The generation and maintenance of membrane potential is a fundamental part of Membrane Pump Theory. One of the key points of this hypothesis is based on a natural or facilitated molecular diffusion through several types of ion channels and pumps like the Na/K ATPase. Following the principles of chemistry, electrostatics and geometry, it becomes clear that ion channels cannot function in this way. The ions channels cannot by their location have both a filter function and be ion concentrators, and the Na/K pump by its position in the membrane and by the proposed assumptions is not able to perform its regulatory function. The current model must absolutely be revised according to the current state of our knowledge and allow an advance in the understanding of the phenomena opening new research perspectives.

Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may cause stroke or sudden cardiac death. Automatic long-term electrocardiogram (ECG) analysis algorithms could provide diagnosis suggestion even early warning for physicians, however, they are mutually-exclusive in terms of robustness, generalization and low complexity. In this study, a novel PVC recognition algorithm that combines deep learning-based heartbeat template clusterer and expert system-based heartbeat classifier is proposed. Long short-term memory-based auto-encoder (LSTM-AE) network was used to extract features from ECG heartbeats for K-means clustering. Thus, the templates were constructed and determined based on clustering results. Finally, the PVC heartbeats were recognized based on a combination of multiple rules, including template matching and rhythm characteristics. Three quantitative parameters, sensitivity (Se), positive predictive value (P+) and accuracy (ACC), were used to evaluate the performances of the proposed method on the MIT-BIH Arrhythmia database and the St. Petersburg Institute of Cardiological Technics database. Se on the two test databases was 87.51% and 87.92%, respectively; P+ was 92.47% and 93.18%, respectively; and ACC was 98.63% and 97.89%, respectively. The PVC scores on the 3rd China Physiological Signal Challenge 2020 training set and hidden test set were 36,256 and 46,706, respectively, which could rank first in the open-source codes. The results showed that the combination strategy of expert system and deep learning can provide new insights for robust and generalized PVC identification from long-term single-lead ECG recordings.

Trichomes are a common morphological defense against pests, in particular, type IV glandular trichomes have been associated with resistance against different invertebrates. Cultivated tomatoes usually lack or have a very low density of type IV trichomes. Thus, specific breeding programs to incorporate these natural defences, that are common within the Solanum genus, might improve a more sustainable management. We have identified a S. pimpinellifolium accession with very high density of this type of trichomes. Two F2 mapping populations using two different parents have been developed, characterized and genotyped using a new genotype methodology, K-seq. We have been able to build an ultra-dense genetic map with 147,326 markers with an average distance between markers of 0.2 cM that has allowed us to perform a detailed mapping. We have used two different families and two different approaches, QTL mapping and QTL-seq, to identify several QTLs implicated in the control of trichome type IV developed in this accession on the chromosomes 5, 6, 9 and 11. The QTL located on chromosome 9 is a major QTL that has not been previously reported in S. pimpinellifolium that increases by a factor of 9 the density of trichomes.

Banks are normally offered two kinds of deposit accounts. It consists of deposits like current/saving account and term deposits like fixed or recurring deposits. For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate uplifting of finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer detail analysis can influence term deposit subscription chances. An automated system is approached in this paper that works towards prediction of term deposit investment possibilities in advance. This paper proposes deep learning based hybrid model that stacks Convolutional layers and Recurrent Neural Network (RNN) layers as predictive model. For RNN, Gated Recurrent Unit (GRU) is employed. The proposed predictive model is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concludes that proposed model attains an accuracy of 89.59% and MSE of 0.1041 which outperform well other baseline models.

There are no studies that quantitatively compare life histories among scorpion species. Statistical procedures applied to 94 scorpion species indicate that those with larger bodies do not necessarily have larger litters or longer life cycles, opposite to some theoretical predictions.

General characteristics of K changes together with their fine structure associated with ground flashes in Sri Lanka in the tropics are presented. It is found that on average there are about 2 K changes associated with each return stroke. Analysis of the fine structure of the K changes shows that the K change is a chaotic pulse burst. Some of these chaotic pulse bursts start and the others end as a regular pulse bursts. Sometimes the chaotic part occurs in between two regular pulse bursts. This is in agreement with the recent published results that claim that chaotic pulse bursts are a random superposition of regular pulse bursts. The results show that the small step fields identified in the literature as K changes are the static fields associated with these pulse bursts.

This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf) and noise less vessels. Generally, in passive sonar the targets are detected by sonar equation (with constant threshold) which increase the detection error in shallow water. Purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound) is processed in time and frequency domain. For classifying, Bayesian classification is used and prior distribution is estimated by Maximum Likelihood algorithm. Finally, target was detected by combining the detection points in both domains using LMS adaptive filter. Results of this paper has showed that proposed method has improved true detection rate about 27% compare other the best detection method.

1) Background: Impeded resolution of inflammation contributes substantially to the pathogenesis of Alzheimer's disease (AD); consequently, resolving inflammation is pivotal to the amelioration of AD pathology. This can potentially be achieved by the treatment with specialized pro-resolving lipid mediators (SPMs), which should resolve neuroinflammation in brains. 2) Methods: Here, we report the effects of long-term treatment with a SPM, maresin like 1 (MarL1), on AD pathogenesis in a transgenic 5xFAD mouse model. 3) Results: MarL1 treatment reduced Aβ overload, curbed the loss of neurons in brains especially cholinergic neurons associated with cleaved-caspase-3-associated apoptotic degeneration, reduced astrogliosis and microgliosis and the pro-inflammatory M1 polarization of microglia, curbed the AD-associated decline in an-ti-inflammatory Iba1+Arg-1+-M2 microglia, reduced astrogliosis-associated level of neuroin-flammatory TNF-α, inhibited phenotype switching of pro-inflammatory neurotoxic A1 astrocytes and N1 neutrophils, promoted polarization of inflammation-resolving neuroprotective A2 as-trocytes, promoted the blood–brain-barrier-associated tight-junction protein claudin-5 and de-creased neutrophil leakage in 5xFAD brains, and induced the switch of neutrophils toward the inflammation-resolving N2 phenotype. 4) Conclusion: Long-term administration of MarL1 mit-igates AD-related neuropathogenesis in brains by curbing neuroinflammation and neurodegen-eration. These findings provided the preclinical leads and mechanistic insights for the develop-ment of MarL1 into an effective modality to ameliorate AD pathogenesis.

In this paper, we report a comprehensive and consistent annotation of the locus encoding the horse T cell receptor b-chain (TRB), as inferred from the most recent genome assembly. The horse TRB locus spans approximately 1 Mb, making it the largest locus among the mammalian species stud-ied to date, with a significantly higher number of genes related to extensive duplicative events. In the region, 136 TRBV, belonging to 29 subgroups, 2 TRBD, 13 TRBJ and 2 TRBC genes, were iden-tified. The general genomic organization resembles that of other mammals, with a V-cluster of 135 TRBV genes, located upstream of two in-tandem aligned TRBD-J-C clusters, and an inverted TRBV gene at the 3’ end of the last TRBC gene. However, the horse b-chain repertoire would be affected by a high number of non-functional TRBV genes. Thus, we queried a transcriptomic da-taset derived from splenic tissue of a healthy adult horse, using each TRBJ gene as a probe to ana-lyse clonotypes encompassing the V(D)J junction. This analysis provided insights into the usage of the TRBV, TRBD and TRBJ genes and the variability of the juxtaposition region. Our results clearly demonstrated that the horse β-chain constitutes a complex level of variability broadly like that described in other mammalian species.

The opportunistic pathogen Pseudomonas aeruginosa is responsible for numerous chronic infections and has a case fatality rate of 50%. All P. aeruginosa strains express β–lactamase, an enzyme capable of inactivating β–lactam antibiotics, including penicillins. However, β–lactams are still considered desirable therapeutics by physicians due to their low toxicity. The short-term goal of this study was to create an optimal model for ampC expression in P. aeruginosa and determine the selecting antibiotic to be used during mutagenesis. In the long term, this study aims to renew effectiveness of β–lactams by identifying potential allosteric binding sites on β–lactamase for the development of novel β–lactamase inhibitors. To create a system for ampC expression, the chromosomal P. aeruginosa ampC gene encoding for β–lactamase was cloned into Escherichia coli, then conjugated into P. aeruginosa ∆ampC. β– lactamase assays on recombinant E. coli and P. aeruginosa detected much higher production of β–lactamase in pMMB67HE, which was confirmed with antibiotic susceptibility testing (AST) to numerous β-lactams. From AST, carbenicillin was chosen as the antibiotic to select functional β–lactamase production during mutagenesis. Future work includes conducting mutagenesis on ampC to identify allosteric binding sites on the β–lactamase enzyme that may enable the discovery of new β–lactamase inhibitors. This work allows for the development of novel β–lactamase inhibitors that could renew the utility of β–lactams and drastically reduce morbidity and mortality from chronic Pseudomonas infections.

The aim of the study was the comparison of conventional sintering versus additive manufacturing techniques for β-TCP bioceramics, focusing on mechanical properties and biocompatibility. A "critical" bone defect requires surgical intervention beyond simple stabilization. Autologous bone grafting is the gold standard treatment for such defects but it has its limitations. Alloplastic bone grafting using synthetic materials is becoming increasingly popular. The use of bone graft substitutes has increased significantly and current research was focused on optimizing these substitutes, whereas this study compares two existing manufacturing techniques and the thereby produced β-TCP implants. The 3D-printed β-TCP hybrid structure implant was fabricated using two components, a column structure and a freeze-foam, which were sintered together. The conventionally manufactured ceramics were made by pouring. Both scaffolds were characterized according to porosity, mechanical properties and biocompatibility. The hybrid structure had a total porosity of 74.4 ± 0.5%. Microporous β-TCP implants had a porosity of 43.5 ± 2.4%, while macroporous β-TCP implants had a porosity of 61.81%. Mechanical testing revealed that the hybrid structure had a compressive strength of 10.4 ± 6 MPa, significantly lower than the microporous β-TCP implant’s with 32.9 ± 8.7 MPa. Biocompatibility evaluations showed a steady increase in cell proliferation over time for all β-TCP implants, with minimal cytotoxicity. This study provides valuable insight into the potential of additive manufacturing for β-TCP bioceramics in the treatment of bone defects.

Today, various dietary supplements are taken to improve endurance performance during physical activity. These supplements have proven to be very successful in controlling and balancing various hormone levels and have contributed to the prevention and healing of metabolic disorders and physical injuries. In this study, we sought to investigate the effects of the ACTN3 gene and nutrient supplementation, including beta-alanine, ashwagandha, L-carnitine, and iron, on athletic performance. The ACTN3 gene has been identified as a potential genetic determinant of athletic performance, particularly in activities that require high levels of power and strength. This study investigated the interaction between the ACTN3 gene and supplementation and highlighted the potential for personalized approaches to improve athletic performance. 24 subjects per group, were randomized in a parallel-group design to examine the effects of supplementation on the ACTN3 gene and athletic performance over a 21-day intervention period. Participants in the intervention were divided into four groups of six members each. The same subjects who did not take supplements formed the control group. In addition, the subjects were divided into 4 groups (G1, G2, G3, and G4), each consisting of subgroups of control and a treated. All treated groups (TG1, TG2, TG3, and TG4) received 4 supplements for 21 days, namely S1 (ashwagandha), S2 (iron), S3 (beta-alanine) and S4 (L-carnitine), together with the 4 control groups, i.e. CG1, CG2, CG3 and CG4, who received no supplements during the same period. In particular, this study determines the effect of these 4 supplements on actn3 gene expression, testosterone, cholesterol and BUN levels of the participants. The P-values determined for all parameters showed statistically significant values and the final result showed that all supplements had positive effects on the tested parameters. The result showed a highly significant difference between the intake of supplements before and after the intake of 24 athletes per group on the ACTN3 gene expression level and biochemical indicators.

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.

Background: Amyloid beta peptides (Aβ) have been identified as the main pathogenic agents in Alzheimer’s disease (AD). Soluble Aβ oligomers, rather than monomer or insoluble amyloid fibrils, show membrane-binding capacity to red blood cells (RBCs) and trigger several morphological and functional alterations in RBCs that can result in impaired oxygen transport and delivery. Since bioactive lipids have been recently proposed as potent protective agents against Aβ toxicity, we investigated the role of sphingosine-1-phosphate (S1P) in signaling pathways involved in the mechanism underlying ATP release in Aβ-treated RBCs. Methods: In RBCs following different treatments, ATP, 2,3 DPG, cAMP levels, and caspase 3 activity were determined by spectrophotometric and immunoassay. Results: S1P rescued the inhibition of ATP release from RBCs triggered by Aβ through a mechanism involving caspase-3 and restoring 2,3 DPG and cAMP levels within the cell. Conclusions: These findings reveal the molecular basis of S1P protection against Aβ in RBCs and suggest new therapeutic avenues in AD.

Directed energy deposition (DED) parameters were determined for near-β alloy Ti-55511 by employing statistical design of experiments (DOE) methods. Parameters resulting in fully dense freeform deposits were identified using two sequential DOEs. Single laser tracks were printed with several laser power, traverse rate, and powder feed rate settings in an initial DOE to identify promising build parameters. Capture efficiency and effective deposition rate were used to characterize and rank the single track deposits. The best parameters were then used to print solid cube with various X-Y and Z-overlaps (different hatch spacing, HS, and layer thickness, ZS) in a second DOE. Suitable deposition parameters were selected based on cube density and microstructure and were used to fabricate larger tensile samples for mechanical testing. Multiple parameter sets were found to provide dense Ti-55511 deposits with acceptable mechanical properties and parametric models showed statistical significance.

Despite substantial heterogeneity of studies, there is evidence that antibiotics commonly used in primary care influence the composition of the gastrointestinal microbiota in terms of changing the composition and/or diversity. Benzyl isothiocyanate (BITC) from the food and medicinal plant nasturtium (Tropaeolum majus) is known for its antimicrobial activity and is used for the treatment against infections of the draining urinary tract and upper respiratory tract. Against this background, we raised the question whether 14 d nasturtium intervention (3 g daily, N=30 healthy females) could also impact the normal gut microbiota composition. Spot urinary BITC excretion highly correlated with a weak, but significant antibacterial effect against Escherichia coli. A significant increase in human beta defensin 1 as parameter for host defense was seen in urine and exhaled breath condensate (EBC) upon verum intervention. Pre-to-post analysis revealed that mean gut microbiome composition did not significantly differ between groups, nor did circulating serum metabolome. On an individual level, partly large changes were observed between sampling points, though. Explorative Spearman rank correlation analysis in subgroups revealed associations between gut microbiota and the circulating metabolome, as well as between changes in blood markers and bacterial gut species.

Mitochondria are involved in the regulation of cellular energy metabolism, calcium homeostasis, and apoptosis. For mitochondrial quality control, dynamic processes, such as mitochondrial fission and fusion, are necessary to maintain shape and function. Disturbances of mitochondrial dynamics lead to dysfunctional mitochondria which contribute to the development and progression of numerous diseases, including Type 2 Diabetes (T2D). Compelling evidence put forward that mitochondrial dynamics play a significant role in the metabolism-secretion coupling of pancreatic β cells. The disruption of mitochondrial dynamics is linked with defects in energy production and increased apoptosis, ultimately impairing insulin secretion and β cell death. This review provides an overview of altered mitochondrial dynamics in pancreatic β cells using ge-netic/pharmacologic approaches, and how these affect insulin secretion.

Alzheimer’s disease (AD) is an age-related neuropsychiatric disorder and a common cause of progressive dementia. Diltiazem (DTZ), the non-dihydropyridine benzothiazepine class of calcium channel blocker (CCB), used clinically in angina and other cardiovascular disorders have proven neurological benefits. In the present study, the neuroprotective anti-dementia effects of DTZ against intra-cerebroventricular-streptozotocin (ICV-STZ)-induced sporadic AD (SAD)-type rat model was investigated. ICV-STZ-induced cognitive impairments were measured by passive avoidance and Morris water maze tasks. Anti-oxidative enzyme status, pro-inflammatory markers, and amyloid-beta (Aβ) protein expression in rat brain tissues were measured by ELISA kits, Western blotting, and immunostaining techniques. Data revealed that ICV-STZ injection in rats significantly induced cognitive deficits and altered the levels of oxidative and pro-inflammatory markers (p < 0.05 ~ p < 0.001). Treatment with DTZ (10 mg/kg, 20 mg/kg, and 40 mg/kg. p.o.) daily for twenty-one days, 1 h before a single ICV-STZ (3 mg/kg) injection, significantly improved cognitive impairments, ameliorated the ICV-STZ-induced altered nitrite, pro-inflammatory cytokines (TNF-α, and IL-1β) and anti-oxidative enzyme levels (superoxide dismutase, lipid peroxidation, and glutathione). Further, DTZ restored the increased Aβ protein expression in ICV-STZ-induced brain tissue Considering the data obtained, DTZ exhibited a potential neuroprotective anti-dementia role in ICV-STZ-induced SAD-type conditions in rats and might be repurposed as a potential therapeutic agent in the treatment and management of AD and related dementia pathologies.

Recent reports suggest that dysregulation of lipid metabolism is a key feature of the most invasive cancers. To identify potential biomarkers of tumor aggressiveness, we compared the proteomes of two experimental models of malignant mesothelioma in rats exhibiting different invasive properties. Quantitative changes between the most invasive, M5-T1, versus the least invasive, F4-T2, first led to a list of 424 proteins. A second step, cross-comparing this list with 433 proteins distinguishing invasive vs non-invasive tumors, led to identifying 88 proteins that specifically increased and 157 that decreased, respectively, characterizing the most aggressive M5-T1 tumor. Among the 15 mitochondrial proteins found in these lists, the very long-chain specific acyl-CoA dehydrogenase, encoded by the Acadvl gene and involved in fatty acid beta oxidation, appeared to play an important role in the metabolic reprogramming of the tumor microenvironment. Immunohistochemical staining of tumor sections confirmed increased expression of Acadvl in the M5-T1 tumor. Finally, the dramatic increase and decrease, observed in 25 and 17 proteins, respectively, suggested the existence of a strong link between mitochondrial events and modifications of the extracellular matrix, immune cell components or other subcellular compartments. These findings highlight some important aspects of the tumor microenvironment changes linked to aggressiveness.

Probabilistic and parsimony-based arguments regarding available genetics data are used to propose that Hardy and Higgin’s amyloid cascade hypothesis is valid but is commonly interpreted too narrowly to support, incorrectly, the primacy of the amyloid beta peptide (Aβ) in driving Alzheimer’s disease pathogenesis. Instead, increased activity of the βCTF (C99) fragment of APP is likely the critical pathogenic determinant altered by mutations in the APP gene. This model is consistent with the regulation of APP mRNA translation via its 5’ iron responsive element (IRE). Similar arguments support that the pathological effects of familial Alzheimer’s disease mutations in the genes PSEN1 and PSEN2 are not exerted directly via changes in APP cleavage to produce different ratios of Aβ length. Rather, these mutations likely affect the stability of presenilin holoprotein and/or γ-secretase multimers with consequences for γ-secretase activity and other important cellular functions. All fAD mutations in APP, PSEN1, and PSEN2 likely find unity of pathological mechanism in their actions on endolysosomal acidification and mitochondrial function, with detrimental effects on iron homeostasis and promotion of “pseudo-hypoxia” being of central importance. Aβ production is enhanced and distorted by oxidative stress and accumulates due to decreased lysosomal function. It may act as a disease-associated molecular pattern (DAMP) enhancing oxidative stress-driven neuroinflammation during the cognitive phase of the disease. We also discuss fascinating, but largely ignored, data on presenilin biology that may be important in understanding presenilins’ central role in familial Alzheimer’s disease.

The mutton quality of Chinese Tan lambs (Ovis aries) has declined as feeding patterns have shifted from pasturing to pen rationing. Mutton quality is affected by fatty acids, and rumen microorganisms play a role in the synthesis of short-chain fatty acids, long-chain fatty acids, and conjugated linoleic acids. We used 16S rDNA sequencing to analyze the effects of two feeding patterns on the rumen bacteria of Tan lambs. In a randomized block design with 24 newborn Tan lambs, 12 lambs were fed by ewes in pasture and 12 were fed by pen-fed ewes. At 2 months, the biceps femoris and the longissimus dorsi were analyzed by gas chromatography for intramuscular fat content and fatty acid composition, and DNA in the rumen contents was extracted and used to analyze the structure of the bacterial community. Different feeding patterns had no significant effect on the intramuscular fat content of the biceps femoris and longissimus dorsi of the lambs, but there was a significant effect on fatty acid composition. Rumen bacteria were significantly more diverse in the pasture group than in the pen-ration group (P < 0.01). Twenty-one phyla were identified in the pasture group, and 14 phyla were identified in the pen-ration group. The dominant phyla in the pasture group were Bacteroidetes and Fibrobacteres; the dominant phyla in the pen-ration group were Proteobacteria and Bacteroidetes. The relative abundance of Proteobacteria was significantly higher in the pen-ration group than in the pasture group (P < 0.01). Diversity at the genus level was also higher in the pasture group, with 176 genera in the pasture group and 113 genera in the pen-ration group. The dominant genera in the pasture group were Prevotella_1, Rikenellaceae_RC9_gut_group, and Bacteroidales_BS11_gut_group_Na; the dominant genera in the pen-ration group were Prevotella_1, Prevotella_7, Succinivibrionaceae_UCG-001, and Succinivibrionaceae_NA.

Photothrombotic stroke (PTS) stimulates the level of N- and C-terminal fragments of Amyloid precursor protein (APP) growth in the cytoplasm of ischemic penumbra cells not earlier but at 24 hours. Here we have shown that APP fragments are visualized in thin unmyelinated fibers of neurons, in containing mitochondria large fibers and in synapses but absent in the nuclei. At 24 hours after PTS, some elements of the destroyed tissue accumulated a significant amount of APP protein. The level of ADAM10 α-secretase decreased on the first day after PTS in the rat brain cortex and ADAM-10 co-localized with the lipid raft marker caveolin-1. PTS caused no changes in the level of β-secretase BACE1 either on the first day after PTS or in the early recovery period. The expression of proteins of the γ-secretase complex: presenilin-1 and nicastrin increased in astrocytes, but not in penumbra neurons after PTS. The β-secretase inhibitor LY2886721 did not affect the infarct size of the mouse cerebral cortex and the level of apoptosis of cells in the perifocal region after PTS. Whereas the inhibitor of γ-secretase DAPT reduced the expression of glial fibrillary acidic protein (GFAP) in astrocytes, prevented the growth of apoptosis of mouse cerebral cortex cells reducing the infarct volume on the 7th and 14th days after PTS. DAPT may be considered as a drug for stroke therapy.

Beta cells couple stimulation by glucose with insulin secretion and impairments in this coupling play a central role in diabetes mellitus. To clarify the effect of cAMP and the role of Epac2A in intracellular calcium signals and intercellular coupling, we performed functional multicellular calcium imaging in beta cells in mouse pancreas tissue slices after stimulation with glucose and forskolin in wild-type and Epac2A knock-out mice. Increased cAMP evoked calcium signals in otherwise sub-stimulatory glucose and beta cells from Epac2A knock-out mice displayed a faster activation. During the plateau phase, beta cells from Epac2A knock-out mice displayed a slightly higher active time in response to glucose compared with wild-type littermates, and increased cAMP increased the active time via a large increase in oscillation frequency and small decrease in oscillation duration in both Epac2A knock-out and wild-type mice. Functional network properties during stimulation with glucose did not differ in Epac2A knock-out mice, but the presence of Epac2A was crucial for the protective effect of increased cAMP in preventing a decline in beta cell functional connectivity with time. Finally, increased cAMP prolonged beta cell activity during deactivation in an Epac2A-independent manner.

Searching for neutrinoless double beta decay is a top priority in particle and astroparticle physics, being the most sensitive test of lepton number violation and the only suitable process to probe the Majorana nature of neutrinos. In order to increase the experimental sensitivity for this particular search, ton-scale detectors operated at nearly zero-background conditions with a few keV energy resolution are required. In this scenario, cryogenic detectors have proven effective in addressing many of these issues simultaneously. After long technical developments, the CUORE experiment established the possibility to operate large scale detectors based on this technology. Parallel studies pointed out that scintillating cryogenic detectors represent a suitable upgrade for the CUORE design, directed towards higher sensitivities. In this work, we review the recent development of cryogenic detectors, starting from the status of the art and outlying the path toward next-generation experiments.

Diabetes mellitus (DM) is one of the major risk factors for COVID-19 complications as it is one of the chronic immune-compromising conditions especially if patients have uncontrolled diabetes, poor HbA1c &/or irregular blood glucose levels. Diabetic patient’s mortality rates with COVID-19 are higher than cardiovascular or cancer patients. Recently Bacillus Calmette–Guérin (BCG) has shown successful results in reversing diabetes in both rats and clinical trials based on different mechanisms from aerobic glycolysis to Beta cells regeneration. BCG is a multi-face vaccine that has been used extensively in protection from TB and leprosy and has been repositioned for treatment of bladder cancer, diabetes & multiple sclerosis. Recently, the COVID-19 epidemiological study confirmed that universal BCG vaccination reduced morbidity and mortality in certain geographical areas. Countries without universal policies of BCG vaccination (Italy, Nederland, USA) have been more severely affected compared to countries with universal and long-standing BCG policies that have shown low numbers of reported COVID-19 cases. Some countries have started clinical trials that included a single dose BCG vaccine as prophylaxis from COVID-19 or an attempt to minimize its side effects. This proposed research aims to use BCG vaccine as a double-edged weapon countering both COVID-19 & diabetes, not only as protection but also as therapeutic vaccination. The work includes a case study of regenerated pancreatic beta cells based on improved C-peptide & PCPRI laboratory findings after BCG vaccination for a 9 years’ patient. The patient was re-vaccinated based on a negative tuberculin test & no scar at the site of injection of the 1st BCG vaccination at birth. Furthermore, the authors in the present article described a prospective BCG multi-dose clinical study in full details that they will apply in case of acceptance of their submitted grant & the ethical committee approval. The aim of the clinical study is to check if double dose BCG (4 weeks apart) will show a significant difference in the protection of health care professionals in Egypt. The authors suggest and invite the scientific community to take into consideration the concept of direct BCG re-vaccination (after 4 weeks) because of the reported gene expressions & exaggerated innate immunity consequently. As the diabetic MODY-5 patient (mutation of HNF1B, Val2Leu) was on low dose Riomet® while eliminating insulin gradually, a simple analytical method for metformin assay was recommended to ensure its concentration before use as it is not approved yet by the Egyptian QC labs.

Pyracantha angustifolia has been used in traditional medicine to treat a range of diseases of the stomach and improve digestion, blood circulation, diarrhea, dysentery, and hemostasis. This study evaluated bioactivity-guided fractionation as a means to identify therapeutic phytochemicals from P. angustifolia that can attenuate melanogenesis and oxidation. Seven compounds with inhibitory effects on melanin production and tyrosinase (TYR) activity, as well as ABTS and DPPH radical scavenging activities, and have not been reported as whitening materials, were isolated from the n-butanol fraction from P. angustifolia leaves (PAL). Among the seven compounds, p-hydroxybenzoic acid beta-d-glucosylester (HG), and cimidahurinine (CD) had strong inhibitory effects of melanin production, TYR activity, and ABTS and DPPH radical scavenging activities. Western blot analysis showed that HG and CD suppressed tyrosinase-related protein (TYRP)-1 and TYRP-2 expression. These results suggest that P. angustifolia containing active compounds, such as HG and CH, is a potent therapeutic candidate for the development of hypopigmenting agents.

Hypertension is a common and growing medical problem that leads to enormous cardiovascular and kidney disease worldwide. While many drugs exist to treat hypertension, there is large individual variation in how a given individual responds to different agents, which contributes to dismal rates of hypertension control. While demographic factors predict which drugs may work better in certain individuals, a great degree of this variation has a genetic basis. In recent years, genome wide association studies have begun to identify specific gene variants that predict drug response to particular agents. This review identifies the major genetic variants influencing antihypertensive response that have emerged from this growing body of work. For novel genetic variants without a previously known biologic basis in blood pressure, it is crucial to validate initial findings in subsequent studies. This information may eventually lead to a more personalized approach to hypertension management that will improve blood pressure control and patient outcomes. The integration of this large amount of data and its real world application will be highly challenging, but strategies to accomplish this are discussed.

1) Background: Neotropical montane forests represent one of the most diverse ecosystems; however, they are also the most threatened for deforestation. Our main goal is to evaluate the change in Basal Area (BA), Density and Species Composition of montane forests in the southern Ecuador and to determine the influence on some critical ecological and geomorphological factors. 2) Methods: One hundred thirty-two temporary plots of 400 m² each were installed; we identified and measured all trees> 10 cm DBH. We modeled species diversity (Fisher’s alpha) change in relation to climatic, elevational and geomorphological gradients with GLM and Kruskall-Wallis analyses. The change in composition was determined using Cluster Analyses (BIOENV analysis followed by a LINKTREE procedure). Non-metric multidimensional scaling (NMDS) was used to analyze changes across climatic and geomorphological gradients. Finally, we used SIMPER analysis to identify the species that contributed most to the dissimilarity among the different elevations. 3) Results: Formation of floristic groups was influenced by altitude, temperature and Isothermality; physiographic province, great landscape, geological landscape and lithology. Plots located in low hills have higher alpha diversity with respect to the high hills and dissected mountains. 4) Conclusions: The elevation is first hierarchical factor responsible of the division of structural and floristic groups. Plots located on the whitish tuff have a higher alpha value diversity compared with plots in andesitic tuffs. Wettest quarter (> 839 mm) and Isothermality (> 90.5) are the climatic factors that driven de floristic divisions.

Klebsiella pneumoniae, a member of the ESKAPE pathogen group, is a prominent cause of hospital-acquired infections. The WHO recognized carbapenem-resistant K. pneumoniae as a critical-one priority pathogen. These resilient superbugs have the ability to form biofilms and present a significant global threat. In the present study, we isolated and characterized a bacteriophage SAKp02, from hospital sewage, infectious to carbapenem-resistant K. pneumoniae patient isolates. SAKp02 could infect 43 of 72 clinical isolates, indicating a broad host spectrum. Whole genome analysis classified SAKp02 within the family Casjensviridae, with a 59,343 bp genome encoding 82 ORFs. Comparative genomic analysis revealed significant differences between SAKp02 and its closest viruses, indicating a distinct genetic makeup positioning it as a novel phage strain within the lineage. The SAKp02 genome comprises bacteriolytic enzymes, including holin, endolysin, and phage depolymerase, crucial for bacterial lysis and biofilm disruption. It reduced biofilm biomass by over threefold compared to the control and eradicated 99% of viable cells within a 4-hour treatment period. Scanning electron microscopy corroborated the ability of the phage to dismantle biofilm matrices and lyse bacterial cells. Safe and effective treatments are warranted, and hence, the fully characterized lytic phages with therapeutic potential against drug-resistant clinical isolates of bacteria are needed. Our study is the first to report the antibacterial and antibiofilm activity of Casjensviridae phages, and our discovery of a novel K. pneumoniae phage broadens the arsenal against the bacteria.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

Slave Province in Canada is an Archean granite-supracrustal terrane at the northwestern corner of the Canadian Shield. It is bordered by the Thelon–Taltson orogen (2.0 to 1.9 Ga) to the south-east and the Wopmay orogen (1.9 to 1.8 Ga) to the west. Acasta gneisses exposed in the western-most Slave province and the Wopmay rocks close to the gneisses were collected systematically for K-Ar and laser step-heating 40Ar /39Ar analyses of the biotite and amphibole. The K-Ar biotite ag-es of the four Wopmay samples range from 1816 ± 18 Ma to 1854 ± 26 Ma, which is within the reported U-Pb zircon age range of the Wopmay orogen. The K-Ar biotite ages of the fifteen Acasta gneisses range from 1779 ± 25 Ma to 1877 ± 26 Ma, except for a younger sample (1711 ± 25 Ma). The 40Ar/39Ar biotite analyses of the three samples from the Wopmay orogen give the plateau ages of 1826 ± 21 Ma, 1886 ± 13 Ma, and 1870 ± 18 Ma. On the other hand, the 40Ar/39Ar analyses of the biotite crystals from the Acasta gneiss show a variety of ages. Three samples show the plateau ages of 1877 ± 8 Ma, 1935 ± 14 Ma, and 1951 ± 11 Ma. These plateau ages are a little older than the total gas ages. The 40Ar/39Ar analyses of the amphibole crystals show more varied age rela-tions. The two samples show consistent age relations between the plateau ages (1814 ± 22 Ma and 1964 ± 12 Ma) and the total gas ages (1789 ± 23 Ma and 1967 ± 11 Ma), respectively. Some sam-ples have the apparent old age of 2000 Ma in the middle temperature fractions. These old frac-tions are due to that the originally existed amphibole crystals formed in Archean were affected by the thermal events during the Wopmay orogeny. but did not fully reset. The results suggest that the K-Ar system ages of the biotite and amphibole of the Archean Acasta gneiss that is aged from 4200 to 2600 Ma of zircon U-Pb ages were rejuvenated in the Paleo–Proterozoic ages. The heat source that rejuvenated the K-Ar system ages may have arisen due to the asthenospheric intrusion into the wedge mantle, which took place because of the subduction rollback.

Finding the ideal statistical method for grouping phenological data is always an important step for breeders to draw correct conclusions from it possibly. In this paper, K-cluster analysis is presented as a perfect tool for grouping phenological data. The present research was performed based on the phenological data of 61 strawberries (Fragaria × ananassa) cultivars of different geo-graphical origins grown in Estonian conditions. Groups of strawberry cultivars were deter-mined according to flowering and ripening time: early, middle and late, based on the sum of ef-fective temperatures above +5°C. The result of the K-cluster analysis carried out in this way makes it possible to precisely plan the ripening time of berries of different strawberry cultivars. Using such analysis data, it is possible to combine with different early, mid or late strawberry cultivars to extend the picking period. Also, this technique can be used to study the effect of cli-matic changes occurring over the years on the phenology of strawberry cultivars grown in the region.

In the particular configuration of the scalar field K-essence in the Wheeler-DeWitt quantum equation, for some age in the Bianchi type I anisotropic cosmological model, a fractional differential equation for the scalar field arises naturally. The order of the fractional differential equation is $\beta=\frac{2\alpha}{2\alpha - 1}$. This fractional equation belongs to different intervals, depending on the value of the barotropic parameter; when $\omega_{X} \in [0,1]$, the order belongs to the interval $1\leq \beta \leq 2$, and when $\omega_{X}\in[-1,0)$, the order belongs to the interval $0<\beta \leq 1$. In the quantum scheme, we introduce the factor ordering problem in the variables $(\Omega,\phi)$ and its corresponding momenta $(\Pi_\Omega, \Pi_\phi)$, obtaining a linear fractional differential equation with variable coefficients in the scalar field equation, then the solution is found using a fractional power series expansion. The corresponding quantum solutions are also given. We found the classical solution in the usual gauge N obtained in the Hamiltonian formalism and without a gauge. In the last case, the general solution is presented in a transformed time $T(\tau)$, however in the dust era we found a closed solution in the gauge time $\tau$.

Abstract: The surge of diabetes poses a significant global health challenge, particularly in Oman and the Middle East. Early detection of diabetes is crucial for proactive intervention and improved patient outcomes. This research leverages the power of machine learning, specifically, Convolutional Neural Networks (CNNs), to develop an innovative 4D CNN model dedicated to early diabetes prediction. A region-specific dataset from Oman is utilized to enhance health outcomes for individuals at risk of developing diabetes. The proposed model showcases remarkable accuracy, achieving an average accuracy of 98.49% to 99.17% across various epochs. Additionally, it demonstrates excellent F1 score, recall, and sensitivity, highlighting its ability to identify true positive cases. The findings contribute to the ongoing effort to combat diabetes and pave the way for future research in using deep learning for early disease detection and proactive healthcare.

This paper explores the dynamic interplay of K-12 education, the Fourth Industrial Revolution (IR 4.0), and internationalization in the Philippines. Through qualitative content analysis, key themes emerged, shedding light on the impact of K-12 education on global competitiveness, challenges in embracing IR 4.0 technologies, and opportunities arising from internationalization efforts. The findings underscore the significance of curriculum alignment with international standards, comprehensive digital literacy training, and fostering a global mindset to prepare students for the digitally-driven, interconnected world. Understanding the implications of these themes is crucial for the Philippines' education system, as it navigates towards a transformative and globally competitive future. Further, this research offers evidence-based recommendations and addresses research gaps, contributing to a broader understanding of how the convergence of these forces shapes the future of Philippine education. Future research avenues may explore long-term impacts on workforce preparedness, innovative IR 4.0 integration, and the effectiveness of internationalization efforts on educational outcomes. Eventually, this study inspires an education system that nurtures learners equipped to thrive in an ever-evolving global landscape.

Forensic document examiners can determine the authenticity of questioned documents by analyzing the ink used to create them. If an ink mismatch is found, it could be a sign of scam, backdating, or forgery. In this research a Hyperspectral Images of iVision HHID dataset is used to detect number of possible inks used in document. By using Hyperspectral Images, it’s possible to detect ink mismatch in a given document. In this research unsupervised learning method K-means is used to detect number of inks. Approximate number of clusters are determined by Elbow and Silhouette method before implementation of K-means.

Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenarios require varying levels of granularity in address components, further complicating the parsing process. To address these challenges and adapt to low-resource environments, we propose CapICL, a novel Chinese address parsing model based on the In-Context Learning (ICL) framework. CapICL leverages a sequence generator, regular expression matching, BERT semantic similarity computation, and GPT modeling to enhance parsing accuracy by incorporating contextual information. We construct the sequence generator using a small annotated dataset, capturing distribution patterns and boundary features of address types to model address structure and semantics, mitigating interference from unnecessary variations. We introduce the REB-KNN algorithm, which selects similar samples for ICL-based parsing using regular expression matching and BERT semantic similarity computation. The selected samples, raw text, and explanatory text are combined to form prompts, and inputted into the GPT model for prediction and address parsing. Experimental results demonstrate significant achievements of CapICL in low-resource environments, reducing dependency on annotated data and computational resources. Our model's effectiveness, adaptability, and broad application potential are validated, showcasing its positive impact in natural language processing and geographical information systems.

The Na+/K+ ATPase is a protein involved in the active transport of ions across the cellular membrane. Ouabain is a cardiotonic glycoside that, by inhibiting the Na+/K+ pump, interferes with cell processes mediated directly by the pump, but also indirectly influences other cellular processes, such as cellular cycle and proliferation, growth, cell differentiation, angiogenesis, migration, adhesion and invasion. We used the SK-BR-3 breast cancer cell line, mesenchymal stem cells (MSCs), and tumor-associated fibroblasts (TAFs) in vitro for determining the changes induced by Ouabain in concentration of 10-5 M, 10-6 M, 10-8 M, 10-9 M on these cellular types, employing specific methods: SEM for morphological evaluation; immunocytochemistry, flowcytometry to assess immunophenotypical markers expression, cell cycle and Annexin V/PI assay for cellular proliferation and viability testing; flowchamber assay to evaluate functional adhesion behavior; RT-PCR for Na+/K+ ATPase subunits molecular expression. Being indicative of the pro-apoptotic and inhibitory effect of Ouabain on tumor invasion and metastasis, the results support the addition of Ouabain to the oncological therapeutic arsenal, trailing the “repurposing drugs” approach.

In an $m$-person symmetric game, all players are identical and indistinguishable. In this paper, we find that the payoff tensor of the player $k$ in an $m$-person symmetric game is $k$-mode symmetric, and the payoff tensors of two different individuals are the transpose of each other. Furthermore, we reformulate the $m$-person symmetric game as a tensor complementary problem and demonstrate that locating a symmetric Nash equilibrium is equivalent to finding a solution to the resulting tensor complementary problem. Finally, we use the hyperplane projection algorithm to solve the resulting tensor complementary problem, and we present some numerical results to find the symmetric Nash equilibrium.

This study aimed to investigate the possibility of using one-shot hyperspectral airborne images to recognize crops for an area with many small plots. The results showed that unsupervised clustering methods could classify crops with an accuracy of 80%, which improved to 90% when restricted to only grain crops, using a single airborne hyperspectral recording. However, additional layers such as NDVI, DTM, slope, and aspect did not improve classification accuracy. For comparison, the accuracy of clustering time series Sentinel-2 images with NDVI layers and DTM-derived data yielded an accuracy of: 74% ,Sentinel-2 time series 68% and single one registration before harvest - 39%. The results of the random forest classification were slightly less accurate due to a lack of sufficient reference data. However, it is challenging to verify the reported accuracy of crop recognition in the literature above 90% due to differences in analysis methodologies, reference data selection, pixel/object approaches, metric choice, and calculation formulas used.

Antimicrobial resistance is on the rise, and there aren't enough new treatments to combat it. This might send the modern world back to the pre-antibiotic age. The molecular hybrids of pyrazolo[3,4-b]pyridine and triazole have been designed, synthesized, and analyzed for their drug-like molecule nature and in vitro analyses for their inhibition potentials against S. Aureus and K. Pneumoniae. The compounds CY-R2-25 and CY-R2-28 have been identified as the high potential molecules in this series based on in vitro experiments. CY-R2-25 has zone of inhibition values of 15 0.82 and 14 0.7, whilst CY-R2-28 has the zone of inhibition values of 18 0.95 and 16 0.82 against S. Aureus and K. Pneumoniae, respectively. MIC and MIB values for CY-R2-25 and CY-R2-28 against S. Aureus and K. Pneumoniae are 0.25 and 0.5, respectively.

In this paper, we have established some new bounds of Fejér type Hermite-Hadamard inequality for k−fractional integrals involving r−times differentiable preinvex functions. It is noteworthy that in the past there was no weighted version of left and right sides of the Hermite-Hadamard inequality for k-fractional integrals for generalized convex functions available in literature.

Scale invariance is expected in empty Universe models, while the presence of matter tends to suppress it. As shown recently, scale invariance is certainly absent in cosmological models with densities equal to or above the critical value ρ_c = 3(H₀)²/(8πG). For models with densities below ρc, the possibility of limited effects remains open. If present, scale invariance would be a global cosmological property. Some traces could be observable locally. For the Earth-Moon two-body system, the predicted additional lunar recession would be increased by 0.92 cm/yr, while the tidal interaction would also be slightly increased. The Earth-Moon distance is the most systematically measured distance in the Solar System, thanks to the Lunar Laser Ranging (LLR) experiment active since 1970. The observed lunar recession from LLR amounts to 3.83 (±0.009) cm/yr; implying a tidal change of the length-of-the-day (LOD) by 2.395 ms/cy. However, the observed change of the LOD since the Babylonian Antiquity is only 1.78 ms/cy, a result supported by paleontological data, and implying a lunar recession of 2.85 cm/yr. The significant difference of (3.83-2.85) cm/yr = 0.98 cm/yr, already pointed out by several authors over the last two decades, corresponds well to the predictions of the scale-invariant theory, which is also supported by several other astrophysical tests.

Cancer stem cells (CSCs) are a tumor cell subpopulation that drives tumor progression and metastasis, leading to poor overall survival of patients. In colorectal cancer (CRC), hyper-activation of Wnt/β-catenin signaling by mutation of both Adenomatous polyposis coli (APC) and K-Ras increases the size of the CSC population. We previously showed that the CPD0857 inactivates Wnt/β-catenin signaling by promoting ubiquitin-dependent proteasomal degradation of β-catenin and Ras proteins, thereby decreasing proliferation and increasing apoptosis of CRC lines. CPD0857 also decreased growth and invasiveness of CRC cells harboring mutant K-Ras resistant to EGFR mAb therapy. Here, we show that CPD0857 treatment decreases proliferation and increases neuronal differentiation of neural progenitor cells (NPCs). CDP0857 effectively reduced expression of CSC markers and suppressed self-renewal capacity. CPD0857 treatment also inhibited proliferation and expression of CSC markers in D-K-Ras MT cells carrying K-Ras, APC and PI3K mutations, indicating inhibition of PI3K/AKT signaling. Moreover, CPD0857-treated xenograft mice showed regression of tumor growth and decreased numbers of CSCs in tumors. We conclude that CPD0857 could serve as the basis of a drug development strategy targeting CSCs activated through Wnt/β-catenin-Ras MAPK-PI3K/AKT signaling in CRCs.

Following legalization, cannabis has quickly become an important horticultural crop in Canada and increasingly so in other parts of the world. However, due to previous legal restrictions on cannabis research there are limited scientific data on the relationship between nitrogen (N), phosphorus (P), and potassium (K) supply (collectively: NPK) and the crop yield and quality. This study examined the response of a high delta-9-tetrahydrocannabinol (THC) Cannabis sativa cultivar grown in deep-water culture with different nutrient solution treatments varying in their concentrations (mg L^-1) of N (70, 120, 180, 250, 290), P (20, 40, 60, 80, 100) and K (60, 120, 200, 280, 340) according to a central composite design. Results demonstrated that inflorescence yield responded quadratically to N and P, with the optimal concentrations predicted to be 194 and 59 mg L^-1, respectively. Inflorescence yield did not respond to K in the tested range. These results can provide guidance to cultivators when formulating nutrient solutions for soilless cannabis production and demonstrates the utility of surface response design for efficient multi-nutrient optimization.

The visualization of hyperspectral images in display devices, having RGB colour composition channels is quite difficult due to the high dimensionality of these images. Thus, principal component analysis has been used as a dimensionality reduction algorithm to reduce information loss, by creating uncorrelated features. To classify regions in the hyperspectral images, K-means clustering has been used to form clusters/regions. These two algorithms have been implemented on the three datasets imaged by AVIRIS and ROSIS sensors.

The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk level in different counties have been determined and analyzed. Using Pearson Correlation, K-means clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.

This paper presents an effective heart disease prediction model through detecting the anomalies, also known as outliers, in healthcare data using the unsupervised K-means clustering algorithm. Most existing approaches for detecting anomalies are based on constructing profiles of normal instances. However, such techniques require an adequate number of normal profiles to justify those models. Our proposed model first evaluates an \textit{optimal} value of K using Silhouette method. Next, it intends to locate anomalies that are far from a certain threshold distance with respect to their clusters. Finally, the five most popular classification techniques such as K-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Machines (SVM), Naive Bayes (NB), and Logistic Regression (LR) are applied to build the resultant prediction model. The effectiveness of the proposed methodology is justified using a benchmark dataset of heart disease.

More than 15,000 prescriptions and over the counter drugs are available according to the US Food and Drug Administration website. Moreover, several herbal medicines and dietary supplements are readily available to add to the list of possible drugs, which can potentially cause adverse drug interactions. These are a pressing concern for all as they can interfere with many dental procedures. Additionally, the number of geriatric patients seen in routine dental practice has increased over time. This implies that there are more patients with multiple diseases and health conditions like hypertension, diabetes, problems associated with the cardiovascular, renal and gastrointestinal systems, arthritis, osteoporosis, etc. All these require patients to be on certain medications. Furthermore, advancement in the dental field has led to more complex dental procedures (implants, grafts) being carried out in a general dental practice. These advanced and slightly more invasive treatments require the use of certain drugs before, during and after the treatment like local anesthetics, vasoconstrictors, anxiolytics, analgesics and antibiotics. All of these can possibly interact with medications a patient is already taking and can also interfere with the current dental treatment and create complications. This article aims to provide necessary information about commonly encountered systemic diseases and associated treating medications, their mechanism of action, possible complications and their management. The classes of drugs discussed include anti-platelet agents, vitamin K antagonists, novel oral anticoagulants, bisphosphonates, disease-modifying anti-rheumatic drugs and oral contraceptives.

Concept Knowledge (C-K) theory has been used in engineering and science-based research for more than a decade. Design of an Information Technology (IT) artefact is mostly pragmatic in nature. Design Science Research (DSR) methodology applied and studied in many Information Systems (IS) research. Many sub design decisions involved through the design of an IT artefact from a concept (idea) to a working prototype. A DSR artefact is based on a combination of decisions made during several sub-design stages. Artefacts are built based on the selection of elements in each sub-design space. Recording the design decisions on each sub-design space would be beneficial for future researchers. By knowing the design decisions on each sub-design space, researchers would be able to try different combinations of the design. C-K theory provides the ability to capture the design processes’ several sub-design spaces. In this paper, we discuss the DSR research methodology by looking at the stages proposed in the literature, and the application of C-K theory in an IT-based DSR. This paper also proposed a C-K theory-based protocol called Concept Tree for tracking and reporting artefact design steps. The application of C-K theory in DSR is exhibited using the implementation of the Concept Tree for a prototype design IT artefact.

The violation of privacy, others people or personal, is a very current problem, which concerns not only on the web but also in private life. In the years 1990 it was expected that nowadays, that any routine operation was carried out "manually", and it would be performed through mobile phones or personal computers. The problem pertains the distribution network that allows to share and bring together information and as result the network becomes unsafe, if subjected to attacks. Nowaday we put personal information on web because otherwise we are seen as “weak”. This work aims to measure and analyze how much information are shared by users of a pre-established social network and it is carried out through a set of algorithms techniques of machine learning.

A Pogorelov polytope is a combinatorial simple 3-polytope realizable in the Lobachevsky (hyperbolic) space as a bounded right-angled polytope. It has no 3- and 4-gons and may have any prescribed numbers of k-gons, k ≥ 7. Any polytope with only 5-, 6- and at most one 7-gon is Pogorelov. For any other prescribed numbers of k-gons, k ≥ 7, we give an explicit construction of a Pogorelov and a non-Pogorelov polytopes. Any Pogorelov polytope different from Löbel polytopes can be constructed from the 5- or the 6-barrel by cuttings off pairs of adjacent edges and connected sums with the 5-barrel along a 5-gon with the intermediate polytopes being Pogorelov. For fullerenes there is a stronger result. Any fullerene different from the 5-barrel and the (5, 0)-nanotubes can be constructed by only cuttings off adjacent edges from the 6-barrel with all the intermediate polytopes having 5-, 6- and at most one additional 7-gon adjacent to a 5-gon. This result can not be literally extended to the latter class of polytopes. We prove that it becomes valid if we additionally allow connected sums with the 5-barrel and 3 new operations, which are compositions of cuttings off adjacent edges. We generalize this result to the case when the 7-gon may be isolated from 5-gons.

While lidar-based forest inventory methods have been widely demonstrated, prediction of tree diameters with lidar is not well understood. The performance metrics typically used in studies for prediction of diameters can be difficult to interpret and may not support comparative inferences between sampling designs or study areas. We evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions using two indices which are easier to interpret and compare. The indices are based on the coefficient of determination (R²), and root mean square deviation (RMSD). These indices facilitate comparisons with alternative (non-lidar) inventory strategies, and with other project areas. We evaluate k nearest neighbors (k-NN) dbh density (relative frequency by dbh class) prediction strategies with lidar for 190 training plots distribute across the 800 km² Savannah River Site in South Carolina, USA. We evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. Amongst the examined strategies we found Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

The globe and more particularly the economically developed regions of the world are currently in the era of the fourth Industrial revolution (4IR). Conversely; the economically developing regions in the world and more particularly the African continent have not yet even fully passed through the Third Industrial Revolution (3IR) wave and its economy is still heavily dependent on the agricultural field. On the other hand, the state of global food insecurity is worsening on an annual basis thanks to the exponential growth of the global human population which continuously heightens the food demand in both quantity and quality. This justifies the significance of the focus on digitizing agricultural practices to improve the farm yield to meet up with the steep food demand and stabilize the economy of the African continent and countries like India whose economy is mainly dependent on Agriculture. The tools we have at our disposal to utilize in the digitization of farming practices include space technology and Global Navigation and Satellite System (GNSS) in particular, Machine learning (ML), precision agriculture and communication systems such as the Internet of Things (IoT) and Information And Communication Technologies (ICT). The most pressing challenges in the farming field include the monitoring of diseases, pests, weeds and nutrient deficiencies in the crops as early detection translates to swift and timely correction actions and hence more yield at the end of a farming cycle. Vast opportunities in the field of precision agriculture still exist that can amount to further research studies such as the lack of real-time monitoring and real-time corrective action focus.

Metallo-β-lactamases (MBLs) are members of the structurally conserved but functionally diverse MBL-fold superfamily of metallohydrolases. MBLs are a major concern for global health care as they efficiently inactivate β-lactam antibiotics, including the “last-resort” carbapenems, and no clinically suitable inhibitors are currently available. Increasingly, promiscuous β-lactamase activity is also observed in other members of the superfamily, including from viruses, which represents an underexplored reservoir for future pathways to antibiotic resistance. Here, two such MBL-fold enzymes from Bacillus phages, the cyclic mononucleotide-degrading proteins ApycGoe3 and ApycGrass, are shown to efficiently degrade β-lactam substrates in vitro. In particular, ApycGrass displays a distinct preference for carbapenem substrates with a catalytic efficiency that is within one order of magnitude of that of the clinically relevant MBL NDM-1. Mutagenesis experiments also demonstrate that the loss of a metal-bridging aspartate residue reduces nuclease activity up to 35-fold, but improves carbapenemase activity. In addition, we propose that the oligomeric state significantly influences β-lactamase activity by modifying access to the active site pocket. Together, these observations hint at a possible new avenue of resistance via the spread of phage-borne MBL-fold enzymes with β-lactamase activity.

Arterivirus can establish persistent infection in animals such as equids, pigs, nonhuman primates, rodents, and possums. Some Arterivirus can even cause overt and severe diseases such as Equine Arteritis in horses and Porcine Reproductive and Respiratory Syndrome in pigs, leading to huge economic losses. Arterivirus have evolved viral proteins to antagonize the host cell’s innate immune responses by inhibiting type I interferon (IFN) signaling, assisting viral evasion and persistent infection. So far, the role of the Arterivirus glycoprotein 5 (GP5) protein in IFN signaling inhibition remains unclear. Here, we investigated the inhibitory activity of 47 Arterivirus GP5 proteins derived from various hosts. We demonstrated that all GP5 proteins showed conserved activity for antagonizing TIR-domain-containing adapter protein inducing interferon-β (TRIF)-mediated IFN- signaling through TRIF degradation. In addition, Arterivirus GP5 proteins showed conserved inhibitory activity against IFN-β signaling, induced by either pig or human TRIF. Furthermore, certain Arterivirus GP5 proteins could inhibit the induction of IFN-stimulated genes. These findings highlight the role of Arterivirus GP5 proteins in supporting persistent infection.

Regulatory cystathionine β-synthase (CBS) domains are widespread in proteins; however, difficulty in structure determination prevents a comprehensive understanding of the underlying regulation mechanism. Tetrameric microbial inorganic pyrophosphatase containing such domains (CBS-PPase) is allosterically inhibited by AMP and ADP and activated by ATP and cell alarmones diadenosine polyphosphates. Each CBS-PPase subunit contains a pair of CBS domains but binds cooperatively only one molecule of the mono-adenosine derivatives. We used site-directed mutagenesis of Desulfitobacterium hafniense CBS-PPase to identify the key elements determining the direction of the effect (activation or inhibition) and the “half-of-the-sites” ligand binding stoichiometry. Seven amino acid residues were selected in CBS1 domain based on the available X-ray structure of the regulatory domains and substituted by alanine and other residues. The interaction of 11 CBS-PPase variants with the regulating ligands was characterized by activity measurements and isothermal titration calorimetry. Lys100 replacement reversed the effect of ADP from inhibition to activation, whereas Lys95 and Gly118 replacements made ADP activator at low concentrations but inhibitor at high concentrations. Replacements of these residues for alanine increased the stoichiometry of mono-adenosine phosphate binding twofold. These findings identify several key protein residues and suggest “two non-interacting pairs of interacting regulatory sites” concept in CBS-PPase regulation.

Background: The effectiveness of the anti-COVID-19 vaccine remains a matter to be clarified. Methods: The humoral and cellular immunity after the administration of three doses of the Pfizer–BioNTech and Oxford AstraZeneca vaccines against SARS-CoV-2 over one year and the appearance of post-vaccination COVID-19 have been studied. Results: Anti-SARS-CoV-2 IgG and IgA antibodies showed a progressive increase throughout the vaccination period. This increase was greatest after the third dose. The highest levels were observed in subjects who had anti-SARS-CoV-2 antibodies prior to vaccination. There was an increase in CD4+ αβ, CD8+ γδ and TEM CD8+ γδ T cells, and a decrease in apoptosis in CD4+CD8+ and CD56+ αβ and γδ T cells. Post-vaccination SARS-CoV-2 infection was greater than 60%. The symptoms of COVID-19 were very mild and were related to γδ T cell deficit, specifically CD8+ TEMRA and CD56+ γδ TEM, as well as lower pre-vaccine apoptosis levels. Conclusions: Those results demonstrate the important role that γδ T cells play in SARS-CoV-2 vaccine immunization.

Populational aging is marked by chronic non-communicable diseases, such as metabolic syndrome (MetS). IL-10 and IL-1β are pleiotropic cytokines with multiple biological effects linked to metabolic disorders. This cross-sectional study assessed 193 participants' IL-10 and IL-1β serum levels regarding their role in developing MetS, clinical characteristics, and their IL1B rs1143627 and IL10 rs1800890 variants' genotype frequencies in a population over 60. IL-10 levels correlated weakly with HDL levels and fat mass and inversely with triglycerides, glucose, glycated hemoglobin, and estimated average blood glucose levels. IL-10 levels were also indirectly influenced by the patient's T2DM duration, lean mass amount, and bone mineral content. Participants with altered HDL, elevated serum glucose, raised HbA1c levels, or those over 80 had reduced serum IL-10 levels compared to those with normal levels or other age groups, respectively. Women also had higher serum IL-10 levels than men. Dissimilarity, IL-1β levels correlated directly only with the number of total leukocytes and segmented neutrophils, showing only significant variations with self-reported alcohol consumption. Our study also found that those with the IL10 AA genotype (lower IL-10 levels) had a significantly higher risk of developing MetS. These findings may help direct future research and more targeted therapeutic approaches in older adults.

Curdlan is a water-insoluble polymer that has structure and gelling properties useful in a wide variety of applications such as in medicine, cosmetics, packaging and the food and building industries. The capacity to produce curdlan has been detected in certain soil-dwelling bacteria of various phyla, although the role of curdlan in their survival remains unclear. One of the major limitations of the extensive use of curdlan in industry is the high cost of production during fermentation, partly because production involves specific nutritional requirements such as nitrogen limitation. Engineering of the industrially relevant curdlan-producing strain Agrobacterium sp. ATTC31749 is a promising approach that could decrease the cost of production. Here, during investigations on curdlan production, I found that curdlan was deposited as a capsule. Curiously, only a part of the bacterial population produced a curdlan capsule. This heterogeneous distribution appeared to be due to the activity of Pcrd, the native promoter responsible for the expression of the crdASC biosynthetic gene cluster. To improve curdlan production, Pcrd was replaced by a promoter (PphaP) from another Alphaproteobacterium, Rhodobacter sphaeroides. Compared to Pcrd, PphaP was stronger and only mildly affected by nitrogen levels. Consequently, PphaP dramatically boosted crdASC gene expression and curdlan production. Importantly, the genetic modification overrode the strict nitrogen depletion regulation that presents a hindrance for maximal curdlan production and from nitrogen rich, complex media, demonstrating excellent commercial potential for achieving high yields using cheap substrates under relaxed fermentation conditions.

Landscape configuration and forest structure assume an increasing importance as determinants of animal communities. This paper focused on nocturnal lepidoptera inhabiting alder patches in the Sila National Park, Italy. According to their shape, patches were divided into linear and compact ones to disentangle the role of forest structure and landscape configuration in determining the composition of nocturnal lepidopteran communities at different observation scales. We used the Mann-Whitney test for medians to Shannon diversity, Equitability, Fisher’s alpha, and nestedness to test differences among moth communities. We found that compact patches inhabit richer and more abundant communities. The abundance-based Correspondence Analysis showed moth communities clustered according to woodlot shape, except a compact woodlot having a linear-like moth community because entirely surrounded by grasslands. Percentage of forested area and abundance and composition of communities are positively correlated at 50 and 200 m buffers, while correlations are absent at smaller and larger buffers. Our results demonstrated that a width of 50 m may not be sufficient to give proper functionality to the wooded area, at least for moths. As consequence, planning of forest restorations should consider the importance to increase structural habitat continuity at larger scales.

Most neurodegenerative diseases have the characteristics of proteinopathies, i.e. they cause lesions to appear in vulnerable regions of the nervous system, corresponding to protein aggregates that progressively spread through the neuronal network as the symptoms progress. Alzheimer's disease is one of these proteinopathies. It is characterized by two lesions, neurofibrillary tangles (NFTs) and senile plaques, formed essentially of amyloid peptides (Aβ). A combination of factors ranging from genetic mutations to age-related changes in the cellular context converge in this disease to accelerate Aβ deposition. Over the last two decades, numerous studies have attempted to elucidate how structural determinants of its precursor (APP) modify Aβ production, and to understand the processes leading to the formation of different Aβ aggregates; e.g. fibrils and oligomers. The synthesis proposed in this review indicates that the same motifs can control APP function and Aβ production essentially by regulating membrane dimerization, and subsequently Aβ aggregation processes. The distinct properties of these motifs and the cellular context regulate the APP conformation to trigger the transition to the amyloid pathology. This concept can be transposed to the study of other proteinopathies, providing a framework for improving our understanding of these mechanisms that devastate neuronal functions.

Macroautophagy/autophagy plays an important role in cellular copper clearance. The means by which the copper metabolism and autophagy pathways interact mechanistically is vastly unexplored. Dysfunctional ATP7B, a copper-transporting ATPase, is involved in the development of monogenic Wilson disease, a disorder characterized by disturbed copper transport. Using in silico prediction, we found that ATP7B contains a number of potential binding sites for LC3, a central protein in autophagy pathway, so-called LC3 interaction regions (LIRs). The conserved LIR3, located at the C-terminal end of ATP7B, was found to directly interact with LC3B in vitro. Replacing the two conserved hydrophobic residues W1452 and L1455 of LIR3 significantly reduced interaction. Furthermore, autophagy was induced in normal human hepatocellular carcinoma cells (HepG2) leading to enhanced colocalization of ATP7B and LC3B on the autophagosome membranes. By contrast, HepG2 cells deficient of ATP7B (HepG2 ATP7B-/-) showed autophagy deficiency at elevated copper condition. This phenotype was complemented by heterologous ATP7B expression. These findings suggest a cooperative role of ATP7B and LC3B in autophagy-mediated copper clearance.

Yogic and meditative traditions have long held that the fluctuations of the breath and the mind are intimately related. While respiratory modulation of cortical activity and attentional switching are established, the extent to which electrophysiological markers of attention exhibit synchronization with respiration is unknown. To this end, we examined 1) frontal midline theta-beta ratio, an indicator of attentional control state known to correlate with mind wandering episodes and functional connectivity of the executive control network; 2) pupil diameter (PD), a known proxy measure of locus coeruleus (LC) noradrenergic activity; and 3) respiration for evidence of phase synchronization and information transfer (multivariate Granger causality) during quiet restful breathing. Our results indicate that both TBR and PD are simultaneously synchronized with the breath, suggesting an underlying oscillation of an attentionally relevant electrophysiological index that is phase-locked to the respiratory cycle which could have the potential to bias the attentional system into switching states. We highlight the LC’s pivotal role as a coupling mechanism between respiration and TBR, and elaborate on its dual functions as both a chemosensitive respiratory nucleus and a pacemaker of the attentional system. We further suggest that an appreciation of the dynamics of this weakly coupled oscillatory system could help deepen our understanding of the traditional claim of a relationship between breathing and attention.

Crustacean hyaluronidases are 1 poorly understood both in terms of their enzymatic properties and in terms of their structural features. In this work, we have shown that the hepatopancreas homogenate of the red king crab has a hyaluronidase activity that is an order of magnitude higher than its commercial counterpart. Zymography revealed the hyaluronidase activity of the protein roughly from40 to 50 kDa relative to the molecular marker used in electrophoresis. Analysis of the hepatopancreas transcriptome revealed a hyaluronidase sequence with an expected molecular weight of 42.5 kDa. It turned out that the reaction of cleavage of hyaluronate in the presence of a homogenate proceeds by the mechanism of b-elimination, which is well known for bacterial hyaluronidases. Thus, a new hyaluronidase of higher eukaryotes was found and described, which is not integrated into the modern classification of hyaluronidases.

Fraudulent transactions pose a significant threat to financial institutions and e-commerce platforms.Machine learning models, trained on historical labeled data (fraudulent vs. legitimate transactions), are often employed to identify and prevent fraud. However, real-world datasets frequently exhibit class imbalance, where fraudulent transactions (minority class) are significantly outnumbered by legitimate transactions (majority class). Machine learning models may perform poorly as a result of this imbalance, underestimating fraud and favouring the majority class. This paper proposes a novel approach to address class imbalance and improve fraud detection accuracy. We explore the implementation of FROST (Feature space RObust Synthetic saTuration) oversampling, a technique specifically designed to generate synthetic samples for the minority class. The FROST function leverages the k-nearest neighbors (KNN) algorithm and a user-defined amplification factor (m) to create synthetic data points that closely resemble existing minority class instances. We integrate the FROST-enhanced oversampling technique into the machine learning pipeline for fraud detection. The paper evaluates the effectiveness of this approach compared to traditional oversampling methods and analyzes its impact on classification accuracy metrics.

This paper provides a new discovery that adds to the contemporary theory of modelling of non-stationary queues, by capturing analytically the behavior of the root parameter, for the G1/M/1 PSFFA model of non-stationary Ek/M/1 queue. Additionally, it has been also revealed that the resulting root parameter reduces to the PSFFA model of non-stationary queue. Potential applications of PSFFA to Computer engineering are provided. Some challenging open problems are addressed combined with closing remarks and future research directions.

Malaria, leishmaniasis, and African trypanosomiasis are protozoan diseases that constitute a major global health problem, especially in developing countries; however the development of drug resistance coupled with the toxicity of current treatments have hindered their management. The implication of certain enzymes (dihydrofolate reductase, DHFR) or proteins (potassium channels) in the pathogenesis of these protozoan diseases is undeniable. In this study, a series of three DHFR inhibitors (6-5 fused heterocyclic derivatives X, Y and Z) and one K+ channel blocker (E4031) were screened for their inhibitory effect on Leishmania donovani, Plasmodium falciparum, and Trypanosoma brucei. Resazurin assay was used to assess antitrypanosomal and antileishmanial activities of test compounds, whereas the antimalarial activity was appraised through SYBR Green I test. Moreover, cytotoxicity of test compounds was evaluated on Vero, Raw 264.7 and HepG-2 cells using the resazurin-based test, whilst their pharmacokinetic properties were predicted using the online tool pkCSM. As a result, compound Y revealed a selective (selectivity index range: 2.69 - &gt;61.4; Vero, Raw 264.7 and HepG-2 cells) and broad-spectrum antiprotozoal activity against L. donovani promastigotes (IC50: 12.4 µM) and amastigotes (IC50: 4.28 µM), P. falciparum (IC50: 0.028 µM), and T. brucei brucei (IC50: 0.81 µM). In addition, compound X inhibited the growth P. falciparum (IC50: 0.0052 µM) and T. brucei brucei (IC50: 6.49 µM). In silico screening of the active antiprotozoal compounds revealed positive drug-likeness scores as none of Lipinski's rule of five’s criteria was violated by these compounds. However, in-depth pharmacokinetic and mechanistic studies are warranted to support discovery of novel antiprotozoal agents against malaria, leishmaniasis, and African trypanosomiasis by repurposing K+ channel blocker and DHFR inhibitors.

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by the dimensions of its re-entrant corners and the overall building height. The present study aims to find the wind effects and study of the pressure distribution with different flow patterns. Plan area of the building is around 300 square meter while the height of the building is 50 meters by keeping the equal length of the re-entrant corners. The research is performed using ANSYS CFX academic version and the results are depicted in various forms such as pressure coefficient (Cpe), stream lines in both vertical as well as in specific surface and pressure contours. The analysis is carried out by varying the wind incident angles, from 0° to 90° at the interval of 15°. The building dimension are scale down to perform the test on length scale of 1:100. Since the considered building model exhibits symmetry along both the axes, present study mostly emphasis on examining re-entrant corners located in the building. This method yields valuable information about how air circulates and how pressure is distributed across a broad spectrum of wind angles. This study provides valuable insights into flow circulation and pressure distribution for a wide range of wind angles.

The large quantity of information retrieved from communities, public data repositories, web pages, or data mining can be sparsed and poorly classified. This work shows how to employ unsupervised classification algorithms such as K-means proper to classify user reviews into their closest category, forming a balanced data set. Moreover, we found that the text vectorization technique significantly impacts the clustering formation, comparing TF-IDF and Word2Vec. The value for mapping a cluster with movie genre was 81.34% ± 20.48 of the cases when the TF-IDF was applied, whereas Word2Vec only yielded a 53.51% ± 24.1. In addition, we highlight the impact of the removal of stop-words. Thus, we detected that pre-compiled lists are not the best method to remove stop-words before clustering because there is much ambiguity, centroids are poorly separated, and only 57% of clusters could match a movie genre. Thus, our proposed approach achieved a 94% of accuracy. After analyzing the classifiers’ results, we appreciated a similar effect when divided by the stop-words method removal. Statistically significant changes were observed, especially in precision metric and Jaccard scores in both classifiers, using custom-generated stop lists rather than pre-compiled ones. Reclassifying sparse data is strongly recommended as using custom-generated stop lists.

The present work is a numerical simulation of velocity and mixture fraction fields in a turbulent non-reaction Propane jet flow issuing into parallel co-flowing air, in isothermal condition which has been experimentally described here: http://www.sandia.gov/TNF/DataArch/ProJet.html. The objective is a better understanding of the flow structure and mixing process, a situation in which there is no chemical interaction and heat-transfer. The two-equation Realizable k-ε eddy viscosity turbulence model has been used to simulate the turbulent flow field on a 2D plane (i.e., on a 5-degree sector of the experimental domain), because Realizable k-ε more accurately predicts the spreading rate of both planar and round jets and presents the best proficiency in comparison with all versions of the k-ε models. Afterward, axial and radial profiles of mean velocities, turbulence energy, mean mixture fraction, the mixture fraction half radius (Lf), and the mass flux diagram have been numerically elicited for grid independent mesh (mesh B) and compared with corresponding experimental data to assess the numerical model. To obtain turbulence kinetic energy, k, due to lack of w' in the experimental data, the assumption of w'=v' seems to be valid. Simulations have demonstrated that mean mixture fraction (at radial profiles at locations x/D=0, 4, 15, 30 and 50) and its half radius, Lf, which characterizes jet width expanse, are prominently well-captured; Moreover, mean vertical velocity fields (in X-direction: Umean) have revealed less accuracy but still conspicuously well-captured. However, mean vertical velocity fields (in Y-direction: Vmean) have disclosed less resolution; Likewise, turbulence kinetic energy, k, have manifested moderate accuracy (between Umean and Vmean). It should be noticed that although numerical results for absolute pressure, p, have been obtained on aforementioned sections, there were no experimental data to compare with them. Thus, the corresponding numerical data has not been demonstrated in this study.

In this paper, we give explicit asymptotic formulas for some sums over primes involving generalized alternating hyperharmonic numbers of types I, II and III. Analogous results for numbers with $k$-prime factors will also be considered.

Human endogenous retroviruses (HERVs) are ancient retroviral DNA sequences established into germline. They contain regulatory elements and encoded proteins few of which may provide benefits to hosts when co-opted as cellular genes. Their tight regulation is mainly achieved by epigenetic mechanisms which can be altered by environmental factors, e.g. viral infections, leading to HERV activation. Aberrant expression of HERVs associates with neurological disease, such as multiple sclerosis (MS) or amyotrophic lateral sclerosis (ALS), inflammatory processes and neurodegeneration. This review summarizes recent advances on the epigenetic mechanisms controlling HERV expression and the pathogenic effects triggered by HERV derepression. The article ends describing new promising therapies targeting HERV elements, one of which, temelimab, has completed phase II trials with encouraging results in treating MS. The information gathered here may turn helpful in the design of new strategies to unveil epigenetic failures behind HERV-triggered disease, opening new possibilities for druggable targets and/or for extending the use of temelimab to treat other associated diseases.

Single sample face recognition (SSFR) is a computer vision challenge. In this scenario, there is only one example from each individual on which to train the system, making it difficult to identify persons in unconstrained environments, particularly when dealing with changes in facial expression, posture, lighting, and occlusion. This paper suggests a different method based on a variant of the Binarized Statistical Image Features (BSIF) descriptor called Multi-Block Color-Binarized Statistical Image Features (MB-C-BSIF) to resolve the SSFR Problem. First, the MB-C-BSIF method decomposes a facial image into three channels (e.g., red, green, and blue), then it divides each channel into equal non-overlapping blocks to select the local facial characteristics that are consequently employed in the classification phase. Finally, the identity is determined by calculating the similarities among the characteristic vectors adopting a distance measurement of the k-nearest neighbors (K-NN) classifier. Extensive experiments on several subsets of the unconstrained Alex &amp; Robert (AR) and Labeled Faces in the Wild (LFW) databases show that the MB-C-BSIF achieves superior results in unconstrained situations when compared to current state-of-the-art methods, especially when dealing with changes in facial expression, lighting, and occlusion. Furthermore, the suggested method employs algorithms with lower computational cost, making it ideal for real-time applications.

Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) signals is a key signal processing problem. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis of long-term EEG recordings. This paper presents a new SWD method with a low computational complexity that can be easily trained with data from standard medical protocols. Precisely, EEG signals are divided into time segments for which the Morlet 1-D decomposition is applied. The generalized Gaussian distribution (GGD) statistical model is fitted to the resulting wavelet coefficients. A k-nearest neighbors (k-NN) self-supervised classifier is trained using the GGD parameters to detect the spike-and-wave pattern. Experiments were conducted using 106 spike-and-wave signals and 106 non-spike-and-wave signals for training and another 96 annotated EEG segments from six human subjects for testing. The proposed SWD classification methodology achieved 95 % sensitivity (True positive rate), 87% specificity (True Negative Rate), and 92% accuracy. These results set the path to new research to study causes underlying the so-called absence epilepsy in long-term EEG recordings.

Specifically this work is based on the concept of ‘dark energy’ as a phenomenal effect of expansion through which a theoretical value of Hubble’s constant has been introduced. It is a constant that is based on a postulate that the square root of ratio of the Siva’s constant ‘K’ and Hubble’s constant ‘H’ is exactly equal to the diameter of the neutral hydrogen atom. That is the, exact theoretical value of Hubble’s constant. This is always constant .However, space-time conversions and the changes in the velocity of light will affect the distance and velocity in Hubble’s equation. Deviation factors in velocity, distance and the Hubble’s constant have been calculated separately which are affected by change of velocity of light with expansion of space time. The observations are related to red shift. So the change factor in terms of Hubble’s constant has been calculated with respect to red shift. Thus a factor which affects the theoretical Hubble’s constant has been calculated to find the exact value of Hubble’s constant that satisfies the experimental results. The present theoretical value of Hubble’s constant has been calculated. The experimental results by plank, ACT (Atacama Cosmology Telescope), WMAP (Wilkinson Microwave Anisotropy Probe) etc. experiments are at par with the theoretical result. Thus the ontology of space time introduced in this theoretical work supposed to be correct and leads to a new theory of origin of universe for which a brief description has been provided.

Hyperspectral imaging provides vital information about the objects and elements present inside the image. That’s why they are very useful in satellite imagery as well as image forensics. Hyperspectral document analysis (HSDI) can be used for document authentication using ink analysis which can provide sufficient information about the composition and type of ink. In this project, we have implemented HSDI based ink classification technique using Principle Component Analysis for dimensionality reduction and K-means clustering for ink classification. This is unsupervised learning approach and it is very simple and efficient in order to classify limited number of bands. We have used this technique to classify 33 different bands of ink.

For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer details are influential while considering possibilities of taking term deposit subscription. An automated system is provided in this paper that approaches towards prediction of term deposit investment possibilities in advance. Neural network(NN) along with stratified 10-fold cross-validation methodology is proposed as predictive model which is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concluded that proposed model provides significant prediction results over other baseline models with an accuracy of 88.32% and Mean Squared Error (MSE) of 0.1168.

Imaging techniques such as computed tomographies (CT) play a major role in clinical imaging and diagnosis of malignant lesions. In recent years, spectral CT has emerged in the field of computed tomographies, utilizing detailed information from extracted spectral parameters of the specimen. Metal nanoparticle platforms enable effective payload delivery for this technique. Due to the possibility of surface modification, metal nanoparticles are predestined to facilitate molecular tumor targeting. In this work, we demonstrate the feasibility of anti-plasma membrane Heat shock protein 70 functionalized gold nanoparticles (AuNPs) for tumor specific multimodal imaging. Membrane-associated Hsp70 is exclusively presented on the plasma membrane of malignant cells of multiple tumor entities, but not on corresponding normal tissue cells, predestining this target epitope for tumor-selective in vivo targeting. In vitro microscopical analysis revealed the presence of cmHsp70.1-AuNP in the cytosol of tumor cell lines, being internalized via the endosomal-lysosomal pathway. In tumor bearing mice the biodistribution as well as the intratumorally enrichment of AuNP were examined 24h after i.v. application, in vivo. In parallel to spectral CT analysis, histological analysis confirmed the presence of tumor cells. In contrast to control NP, a significant enrichment of cmHsp70.1-AuNPs has been detected selectively in tumors of different preclinical mouse models. Furthermore, the biodistribution of AuNP, following i.v. injection, was analyzed by a machine-learning approach on digitalized slides. In summary, utilizing mHsp70 on tumor cells for guidance of cmHsp70.1 antibody functionalized nanoparticles enables sufficient enrichment and uniform distribution of AuNPs in mHsp70-expressing tumor cells, adequate for various microscopical imaging techniques and spectral-CT-based tumor delineation, in vivo.

Various peptides or non-structural amino acids are recognized by their specific target proteins and perform biological role in various pathways in vivo. Understanding the interactions between target protein and peptides (or non-structural amino acids) provides key information on the molecular interactions, which can be potentially translated to the development of novel drugs. However, it is experimentally challenging to determine the crystal structure of protein-peptide complexes. To obtain structural information on substrate recognition of peptide-recognizing enzyme, X-ray crystallographic studies were performed using triglycine (Gly-Gly-Gly) as main-chain of peptide. The crystal structure of Parengyodontium album Proteinase K in complex with triglcyine was determined at 1.4 Å resolution. Two different bound conformations of triglycine were observed at the substrate recognition site. The triglycine backbone forms stable interactions with β5-α4 and α5-β6 loops of main-chain. One of the triglycine-binding conformations was identical with the binding mode of a peptide-based inhibitor from a previously reported crystal structure of Proteinase K. Triglycine has potential application X-ray crystallography to identify substrate recognition sites in peptide binding enzymes.

A non-Newtonian fluid model is used to investigate the two-dimensional pulsatile blood flow through a tapered artery with a stenosis. The mixed convection effects of heat and mass transfer are also taken into account. By applying non-dimensionalization and radial coordinate transformation, we simplify the system in a tube. Under the finite difference scheme, numerical solutions are calculated for velocity, temperature concentration, resistance, impedance, wall shear stress and shearing stress at the stenosis throat. Finally, Quantitative analysis is carried out.

Although the signaling function of Na/K ATPase is been studied for decades, the chasm between the pumping function and the signaling function of Na/K – ATPase is still an open issue. This article explores the relationship between ion pumping and signaling with attention to the amplification of oxidants through this signaling function. Starting with some experimental observations published by our laboratories and others, we develop some predictions regarding cellular oxidant stress.

Yeast, crucial in beer production, holds promise as a valuable by-product resource, known as brewer's spent yeast (BSY), with potentially beneficial physiological effects. This study aimed to compare the composition and soluble polysaccharide content of Brewer's spent yeast with those of pure cultured yeast strains, namely Saccharomyces cerevisiae (SC) and S. boulardii (SB), to facilitate the utilization of BSY as an alternative source of functional polysaccharides. BSY exhibited significantly higher carbohydrate content and lower crude protein content than SC and SB cells. The residues recovered through autolysis were 53.11%, 43.83%, and 44.99% for BSY, SC, and SB, respectively. Notably, the polysaccharide content of BSY residue (641.90 μg/mg) was higher than that of SC (553.52 μg/mg) and SB (591.56 μg/mg). The yields of alkali-extracted water-soluble polysaccharides were 40%, 30%, and 35% for BSY, SC, and SB, respectively, with BSY comprising a higher proportion of water-soluble saccharides than SC and SB, including 49.3% mannan and 20.1% β-glucan. Furthermore, BSY demonstrated antioxidant activities, including superoxide dismutase (SOD), ABTS, and DPPH scavenging potential, suggesting its ability to mitigate oxidative stress. BSY also exhibited a significantly higher total phenolic compound content, indicating its potential as an effective functional food material.

Abstract: Breast cancer is one of the leading causes of death in the female population due to the re-sistance of cancer cells to many anticancer drugs used. Curcumin has cytotoxic activities against breast cancer cells, although it has limited use due to its poor bioavailability and rapid metabolic elimination. The synthesis of metal complexes of curcumin and curcuminoids is a relevant topic in the search for more active and selective derivatives of these molecular scaffolds. However, solubil-ity and bioavailability are concomitant disadvantages of these types of molecules. To overcome such drawbacks, the preparation of inclusion complexes offers a chemical and pharmacologically safe option for improving the aqueous solubility of organic molecules. Herein, we describe the preparation of the inclusion complex of dimethoxy curcumin magnesium complex with cyclodex-trin (DiMeOC-Mg-BCD, 5) in the stoichiometric relationship 1:1. This new inclusion complex's solubility in aqueous media (PBS) was improved by a factor of 6x over the free metal complex (DiMeOC-Mg). Furthermore, 5 affects cell metabolic rate, cell morphology, cell migration, induced apoptosis, and downregulation of the MMP-2 and MMP-9, IL-6, and STAT3 expression levels on MDA MB 231 cell lines. Results of an antitumor assay in an in-ovo model showed up to 30% inhi-bition of tumour growth for breast cancer (MDA-MB-231) when using 5 (0.650 mg/Kg dose), and 17.29 % inhibition with the free homoleptic metal complex (1.5 mg/Kg dose, DiMeOC-Mg). While the formulation of inclusion complexes from metal complexes of curcuminoids demonstrates its usefulness in improving the solubility and bioavailability of these metallodrugs, the new DiMeOC-Mg-BCD exhibits excellent potential for use as a therapeutic agent in the battle against breast cancer.

: Intracellular tripeptide glutathione is an important agent of cell survival in hypoxia. Glutathione covalently binds to SH-groups of hemoglobin cysteine residues, protecting them from irreversible oxidation and changes its affinity to oxygen. Reduced glutathione (GSH) can also form a non-covalent complex with hemoglobin. Previously, we showed that hemoglobin tetramer has four noncovalent binding sites of glutathione GSH molecules inside, two of which are released during hemoglobin transition to deoxy form. In this study, we characterized the conserved cysteine residues and residues of non-covalent glutathione binding sites in the sequences of a number of hypoxia tolerant and hypoxia-sensitive mammals. The alpha subunit of all species considered was found to have no conserved cysteines, whereas the beta subunit contains Cys94 residue, which is conserved across species and whose glutathionylation changes the affinity of hemoglobin for oxygen 5-6-fold. In addition, the key residues of noncovalent glutathione binding sites in both alpha and beta subunits are absolutely conserved in all species considered, suggesting a common mechanism of hemoglobin redox regulation for both hypoxia-sensitive and hypoxia-tolerant mammals. The solvent accessibility of all HbA and HbB residues in oxy- and deoxy- forms was analyzed. The key residue betaCys94 is solvent accessible only in the deoxy form.

In diabetic foot infections (DFI), the clinically virulence of skin commensals are generally pre-sumed to be of low virulence. In this single-center study, we divided the wound isolates into two groups: skin commensals (coagulase-negative staphylococci, micrococci, corynebacteria, cutibacteria); and, pyogenicpathogenic pathogens, and followed the patients for ≥ 6 months. In this retrospective study among 1,018 DFI episodes (392 [39%] with osteomyelitis), we identified skin commensals as the sole culture isolates (without accompanying pyogenicpathogenic patho-gens) in 54 cases (5%). After treatment (antibiotic therapy [median of 20 days], hyperbaric oxy-gen in 98 cases [10%]), 251 episodes (25%) were clinical failures. Group comparisons between those growing only skin commensals and controls found no difference in clinical failure (17% vs 24 %, p=0.23) or microbiological recurrence (11% vs 17 %, p=0.23). The skin commensals were mostly treated with non-beta-lactam oral antibiotics. In multivariate logistic regression analysis, isolation of only skin commensals was not associated with failure (odds ratio 0.4, 95% confi-dence interval 0.1-3.8). Clinicians might wish to consider these isolates as potential pathogens when selecting a targeted antibiotic regimen, which may equally base on oral non-beta-lactam antibiotic agents susceptible to the corresponding skin pathogens.

Plasmodium species that cause malaria, a disease responsible for about half a million deaths per annum despite concerted efforts to combat it. The causative agent depends on type III beta phosphatidylinositol 4-kinase (PPI4K) during the development of merozoite. PPI4K is the only clinically validated Plasmodium kinase so far and its inhibitors are effective both in vitro and in vivo. In this work, a small library of ~22 000 fragments was virtually screened using PPI4K homology model to discover potential ligands of the enzyme. 16 virtual hits were selected based on ≤ -9.0 kcal/mol binding energy cut off and were subjected to similarity and substructure searching after they had passed PAINS screening. The derivatives obtained showed improved binding energies, which ranged from -10.00 to -13.80 kcal/mol. Moreover, the topmost ranking compound 31, with interesting drug-like quality was stable within the protein’s binding cavity during the 10 ns molecular dynamics simulation period. In addition, analysis of its binding pose revealed some unique binding interactions with PPI4K active site residues as the basis for the observed improved binding affinity. Overall, compound 31 appears to be a viable starting point for the development of PPI4K inhibitors with antimalarial activity.

Medicinal plants possess a surplus of novel and biologically active secondary metabolites that are responsible for counteracting diseases. Traditionally, Gomphandra tetrandra (Wall.) Sleumer is used to treat mental disorders. The present research was designed to explore phytochemicals from the ethanol leaf extract of Gomphandra tetrandra (Wall.) Sleumer to identify the potential pharmacophore(s) in the treatment of neurological disorders. The chemical compounds of the experimental plant were identified through GC-MS analysis. Besides, in-vitro antioxidant activity was assessed using different methods. Furthermore, in-vivo neurological activity was assessed in Swiss-albino mice. Computer aided analysis was appraised to determine the best-fit phytoconstituent of a total of fifteen identified compounds in the experimental plant extract against beta-amyloid precursor protein. The experimental extract revealed fifteen compounds in GC-MS analysis and the highest content was 9, 12, 15-octadecatrienoic acid (Z, Z, Z). Also, the extract showed potent anti-oxidant activity in in-vitro assays. Furthermore, in in-vivo neurological assays, the extract disclosed significant (p<0.05) neurological activity. The most favorable phytochemicals as neurological agents were selected via ADMET profiling and molecular docking was studied with beta-amyloid precursor protein. Moreover, in the computer aided study, 1, 5-Diphenyl-2H-1, 2, 4-triazoline-3-thione (Pub Chem CID: 2802516) was more active than other identified compounds with strong binding affinity to beta-amyloid precursor protein. The present in vivo and in silico studies revealed neuropharmacological features of G. tetrandra leaves extract as a natural agent against neurological disorders, especially Alzheimer’s disease.

During type 1 diabetes mellitus (T1DM) development, beta-cells undergo intense endoplasmic reticulum (ER) stress that could result in apoptosis through the failure of adaptation to the unfolded protein response (UPR). Islet transplantation is considered an attractive alternative among beta-cell replacement therapies for T1DM. To avoid the loss of beta-cells that will jeopardize the transplant´s outcome, several strategies are being studied. We have previously shown that prolactin induces protection against pro-inflammatory cytokines and redox imbalance-induced beta-cell death by increasing heat shock protein B1 (HSPB1) levels. Since the role of HSPB1 in beta cells has not been deeply studied, we investigated the mechanisms involved in unbalanced protein homeostasis caused by intense ER stress and overload of the proteasomal protein degradation pathway. We tested whether HSPB1-mediated cytoprotective effects involved UPR modulation and improvement of protein degradation via the ubiquitin-proteasome system. We demonstrated that increased levels of HSPB1: attenuated levels of pro-apoptotic proteins like CHOP and BIM, increased protein ubiquitination and the speed of proteasomal protein degradation. Our data showed that HSPB1 induced resistance to proteotoxic stress and thus enhanced cell survival via an increase in beta-cell proteolytic capacity. These results could contribute to generate strategies aiming at optimization of beta-cell replacement therapies.

Study of gross alpha (GA) and gross beta (GB) activity in road and surface deposited sediments were performed in various geographical areas in three Russian cities. To perform radiation measurements, new methods were applied which allow dealing with low mass and low volume dust size (2-100μm) samples obtained after the size fractionation procedure. The 2-10 μm fraction size has the highest gross beta activity concentration (GB)– 1.32Bq/g in Nizhny Novgorod (NN) and Rostov-On-Don (RND) while the 50-100 μm fraction size in Ekaterinburg. This is maybe associated with the subsistence of radionuclides that conveyed through natural processes and anthropogenic applications. The highest gross alpha activity concentration (GA) in fraction sizes was found in Rostov-on-Don city within the 50-100 μm– 0.22Bq/g. The fraction size 50-100 μmhas a higher gross alpha activity concentration than 2-10 and 10-50 μmfraction sizes due to natural partitioning of the main minerals constituting the urban surface deposited sediment (USDS). The geochemical processes that occur during the formation and transportation of USDS are reflected in the observed dependencies.Developed experimental methods of radiation measurements allowed to the extent the methodological base of urban geochemical studies.

The astacin protease Meprin β represents an emerging target for drug development due to its potential involvement in disorders such as acute and chronic kidney injury and fibrosis. Here, we elaborate on the structural basis of inhibition by a specific Meprin β inhibitor. Our analysis of the crystal structure suggests different binding modes of the inhibitor to the active site. This flexibility is caused, at least in part, by movement of the C-terminal region of the protease domain (CTD). The CTD movement narrows the active site cleft upon inhibitor binding. Compared with other astacin proteases, among those the highly homologous isoenzyme Meprin α, differences in the subsites account for the unique selectivity of the inhibitor. Although the inhibitor shows substantial flexibility in the orientation within the active site, the structural data as well as binding analyses including molecular dynamics simulations support a contribution of electrostatic interactions, presumably by arginine residues, to binding and specificity. Collectively, the results presented here and previously support an induced fit and substantial movement of the CTD upon ligand binding and, possibly, during catalysis. To the best of our knowledge, we here present the first structure of a Meprin β holoenzyme containing a zinc ion and a specific inhibitor bound to the active site. The structural data will guide rational drug design and the discovery of highly potent Meprin inhibitors.

Cancer immunotherapy reaches a remarkable achievement in various cancer types and brings new possibilities to improve cancer patients’ long-term survival. However, outcomes vary from case to case, and the present protocol benefits a small fraction of patients. One notable factor is the tumor microenvironment, especially the immune cell components, that may reflect the immune response's status quo on site. Thus, understanding the content of infiltrating immune cells in tumors is not only for research interesting but also a crucial subject toward precision medicine. We implement an algorithm for resolving relative proportions of twenty-one immune cell subclasses from a human tissue profiled transcriptome by microarray technology to reach the goal above. By selecting gene features and then adopting ?-Support Vector Regression, we can construct a deconvolution model and resolve the immune cell context. The excellent consistency between the estimated values and the correct immune-cell composition further demonstrates this approach provides a more natural alternative to revealing samples' immune cell content and reliable results like recent single-cell technologies. Based on this algorithm, the web-based deconvolution tool implemented named mySORT provides a user-friendly interface for estimating the immune cell content by uploading gene expression profiling. We also present comprehensive visualization 2D/3D plots in mySORT so that users can easily make a comparison between different samples. Finally, we synthesized pseudo-bulk expression data from single-cell transcriptomic datasets of 17 melanoma and 16 head and neck cancer patients. The deconvolution results of microarray-based data in the previous study and synthetic pseudo-bulk data all proved the excellent performance of mySORT. We believe that mySORT can help researchers in all fields easily understand complex immune microenvironment. The website of mySORT is freely accessible on https://symbiosis.iis.sinica.edu.tw/mySORT/.

In this brief communication, we propose the concept that capillary regression may represent a primary pathogenic process underlying COVID-19 infection, particularly in the serious and life-threatening manifestations of the disease. We suggest that the marked elevations of pro-inflammatory mediators that are observed in these seriously ill patients may directly induce capillary regression and endothelial cell (EC) loss. Recent autopsy studies are demonstrating EC loss leading to widespread microthrombi and associated tissue damage. Recent work has indicated that interleukin-1 beta (IL-1β), tumor necrosis factor-alpha (TNFα), and thrombin, individually and in combination, can potently cause capillary tube regression in experimental models in vitro and in vivo. Other pro-inflammatory mediators including interferon gamma (IFNγ), interleukin-4 (IL-4), and interleukin-13 (IL-13) were also shown to be pro-regressive and could be relevant mediators in COVID-19 patients. Interestingly, combinations of pharmacologic agents were identified that reduced capillary regression and protected capillary tube networks against these pro-inflammatory mediators. Such an approach might be an important therapeutic option going forward to treat key disease states where capillary regression plays a major underlying pathogenic role. Finally, if capillary regression is occurring in response to these pro-inflammatory mediators during COVID-19 infection, we suggest that combinations of blocking agents directed to these key pro-regressive mediators might be necessary to appropriately treat patients.

The novel coronavirus pneumonia (COVID-19) is a contagious acute respiratory infectious disease whose causative agent has been demonstrated to be a novel virus of the coronavirus family, SARSCoV-2. A recent pre-print study has showed a heme attack on the 1-beta chain of hemoglobin by COVID19. Beta-thalassemia results of a default in the hemoglobin beta- chain synthesis. 1,5% global population are heterozygotes for this disease. In this study, by a multiple linear regression, we have analyzed the evolution of COVID-19 infection in three Italian regions (Puglia, Sardinia, Sicilia) with different beta-thalassemic prevalences, in order to search a link. The results have showed that betathalassemic heterozygote population prevalence is correlated to immunity against COVID-19, by a regression. This paper is only for academic discussion, the hypotheses and conclusions needs to be confirmed by further research .

Given the high prevalence of cutaneous genus beta human papillomavirus (β-HPV) infections, it is important to understand how they are manipulating their host cells. This is particularly true for cellular responses to UV damage, since our skin is continually exposed to UV. The E6 protein from β-HPV (β-HPV E6) decreases the abundance of two essential UV-repair kinases (ATM and ATR). Since β-HPV E6 reduces their availability, the impact on downstream signaling events has been uncertain. We demonstrate that β-HPV E6 decreases ATM and ATR activation. This inhibition extended to XPA, an ATR target necessary for UV repair, lowering both its phosphorylation and accumulation. β-HPV E6 hinders POLη phosphorylation and foci formation, critical steps in translesion synthesis. ATM’s phosphorylation of BRCA1 is also attenuated by β-HPV E6. However, β-HPV E6’s hindrance of ATM/ATR signaling during UV-associated cell cycle arrest was incomplete. While there was less phosphorylation of immediate downstream targets (CHK1), events further down the cascade were not decreased. These observations are consistent with β-HPV infections making UV radiation more deleterious and support the proposed role of β-HPV in early stages of non-melanoma skin cancer development.

In the paper, the author presents explicit and unified expressions for a sequence of improper integrals in terms of the beta functions and the Wallis ratios. Hereafter, the author derives integral representations for the Catalan numbers originating from combinatorics.

Spectral photon counting cone-beam CT imaging is challenged by individual pixel response behaviour, which leads to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform post-processing ring artefact correction of sinogram data or scan reconstructions, without taking the pixel response explicitly into account. Here we present a novel post-processing method (DAC-shifting), which explicitly measures the current pixel response using flat field images, and subsequently corrects the projection data. The DAC-shifting method was evaluated with a repeat series of spectral photon counting imaging (Medipix3) of a phantom with different density inserts, and in iodine K-edge imaging. The method was also compared against PMMA based STC. The DAC-shifting method was shown to be effective in correcting individual pixel response, and was robust against detector instability. On the contrary, STC correction showed varying results, which was almost as good as DAC-shifting when data was acquired just after STC calibration, but worse with larger time differences. In K-edge imaging, DAC-shifting provides a sharper attenuation peak, and more uniform CT values, which is expected to benefit iodine concentration quantification.

In a context of increasingly necessary energy transition, precise modelling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSO) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modelling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow the estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

The agricultural sector in Palestine has a significant role in its economy. However, the production of this sector is affected by different kinds of plant diseases, specifically leaf diseases. Automatic agricultural leaf disease detection is essential for the early diagnosis and controls the overall health of fields. Image segmentation techniques, clustering, and deep learning are often used to detect diseased leaves. This study proposes a novel hybrid approach based on image classification. The hybrid approach combines the k-means clustering algorithm with Convolutional Neural Network (CNN), where k-means is used to detect the leaf’s infected area, then CNN is used for specifying the disease. We used the PlantVillage dataset for experimental verification as it contains several crops with different kinds of challenging diseases. We also examined the selection of optimal k-value using the Silhouette coefficient, Elbow method, and Kneedle Algorithm. The Silhouette technique was analyzed using three distance metrics; Euclidean, Manhattan, and Cosine. Its scores for the three-distance metrics were low, near-zero, and failed to produce the optimum k value. Besides, the Elbow method was complicated to use in image segmentation in terms of executing and visualizing the k value in its graph plot. Based on verification results, the Kneedle Algorithm produced better results in the consistency of choosing the optimal k value and showed superiority over other approaches. Therefore, the processed images were segmented with the k-means clustering algorithm with a Kneedle algorithm-based k value. Finally, a Convolutional Neural Network (CNN) is trained to classify the type of disease based on analyzing and testing leaf images. The hybrid model achieved high accuracy of 93.79% in disease identification, confirming the proposed model’s robustness.