genotyping before Allopurinol Treatment to Prevent Severe Cutaneous Adverse Drug Reactions

Objective. Patients with an HLA-B*58:01 allele have an increased risk of developing severe cutaneous adverse drug reactions (SCAR) when treated with allopurinol. Although one-off pharmacogenetic testing may prevent life-threatening adverse drug reactions, testing prior to allopurinol initiation incurs additional costs. The study objective was to evaluate the cost-effectiveness of HLA-B*58:01 screening compared with using other available urate-lowering agents (ULA). Methods. A decision-analytical model was used to compare direct medical costs and effectiveness [including lifetime saved, quality-adjusted life-yrs (QALY) gained] in treating new patients with the following options: (1) genetic screening followed by allopurinol prescribing for noncarriers of HLA-B*58:01, (2) prescribing benzbromarone without screening, (3) prescribing febuxostat without screening, and (4) prescribing allopurinol without screening. A 1-year time frame and third-party payer perspective were modeled for both the entire cohort (base-case) and for the subgroup of patients with chronic kidney disease (CKD). Results. The incremental cost-effectiveness ratio of genetic screening prior to ULA therapy was estimated as New Taiwan (NT) $234,610 (US$7508) per QALY gained in the base-case cohort. For patients with CKD, it was estimated as NT$230,925 (US$7390) per QALY. The study results were sensitive to the probability of benzbromarone/febuxostat-related hypersensitivity, and a negative predicted value of genotyping. Conclusion. HLA-B*58:01 screening gave good value for money in preventing allopurinol-induced SCAR in patients indicated for ULA therapy. In addition to the costs of genotyping, it is important to monitor ULA safety closely in adopting HLA-B*58:01 screening in practice.
Adult‐specific insulin‐producing neurons in Drosophila melanogaster

Holometabolous insects undergo metamorphosis to reorganize their behavioral and morphological features into adult‐specific ones. In the central nervous system (CNS), some larval neurons undergo programmed cell death, whereas others go through remodeling of axonal and dendritic arbors to support functions of re‐established adult organs. Although there are multiple neuropeptides that have stage‐specific roles in holometabolous insects, the reorganization pattern of the entire neuropeptidergic system through metamorphosis still remains largely unclear. In this study, we conducted a mapping and lineage tracing of peptidergic neurons in the larval and adult CNS by using Drosophila genetic tools. We found that Diuretic hormone 44‐producing median neurosecretory cells start expressing Insulin‐like peptide 2 in the pharate adult stage. This neuronal cluster projects to the corpora cardiaca and dorsal vessel in both larval and adult stages, and also innervates an adult‐specific structure in the digestive tract, the crop. We propose that the adult‐specific insulin‐producing cells may regulate functions of the digestive system in a stage‐specific manner. Our study provides a neuroanatomical basis for understanding remodeling of the neuropeptidergic system during insect development and evolution.
Information Flow based Ontology Mapping

The use of ontology for knowledge organization is a common way to solve semantic heterogeneity. But when the categories of the relative concepts of ontologies are different, the semantic interoperation will encounter new obstacles. A new theory model is needed to solve this kind of problem. Information flow (IF) theory seems to be a promising avenue to this end. In this paper, we analyze semantic heterogeneities among two data sources in distributed Xu Beihongpsilas Galleries and describe an instance based approach to accomplish semantic interoperation and IF based formulation process of the global semantics. The emphasis is how to use IF theory to discover concept and instance duality in knowledge sharing. In the end, the more interrelated problems are farther discussed.
Frog-inspired hind limb for jumping robots

Frog can jump more than 15 times its body length. This impressive bounce ability movement can be attributed to their hind limbs that transfer elastic energy into kinetic energy rapidly. This paper presents a frog-inspired hind limb mechanism for biometric jumping robots. A robotic design is created to realize the mechanism for the biological hind limb with shape memory alloy (SMA) spring actuators and smart composite microstructure (SCM). SMA spring actuators have advantages over conventional actuators in reducing the size and simplifying the structure. The design employs a unique mechanism that simulates a frog's hind limb kinematics with reduced degrees of freedom. Dynamic modelling is derived and the limb design is optimized through simulations to reach the maximal takeoff speed. A robotic prototype is fabricated that can jump five times its body length.
Distribution of virtual devices on the fog for delay and araffic aeduction

By emerging Internet of Things (IoT) applications, in near future billion of devices will be connected to the internet. Because of variations in IoT standards, protocols, and devices and also the limited resources of devices, many studies have suggested exploiting virtual devices that perform computation and communication tasks on behalf of physical devices. However, locating virtual devices on far clouds will increases communication delay of devices and overall internet traffic. For this reason, in many studies, the fog computing is used for offloading devices' tasks on resources that are located near the physical device. In this paper, we propose a way to assign virtual devices to fog resources to minimize total delay of communication between physical devices with their corresponding virtual devices. Because computational complexity of the proposed virtual device assignment problem like a generalized assignment problem is NP-Hard, in this paper we propose a genetic algorithm for obtaining near-optimal solutions. First, for solving the problem we use the clustering algorithm, then we improve the results by using proposed genetic algorithm. Simulation results shows that the genetic algorithm improves the results 8.2 percent.
Genome-Wide Identification of circRNAs in Pathogenic Basidiomycetous Yeast Cryptococcus neoformans Suggests Conserved circRNA Host Genes over Kingdoms

Circular RNAs (circRNAs), a novel class of ubiquitous and intriguing noncoding RNA, have been found in a number of eukaryotes but not yet basidiomycetes. In this study, we identified 73 circRNAs from 39.28 million filtered RNA reads from the basidiomycete Cryptococcus neoformans JEC21 using next-generation sequencing (NGS) and the bioinformatics tool circular RNA identification (CIRI). Furthermore, mapping of newly found circRNAs to the genome showed that 73.97% of the circRNAs originated from exonic regions, whereas 20.55% were from intergenic regions and 5.48% were from intronic regions. Enrichment analysis of circRNA host genes was conducted based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases. The results reveal that host genes are mainly responsible for primary metabolism and, interestingly, ribosomal protein production. Furthermore, we uncovered a high-level circRNA that was a transcript from the guanosine triphosphate (GTP)ase gene CNM01190 (gene ID: 3255052) in our yeast. Coincidentally, YPT5, CNM01190′s ortholog of the GTPase in Schizosaccharomyces pombe, protists, and humans, has already been proven to generate circRNAs. Additionally, overexpression of RNA debranching enzyme DBR1 had varied influence on the expression of circRNAs, indicating that multiple circRNA biosynthesis pathways exist in C. neoformans. Our study provides evidence for the existence of stable circRNAs in the opportunistic human pathogen C. neoformans and raises a question regarding their role related to pathogenesis in this yeast.
Biophysical insights into the interaction of hen egg white lysozyme with therapeutic dye clofazimine: modulation of activity and SDS induced aggregation of model protein

The present study details the binding process of clofazimine to hen egg white lysozyme (HEWL) using spectroscopy, dynamic light scattering, transmission electron microscopy (TEM), and molecular docking techniques. Clofazimine binds to the protein with binding constant (Kb) in the order of 1.57 × 104 at 298 K. Binding process is spontaneous and exothermic. Molecular docking results suggested the involvement of hydrogen bonding and hydrophobic interactions in the binding process. Bacterial cell lytic activity in the presence of clofazimine increased to more than 40% of the value obtained with HEWL only. Interaction of the drug with HEWL induced ordered secondary structure in the protein and molecular compaction. Clofazimine also effectively inhibited the sodium dodecyl sulfate (SDS) induced amyloid formation in HEWL and caused disaggregation of preformed fibrils, reinforcing the notion that there is involvement of hydrophobic interactions and hydrogen bonding in the binding process of clofazimine with HEWL and clofazimine destabilizes the mature fibrils. Further, TEM images confirmed that fibrillar species were absent in the samples where amyloid induction was performed in the presence of clofazimine. As clofazimine is a drug less explored for the inhibition of fibril formation of the proteins, this study reports the inhibition of SDS-induced amyloid formation of HEWL by clofazimine, which will help in the development of clofazimine-related molecules for the treatment of amyloidosis.
Photoperiod- and Triiodothyronine-dependent Regulation of Reproductive Neuropeptides, Proinflammatory Cytokines, and Peripheral Physiology in Siberian Hamsters (Phodopus sungorus)

Seasonal trade-offs in reproduction and immunity are ubiquitous in nature. The mechanisms that govern transitions across seasonal physiological states appear to involve reciprocal switches in the local synthesis of thyroid hormone. In long-day (LD) summer-like conditions, increased hypothalamic triiodothyronine (T3) stimulates gonadal development. Alternatively, short-day (SD) winter-like conditions increase peripheral leukocytes and enhance multiple aspects of immune function. These data indicate that the localized effects of T3 in the hypothalamus and leukocytes are photoperiod dependent. We tested the hypothesis that increased peripheral T3 in SD conditions would increase aspects of reproductive physiology and inhibit immune function, whereas T3 injections in LD conditions would facilitate aspects of immune function (i.e., leukocytes). In addition, we also examined whether T3 regulates hypothalamic neuropeptide expression as well as hypothalamic and splenic proinflammatory cytokine expression. Adult male Siberian hamsters were maintained in LD (15L:9D) or transferred to SD (9L:15D) for 8 weeks. A subset of LD and SD hamsters was treated daily with 5 µg T3 for 2 weeks. LD and SD controls were injected with saline. Daily T3 administration in SD hamsters (SD+T3) resulted in a rapid and substantial decrease in peripheral leukocyte concentrations and stimulated gonadal development. T3 treatment in LD (LD+T3) had no effect on testicular volumes but significantly increased leukocyte concentrations. Molecular analyses revealed that T3 stimulated interleukin 1β messenger RNA (mRNA) expression in the spleen and inhibited RFamide Related Peptide-3 mRNA expression in the hypothalamus. Moreover, there was a photoperiod-dependent decrease in splenic tumor necrosis factor–α mRNA expression. These findings reveal that T3 has tissue-specific and photoperiod-dependent regulation of seasonal rhythms in reproduction and immune function.