Alteration in heparan sulfate (HS) biosynthesis has been described to impact a range of pivotal processes involved in cancer progression. HS 3-O-sulfotransferase 3B1 (HS3ST3B1) catalyzes the reaction of 3-O-sulfation within HS chains. Over the past few years, a growing number of studies has reported a tumor-promoting effect of this HS-modifying enzyme in various cancers. Consistent with these studies, we previously reported that HS3ST3B1 overexpression increased survival and resistance to apoptosis in MDA-MB-231 breast cancer (BrCa) cells. In the present study, we further investigated the biological and clinical significance of HS3ST3B1 expression in BrCa. Interrogation of public databases revealed that high expression levels of HS3STB1 are associated with invasive and mesenchymal-like phenotype in BrCa cells and predict poor clinical outcome in BrCA patients with chemotherapy. In vitro, HS3ST3B1 overexpression increased the invasive properties of MDA-MB-231 cells and enhanced chemo-resistance to conventional anticancer drugs. Mechanistically, we found that the advantage given by HS3ST3B1 was linked to the expression and activation of PDGF-Rβ. Silencing the expression of this receptor reversed the effects driven by HS3ST3B1 overexpression. Altogether, our results suggest that HS3ST3B1 may play an important role in the progression of aggressive BrCa and offer a potentially druggable target for therapeutic application.

The nervous system demands an adequate oxygen and metabolite exchange, making pericytes (PCs), the only vasoactive cells on the capillaries, essential to neural function. Loss of PCs is a hallmark of multiple diseases, including diabetes, Alzheimer’s, amyotrophic lateral sclerosis (ALS) and Parkinson’s. Platelet-Derived Growth Factor Receptors (PDGFRs) have been shown to be critical to the PC function and survival. However, how PDGFR-mediated PC activity affects vascular homeostasis is not fully understood. Here, we tested the hypothesis that imatinib, a chemotherapeutic agent and a potent PDGFR inhibitor, alters the PC distribution and thus induces vascular atrophy. We performed a morphometric analysis of the vascular elements in sham control and imatinib-treated NG2-DsRed mice. Vascular morphology and the integrity of the blood-retina barrier (BRB) were evaluated using blood albumin labeling. We found that imatinib decreased the number of PCs and blood vessel (BV) coverage in all retinal vascular layers, this was accompanied by a shrinkage of BV diameters. Surprisingly, the total length of capillaries was not altered, suggesting a preferential effect of imatinib on PCs. Furthermore, the blood-retina barrier disruption was not evident. In conclusion, our data suggest that imatinib could help in treating neurovascular diseases and serve as a model for PC loss, without BRB disruption.

In the present study. At first, some properties of r-fuzzy soft β-closed sets are introduced on fuzzy soft topological spaces based on the paper Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). Also, we define the closure and interior operators with respect to the classes of r-fuzzy soft β-closed and r-fuzzy soft β-open sets, and investigate some of their properties. In addition, the concept of r-fuzzy soft β-connected sets is introduced and characterized with help of fuzzy soft β-closure operators. Thereafter, some properties of a fuzzy soft β-continuity are studied. Furthermore, we introduce and study the concepts of fuzzy soft almost (weakly) β-continuous functions, which are weaker forms of a fuzzy soft β-continuity. Also, the relationships between these classes of functions are specified with the help of some illustrative examples. Finally, we explore new types of fuzzy soft functions called, fuzzy soft β-irresolute (strongly β-irresolute, β-irresolute open, β-irresolute closed and β-irresolute homeomorphism) functions, and discuss some properties of them. Also, we show that fuzzy soft strongly β-irresolute → fuzzy soft β-irresolute → fuzzy soft β-continuity, but the converse may not be true.

Balínt Syndrome is an acquired disorder manifesting in the inability to recognize several objects at once (simultagnosia), inaccurate visually guided limb movements despite intact motor function (optic ataxia) and the inability to make accurate voluntary saccades to visual targets despite demonstrating unrestricted range of eye movements (ocular motor apraxia). Here we report the first case of a patient presenting with Balínt Syndrome caused by a platelet-derived growth factor receptor A mutation (PDGFRA)-induced Hypereosinophilic Syndrome (HES).

Abstract: Bulgaria is famous for its oil-bearing rose. R. damascena Mill. and R. alba L. are mainly cultivated in the country, but a recent survey of industrial plantations in 2020 revealed that R. centifolia L. and hybrids of R. damascena Mill. x R. gallica L. are also common in the rose valley. Although their essential oil cannot be compared in quality with the classic, they are preferred by farmers with high yields of flowers and resistance to diseases and pests. All these roses are also used to produce rose water and extracts. The aim of this investigation was to compare the yield and chromatographic fingerprints of seven rose oils and hydrosols produced in Bulgaria. The quantitative composition of the main components of the oils was compared with the norms of the world standard. Our study showed that the yield of essential oil from these roses was in the range of 0.015 - 0.048%. The main group in the chemical composition is terpene alcohols, which vary in the range: geraniol (17.60 - 34.02 %), citronellol (8.38 - 28.7 %), and nerol (4.8 - 11.90 %), but with a different ratio. Hydrocarbons are represented by saturated aliphatic homologs with an odd number of carbon atoms, the main ones being: nonadecane (8.10 - 22.67 %), heneicosane (4.37 - 10.21 %), heptadecane (1.07 - 2.98 %) and triclosan (0.81 - 5.90 %). In contrast, the chemical profile of the hydrosols was performed by phenyl ethyl alcohol (27.45 - 69.88 %), geraniol (13.72 - 28.67 %), and citronelol+nerol (4.56 - 17.37 %). The results show that the presence of plantations with a genotype different from that of R. damascena implies differences in the quality of rose oils and hydrosols. This predetermines their properties of use.

To ensure the safety in aircraft flying, we aim use of the deep learning methods of nondestructive examination with multiple defect detection paradigms for X-ray image detection posed. The use of the Fast Region-based Convolutional Neural Networks (Fast R-CNN) driven model seeks to augment and improve existing automated Non-Destructive Testing (NDT) diagnosis. Within the context of X-ray screening, limited numbers insufficient types of X-ray aeronautics engine defect data samples can thus pose another problem in training model tackling multiple detections perform accuracy. To overcome this issue, we employ a deep learning paradigm of transfer learning tackling both single and multiple detection. Overall the achieve result get more then 90% accuracy based on the AE-RTISNet retrained with 8 types of defect detection. Caffe structure software to make networks tracking detection over multiples Fast R-CNN. We consider the AE-RTISNet provide best results to the more traditional multiple Fast R-CNN approaches simpler translate to C++ code and installed in the Jetson™ TX2 embedded computer. With the use of LMDB format, all images using input images of size 640 × 480 pixel. The results scope achieves 0.9 mean average precision (mAP) on 8 types of material defect classifiers problem and requires approximately 100 microseconds.

Grass pea (Lathyrus sativus L.) is a protein-rich crop that is resilient to various abiotic stresses, including drought. However, it is not cultivated widely for human consumption due to the neurotoxin β-N-oxalyl-L-α, β-diaminopropionic acid (β-ODAP), and its association with neurolathyrism. Though some varieties with low β-ODAP have been developed through classical breeding, the β-ODAP content is increasing due to genotype x environment interactions. This review covers grass pea nutritional quality, β-ODAP biosynthesis, mechanism of paralysis, traditional ways to reduce β-ODAP, candidate genes for boosting sulfur-containing amino acids, and the potential and targets of gene editing to reduce β-ODAP content. Recently, two key enzymes (β-ODAP synthase and β-cyanoalanine synthase) have been identified in the biosynthetic pathway of β-ODAP. We proposed four strategies through which the genes encoding these enzymes can be targeted and suppressed using CRISPR/Cas9 gene editing. Compared to its homology in Medicago truncatula, the grass pea β-ODAP synthase gene sequence and β-cyanoalanine synthase showed 62.9% and 95% similarity, respectively. The β-ODAP synthase converts the final intermediate L-DAPA into toxic β-ODAP whist β-cyanoalanine synthase converts O-Acetylserine into β-isoxazolin-5-on-2-yl-alanine. Since grass pea is low in methionine and cysteine amino acids, improvement of these amino acids is also needed to boost its protein content.

Beta-lactam resistant bacteria, commonly resident in tertiary hospitals, have emerged as a worldwide health problem because of ready-to-eat vegetable intake. We aimed to characterize the genes providing resistance to beta-lactam antibiotics in Enterobacteriaceae, isolated from five commercial salad brands for human consumption in Mexico City. 25 samples were collected, grow in blood agar plates, the bacteria were biochemistry identified and antimicrobial susceptibility testing was done, the carried family genes were identified by endpoint PCR and the specific genes were confirmed with WGS by NGS. 12 positive cultures were identified and their microbiological distribution was as follows, 8.3% for Enterobacter aerogene (n=1), 8.3% for Serratia fonricola (n=1), 16.7% for Serratia marcesens (n=2), 16.7% for Klebsiella pneumoniae (n=2), and 50% (n=6) for Enterobacter cloacae. The endpoint PCR results showed 11 colonies positive for blaBIL (91.7%), 11 for blaSHV (91.7%), 11 for blaCTX (97.7%), 12 for blaDHA (100%),4 for blaVIM (33.3%), 2 for blaOXA (16.7%), 2 for blaIMP (16.7%), 1 for blaKPC (8.3%) and 1 for blaTEM (8.3%) gene, all samples were negative blaROB, blaCMY, blaP, blaCFX and blaLAP gene. The sequencing analysis revels a specific genotypes for Enterobacter cloacae (blaSHV-12, blaCTX-M-15, blaDHA-1, blaKPC-2); Serratia marcescens (blaSHV-1, blaCTX-M-3, blaDHA-1, blaVIM-2); Klebsiella pneumoniae (blaSHV-12, blaCTX-M-15, blaDHA-1); Serratia fonticola (blaSHV-12, blaVIM-1, blaDHA-1) and Enterobacter aerogene (blaSHV-1, blaCTX-M-1, blaDHA-1, blaVIM-2, blaOXA-9). Our results indicate that beta-lactam resistant bacteria have acquired integrons with a different number of genes that providing panresistance to beta-lactam antibiotics, including penicillins, oxacillins, cefalosporins, monobactams, carbapenems and imipenems.

In this paper, we explore a new norm on L^p-space called r-norm, and hence producing a new normed space called r-normed space. Measure theoretic and functional analytic properties are covered such as the relation between r-norm and the classical p-norm. An application of r-normed space in probability theory and statsitics is also presented, notably, its role as a rigorous framework in describing the coefficient of determination.

Recently, Shehata et al. [37] introduced the r+1Rs(B;C; z) matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, dierential properties, new integral representations, k- Beta transform, Laplace transform, fractional k-Fourier transform, fractional integral properties, the k-Riemann{Liouville and k-Weyl fractional integral and derivative operators an extended version of r+1Rs;k matrix function. We establish its relationships with other well known special matrix functions which have some particular cases in the context of three parametric Mittag-Leer matrix function, k- Konhauser and k-Laguerre matrix polynomials. Finally, some special cases of the established formulas are also discussed.

In this article, we first defined a stronger form of (r,s)-generalized fuzzy semi-closed sets (briefly, (r,s)-gfsc sets) called (r,s)-g*fsc sets and investigated some of its features. Moreover, we showed that (r,s)-fsc set → (r,s)-g*fsc set → (r,s)-gfsc set, but the converse may not be true. In addition, we explored novel types of fuzzy generalized mappings between double fuzzy topological spaces (U, τ, τ*) and (V, η, η*), and the relationships between these classes of mappings were examined with the help of some illustrative examples. Thereafter, we introduced novel types of higher separation axioms called (r,s)-GFS-regular and (r,s)-GFS-normal spaces with the help of (r,s)-gfsc sets and discussed some topological properties of them. Finally, some novel types of compactness via (r,s)-gfso sets were defined and the relationships between them were introduced.

This article presents a proposed system that enables energy transfer from the dc grid to a single-phase onboard grid, operating at an hi frequency. In addition to the energy transfer function, it additionally enables compensation of reactive power in the ac grid when the converter operates at less than rated power. To operate in compensator mode, it is necessary to decouple the current from the grid into active and reactive components and control them independently. To achieve good dynamics, synchronizers that operate in the dq system are used. In the case of a single-phase grid, it requires such a synchronizer to generate virtual quadrature signals. The used systems based on second-order generalized integrator are good, but to improve dynamics in the work a quadrature generator based on trigonometric calculations was proposed. The developed system was implemented in a proportional resonant current control system. Tests performed in steady state and in dynamic states related to typical grid disturbances showed better dynamic properties than the standard integrator-based system.Keywords: power transfer; compensator; P+R controller

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

Herein, a chemophenetic significance, based on phenolic metabolite profiling of three Senecio (S. hercynicus, S. ovatus and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima) coupled to morphometric data, is presented. A set of twelve morphometric characters were recorded from each plant species and used as predictor variables in a Linear Discriminant Analysis (LDA) model. From a total 75 observations (15 from each of the five species), the model correctly assumed their species' membership, except 2 observations. Among the studied species, S. hercynicus and S. ovatus presented the greatest morphological similarity. A phytochemical profiling of phenolic specialized metabolites by UHPLC-Orbitrap-HRMS revealed 46 hydroxybenzoic, hydroxycinnamic, acylquinic acids and their derivatives, 1 coumarin, and 21 flavonoids. Hierarchical and PCA clustering applied to the phytochemical data corroborated the similarity of S. hercynicus and S. ovatus, observed in the morphometric analysis. This study contributes to the phylogenetic relationships between the tribe Senecioneae taxa and highlights the chemophenetic similarity/dissmilarity of the studied species belonging to Senecio and Jacobaea genera.

Neuroinflammation, defined as inflammatory reactions mediated by cytokines, chemokines, reactive oxygen species, and secondary messengers in the central nervous system (CNS) including the brain and spinal cord is the basis of many neurological disorders. Recently, erythropoietin (EPO) has been considered and studied as a modulator of neuroinflammation. On this article minireview of pathophysiology of neuroinflammation and the neuroprotective effects of EPO is discussed and a case of subacute huge subdural hematoma with double mydriasis operated urgently, treated with low daily dose (vs high dose once or twice a month in the literature) of EPO and recovered fully and discharged home with good consciousness is reported. In addition, the probable unfavorable outcome of erythropoietin administration in patients with neuroinflammation in COVID-19 is considered.

Diabetes is a group of diseases characterized by loss of β cell mass and/or -function, resulting in hyperglycemia. Approx. 537 million people worldwide suffer from diabetes – a number which is expected to increase. Diabetes is primarily treated by exogenous insulin, which comes with the challenges of maintaining glycemic control to prevent ketoacidosis and severe complications. The need for a curative treatment has initiated the research in β cell regeneration. Several studies in mice have identified essential genes for β cell fate, which can be manipulated in other cells to induce generation of new β cells. Zebrafish, a regeneration-positive animal model, has shown several different sources of new β cells, including regeneration by self-replication, neogenesis by duct-associated progenitor cells, and transdifferentiation of other endocrine islet cells. The animal models used in this research area are either limited by their low regenerative ability (mice), or their small size and remoteness from humans (zebrafish). There is a need for new animal models of diabetes, in which the molecular pathways of endogenous regeneration can be studied. This study proposes the axolotl salamander (Ambystoma mexicanum) as a model for studying the regeneration of β cells. The axolotl has shown great regenerative capability, as they have proven capable of regenerating amputated limbs, and hearts with myocardial infarction, among other organs. This study aims to establish a diabetic axolotl model, investigate their regenerative ability in the pancreas, and examine the potential systemic effects of the induced disease. In a pilot study, five different protocols using STZ (streptozotocin) were tested, and the most optimal protocol was found. Furthermore, the glucose tolerance test was optimized to characterize the glycemic state of the animals. The effect of the treatment on blood glucose levels was measured to characterize the development and decline of the disease. The histological changes in the pancreas were examined. Moreover, the systemic effects of the STZ treatment were investigated in blood and urine. The study indicated that it is possible to induce diabetes in the axolotl, but variations between the animals should be minimized, or the sample size should be increased to conduct a satisfying experiment, as it was not possible to induce diabetes in all animals. Regeneration was not observed histologically, but a restoration of blood glucose levels was seen over the span of the experiment. Lastly, edema formation was observed in some of the STZ-treated animals, but the cause of edema remains undetermined.

Cardiac fibrosis is a pathological process associated with development of heart failure. TGF-β and WNT signaling have been implicated in pathogenesis of cardiac fibrosis, however little is known about molecular cross-talk between these two pathways. The aim of this study was to examine the effect of exogenous canonical WNT3a and non-canonical WNT5a in TGF-β-activated human cardiac fibroblasts. We found that WNT3a and TGF-β induced -catenin-dependent response, whereas WNT5a prompted AP-1 activity. TGF-β triggered profibrotic signature in cardiac fibroblasts, and co-stimulation with WNT3a or co-activation of the β-catenin pathway with GSK3β inhibitor CHIR99021 enhanced collagen I and fibronectin production and development of active contractile stress fibers. In the absence of TGF-β, neither WNT3a nor CHIR99021 exerted profibrotic response. On a molecular level, in TGF-β-activated fibroblasts WNT3a enhanced phosphorylation of TAK1 and production and secretion of IL-11 but showed no effect on Smad pathway. Neutralization of IL-11 activity with the blocking anti-IL-11 antibody effectively reduced profibrotic response of cardiac fibroblasts activated with TGF-β and WNT3a. In contrast to canonical WNT3a, co-activation with non-canonical WNT5a suppressed TGF-β-induced production of collagen I. In conclusion, WNT/β-catenin signaling promotes TGF-β-mediated fibroblast-to-myofibroblast transition by enhancing IL-11 production. Thus, the uncovered mechanism broadens our knowledge on molecular basis of cardiac fibrogenesis and defines novel therapeutic targets for fibrotic heart diseases.

Using the method of the beta function, Sun has recently evaluated some series of the type $\sum_{k=0}^{\infty}(ak+b)x^k/\binom{mk}{nk}$. By factorization of the polynomial $t^{m-n}(1-t)^n-x$, we will give a general method to find new $\pi$-series.

Antibiotic resistance, particularly beta-lactam resistance, is a major problem worldwide. Imipenemase or IMP-type metallo-beta-lactamase (MBL) has become a more prominent enzyme, especially in Asia, since it was discovered in the 1990s in Japan. There are currently more than 91 variants of IMP-type enzymes. The most commonly identified variant of IMP-type enzymes is IMP-1 variant. IMP-type MBLs have been identified in more than 10 species in Enterobacterales. Pseudomonas aeruginosa is the most frequent carrier of IMP-type enzymes worldwide. In Asia, IMP-type MBLs have been distributed in many countries in the region. This work investigated a variety of currently available IMP-type MBLs in both global level and regional level. Out of 88 variants of IMP-type MBLs reported worldwide, only 32 variants were found to have susceptibility profiles. Most of the IMP-type MBLs were resistant to Carbapenems, especially Imipenem and Meropenem, followed by the 3rd generation cephalosporins, and interestingly, monobactams. Our results comprehensively indicated the distribution of IMP-type MBLs in Asia and raised the awareness of the situation of antimicrobial resistance in the region.

December 4, 2020 marks 90 years since the concept of neutrinos was proposed as a consequence of the observed discrepancies in several experiments on radioactive decays of various isotopes. There have been great many developments in our understanding of this elusive particle over the past nine decades, also leading to several Nobel Prizes awarded to work on neutrino physics. But there are many aspects of the neutrinos that are still not completely understood, including even its actual rest mass. The neutrino still remains an enigma and we have yet to learn a lot about its different properties. This article summarises the overall picture of the current understanding of the neutrino, right from its inception.

Abstract: Composite sintered bodies comprising silicon dioxide (SiO2) nanoparticles dispersed in β-tricalcium phosphate (β-TCP) were prepared. The addition of nano-sized colloidal SiO2 to the β-TCP produced well-dispersed secondary phase nanoparticles that promoted densification by suppressing grain growth and increasing volume shrinkage of the sintered bodies. The SiO2 was found not to react with the β-TCP at 1120 °C and the substitution of silicon for phosphorous to produce a solid solution did not occur. This lack of a reaction is ascribed to the absence of avail-able calcium ions to compensate for the increase in charge associated with this substitution. The SiO2 nanoparticles were found to be present near the intersections of grain boundaries in the β-TCP. A β-TCP composite sintered body containing 4.0 wt% SiO2 exhibited a bending strength comparable to that of cortical bone and hence could potentially be used as a bone filling material.

Abstract: Due to their rapid evolution and their impact on health care, be-ta-lactamases, protein degrading beta-lactam antibiotics, are used as generic model of protein evolution. Therefore, we investigated the mutation effects in two distant beta-lactamases TEM-1 and CTX-M-15. Interestingly we found a site with a complex pattern of genetic interactions. Mutation G251W in TEM-1 is in-activating the protein’s function just as the reciprocal mutation W251G in CTXM-15. Phylogenetic analysis revealed that mutation G has been entrenched in TEM-1 background: while rarely observed throughout the phylogeny it is es-sential in TEM-1. Using a rescue experiment in TEM-1 G251W mutant, we could identify sites that alleviates the deviation from G to W. While few of these muta-tions could potentially involve local interactions, most of them were found on distant residues in the 3D structure. Many well-known mutations having an impact on protein stability, such as M182T, were recovered. Our results there-fore suggest that entrenchment of an amino acid may rely on diffuse interactions among multiple sites with a major impact on protein stability.

Pulmonary Embolism (PE) is the obstruction of blood arteries in the lungs by a blood clot. The mortality risk for PE is approximately 30%. Detecting pulmonary embolism in the segmental arteries of the lung is more challenging than in the main arteries and is very prone to being missed. A computer-based approach was created in this work to automatically identify pulmonary embolism in the segmental arteries using computed tomography images. The system's infrastructure includes an enhanced Mask R-CNN deep neural network that has been trained with images containing PE. The network accurately identifies the location of the pulmonary embolism on the computed tomography picture and successfully extracts its borders. The investigation was conducted by generating a local dataset. The study's performance was evaluated using pulmonary embolisms identified manually by the expert radiologist. The sensitivity, specificity, accuracy, dice coefficient, and Jaccard index values for 2130 pictures were 96.4%, 93.5%, 96.1%, 0.96, and 0.90, respectively. The improved Mask R-CNN model has demonstrated superior performance when compared to the traditional Mask R-CNN and U-Net models. This high-performance technology is designed to identify pulmonary embolism and will aid professionals in assessing the size of the embolism.

Introduction: EEGLAB is one of the most famous software for processing, analyzing, and researching experiments that have Electroencephalography (EEG) datasets. Due to the numerous and famous add-ins along with global, widespread communications and online free training, its popularity increased every year. Method: To address this phenomenon from a bibliographic perspective, we found 20,464 citations in Google Scholar for the main EEGLAB reference since 8/27/2023. Then, only the Web of Science (WOS) articles were 12,700 that they were extracted. The results were analyzed with Bibliometrix package from CRAN R software. Results: The time span of these articles is from 2004 to 2023 with 12,700 documents in 1,125 sources (journals, books, etc.), 29,125 authors, 19,062 author’s keywords, 13,707 keywords PLUS, 279,617 references. The annual growth rate is 28.12 %, international Co-authorship is 37.27 % and Co-authors per document is s 4.89 and the average citations per document is 22.51. The most relevant sources are Neuroimage, Frontiers in Human Neurosciences, Scientific Reports, Psychophysiology, and PLOS One with 780, 526, 446,425, and 371 articles, respectively. The most cited countries are the USA, Germany, and the United Kingdom with 93,093, 32,621, and 20,748 total citations, respectively. The ERPLAB, ADJUST, and ICLabel add-ins have the local to global citation ratios equal to 85.4%, 65.1%, and 78.2% respectively. Other bibliometric analyses such as co-occurrence networks and thematic maps of abstracts, titles, and keywords are estimated and presented. Conclusions: EEGLAB is among the most cited MATLAB toolboxes in computational neuroscience. Many developed and developing countries use it in their research publications.

This research aims to obtain empirical evidence of the influence of the masculinity of male CEOs on the of research & development, this research seeks to identify the influence of the face of mas-culinity of male CEO’s on the of research & development. The study used a quantitative approach with population and research samples using companies listed on the Indonesia Stock Exchange from 2016 to 2021. The study collected images of faces identified as male CEOs from data from the Indonesia Stock Exchange website and company as utilizing Google searches. The data analysis method in this study used Regression Ordinary Least Square (OLS) with Stata Software. Stata software is one of the regression completion procedures that has a high degree of flexibility in re-search that connects theories, concepts and data that can be done on variables in research. The findings empirically explain that the higher the face value of male CEO masculinity has an impact on reducing research & development costs, and vice versa the lower the face value of male CEO masculinity has an impact on increasing research & development. The practical implications of the research results can help the Indonesian Association of Accountants in developing Financial Accounting Standard No. 19 in Indonesia. The theoretical implications of the research results can explain the Theory of Agency and the Theory of Consistency of Behavior. The policy implications of the results of the study can provide empirical evidence that the higher the facial value of male CEO masculinity has an impact on reducing research & development, while also the lower the face value of male CEO masculinity has an impact on increasing research & development.

Potholes on roads pose a major threat to motorists and autonomous vehicles. Driving over a pothole has the potential to cause serious damage to a vehicle, which in turn may result in fatal accidents. Currently, many pothole detection methods exist. However, these methods do not utilize deep learning techniques to detect a pothole in real-time, determine the location thereof and display its location on a map. The success of determining an effective pothole detection method, which includes the aforementioned deep learning techniques, is dependent on acquiring a large amount of data, including images of potholes. Once adequate data had been gathered, the images were processed and annotated. The next step was to determine which deep learning algorithms could be utilized. Three different models, including Faster R-CNN, SSD and YOLOv3 were trained on the custom dataset containing images of potholes to determine which network produces the best results for real-time detection. It was revealed that YOLOv3 produced the most accurate results and performed the best in real-time, with an average detection time of only 0.836s per image. The final results revealed that a real-time pothole detection system, integrated with a cloud and maps service, can be created to allow drivers to avoid potholes.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was dome in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.

Several efforts have been made to estimate the prevalence of different types of antibiotic resistance in different regions of Nigeria. The study investigated the prevalence of Klebsiella pneumoniae encoding genes for CTX-M, TEM, and SHV-1 extended-spectrum beta-lactamases (ESBL) enzymes isolated from urine samples of non-hospitalized patients with suspected UTI in Lagos State, Nigeria. A 4-month retrospective study, spanning from May 2023 to August 2023, was conducted. K. pneumoniae was isolated from urine samples using standard microbiological methods. The modified Kirby-Bauer disc diffusion method was used to test for antibiotic susceptibility, and Clinical and Laboratory Standard Institute (CLSI) guidelines were followed for interpretation. The double-disk synergy method was used to confirm the phenotypic identity of ESBL producers, and the results were interpreted in accordance with CLSI guidelines. The phenotypic method was utilized for ESBL screening, employing the standard disk diffusion method. The CTX-M ESBL gene, TEM gene, and SHV gene were found using multiplex PCR. Results revealed that 41 K. pneumoniae isolates were resistant to third-generation Cephalosporins; the isolates showed resistance to ceftazidime in 100% of cases and ceftriaxone in 80.49% of cases respectively. It was determined that 8 (19.51%) of the isolates produced ESBL. Among Klebsiella isolates, the frequencies of the SHV, TEM, and CTX-M genes were 31 (75.61%), 4 (9.76%), and 10 (24.39%), in that order. Four isolates (9.67%) had the SHV, TEM, and CTX-M genes, while eight (19.51%) of the isolates possessed both the SHV and CTX-M genes. This investigation demonstrates high frequency, wide range of patterns and coexistence of ESBL genes in K. pneumoniae isolates from outpatient UTI patients. Although several phenotypic tests have been used for ESBL detection, testing directly for the presence of ESBL genes is always more accurate. The majority of the isolates of Klebsiella pneumoniae ESBL producers had the SHV gene identified.

Weak interaction processes continue to be hot topics in fundamental physics research. In this paper, we briefly review some recent advances in the theoretical study of beta and double-beta decays that include both the nuclear and atomic part of these processes. On the nuclear side, we present a statistical approach for the computation of the nuclear matrix elements (NME) for neutrinoless double-beta (0νββ). A range of NME values, the most probable value for NME, and the associated theoretical uncertainty are given. Correlations with other related observables are shown as well. On the atomic side, we first briefly review the methods used to get the electrons’ wave functions. Further, we use them for the computation of some relevant kinematic quantities such as Fermi functions, electron spectra and angular correlation between the emitted electrons. Then, we present applications of these calculations to the experimental data analysis related to the search of the Lorentz invariance violation in two-neutrino double-beta (2νββ) decay and description of the decay rates and decay rate ratios for allowed and unique forbidden electron capture (EC) processes.

Objectives: Epidemiologic and experimental animal studies have shown that stress can alter tumor growth and that adrenergic fibers from the sympathetic nervous system, acting through stromal β2-adrenergic receptors, promote tumor cell survival during the initial phases of cancer development. Recent epidemiological data suggest that beta blocker intake improves survival of prostate cancer patients. Methods: Signaling mediated by β-adrenergic receptors promotes neuroendocrine differentiation in prostate cancer cell line. Although neuroendocrine cells are a minor population in the epithelial compartment of normal prostate glands, the population of neuroendocrine-like cells that express markers such as SYN, Bcl-2, Dll-3, and AMACR correlates with cancer progression, androgen-independent state, and poor prognosis in prostate cancer patients. As recent studies show that an increase in neuroendocrine cell density occurs before development of benign prostatic hyperplasia (BPH), a non-lethal disease affecting the transition zone, in hypertensive rats, we investigated whether neuroendocrine differentiation is associated with BPH. Results: Our results showed that isobutyl-methyl-xanthine and forskolin leading to sustained activation of the cAMP/PKA pathway led to an increase in neuroendocrine differentiation markers in BPH-1 cell line. Similar results were observed by combining the β-adrenergic receptors agonist isoproterenol with forskolin. These treatments reduced BPH-1 cell proliferation rates by 40% and 60%, respectively. Effects on neuroendocrine markers expression and cell proliferation were fully reversed by the β2 blocker carvedilol. Conclusion: These data suggest that β-adrenergic receptors are linked to the development of neuroendocrine-like cells in BPH. As 20% of the prostate cancer tumors occur in this zone, this observation warrants further investigation.

Cardiovascular complications are the major cause of diabetes-related morbidity and mortality. Increased renin-angiotensin-aldosterone system activity and decreased β-adrenergic receptor (β-AR) responsiveness contribute to diabetic cardiac dysfunction. We evaluated the effect of sacubitril/valsartan (neprilysin inhibitor plus angiotensin receptor antagonist combination), and valsartan treatments on the diabetic cardiac function through β-AR responsiveness, and on protein expression of diastolic components. 6-week-old male Sprague-Dawley rats were divided into control, diabetic, sacubitril/valsartan (68 mg/kg), and valsartan treated (31 mg/kg) diabetic groups. Diabetes was induced by high fat diet plus low dose streptozotocin (30 mg/kg, intraperitoneal). After 10 weeks of diabetes, rats were treated for 4 weeks. Systolic/diastolic function was assessed by in vivo echocardiography and pressure-volume loop analysis. β-AR mediated responsiveness was assessed by in vitro papillary muscle and Langendorff heart experiments. Protein expression of sarcoplasmic reticulum calcium ATPase2a, phospholamban, and phosphorylated phospholamban was determined by Western blot. Sacubitril/valsartan improved ejection fraction and fractional shortening to a similar extent as valsartan alone. None of the treatments affected in vivo diastolic parameters or expression of related proteins. β1-/β2-AR mediated responsiveness was partially restored in treated animals. β3-AR mediated relaxation responses were comparable among groups. The beneficial effect of sacubitril/valsartan on systolic function may be attributed to improved β1-/β2-AR responsiveness.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder. A wealth of evidence indicates that the amyloid β (Aβ) aggregates result from dyshomeostasis between Aβ production and clearance, which plays a pivotal role in the pathogenesis of AD. Consequently, therapies targeting Aβ reduction represent a promising strategy of AD intervention. Tetramethylpyrazine nitrone (TBN) is a novel tetramethylpyrazine derivative with the potential for the treatment of AD. Previously, we demonstrated that TBN markedly improved cognitive functions and reduced Aβ, APP, BACE 1 and hyperphosphorylated tau levels in 3 × Tg-AD mice. However, the mechanism by which TBN inhibits Aβ deposition still unclear. In this study, we employed the APP/PS1 mice treated with TBN (60 mg/kg, ig, bid) for six months and N2a/APP695swe cells treated with TBN (300 μM) to explore the mechanism of TBN on the Aβ reduction. Our results indicated that TBN significantly alleviated cognitive impairment and reduced Aβ depositions in APP/PS1 mice. Further investigation of the underlying mechanisms revealed that TBN decreased the expression of APP and BACE1, activated the AMPK/mTOR/ULK1 autophagy pathway and inhibited the PI3K/AKT/mTOR/ULK1 autophagy pathway, as well as decreased the phosphorylation levels of JNK and ERK in APP/PS1 mice. Moreover, TBN was found to significantly reduce the mRNA levels of APP and BACE1, as well as those of SP1, CTCF, TGF-β, and NF-κB, transcription factors involved in regulating gene expression. Additionally, TBN was observed to decrease the level of miR-346 and increase the levels of miR-147 and miR-106a in the N2a/APP695swe cells. These findings indicate that TBN may reduce Aβ levels likely via reducing APP expression by regulating APP gene transcriptional factors and miRNAs, reducing BACE1 expression, and promoting autophagy activities.

Increased norepinephrine (NE) release from the sympathetic nerves during pregnancy in women or animal models, as occurs during stress, modifies the fetal environment and increases flow of NE to the fetus, programing the progeny and affecting its cardiovascular and metabolic function in adulthood. In the present work, gestating rats were exposed to stress during gestation and the female progeny was analyzed for heart and metabolic function. Pregnant Sprague–Dawley rats were exposed to cold stress (4 °C/3 h/day); rats’ female progeny were euthanized at 4, 20 and 60 days old and their hearts evaluated to determine the β-adrenergic receptor (βAR) mRNA, abundance and affinity to agonists and NE concentration. The in vivo response to glucose overload and the arterial pressure response to isoproterenol (ISO, 125 µg/kg weight/day/10 days) were monitored. Results: At 20 and 60 days old, stressed female progeny presented an increase in ventricular weight and no changes in the cardiac NE as compared with their age-matched controls. The β1AR mRNA in control rats decreased between 4 and 20 days of age, but stressed rats maintained 50% higher levels of mRNA as compared with their age-matched controls. This difference was also found in the protein abundance of β1AR. No differences were found at 60 days old. The β2AR mRNA levels were higher than in controls at both 4 and 20 days old, but not expressed in the amount of protein. An increase in the ratio of β1/β2 receptors was found at 20 days old but not at 60 days old. The displacement of 3H-dihydroalprenolol (DHA) from a membrane fraction with propranolol (β antagonist) showed decreased affinity (at 60 days old) but no changes in the βAR number. In vivo exposure to ISO induced a β-adrenergic overload and provoked death in 40% of stressed females by day 3 of ISO treatment. Regarding metabolic function, we found that stressed rats presented insulin resistance when adults. These data suggest permanent changes to the heart’s adrenergic response and metabolic function after rat progeny were stressed in the uterus.

Thalassemia syndromes are common monogenic disorders that represent a significant global health issue. No systematic epidemiological and molecular investigations on thalassemias in Croatian population have been reported to date. This prospective study included 70 children with a presumptive diagnosis of thalassemia, and their 42 first-degree relatives. Molecular characterization was performed using direct sequencing and gap-PCR methods. We identified 46 (30 children and 16 first-degree relatives) β-thalassemia heterozygous carriers from 24 unrelated families, carrying eight different mutations and one hemoglobin variant. Five variants account for approximately 85% of all affected β-globin alleles: Hb Lepore-Boston-Washington (32,6%), HBB: c.93-21G>A (19,6%), HBB:c.315+1G>A (13,1%), HBB:c.92+1G>A (10,9%), and HBB:c.92+6T>C variant (8,7%). A need for more detailed genetic profiling of β-thalassemia carriers is emphasized since genetic modifiers can significantly impact their phenotype. Our study provides important new insights into the relevance of β-thalassemia heterozygosity in the pediatric clinical practice.

Based on a rich data set of recoveries donated by a debt collection business, recovery rates for non-performing loans taken from a single European country are modelled using linear regression, linear regression with Lasso, beta regression and inflated beta regression. We also propose a two-stage model: beta mixture model combined with a logistic regression model. The proposed model allows us to model the multimodal distribution we find for these recovery rates. All models are built using loan characteristics, default data and collections data prior to purchase by the debt collection business. The intended use of the models is to estimate future recovery rates for improved risk assessment, capital requirement calculations and bad debt management. They are compared using a range of quantitative performance measures under K-fold cross validation. Among all the models, we find that the proposed two-stage beta mixture model performs best.

The objective of this study was to perform a systematic review and meta-analysis of the articles that addressed the effect BA or carnosine supplementation on physical exercise (PE)-induced oxidative stress (OS). Before May 2018 we searched throughout PubMed, CAPES Periodic and SPORTDiscus human model peer review, randomized control studies with chronic BA or carnosine supplementation on PE-induced OS. A total of 128 citations were found. Only four articles met criteria for inclusion. All four studies used healthy young sedentary, recreationally active or athletic participants. After a chronic BA or carnosine supplementation, the studies evaluated PE-induced OS both immediately and several hours after exercise (0.5 to 48 h). In response to PE-induced OS, when compared to placebo, BA/carnosine supplementation increased total antioxidant capacity [TAC; Effect Size (ES) = 0.35, 95% Confidence Interval (CI) 0.06 to 0.65, p = 0.02] and glutathione (GSH; ES = 0.75, 95% CI 0.32 to 1.19, p = 0.0007) concentrations while decreased direct OS markers (ES = −1.19, 95% CI −1.48 to −0.80, p < 0.01) and superoxide dismutase (SOD) activity (ES = − 0.58, 95% CI −1.10 to −0.06, p = 0.03). BA or carnosine supplementation did not prevent the increase in indirect OS markers (ES: 0.06, 95% CI −0.38 to 0.500, p = 0.80). In humans, following PE-induced OS, initial treatment trials of BA or carnosine supplementation seemed to increase TAC and GSH concentrations, while decreasing SOD activity. Also, albeit mitigating the acute increase in direct OS markers (reactive nitrogen and oxygen species), treatment did not decrease measured values of indirect OS markers (peroxidation or molecule oxidation).

The focus was on developing machine learning models to predict the IC50 values of the compound OTX015 using gene expression levels of cancer cell lines. Through regression-based machine learning models, particularly the SVM model, trained on pre-laboratory data, consistent and generalizable performance with low error scores was achieved. These models underwent enhancement via hyperparameter optimization and were tested on validation data. The results indicate the utility of machine learning in drug discovery processes and personalized medicine, offering rapid and cost-effective predictions of IC50 values. However, for enhanced reliability, further model development, data gathering, and evaluation with diverse compounds are recommended. In conclusion, this research demonstrates the potential of machine learning approaches to optimize experimental processes, reduce costs, and contribute to personalized treatments in healthcare by accurately predicting compound responses.

Yaba monkey tumor virus (YMTV) and Tanapox virus (TPV) are members of the Yatapoxvirus genus and can infect humans and other primates. Despite the threat posed by yatapoxviruses, the factors determining their host range are poorly understood. In this study, we analyzed the ability of YMTV and TPV orthologs of vaccinia virus K3 (called 012 in YMTV and TPV), which share 75% amino acid identity with one another, to inhibit PKR from 15 different primate species. We first used a luciferase-based reporter, and found that YMTV and TPV K3 orthologs inhibited PKR in a species-specific manner and showed distinct PKR inhibition profiles. TPV 012 inhibited PKR from 11 primates, including human, substantially better than YMTV 012. In contrast, both K3 orthologs inhibited the other four primate PKRs comparably well. Using YMTV 012 and TPV 012 hybrids, we mapped the region responsible for the differential PKR inhibition to the C- terminus of the K3 orthologs. Next, we generated chimeric vaccinia virus strains to investigate whether TPV K3 and YMTV K3 orthologs could rescue replication of a vaccinia virus strain that lacks PKR inhibitors K3L and E3L. Virus replication in primate-derived cells generally correlated with the patterns observed in the luciferase-based assay. Together, these observations demonstrate that yatapoxvirus K3 orthologs have distinct PKR inhibition profiles and inhibit PKR in a species-specific manner, which may contribute to the differential susceptibility of primate species to yatapoxvirus infections.

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to the imbalance in samples dataset, as well as the complexity and laboriousness of annotating and acquiring target image masks. In order to solve these problems, a method based on sample and mask auto-generation for deep generative network models is proposed. We first generate an augmented dataset of negative samples using a generative adversarial network(GAN), and then highlight the defect regions in these samples using the training method constructed by the GAN to generate masks for the defect images automatically. Experimental results shows the effectiveness of our proposed method, as it allows for the simultaneous generation of LCD image samples and their corresponding image masks. Through a comparative experiment on the deep learning method Mask R-CNN, we demonstrate that the automatically obtained image masks have high detection accuracy.

The purpose of this study was to determine the income, costs and revenue of the Gontor Putri 3 bakery. Want to know the efficiency of the bakery business in Karangbanyu Regency. The method used in this research is analytical descriptive by conducting a survey. The data used in this research is primary data. Data collection techniques use observation, interviews and documentation, while the process of analysis is quantitative descriptive. Using the R/C ratio, a value of 1.72 per month is obtained. This value indicates that the bakery factory in Karangbanyu is efficient because the value is more than one.

Revenue-sharing (RS) contracts are a common approach to incentivize innovation of upstream suppliers by addressing the uneven profit distribution between upstream and downstream firms. Considering the possible overconfidence characterizing decision makers in the supply chain, we investigate the effect of the RS contract and the tendency of overconfidence of supply chain members on the investment in R&D of key components of products in the context of an upstream supplier that is the leader in the R&D and production of key components. We find that regardless of the bargaining power of either party, a RS contract can increase the R&D investment in key components. Regarding the effects of overconfidence of either downstream manufacturer or up-stream supplier, it can increase the R&D investment in key components. Supplier (manufacturer) overconfidence can harm their own profits but increase the profits of the manufacturer (supplier), and when the level of overconfidence is below a certain threshold, the damage to their own profits is less than the increase in each other's profits, thus benefiting the whole supply chain. In addition, we also find a joint effect of RS contracts and overconfidence: when the bargaining power of the supplier is low, the RS contract has a certain compensatory effect on the loss of their own profits caused by overconfidence.

The circular economy (CE) has emerged as a viable alternative for tackling the problems caused by rising consumption, including solid waste (SW). The present study conducted a meta-analysis of research published between 2012 and 2022 on CE and solid waste management (SWM). A bibliometric analysis was used from the Web of Science (WoS) and Scopus databases. By studying the articles, we briefly discussed the connections between them and how one contributes to the evolution of the other. Some findings point to greater collaboration between Italy and Bolivia, followed by China and Malaysia. However, they move away from the traditional axes as the United States and Canada. In addition, it was found that the adoption of reuse and selective collection, in fact, allow the reduction of the volume of discarded materials. In this way, it was possible to conclude that a greater connection between CE and GRS makes it possible to optimize the useful life of landfills through the treatment of organic waste and recycling, to encourage waste picker cooperatives and selective collection programs, and to reduce the financial costs of the system as a whole, making it more durable and sustainable.

Low-resource languages often face the problem of insufficient data, which leads to poor quality in machine translation. One approach to address this issue is data augmentation. Data augmentation involves creating new data by transforming existing data through methods such as flipping, cropping, rotating, and adding noise. Traditionally, pseudo-parallel corpora are generated by randomly replacing words in low-resource language machine translation. However, this method can introduce ambiguity as the same word may have different meanings in different contexts. This study proposes a new approach for low-resource language machine translation, which involves generating pseudo-parallel corpora by replacing phrases. The performance of this approach is compared with other data augmentation methods, and it is observed that combining it with other data augmentation methods further improves performance. To enhance the robustness of the model, R-Drop regularization is also used. R-Drop is an effective method for improving the quality of machine translation. The proposed method was tested on Chinese-Kazakh (Latin script) translation tasks, resulting in performance improvements of 4.99 and 7.7 for Chinese-to-Kazakh and Kazakh-to-Chinese translations, respectively.

The aim of this study, for determination of verteporfin in real samples (simulated body fluid, and simulated tears, 0.9% isotonic sodium chloride solution, Lactated Ringer IV solution for infusion, 5% dextrose IV solution for infusion, lemon juice and drinking water) was the method validation and to examined by HPLC-DAD-UV. Metod validation parameters such as specificity, linearity, precision, accuracy, robustness, limit of detection (LOD) and limit of quantitation (LOQ) for verteporfin were validated and developed according to the International Conference on Harmonization (ICH) Q2 R1 guidelines. The LOD and LOQ for verteporfin were found 0.06 µg/L and 0.2 µg/L, respectively. The recovery values of the optimization and validation for verteporfin were found in the range of 97.5-100.7%. The relative standard deviations (RSD) for vertepofin were <1%. The developed method was successfully applied to real samples with high accuracy and the recoveries (%) from real samples were 99.9, 100, 98.2, 99.2, 99.4, 98.8 and 99.4, respectively.

Crocodilepox virus (CRV) belongs to the Poxviridae family and mainly infects hatchling and juvenile Nile crocodiles. Most poxviruses encode inhibitors of the host antiviral protein kinase R (PKR), which is activated by viral double-stranded (ds) RNA formed during virus replication, resulting in the phosphorylation of eIF2 and subsequent shutdown of general mRNA translation. Because CRV lacks orthologs of known poxviral PKR inhibitors, we experimentally characterized one candidate (CRV157), which contains a predicted dsRNA-binding domain. Bioinformatic analyses indicated that CRV157 evolved independently from other poxvirus PKR inhibitors. CRV157 bound to dsRNA, co-localized with PKR in the cytosol, and inhibited PKR from various species. To analyze whether CRV157 could inhibit PKR in the context of a poxvirus infection, we constructed recombinant vaccinia virus strains that contain either CRV157 or a mutant CRV157 deficient in dsRNA binding in a strain that lacks PKR inhibitors. The presence of wild type CRV157 rescued vaccinia virus replication, while the CRV157 mutant did not. The ability of CRV157 to inhibit PKR correlated with virus replication and eIF2alpha phosphorylation. The independent evolution of CRV157 demonstrates that poxvirus PKR inhibitors evolved from a diverse set of ancestral genes in an example of convergent evolution.

In this article we have presented a new perception of herd immunity threshold (HIT) which considers that only a “band of population” are susceptible to any pathogenic infection. This is termed as the “effective herd immunity threshold” (EHIT) and the progression of the disease (caused by this pathogenic infection) is mainly determined by this EHIT value. We have argued here that this EHIT value (considering the immunity band picture in the population) will be substantially lower than the estimated canonical HIT values obtained from various existing models. We propose that the actual prediction of the disease progression should now be calculated using the EHIT values.

Inspired by the work of S. D. Odintsov and V. K. Oikonomou, Phys. Rev. D 92, 024016 (2015) [1], the present study reports a reconstruction scheme for f (R) gravity with the scale factor a(t) µ (t _* - t) _c²²describing the pre-bounce ekpyrotic contraction, where t is the big crunch time. The reconstructed f (R) is used to derive expressions for density and pressure contributions and the equation of state parameter resulting from this reconstruction is found to behave like "quintom". It has also been observed that the reconstructed f (R) has satisfied a sufficient condition for a realistic model. In the subsequent phase the reconstructed f (R) is applied to the model of chameleon scalar field and the scalar field f and the potential V(f) are tested for quasi-exponential ex pansion. It has been observed that although the reconstructed f (R) satisfies one of the sufficient conditions for realistic model, the quasi-exponential expansion is not available due to this reconstruction. Finally, the consequences pre-bounce ekpyrotic inflation i n f (R) gravity are compared to the background solution for f (R) matter bounce.

The crux of the paper is to present a detailed analysis of COVID-19 data which is available on global basis. This analysis is performed using some specific package of R software. It provides various insights from the data and help to understand the current status of this pandemic in India so that effective measures can be formulated by policymakers. These insights include global summary of this disease, growth rate of this pandemic and performance of SIR model for the given global data. The analysis has been presented in different tables and graphs to understand the outputs of the problem in a more detailed point of view.

Collisions of low energy electrons with molecules are important for understanding many aspects of the environment and technologies. Understanding the processes that occur in these types of collisions can give insights into plasma etching processes, edge effects in fusion plasmas, radiation damage to biological tissues and more. A radical update of the previous expert system for computing observables relevant to these processes, Quantemol-N, is presented. The new Quantemol Electron Collision (QEC) expert system simplifyies the user experience, improving reliability and implements new features. The QEC GUI interfaces the Molpro quantum chemistry package for molecular target setups and to the sophisticated UKRmol+ codes to generate accurate and reliable cross-sections. These include elastic cross-sections, super elastic cross-sections between excited states, electron impact dissociation, scattering reaction rates, dissociative electron attachment, differential cross-sections, momentum transfer cross-sections, ionization cross sections and high energy electron scattering cross-sections. With this new interface we will be implementing dissociative recombination estimations, vibrational excitations for neutrals and ions, and effective core potentials in the near future.

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming.

We present a methodology to enable users to interact with statistical information owned by an institution and stored in a cloud infrastructure. Mainly based on R, this approach was developed following the open-data philosophy. Also, since we use R, the implementation is mainly based on open-source software. R gives several advantages from the point of view of data management and acquisition, as it becomes a common framework that can be used to structure the processes involved in any statistical operation. This simplifies the access to the data and enable to use all the power of R in the cloud information. This methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to other institutions to enable open access to its data. The infrastructure also was deployed to a cloud infrastructure, to assure the scalability and a 24/7 access.

The exceptional increase in molecular DNA sequence data in open repositories is mirrored by an ever-growing interest among evolutionary biologists to harvest and use those data for phylogenetic inference. Many quality issues, however, are known and the sheer amount and complexity of data available can pose considerable barriers to their usefulness. A key issue in this domain is the high frequency of sequence mislabelling encountered when searching for suitable sequences for phylogenetic analysis. These issues include the incorrect identification of sequenced species, non-standardised and ambiguous sequence annotation, and the inadvertent addition of paralogous sequences by users, among others. Taken together, these issues likely add considerable noise, error or bias to phylogenetic inference, a risk that is likely to increase with the size of phylogenies or the molecular datasets used to generate them. Here we present a software package, phylotaR, that bypasses the above issues by using instead an alignment search tool to identify orthologous sequences. Our package builds on the framework of its predecessor, PhyLoTa, by providing a modular pipeline for identifying overlapping sequence clusters using up-to-date GenBank data and providing new features, improvements and tools. We demonstrate our pipeline’s effectiveness by presenting trees generated from phylotaR clusters for two large taxonomic clades: palms and primates. Given the versatility of this package, we hope that it will become a standard tool for any research aiming to use GenBank data for phylogenetic analysis.

Radar altimetry provides valuable measurements to characterize the state and the evolution of the Antartica and Greenland ice sheet cover. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential capacity of complementing the dedicated radar altimeters incrementing the temporal and spatial resolution of the surface height measurements. In this work we perform an study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission, designed primarily to provide sea state information, like sea surface roughness or wind, but not altimetric products. The data has been analyzed with altimetric methodologies, already proved in aircraft based experiments, to extract signal delay observables to be used to infer the topography of the Greenland cover. The penetration depth of the GNSS signals into ice has also considered. The topographic signal obtained is consistent with those obtained with other passive or active microwave sensors. The main conclusion derived from this work is that GNSS-R also provides valuable measurements of the ice sheet cover and, as taken at a variety of geometries and at least two frequency bands, they prospect different depths into the ice. They have thus potential to complement our understanding of the ice firn and its evolution.

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

The main objective of this paper is to introduce a further extension of extended (p, q)-beta function by considering two Mittag-Leffler function in the kernel. We investigate various properties of this newly defined beta function such as integral representations, summation formulas and Mellin transform. We define extended beta distribution and its mean, variance and moment generating function with the help of extension of beta function. Also, we establish an extension of extended (p, q)-hypergeometric and (p, q)-confluent hypergeometric functions by using the extension of beta function. Various properties of newly defined extended hypergeometric and confluent hypergeometric functions such as integral representations, Mellin transformations, differentiation formulas, transformation and summation formulas are investigated.

Beta thalassemia is an inherited blood disorder that results in inefficient erythropoiesis due to genetic mutation that leads to reduction or absence of the hemoglobin beta-globulin protein. Approximately 8.5% of UAE residents suffer from β-thalassemia, a significant health and financial problem. The treatment options available for β-Thalassemia major are limited and associated with a wide range of complications. β-thalassemia gene therapy is emerging as a potential novel treatment option that eliminates the complications caused by the current long-term treatment modalities and the associated economic burden. This paper reviews the scientific literature related to emerging gene-therapy for β-Thalassemia by analyzing all the articles published from January 2010 to December 2023 in the English language on Databases like PubMed, Scopus, ProQuest, and CINAHL. The use of gene therapy has demonstrated promising outcomes for a permanent cure of β-Thalassemia. ZYNTEGLO (Betibeglogene autotemcel) is the only cell-based gene therapy which was approved by the FDA on 19th August, 2018. To conclude, Gene therapy is an innovative solution. It demonstrates a promising future, but does come with its own set-backs and is something that must be tackled in-order to revolutionize it in the medical world. FDA approved ZYNTEGLO is a potentially one-time curative treatment for β-Thalassemia. Although cutting-edge, its use is limited because of the high cost; a price of $2.8million per patient.

A new generalization of extended beta function and its various properties, integral representations and distribution are given in this paper. In addition, we establish the generalization of extended hypergeometric and con uent hypergeometric functions using the newly extended beta function. The properties these extended and con uent hypergeometric functions such as integral representations, Mellin transformations, dif- ferentiation formulas, transformation and summation formulas are also investigated.

Gender and biological sex have distinct impacts on the pathogenesis of type 2 diabetes (T2D). Estrogen deficiency is known to predispose female mice to T2D. In our previous study, we found that high-fat, high-sucrose diet (HFHSD) induces T2D in male mice through the miR-10b-5p/KLF11/KIT pathway, but not in females, highlighting hormonal disparities in T2D susceptibility. However, the underlying molecular mechanisms of this hormonal protection in females remain elusive. To address this knowledge gap, we utilized ovariectomized, estrogen-deficient female mice, fed them a HFHSD to induce T2D, and investigated the molecular mechanisms pathway in estrogen-deficient diabetic female mice, cell lines, and patients with T2D in female. Initially, female mice fed a HFHSD exhibited delayed onset of T2D, but ovariectomy-induced estrogen deficiency promptly precipitated T2D without delay. Intriguingly, insulin (INS) was upregulated, while insulin receptor (INSR) and protein kinase B (AKT) were downregulated in these estrogen-deficient diabetic female mice, indicating insulin-resistant T2D. These dysregulations of INS, INSR, and AKT were mediated by a miR-10a/b-5p-NCOR2 axis. Treatment of miR-10a/b-5p effectively alleviated hyperglycemia in estrogen-deficient T2D female mice, while β-estradiol temporarily reduced hyperglycemia. Consistent with the murine findings, plasma samples from female T2D patients exhibited significant reductions in miR-10a/b-5p, estrogen, and INSR, but increased insulin levels. Our findings suggest that estrogen protect against insulin-resistant T2D in females through miR-10a/b-5p/NCOR2 pathway, indicating the potential therapeutic benefits of miR-10a/b-5p restoration in female T2D management.

A surge of b-phenylethylamine (PEA), an endogenous monoamine found in traces in the human brain and naturally present in chocolate, has been commonly associated with romantic love earning it the nickname of “love molecule”. The origin of this association must be traced to a speculation dating back to the early eighties that has over time become something of a factoid, reaching a large diffusion through the sharing phenomenon of the Internet. What is disputed in this paper is the existence of any direct biochemical or physiological evidence of the role of PEA in any of the phases of romantic love in the human species. The actual and possible roles of PEA in human physiology are reviewed.

Hemoglobinopathies are a group of disorders in which the hemoglobin molecule has abnormal production or structure. The hemoglobin molecules in red blood cells (RBC) are impacted by the blood disease known as sickle cell disease (SCD), and Thalassemia is one of the major monogenic disorders that reduces hemoglobin production( Kohne et al ., 2011). This disorder results in a large number of red blood cells being destroyed, leading to anemia. India bears a huge burden of hemoglobinopathies; thalassemia is the most prevalent (Mondal SK et al., 2016). A key component of thalassemia prevention is a successful screening procedure to identify Thalassemia carriers. Effective screening programs have numerous obstacles, especially in environments with limited resources. Machine learning (ML) has been used to solve technical and domain-specific problems in a variety of prognostic and diagnostic medical jobs. In this work, we aimed to identify and analyze the most common mutation of β--thalassemia and sickle cell disease from the north Indian population by employing Machine learning-based algorithms. To accurately predict the carrier state from a simple blood test, and to predict pathogenic hemoglobin variants in a group of individuals, these results demonstrate the application of integrated bioinformatics and machine learning approaches. This study contributes to the validation of the models based on data from several individuals and hemoglobinopathies.

Background: Cutaneous melanoma arises from skin melanocytes and has a high risk of metastatic spread. Despite better prevention, earlier detection, and the development of innovative therapies melanoma incidence and mortality increase annually. Major clinical risk factors for melanoma include fair skin, an increased number of nevi, the presence of dysplastic nevi, and a family history of melanoma. However, several external inducers seem to be associated with melanoma susceptibility such as environmental exposure, primarily unprotected sun experience, alcohol consumption, and heavy metals. In recent years, epidemiological studies have highlighted a potential risk of β-hexachlorocyclohexane (β-HCH), the most studied organochlorine pesticide, on cancer induction including melanoma. Methods: We evaluated in vitro the impact of this pollutant on epidermal and dermal cells, attempting to describe mechanisms that could render cutaneous cells more prone to oncogenic transformation. Results: We demonstrated that β-HCH impacts melanocyte biology with a highly cell-type specific signature that involves perturbation of AKT/mTOR and Wnt/β-catenin signaling, and AMPK activation that converges in lowering energy reserve, cell proliferation, and pigment production. Conclusion: In conclusion, long-term exposure to persistent organic pollutants damages melanocyte metabolism in the function of the melanin content with a consequent reduction of melanogenesis indicating a potential augmented skin cancer risk.

We discuss the issues with tentative generalisations of the process matrix formalism from finite-dimensional mechanical systems all the way to quantum field theory. We present a detailed overview of possible open problems that arise when one attempts to move from particle ontology into the realm of field ontology, i.e., when one transitions from mechanics to field theory framework. These issues need to be addressed, and problems solved, if one aims to expand the scope of applicability of the process matrix formalism, and therefore its usefulness. This is far from a trivial and straightforward endeavour, but rather a task for a whole future research programme.

Background and Objectives: Stroke is a main leading cause for mortality and morbidity worldwide. Treat-ment of this pathology is still under development and its risk factors remain the main target to be reached. Therefore, we aim to determine the role of interleukin 1 beta in atheromatosis, as risk factor for stroke and the reole of this biomarker in stroke prognosis. Materials and Methods: The study conducted enrolled 56 patients diagnosed with ischemic stroke in the anterior (AVT) and posterior vascular territory (PVT). All patients had venous blood collected at admission and 7 days after the onset of the cerebral ischemia in order to determine plasma concentration for interleukin 1 beta. At the same time an extracranial carotid ultrasound was performed. Results: Interleukin 1 beta collected at admission was positively correlated with NIHSS at admission (Pearson index 0,424) and both measurements were corelated with carotid stenosis (Spearmen correlation index 0,529, respectively 0,653). Conclusion: Interleukin 1 beta could be a reliable biomarker for stroke prognosis and carotid atheromatosis development.

Beta-carotene is a fat-soluble antioxidant commonly found in foods such as fruits, vegetables, and palm oil. Despite various liquid chromatography methods are proposed to detect and measure the sera carotenoid level, a long retention time to elute this marker is needed. This study attempted to develop a rapid reverse phase method in eluding beta-carotene in human sera. The researchers managed to elute the antioxidant in 2.2 minutes by applying a combination of a C8 column, mobile phase comprising of acetonitrile mixed with methanol in 70:30 proportion, and an ultra-high performance liquid chromatography system. The outputs had a good calibration curve (R²=0.959) and low coefficient of variation (0.2%), suggesting this protocol is reliable. A column with a lower carbon chain such as C8 allows the beta-carotene molecule to flow through the column faster. Besides, selecting solvents with high elution strength coupled with an ultra-high performance liquid chromatography system which equipped with high pressure can force the beta-carotene through the column in a shorter duration compared to previous reported methods. Therefore, it is recommended to adopt this protocol in epidemiological studies where beta-carotene is screened as a dietary biomarker associated with disease of interest by using human sera in the population level.

As the globe becomes more urban, the question how much natural biodiversity can subsist in cities becomes increasingly urgent to answer, and also how is urban diversity structured? To contribute to an answer, we studied the metacommunity of bees in a North European metropolitan area. The system consisted of 13 sites in the city of Aarhus, Denmark, censused from April to September during one year. Bees were sampled monthly in pan traps and a set of traits was related to their presence. In total, 40 species were collected–29 solitary species (40% of all sampled individuals), ten Bombus species (28%), and Apis mellifera (32%). Most sampled bees were soil-nesting, pollen generalists, and relatively common. Habitat diversity within a set of concentric circles with trap as centre and radius from 50 m to 1000 m was related to bee a diversity per site (total bee spp. with and without honeybee, solitary bees, and bumblebees). The relationship was only significant within the 1,000 m circle, and solitary bee diversity did not even correlate with habitat diversity at this large spatial scale level. The bee-site (space) and bee-month (time) networks were analyzed with respect to nestedness, modularity, and spatio-temporal b diversity. The two networks were weakly nested and strongly modular, being composed of five and six modules of tightly linked bees. Total b diversity, b_TOTAL, is the sum of species turnover, b_TURN, and species loss/gain or nestedness, b_NEST; and for both space and time, b_TURN was more important than b_NEST. Furthermore, b_TOTAL was higher than season b_TOTAL. Thus, the urban bee metacommunity was well-structured in both space and time and the high b_TURN indicated, that the network was strongly modular. We suggest the main reason is the high spatio-temporal patchiness of habitats, sustaining many unique species.

Nowadays, we can observe a worldwide trend towards the development of synthetic biomaterials. Numerous researches have been carried out in order to better understand the cellular behavior involved in the inflammation and bone healing processes related to living tissues. The aim of this study is to evaluate the tissue behavior of two different types of biomaterials: synthetic nano-hydroxyapatite / beta-tricalcium phosphate and hydroxyapatite in non-critical bone defects in rat calvaria. Twenty four rats underwent surgery in which two 3 mm defects in each cavity were performed. The rats were divided into 2 groups: Group 1, using xenogen hydroxyapatite (Bio oss ™); Group 2, using synthetic nano-hydroxyapatite / beta-tricalcium phosphate (Blue Bone ™). Sixty days after the surgery, the calvaria bone defect was filled with biomaterial, the animals were sacrificed and marked with Masson's trichrome and PAS staining, and immunohistochemistry (TNF-α, MMP-9) and electron microscopy analyzes were performed. Histomorphometric analysis indicates a greater presence in the protein matrix in Group 2, in addition to higher levels of TNF-α, MMP-9. The ultrastructural analysis shows an association of material with fibroblasts in the tissue regeneration stage. Paired statistical data indicates that Blue Bone ™ can improve bone formation / remodeling when compared to biomaterials of xenogenous origin.

This review was carried out to identify different beta-lactamase resistance genes reported in published literature from Nigeria and to determine the proportion estimates of the important beta-lactamase resistance genes in Nigeria. Sixty-three (63) articles were included in this review based on the eligibility criteria. All the beta-lactamases reported were detected from the Gram-negative bacteria, most especially from Enterobacteriaceae (n=53). Thirty-six different beta-lactamase genes have been reported from Nigeria. These genes belong to the narrow-spectrum, AmpC, extended-spectrum, and carbapenemase beta-lactamase resistance genes. Eight (8) genes (bla_DHA, bla_CTXM-1, bla_CTXM-14, bla_GES-1, bla_VEB-1, bla_OXA-1, bla_OXA-2, and bla_TEM-1) were shared between animals and humans, 5 genes (bla_SHV-1, bla_SHV-2, bla_SHV-11, bla_SHV-12, and bla_NDM-1) were common to both humans and environment while none of the genes was unique to both animals and environment. Four genes including bla_CMY, bla_TEM-1, bla_AmpC, and internationally pandemic bla_CTXM-15 gene were unique to animals, humans, and the environment. No carbapenemase gene was reported from animals yet. The pooled proportion estimate of ESBL genes in Nigeria was 31% (95% CI: 26-36%, P<0.0001), while the estimate of bla_CTXM-15 gene in Nigeria was 46% (95% CI: 36-57%, P<0.0001). The proportion estimate of AmpC genes was 32% (95% CI: 11-52%, P<0.001), while the estimate for carbapenemases was 8% (95% CI: 5-12%, P<0.001). This study has provided information on the beta-lactamases distribution in Nigeria. This is necessary for a better understanding of molecular epidemiology of clinically important beta-lactamases especially the extended-spectrum beta-lactamases and carbapenemases in Nigeria.

Beta thalassemia major (β-TM) disorder characterized by the lack, or severe reduction in the production of hemoglobin β-globin chains. The standard protocol for the management of β-TM is blood transfusion and iron chelation therapy to reduce the iron overload state. The present study aimed to investigate the relationships between two iron regulatory hormones, hepcidin (HEPC) and erythroferrone (ERFE) levels and iron status parameters (ISPs) in Iraqi patients with β-TM. ISPs and hormones were measured in sixty patients and compared with thirty healthy controls. The results indicated significant changes in different iron status parameters, while ferritin (FRT) with the ~11 fold increase showed the most change. Significant reduction in HEPC and increase in ERFE levels were detected in patients as compared to the control group, while no direct correlation was identified with the other measured ISPs. Receiver operating characteristic (ROC) analysis showed that the z-score of the composite of ERFE+FRT has a full diagnostic ability for β-TM. In conclusion, our finding indicated the correlation between different ISPs, FRT as the leading predictor of iron overload and tow main iron regulatory hormones.

The stock beta coefficient literature extensively discusses the proper methods for the estimation of beta as well as its use in asset valuation. However, there are relatively few references with respect to the appropriate time horizon that investors should utilize when evaluating the risk-return relationship of a stock. We examine the appropriate time horizon for beta estimation differentiating our results by sector according to the Industry Classification Benchmark. We employ data from the NYSE and we estimate varying lengths of beta employing data from 30 to 250 trading days. The constructed beta series is then examined for the presence of breaks using the endogenous structural break literature. Results show evidence against the use of betas that employ more than 90 trading days of data provisional to the sector under study.

Cholesterol, a crucial component of cell membranes, influences various biological processes, including membrane trafficking, signal transduction, and host-pathogen interactions. Disruptions in cholesterol homeostasis have been linked to congenital and acquired conditions, including neurodegenerative disorders such as Alzheimer’s disease (AD). Previous research from our group has demonstrated that herpes simplex virus type I (HSV-1) induces an AD-like phenotype in several cell models of infection. This study explores the interplay between cholesterol and HSV-1-induced neurodegeneration. The impact of cholesterol was determined by modulating its levels with methyl-beta-cyclodextrin (MβCD) using the neuroblastoma cell lines SK-N-MC and N2a. We have found that HSV-1 infection triggers the intracellular accumulation of cholesterol in structures resembling endolysosomal/autophagic compartments, a process reversible upon MβCD treatment. Moreover, MβCD exhibits inhibitory effects at various stages of HSV-1 infec-tion, underscoring the importance of cellular cholesterol levels not only in the viral entry pro-cess but also in subsequent post-entry stages. MβCD also alleviated several features of AD-like neurodegeneration induced by viral infection, including lysosomal impairment and intracellu-lar accumulation of amyloid-beta peptide (Aβ) and phosphorylated tau. In conclusion, these findings highlight the connection between cholesterol, neurodegeneration, and HSV-1 infection, providing valuable insights into the underlying mechanisms of AD.

Significant Wave Height(SWH) is a crucial parameter in oceanographic research, essential for understanding various marine and atmospheric processes. Traditional methods for obtaining SWH, such as ship-based and buoy measurements, face limitations like limited spatial coverage and high operational costs. With the advancement of Global Navigation Satellite Systems reflectometry(GNSS-R) technology, a new method for retrieving SWH has emerged, demonstrating promising results. This study utilizes Radio occultation sounder(GNOS) data from the FY-3E satellite and incorporates the latest Vision Transformer(ViT) technology to investigate GNSS-R-based SWH retrieval. We designed and evaluated various deep learning models, including ANN-Wave, CNN-Wave, Hybrid-Wave, Trans-Wave, and ViT-Wave. Through comparative training using ERA5 data, the ViT-Wave model was identified as the optimal retrieval model. The ViT-Wave model achieved an Root Mean Square Error(RMSE) accuracy of 0.4052 meters and Mean Absolute Error(MAE) accuracy of 0.2700 meters, significantly outperforming both traditional methods and newer deep learning approaches utilizing Cyclone Global Navigation Satellite Systems(CYGNSS) data. These results underscore the potential of integrating GNSS-R technology with advanced deep learning models to enhance SWH retrieval accuracy and reliability in oceanographic research.

A Brewer Spent Grain (BSG), the most abundant by-product of the brewing process, is mainly used in animal feed and biogas production. The aim of the present work is BSG valorization by yeast fermentation to produce carotenoids. R. mucilaginosa CBS316 was cultured on BSG syrups, supplemented or not with YE and PEP (s-Fsa and Fsa). The biomass and carotenoid production were optimized in flasks and then scaled-up in bioreactor. In flask tests, the maximum biomass concentration was 5.3 and 6.2 g/L for Fsa and s-Fsa cultures, respectively. The maximum carotenoid production was 833 μg/L in Fsa and 1159 μg/L in s-FSA. Considering that the highest specific productivity value (P 7.16 μg/g*h) was obtained with Fsa syrup, this medium was selected for the process scale-up. In bioreactor tests, the maximum concentrations of biomass (4.29 g/L) and carotenoid (396 ug/L) was reached at 72 hours of fer-mentation, 24 h later than in flask. The total carotenoid produced was 524 and 150 ug in bioreactor and flask cultures, respectively. The carotenoids production by R. mucilaginosa was obtained both in Fsa and s-Fsa syrups. The results confirm the possibility to use the syrup as it is, Fsa, thus limiting the process costs.

This study aims to analyse whether Chinese companies' R&amp;D investment affects management innovation performance. Also, this dissertation defines management innovation as diversification strategies such as technology and industry diversification and analyzes the impact of these diversification strategies. In particular, this paper analyzes whether R&amp;D investment leads to technology and industry diversification and whether technology diversification creates a mediating effect in the process of R&amp;D investment leading to industry diversification. The analysis results can be summarized as follows: First, R&amp;D investment showed a significant positive relationship with industry diversification. Second, R&amp;D investment shows a significantly positive relationship with technology diversification. Third, technology and industry diversification showed a positive relationship. Fourth, this study examined the mediating role of technology diversification, and it was confirmed that technology diversification plays a mediating role in the effect of R&amp;D investment on industry diversification. R&amp;D investment and business innovation play a key role in the sustainable development of enterprises, and the findings of this paper have important reference value for enterprises' R&amp;D investment decision-making. The results of this study provide the following implications that Chinese companies improve business innovation performance by increasing their R&amp;D investment, promoting innovative R&amp;D, and improving technology diversification and industry diversification strategies.

We investigate the impact of incoming nuclear data on the predictions of the neutron star (NS) stripping model for short gamma-ray bursts. The main area to which we pay attention is the NS crust. We show that the uncertain properties of the NS equation of state can significantly influence the stripping time tstr, the main dynamical parameter of the model. Based on the known time delay (tstr≈1.7s) between the peak of the gravitational wave signal GW170817 and the detection of gamma photons from GRB170817A, we obtain new restrictions on the nuclear matter parameters, in particular, the symmetry energy slope parameter: L&lt;114.5MeV. In addition, we study the process of nucleosynthesis in the outer and inner crusts of a low-mass NS. We show that the nucleosynthesis is strongly influenced by both the incoming nuclear data and the equation of state of the NS matter.

We analyze the behavior of relativistic spherical objects within the context of modified $f(R,T)$ gravity considering Tolman VI spacetime, where gravitational lagrangian is a function of Ricci scalar(R) and trace of energy momentum tensor(T) i.e,$ f(R,T)= R+ 2\beta T$, for some arbitrary constant $\beta$. For developing our model, we have chosen $\pounds_{m} = -p$, where $ \pounds_{m}$ represents matter lagrangian. For this investigation, we have chosen three compact stars namely PSR J1614-2230 [Mass=(1.97$\pm$ 0.4)M$_\odot$; Radius= 9.69$_{-0.02} ^{+0.02}$ Km] ,Vela X-1 [Mass=(1.77$\pm$ 0.08)M$_\odot$; Radius= 9.560$_{-0.08} ^{+0.08}$ Km] and 4U 1538-52 [Mass=(9.69)M$_\odot$; Radius= 1.97 Km]. In this theory the equation of pressure isotropy is identical to standard Einstein's theory. So all known metric potential solving Einstein's equations are also valid here. In this paper, we have investigated the effort of coupling parameter ($\beta$) on the local matter distribution. Sound of speed and adiabatic index are higher with grater values of $\beta$ while on contrary mass function and gravitational redshift are lower with higher values of $\beta$ . For supporting the theoretical results, graphical representation are also employed to analyze the physical viability of the compact stars.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

It is a common practice to detect outliers in a financial time series in order to avoid the adverse effect of additive outliers. This paper investigated the performance of GARCH family models (sGARCH; gjrGARCH; iGARCH; TGARCH and NGARCH) in the presence of different sizes of outliers (small, medium and large) for different time series lengths (250, 500, 750, 1000, 1250 and 1500) using root mean square error (RMSE) and mean absolute error (MAE) to adjudge the models. In a simulation iteration of 1000 times in R environment using rugarch package, results revealed that for small size of outliers, irrespective of the length of time series, iGARCH dominated, for medium size of outliers, it was sGARCH and gjrGARCH that dominated irrespective of time series length, while for large size of outliers, irrespective of time series length, gjrGARCH dominated. The study further leveled that in the presence of additive outliers on time series analysis, both RMSE and MAE increased as the time series length increased.

GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the amplitudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the amplitudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.

Diabetic retinopathy (DR), a prevalent complication of diabetes mellitus affecting a significant portion of the global population, has long been viewed primarily as a microvascular disorder. However, emerging evidence suggests that it should be redefined as a neurovascular disease with multifaceted pathogenesis rooted in oxidative stress and advanced glycation end products. The transforming growth factor-β (TGF-β) signaling family has emerged as a major contributor to DR pathogenesis due to its pivotal role in retinal vascular homeostasis, endothelial cell barrier function, and pericyte differentiation. However, the precise roles of TGF-β signaling in DR remain incompletely understood, with conflicting reports on its impact in different stages of the disease. Additionally, the BMP subfamily within the TGF-β superfamily introduces further complexity, with BMPs exhibiting both pro- and anti-angiogenic properties. Furthermore, TGF-β signaling extends beyond the vascular realm, encompassing immune regulation, neuronal survival, and maintenance. The intricate interactions between TGF-β and reactive oxygen species (ROS), non-coding RNAs, and inflammatory mediators have been implicated in the pathogenesis of DR. This review delves into the complex web of signaling pathways orchestrated by the TGF-β superfamily and their involvement in DR. A comprehensive understanding of these pathways may hold the key to developing targeted therapies to halt or mitigate the progression of DR and its devastating consequences.

Since its initial development in the 1970’s by Phil Burke and his collaborators, the R-matrix theory and associated computer codes have become the de facto approach for the calculation of accurate data for general electron-atom/ion/molecule collision and photoionization processes. The use of a non-orthonormal set of orbitals based on B-splines, now called the B-spline R-matrix (BSR) approach, was pioneered by Zatsarinny. It has considerably extended the flexibility of the approach and improved particularly the treatment of complex many-electron atomic and ionic targets, for which accurate data are needed in many modelling applications for processes involving low-temperature plasmas. Both the original R-matrix approach and the BSR method have been extended to the interaction of short, intense electromagnetic (EM) radiation with atoms and molecules. Here we provide an overview of the theoretical tools that were required to facilitate the extension of the theory to the time domain. As an example of a practical application, we show results for two-photon ionization of argon by intense short-pulse extreme ultraviolet radiation

Alzheimer’s disease (AD), the leading cause of dementia (50-70%), is a multifactorial neurodegenerative disorder characterized by progressive cognitive decline and significant neuropathological changes, including β-amyloid plaques and neurofibrillary tangles. This review synthesizes current understanding of the complex interplays that contribute to the pathogenesis of AD, while exploring the mechanisms underlying the formation of β-amyloid plaques and neurofibrillary tangles, with a focus on the amyloidogenic and non-amyloidogenic pathways, Tau protein hyperphosphorylation, and the resultant neurotoxicity. Furthermore, the study delves into mitochondrial dysfunction and oxidative stress as critical contributors to neuronal degeneration, highlighting the mitochondrial cascade hypothesis and its implications in both early (EOAD) and late-onset AD (LOAD). The study emphasizes the irreversible nature of the disease’s progression, detailing the pathological transformations from the preclinical to the severe stage, where lesions disseminate throughout the entire cortex.

The need for solvating and encapsulating hydro-sensitive molecules drives noticeable trends in the applications of cyclodextrins in pharmaceutical industry, food, polymer, materials, and agricultural science. Among them, β-cyclodextrin is one of the most used for the entrapment of phenolic acid compounds to mask the bitterness of wheat bran. In this regard, there is still a need for a good predictive model that assesses β-cyclodextrin bitterness masking capabilities for various phenolic compounds. This study uses a dataset of 20 phenolic acids docked to the β-cyclodextrin cavity to generate three different binding constants. The data from docking study were combined with topological, topographical and quantum-chemical features from the ligands in a machine learning-based structure-activity relationship study. Three different models for each binding constant were computed using a combination of Genetic Algorithm (GA) and Multiple Linear Regression (MLR) approaches. The developed ML/QSAR models showed a very good performance, with high predictive ability and correlation coefficients of 0.969 and 0.984, for training and test sets, respectively. The models revealed several factors responsible for a binding with cyclodextrin, showing positive contributions toward the binding affinity values, including such features as presence of six-membered rings in the molecule, branching, electronegativity values, and polar surface area.

GRK2 and arrestin3, key players in the functional regulation of G protein-coupled receptors (GPCRs), are ubiquitinated by Mdm2, a nuclear protein. The agonist-induced increase in arrestin3 ubiquitination occurs in the nucleus, underscoring the crucial role of its nuclear translocation in this process. Agonist-induced increase in the ubiquitination of arrestin3 occurs in the nucleus, highlighting the pivotal role of its nuclear translocation in this process. In contrast, GRK2 cannot translocate into the nucleus, thus facilitating the cytosolic translocation of nuclear Mdm2 is required to ubiquitinate GRK2 in the cytosol. Among the cellular components and processes explored, arrestin, Gβγ, clathrin, and receptor phosphorylation were required for the nuclear import of arrestin3, ubiquitination of arrestin3 in the nucleus, nuclear export of Mdm2, and the ubiquitination of GRK2 in the cytosol. In conclusion, our findings demonstrate that agonist-induced ubiquitination of arrestin3 in the nucleus is interconnected to the cytosolic GRK2 ubiquitination.

Hepatocellular carcinoma (HCC) development is associated with altered modifications in DNA methylation, changing transcriptional regulation. Emerging evidence indicates that DNA methyltransferase 1 (DNMT1) plays a key role in carcinogenesis process. This study aimed to investigate how pirfenidone (PFD) modifies this pathway and the effect generated by the association between c-Myc expression and DNMT1 activation. Rats F344 were used for HCC development using 50 mg/kg of diethylnitrosamine (DEN) and 25 mg/kg of 2-aminofluorene (2-AAF). HCC/PFD group received simultaneous doses of 300 mg/kg of PFD. All treatments lasted 12 weeks. On the other hand, HepG2 cells were used to evaluate the effects of PFD in restoring DNA methylation in the presence of the inhibitor 5-Aza. Histopathological, biochemical, immunohistochemical, and western blot analysis were carried out and our findings showed that PFD treatment reduced the amount and size of tumors along with decreased Glipican-3, β-catenin, and c-Myc expression in nuclear fractions. Also, this treatment improved lipid metabolism by modulating PPARγ and SREBP1 signaling. Interestingly, PFD augmented DNMT1 and DNMT3a protein expression, which restores global methylation, both in our in vivo and in vitro models. In conclusion, our results suggest that PFD could slow down HCC development by controlling DNA methylation.

A new polymorph of anhydrous β-cyclodextrin (polymorph III) was obtained and characterized for the first time using powder X-ray diffraction, infrared spectroscopy and thermal analysis. Solution enthalpy and time of dissolution in water were determined by solution calorimetry for this polymorph and compared with those of dried commercial form of β-cyclodextrin (polymorph I), its amorphous form and 2-hydroxypropyl-β-cyclodextrin. Specific heat capacity of polymorphs I and III was determined by differential scanning calorimetry in the wide range of temperatures, which gives enthalpy and Gibbs energy of polymorphic transition at 298 K. Affinity of polymorph III and 2-hydroxypropyl-β-cyclodextrin for water was characterized by determination of their hydration isotherms, which gives the values of hydration Gibbs energy. Being energy-rich, the found new polymorph of β-cyclodextrin has a significantly higher dissolution rate and an in-creased affinity for water compared with the dried commercial form of β-cyclodextrin. Such properties make the new polymorph promising in industrial applications for guest inclusion in aqueous solutions and pastes and may be a desirable alternative for water-soluble β-cyclodextrin derivatives.

Following ischemic stroke, the degradation of myelin and other cellular membranes surpasses the lipid-processing capabilities of resident microglia and infiltrating macrophages. This imbalance leads to foam cell formation in the infarct and areas of secondary neurodegeneration, instigating sustained inflammation and furthering neurological damage. Given that mitochondria are the primary sites of fatty acid metabolism, augmenting mitochondrial biogenesis (MB) may enhance lipid processing, curtailing foam cell formation and post-stroke chronic inflammation. Previous studies have shown that the pharmacological activation of the β2-adrenergic receptor (β2-AR) stimulates MB. Consequently, our study sought to discern the effects of intensified β2-AR signal-ing on MB, the processing of brain lipid debris, and neurological outcome using a mouse stroke model. To achieve this goal, aged mice were treated with formoterol, a long-acting β2-AR ago-nist, daily for two and eight weeks following stroke. Formoterol increased MB in the infarct re-gion, modified fatty acid metabolism, and reduced foam cell formation. However, it did not re-duce markers of post-stroke neurodegeneration or improve recovery. Our findings suggest that boosting MB in myeloid cells is one component of a therapeutic avenue for improving brain lipid debris processing after stroke.

Multidrug-resistant (MDR) Pseudomonas aeruginosa infections represent major a public health concern and require comprehensive understanding of their genetic make-up. This study investigated the first occurrence of IMP-carrying MDR P. aeruginosa strains from Bulgaria. Whole genome sequencing identified a novel plasmid-mediated blaIMP-100 allele located in a In1300-like integron embedded in a novel putative transposon. Two other closely related chromosomal blaIMP variants IMP-13 and IMP-84 were also detected. The IMP-producers were resistant to last-line drugs including cefiderocol (CFDC) (2 out of 3) and susceptible to colistin. The blaIMP-13/84 cassettes were situated in a In320 integron inserted in a Tn5051-like transposon as previously reported. Lastly, the p47825-IMP plasmid rendered PAO1 transformant resistant to CFDC, suggesting a transferable CFDC resistance. A variety of virulence factors associated with adhesion, antiphagocytosis, iron uptake, quorum-sensing, as well as secretion systems, toxins, and proteases were confirmed, suggesting significant pathogenic potential consistent with the observed strong biofilm formation. Emergence of IMP-producing MDR P. aeruginosa is alarming as they remain unsusceptible even to last geneneration drugs like CFDC. Newly detected IMP-100 was even located in an CFDC-resistant XDR strain.

A morning lymphocytosis has been observed in patients under methylprednisolone (mPDN) treatment. We here determine prospectively the timing and magnitude of mPDN-induced lymphocytosis and study the effects of concomitant beta-blockers administration on lymphocyte count (L). L was measured before and 24 to 72 hours after initiating mPDN treatment in 20 patients with immune-mediated inflammatory disorders (IMID). After one week, patients with increased L were divided in two groups receiving, in addition to mPDN, either propranolol or a placebo; L was determined 4 days later. Lymphocyte subpopulations and mPDN plasma levels were determined in subsets of the patients. Values are expressed as median with 25%-75% interquartile range. A 73.4 % (37-305) increase of L was observed in 18/20 patients as soon as 48 (48-72) hours after initiating mPDN (32 mg; 16-32). Lymphocytosis (L ≥4,000/µL) was observed in 7 patients and hyperlymphocytosis (L ≥ 5,000/µL) in 4 of them. No significant changes in L variation were shown under propranolol. In conclusion, the morning lymphocytosis observed during mPDN treatment occurs in the very first days of mPDN administration. The lack of effect of propranolol does not support the role of an increased adrenergic tone.

: Supplement the use of ergogenic aids in cyclist’s directly have been improved the body metabolism and hemodynamic factors that are micro supplement in chancing reactions on the body muscle mass and limb muscle. Mostly knowing that, muscle power development progressive fast glycolytic and short time oxidative systems reactions. Sport competition intervals, therefore, during periods has been used specific drinks supported to cyclists. But, be obtained during should be long race times. Athletes directly needed some drug and fluid intake to prevented from metabolic breakdown rapidly the dynamic physiologic performance factors. Beta-alanine supplementation can be direct muscle performance development affects the anaerobic metabolism and capacity. It should be de-termined how the cyclists will use the competitive and training period intervals can increase the cyclists specific sprint and endurance race performance. Science cyclist International Road doses will be created in which, intervals can random effectively the investigate. This study random a cohort studies is examined the effects of beta-alanine supplementation on aerobic and anaerobic power output in specific cyclists. Therefore, we have been databases PubMed, Scopus and Medline initial search 10 August 2020 were created prospective effect the quality of bias work concluded effect size (ES) 95% confidence interval (CI) were used in participant. Participations (N=66) have age range 25 to 38 of the using beta-alanine in training periods to endurance muscle performance, aerobic power, anaerobic power, and sprint time trials. As a result of beta-alanine improved an-aerobic and aerobic power output on 4-week time-dependent trial performance condition. Signifi-cant values are obtained level factor alpha <0.05 and p-value analysis pre-post interactive stand-ardization.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. The interferons (IFNs) were discovered in 1957, and recombinant IFN-β-1b was approved by the US Food and Drug Administration as the first disease-modifying therapy (DMT) for MS in 1993. Since that time, clinical trials and real-world observational studies have demonstrated the effectiveness of IFN therapies. The pivotal intramuscular IFN-β-1a phase 3 trial was the first to demonstrate that a DMT could reduce accumulation of sustained disability in MS. Patient adherence to treatment is higher with intramuscular IFN-β-1a, given once weekly, than with subcutaneous formulations requiring multiple injections per week. Moreover, subcutaneous IFN-β-1a is associated with an increased incidence of injection site reactions and neutralizing antibodies compared with intramuscular administration. In recent years, revisions to MS diagnostic criteria have improved clinicians’ ability to identify patients with MS and have promoted the use of magnetic resonance imaging (MRI) for diagnosis and monitoring. MRI studies show that treatment with IFN-β-1a, relative to placebo, reduces T2 and gadolinium-enhancing lesions and gray matter atrophy. Since the approval of intramuscular IFN-β-1a, several high-efficacy therapies have been approved for MS, though the benefit of these high-efficacy therapies should be balanced against the increased risk of serious adverse events. For some subpopulations of patients, including pregnant women, the safety profile of IFN-β formulations may provide a particular benefit. In addition, the antiviral properties of IFNs may indicate therapeutic opportunities for IFN-β in the treatment of viral infections such as COVID-19.

Bone innate ability to repair without scaring is surpassed by major bone damage. Current gold-standard strategies do not achieve a full recovery of bone biomechanical properties. To bypass these limitations, tissue engineering techniques based on hybrid materials made up of osteoprogenitor cells, like mesenchymal stem cells (MSCs), and bioactive ceramic scaffolds, like calcium phosphate-based (CaPs), are promising. Biological properties of the MSCs, are influenced by the tissue source. The aim of this study is to define the MSC source and construct (MSC and scaffold combination) most interesting for its clinical application in bone regeneration. iTRAQ generated the hypothesis that anatomical proximity to bone has a direct effect on MSC phenotype. MSCs were isolated from adipose tissue, bone marrow and dental pulp. MSCs were cultured both on plastic surface and on CaPs (hydroxyapatite and β-tricalcium phosphate) to compare their biological features. On plastic, MSCs isolated from dental pulp (DPSCs) were the MSCs with the highest proliferation capacity and the greatest osteogenic potential. On both CaPs, DPSCs are the MSCs with the greatest capacity to colonize bioceramics. Furthermore, results show a trend for DPSCs are the MSCs with the most robust increase in the ALP activity. We propose DPSCs as a suitable MSCs for bone regeneration cell-based strategies.What do you want to do ?New mailCopy

Substantial studies have focused on early detection of Alzheimer's disease (AD). Cerebral amyloid beta (Aβ), is hallmark of AD, can be observed in vivo via positron emission tomography imaging using amyloid tracer or cerebrospinal fluid assessment, but costly expensive. The current study aims to identify and compared predictability in magnetic resonance imaging (MRI) markers and neuropsychological markers to predict cerebral Aβ status in AD cohort using machine learning (ML) approaches. The predictability in candidate markers for cerebral Aβ status was examined by analyzing 724 participants from the ADNI-2 cohort. Demographic variables, structural MRI markers, and neuropsychological test scores were used as input in several ML algorithms to predict cerebral Aβ positivity. Out of five combination of candidate markers, neuropsychological markers with demographics showed the most cost-efficient result. A feature selection model could distinguish abnormal levels of Aβ with the predictability of 0.85, indicating the same performance with MRI-based models. The result has first to identified the predictability in MRI markers using ML approaches, and secondary to demonstrate the neuropsychological model with demographics could predict Aβ positivity, suggesting a more cost-efficient method for detecting cerebral Aβ status compared to MRI markers.

Clinical pathogens especially Gram-negative bacteria developing resistance to third-generation cephalosporins are making the clinical outcome more complicated and serious. This study was undertaken to evaluate the distribution of extended-spectrum beta-lactamases in Tamil Nadu regions in India. For this study, clinical samples were collected from five different hospitals located in Tamil Nadu and ESBL producing Gram-negative isolates were characterized. Minimal inhibitory concentration (MIC) was performed using cefotaxime and ceftazidime. The blaESBL producing genes were screened using multiplex PCR for the genes, CTX-M group-1,-2,-8,-9,-26. Conjugation studies were performed using E. coli AB1157 as a recipient for the isolates harbouring plasmid-borne resistance following broth-mating experiment. In total, 1500 samples were collected and 599 Gram-negative bacteria were isolated that included Escherichia coli (n=233), Klebsiella pneumoniae (n=182), Pseudomonas aeruginosa (n=79), Citrobacter spp. (n=30), Proteus mirabilis (n=28), Salmonella spp. (n=21), Acinetobacter baumannii (n=12), Serratia spp. (n=6), Shigella spp. (n=4), Morganella morganii (n=3) and Providencia spp. (n=1). MIC results showed that 358 isolates were resistant to cefotaxime and ceftazidime. Further, ESBL gene amplification results showed that 19 isolates had CTX-M group-1 gene including E. coli (n=16), K. pneumoniae (n=2) and P. aeruginosa (n=1) whereas one M. morganii isolate had CTX-M group-9 gene in their plasmid. Through conjugation studies, 12/20 isolates were found to be involved in the transformation of its plasmid-borne resistance gene. Our study highlighted the role of horizontal gene transfer in the dissemination of plasmid-borne blaCTX-M resistance genes among ESBL producing isolates.

The manuscript surveys the special functions of the Fox-Wright type. These functions are generalizations of the hypergeometric functions. Notable representatives of the type are the Mittag-Leffler functions and the Wright function. The integral representations of such functions are given and the conditions under which these function can be represented by simpler functions are demonstrated. The connection with generalized fractional differential and integral operators is demonstrated and discussed.

By manipulating the various physico-chemical properties of amino acids, design of peptides with specific self-assembling properties has been emerging since more than a decade. In this context, short peptides possessing detergent properties (so-called “peptergents”) have been developed to self-assemble into well-ordered nanostructures that can stabilize membrane proteins for crystallization. In this study, the peptide with “peptergency” properties, called ADA8 extensively described by Zhang et al., is studied by molecular dynamics for its self-assembling properties in different conditions. In water, it spontaneously forms beta sheets with a β barrel-like structure. We next simulated the interaction of this peptide with a membrane protein, the bacteriorhodopsin, in the presence or absence of a micelle of dodecylphosphocholine. According to the literature, the peptergent ADA8 is thought to generate a belt of β structures around the hydrophobic helical domain that could help stabilize purified membrane proteins. Molecular dynamics is here used to challenge this view and to provide further molecular details for the replacement of detergent molecules around the protein. To our best knowledge, this is the first molecular mechanism proposed for ''peptergency''. In addition, our calculation approach should serve as a predicting tool for the design of beta peptergent with diverse amphipathic properties.

The main objective of this paper is to introduce k-fractional derivative operator by using the definition of k-beta function. We establish some results related to the newly defined fractional operator such as Mellin transform and relations to k-hypergeometric and k-Appell's functions. Also, we investigate the k-fractional derivative of k-Mittag-Leffler and Wright hypergeometric functions.

Identification and segmentation of rock particles is very important in geology, mining, engineering construction, and environmental monitoring. Traditional methods for recognizing the rock particle characteristics are time-consuming, labor-intensive, and limited by the geographical scope of the sampling sites, which makes it more difficult to represent the spatial distribution of the rock particles accurately. Recent advancements in deep learning techniques offer promising solutions to automate this process. This study aims at utilizing state-of-the-art (SOTA) Mask R-CNN deep learning algorithm from the Detectron2 framework, to capture global features of rocks that will enable the recognition of rock particles more efficiently, just from having the rock images. These images are subject to image processing techniques such as a Gaussian filter, to denoise and smoothen the image, and an Illumination Adaptive Transformer (IAT) framework, to adjust the lighting exposure; all of which add to improve the quality of the image dataset. Afterward, the Mask R-CNN and Detectron2 models are utilized in training the images using transfer learning. Experimental results from evaluating the performance of the proposed algorithms showcase the effectiveness of the approach, thereby highlighting its potential to revolutionize rock particle segmentation across various domains.