Miracle-dz/UniFAR-FTUs huggingface dataset:
Production, purification, characterization, and applications of α-galactosidase from Bacillus flexus JS27 isolated from Manikaran hot springs

Abstract α-Galactosidase hydrolyzes the α-1,6-linkage present at the non-reducing end of the sugars and results in the release of galactosyl residue from oligosaccharides like melibiose, raffinose, stachyose, etc. In the present study we report, α-galactosidase from Bacillus flexus isolated from Manikaran hot springs (India). Maximum enzyme production was obtained in guar gum and soybean meal after 72 h at 150 rpm. While, the temperature/pH of production was optimized at 50 °C and 7.0, respectively. Isoenzymes (α-gal I and II) were obtained and characterized based on temperature/pH optima along with their stability profile. JS27 α-Gal II was purified with a final purification fold of 11.54. Native and SDS-PAGE were used to determine the molecular weight of the enzyme as 86 and 41 kDa, respectively, indicating its homodimeric form. JS27 α-Gal II showed optimum enzyme activity at 55 °C and pH 7 (10 min). The enzyme displayed Km value of 2.3809 mM and V max of 2.0 × 104 µmol/min/ml with pNPG as substrate. JS27 α-Gal II demonstrated substrate hydrolysis and simultaneous formation of transgalactosylation products (α-GOS) with numerous substrates (sugar/sugar alcohols, oligosaccharides, and complex carbohydrates) which were verified by TLC and HPLC analysis. α-GOS are significant functional food ingredients and can be explored as prebiotics.
Substrate integrated waveguide leaky wave antenna with low cross polarization in X‐Ku band

In this article, a balanced symmetrical low cross polarization (X‐pol) substrate integrated waveguide (SIW) based leaky wave antenna (LWA) is presented. The unit cell of the LWA consists of transverse and longitudinal slots, which provide series and shunt resonant elements, essentially required to radiate at broadside direction efficiently. The radiating slots are arranged in a way such that the unit cell is symmetrical around the centerline so as to achieve the low X‐pol levels. Moreover, the shape of the longitudinal slots are changed and optimized to match the unit cell impedance to the characteristic impedance of the SIW. Parametric constraints of the radiating slots are studied for achieving the continuous beam scanning and the best low X‐pol in the presented LWA. The final presented LWA is capable of continuous beam scanning from −28° to +30° within a frequency range of 9.5‐15.2 GHz including broadside at 12.2 GHz. Moreover, the X‐pol levels are better than −40 dB all over the scanning frequency range. Finally, the antenna prototype is fabricated and tested. Simulated and measured results are in good agreement. The maximum gain of the antenna measured is 13.8 dB.
ROC measures of memory accessibility

Laming has recently proposed a way to measure the accessibility (as opposed to availability) of memories via recognition testing. His measure “Accessibility” is calculated by subtracting the hit rate and false alarm rate that fall at the point where the receiver-operating characteristic (ROC) curve’s derivative is 1. I prove that, if one works within the framework of Unequal-Variance Signal Detection Theory (UVSDT), as Laming does, the measure “Accessibility” depends on the location of the response criterion (though always with a neutral likelihood ratio). Furthermore, I prove that the measure varies with the underlying variances of UVSDT regardless of which definition of bias (criterion or likelihood ratio) is used and, crucially, this holds even when the accuracy of discrimination performance or “sensitivity” ( d a ) in UVSDT is constant. As such, from the standpoint of (at least) UVSDT, it is questionable whether or to what extent the new measure of “Accessibility” actually measures the accessibility of any memory.
Some Statistical Approaches to Multidimensional Scaling Data

Statistical problems associated with multidimensional scaling are reviewed. Indices of similarity or dissimilarity have been fitted by two classes of models: point representation using a distance measure and vector representation using an inner product. In addition to these parameters representing stimulus-attribute relations, it is usual to require some subject-specific parameters to model idiosyncracies in response patterns and variance components. Techniques for coping with nuisance parameters and deriving interval estimates are discussed in the context of maximum likelihood estimation. Some generalizations to multivariate situations are also developed.
Isolation, characterisation and complement fixation activity of acidic polysaccharides from Argemone mexicana used as antimalarials in Mali

Abstract Context Global studies on Argemone mexicana L. (Papaveraceae) traditionally used against malaria in Mali are limited to its low-mass compounds activities, and little information on its bioactive polysaccharides is available. Objective This study determines the structure and the immunomodulatory activity of polysaccharides from aerial parts of A. mexicana. Materials and methods Acidic polysaccharides from this plant material named HMAmA1 and HMAmA2 were isolated from water extracts. Their monosaccharide composition was determined by gas chromatography. Glycosidic linkages were determined using GC-MS. NMR was also applied. The polymers were tested for effects on the human complement system in vitro at different doses. Results The monosaccharide composition showed that the two polysaccharides contained in different amounts the following monomers: arabinose, rhamnose, galactose, and galacturonic acid. Overall structural analysis showed the presence of a low ratio of 1,2-linked rhamnose compared to 1,4-linked galacturonic acid with arabinogalactans substituted on position 4 of rhamnose. NMR data showed the presence of galacturonans alternated by rhamnogalacturonans bearing arabinose and galactose units. α-Linkages were found for l-arabinose, l-rhamnose and d-galacturonic acid, while β-linkages were found for d-galactose. The two polysaccharides exhibited strong complement fixation activities, with HMAmA1 being the highest potent fraction. ICH50 value of HMAmA1 was 5 µg/mL, compared to the control BPII being 15.9 µg/mL. Discussion and conclusions Polysaccharides form A. mexicana presented a complement fixation effect. The complement system is an important part of the immune defense, and compounds acting on the cascade are of interest. Therefore, these polymers may be useful as immunodulatory agents.
Sib-pair subgroup familial type 1 diabetes mellitus in children in the state of Qatar

Background Type 1 diabetes is the most common type of diabetes mellitus (DM) in children. It can be sporadic in onset or cluster in families, which comprises parent-offspring and sib-pair subgroups. The risk of developing DM in first-degree relatives of affected individuals is 8–15 fold higher. There is limited data about familial DM from the Gulf region. This study aims to describe the clinical, biochemical and genetic characteristics of sib-pair familial type 1 diabetes in Qatar. Methods Every child with DM following up at Sidra Medicine was recruited. Data was collected regarding clinical features, family history, type 1 diabetes autoantibodies and whole genome sequencing was performed. Genetic analysis for MODY genes and HLA association analysis was conducted. Results 44 families with sib-pair familial diabetes were identified. Of these, 2 families had 4 affected siblings and 5 families had 3 affected siblings. The majority are of Qatari ethnicity and the most common autoantibody was GAD65. The most common age of onset in the proband was 5–9 years while it was 10–14 years in subsequent siblings. The occurrence of DKA & HbA1c levels were lower in the second affected sibling. No relevant MODY gene variants were found. HLA analysis found 15 variants in at least 50% of the subjects. Most common were HLA-F*01*01*01G, HLA- DPA1*01*03*01G, HLA- DRB3*02*02*01G, HLA- E*01*01*01G & DRB4*03*01N. Conclusions The prevalence of sib-pair diabetes is 3.64%. The second affected siblings were older. MODY is unlikely and Class I and II HLA genes was present in sib-pair diabetes.
Multiresolution representations and wavelets

Multiresolution representations are very effective for analyzing the information in images. In this dissertation we develop such a representation for general purpose low-level processing in computer vision. We first study the properties of the operator which approximates a signal at a finite resolution. We show that the difference of information between the approximation of a signal at the resolutions 2$\sp{j+1}$ and 2$\sp{j}$ can be extracted by decomposing this signal on a wavelet orthonormal basis of ${\bf L}({\bf R}\sp{n}$). In ${\bf L}\sp2({\bf R})$, a wavelet orthonormal basis is a family of functions $\left\lbrack\sqrt{2\sp{j}}\ \psi(2\sp{j}x+n)\right\rbrack\sb{(j,n)\in{\rm Z}\sp2}$, which is built by dilating and translating a unique function $\psi(x)$, called a wavelet. This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm of complexity n log(n). We study the application of this signal representation to data compression in image coding, texture discrimination and fractal analysis. The multiresolution approach to wavelets enables us to characterize the functions $\psi(x) \in {\bf L}\sp2({\bf R})$ which generate an orthonormal basis. The inconvenience of a linear multiresolution decomposition is that it does not provide a signal representation which translates when the signal translates. It is therefore difficult to develop pattern recognition algorithms from such representations. In the second part of the dissertation we introduce a nonlinear multiscale transform which translates when the signal is translated. This representation is based upon the zero-crossings and local energies of a multiscale transform called the dyadic wavelet transform. We experimentally show that this representation is complete and that we can reconstruct the original signal with an iterative algorithm. We study the mathematical properties of this decomposition and show that it is well adapted to computer vision. To illustrate the efficiency of this Energy Zero-Crossings representation, we have developed a coarse to find matching algorithm on stereo epipolar scan lines. While we stress the applications towards computer vision, wavelets are useful to analyze other types of signal such as speech and seismic-waves.
A Neuromorphic Processing System With Spike-Driven SNN Processor for Wearable ECG Classification

This paper presents a neuromorphic processing system with a spike-driven spiking neural network (SNN) processor design for always-on wearable electrocardiogram (ECG) classification. In the proposed system, the ECG signal is captured by level crossing (LC) sampling, achieving native temporal coding with single-bit data representation, which is directly fed into an SNN in an event-driven manner. A hardware-aware spatio-temporal backpropagation (STBP) is suggested as the training scheme to adapt to the LC-based data representation and to generate lightweight SNN models. Such a training scheme diminishes the firing rate of the network with little plenty of classification accuracy loss, thus reducing the switching activity of the circuits for low-power operation. A specialized SNN processor is designed with the spike-driven processing flow and hierarchical memory access scheme. Validated with field programmable gate arrays (FPGA) and evaluated in 40 nm CMOS technology for application-specific integrated circuit (ASIC) design, the SNN processor can achieve 98.22% classification accuracy on the MIT-BIH database for 5-category classification, with an energy efficiency of 0.75 $\mu$J/classification.
Genetic variation in HIF‐2α attenuates ventilatory sensitivity and carotid body growth in chronic hypoxia in high‐altitude deer mice

The gene encoding HIF‐2α, Epas1, has experienced a history of natural selection in many high‐altitude taxa, but the functional role of mutations in this gene is still poorly understood. We investigated the influence of the high‐altitude variant of Epas1 in North American deer mice (Peromyscus maniculatus) on the control of breathing and carotid body growth during chronic hypoxia. We created hybrids between high‐ and low‐altitude populations of deer mice to disrupt linkages between genetic loci so that the physiological effects of Epas1 alleles (Epas1H and Epas1L, respectively) could be examined on an admixed genomic background. In general, chronic hypoxia (4 weeks at 12 kPa O2) enhanced ventilatory chemosensitivity (assessed as the acute ventilatory response to hypoxia), increased total ventilation and arterial O2 saturation during progressive poikilocapnic hypoxia, and increased haematocrit and blood haemoglobin content across genotypes. However, the effects of chronic hypoxia on ventilatory chemosensitivity were attenuated in mice that were homozygous for the high‐altitude Epas1 allele (Epas1H/H). Carotid body growth and glomus cell hyperplasia, which was strongly induced in Epas1L/L mice in chronic hypoxia, was not observed in Epas1H/H mice. Epas1 genotype also modulated the effects of chronic hypoxia on metabolism and body temperature depression in hypoxia, but had no effects on haematological traits. These findings confirm the important role of HIF‐2α in modulating ventilatory sensitivity and carotid body growth in chronic hypoxia, and show that genetic variation in Epas1 is responsible for evolved changes in the control of breathing and metabolism in high‐altitude deer mice.
Framework of Gradient Descent Least Squares Regression-Based NN Structure for Power Quality Improvement in PV-Integrated Low-Voltage Weak Grid System

This paper proposes a novel gradient descent least squares regression (GDLSR)-based neural network (NN) structure for the control of grid-integrated solar photovoltaic (PV) system with improved power quality. Here, a single-layer neuron structure is used for the extraction of fundamental component (FC) from the load current. During FC extraction, GDLSR-based NN structure attenuates harmonic components, noise, dc offsets, bias, notches and distortions from the nonlinear current, which improves the power quality under normal as well as under abnormal grid conditions. This single-layer GDLSR-based NN structure has a very simple architecture, which decreases the computational burden and algorithm complexity. Therefore, it is easy in implementation. In this work, the GDLSR-based control technique is tested on a single-phase single-stage grid-integrated PV topology with the nonlinear loads. The prime objective of the GDLSR-based NN structure is to provide reactive power compensation, power factor correction, harmonics filtering and mitigation of other power quality issues. Moreover, when solar irradiation is zero, the dc-link capacitor and voltage-source converter act as a distribution static compensator, which enhances the utilization factor of the system. The proposed system is modeled, and its performances are verified experimentally on a developed prototype in different grid disturbances as well as solar insolation variation conditions, which performances have satisfied the motive of the proposed technique as well as the IEEE-519 standard.
Coupling riboflavin de novo biosynthesis and cytochrome expression for improving extracellular electron transfer efficiency in Shewanella oneidensis

Shewanella oneidensis MR‐1, as a model exoelectrogen with divergent extracellular electron transfer (EET) pathways, has been widely used in microbial fuel cells (MFCs). The electron transfer rate is largely determined by riboflavin (RF) and c‐type cytochromes (c‐Cyts). However, relatively low RF production and inappropriate amount of c‐Cyts substantially impede the capacity of improving the EET rate. In this study, coupling of riboflavin de novo biosynthesis and c‐Cyts expression was implemented to enhance the efficiency of EET in S. oneidensis. First, the upstream pathway of RF de novo biosynthesis was divided into four modules, and the expression level of 22 genes in above four modules was fine‐tuned by employing promoters with different strengths. Among them, genes zwf*, glyA, and ybjU which exhibited optimal RF production were combinatorially overexpressed, leading to the enhancement of maximum output power density by 166%. Second, the diverse c‐Cyts genes were overexpressed to match high RF production, and omcA was selected for further combination. Third, RF de novo biosynthesis and c‐Cyts expression were combined, resulting in 2.34‐fold higher power output than the parent strain. This modular and combinatorial manipulation strategy provides a generalized reference to advance versatile practical applications of electroactive microorganisms.
Development and validation of monoclonal antibodies specific for Candida albicans Als2, Als9-1, and Als9-2

Fungal agglutinin-like sequence (Als) cell-surface glycoproteins, best characterized in Candida albicans, mediate adhesive and aggregative interactions with host cells, other microbes, and abiotic surfaces. Monoclonal antibodies (MAbs) specific for each C. albicans Als protein are valuable reagents for gaining insight into Als protein localization and function. This manuscript describes development and validation of MAbs specific for C. albicans Als2, as well as for C. albicans Als9-1 and Als9-2, two protein variants produced from the ALS9 locus. Native C. albicans ALS9 expression levels were not sufficiently high to produce detectable Als9 protein on the wild-type cell surface so MAb validation required production of overexpression strains, each featuring one of the two ALS9 alleles. An anti-Als2 MAb was raised against an N-glycosylated form of the protein immunogen, as well as an Endoglycosidase H-treated immunogen. The MAb raised against the N-glycosylated immunogen proved superior and immunolabeled C. albicans yeast cells and germ tubes, and the surface of Candida dubliniensis and Candida tropicalis yeasts. Als2 was visible on C. albicans yeast cells recovered from a murine model of oral candidiasis, demonstrating Als2 production both in vivo and in vitro. These new MAbs add to the collection of anti-Als MAbs that are powerful tools to better understand the role of Als proteins in C. albicans biology and pathogenesis.
CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance

SUMMARY The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization, and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousands sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus, and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast. AVAILABILITY AND IMPLEMENTATION CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
COVID-19 Vaccination Intent and Belief that Vaccination Will End the Pandemic

High vaccination coverage is considered to be key in dealing with the coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy can limit uptake. We examined the specific coronavirus beliefs that persons have regarding COVID-19 and COVID-19 vaccines and to what extent these beliefs explain COVID-19 vaccination intentions. We conducted a survey among 4,033 residents of the Netherlands that examined COVID-19 vaccination intentions and various beliefs. Random forest regression analysis explained 76% of the variance in vaccination intentions. The strongest determinant in the model was the belief the COVID-19 crisis will only end if many persons get vaccinated. Other strong determinants were beliefs about safety of vaccines, specifically in relation to vaccine development and approval process; (social) benefits of vaccination; social norms regarding vaccination behavior; and effectiveness of vaccines. We propose to address these specific beliefs in communications about COVID-19 vaccinations to stimulate vaccine uptake.
Segmentation Based Structure Matching

This paper investigates how to connect low level image segmentation with high level vision tasks. A segmentation gives a middle-level image representation which is robust to the intensity and structure variations that caus e problems for matching based on low-level descriptors. A segmentation descriptor can give more accurate and efficient matching of boundaries tha n methods based on boundary representations. Our recognition tests on several databases verify that when segmentations are reliable the segmentation descriptor can provide robust matching results for recognition. To address the problem caused by unreliability of low level segmentation, we propose a Bayesian structure matching technique. Instead of only basing on the “ maximum likelihood” segmentation, all segmentations should be evaluated and combined in the Bayesian framework. The resulting matching technique is more reliable and more practical. Furthermore, it offers insights about low level image segmentation as well. We demonstrate successful results in both fields.
Association of sodium voltage-gated channel genes polymorphisms with epilepsy risk and prognosis in the Saudi population

Abstract Background Epilepsy is a heterogeneous complex condition that involve the human brain. Genetic predisposition to epilepsy is a fundamental factor of the disorder aetiology. The sodium voltage-gated channel (SCN) genes variants are critical biomarker for the epilepsy development and progression. In this study, we aimed to investigate the association of several SNCs genetic polymorphisms with epilepsy risk and their intrudance of the disease prognosis. Methods Blood samples were withdrawn from 296 Epilepsy patients in addition to 293 healthy matched participants prior to DNA extraction. PCR-sequencing was used for genotyping analysis. Genotyping outputs were then statistically analysed for genotype/phenotype evaluation. Results Within SCN1A gene we found that the rs6432861 (p = 0.014) was in correlation with the risk of epilepsy. In addition, both rs4667485 and rs1469649 of SCN2A gene were significantly correlated to epilepsy risk for both allelic (4e-4 and 1e-3) and genotypic (1e-3 and 5e-3). Moreover, the haplotype analysis showed that the GATGCTCGGTTTCGCTACGCA haplotype of SCN2A gene was significantly related to epilepsy increased risk, p = 6e-3, OR (CI) = 2.02 (1.23–3.31). In relevant to our finding, many of the investigated SCNs variants in the current study were related to several clinical features of epilepsy. Conclusion In light of our results, we infer that SCN genes polymorphisms are strong candidates for epilepsy development and progression. Furthermore, these variant are essential for the disorder prognosis and medications outcomes. Key Messages Genetic polymorphisms of sodium channels SCN1A, SCN2A and SCN3A were found to be associated with the risk of epilepsy. SCN1B polymorphisms were found to be correlated to epilepsy reduced risk. SCNs variants are involved in the epilepsy prognosis and response to treatment.