Autophagy is a highly conserved catabolic process in eukaryotic cells. Reactive nitrogen species play roles as inductors and signaling molecules of autophagy. A key mechanism of NO-mediated signaling is S-nitrosylation, a posttranslational modification (PTM) of proteins at cysteine resi-dues. In the present work we analyzed the patterns of protein S-nitrosylation during the induc-tion of autophagy in Triticum aestivum roots. The accumulation of S-nitrosylated proteins in the cells during autophagy induced by KNO2 and antimycin A was visualized using monoclonal an-tibodies by Western blot analysis, and proteins were identified using a standard bottom-up pro-teomics approach. Protein S-nitrosylation is a labile and reversible PTM, and therefore SNO group can be lost during experimental procedures. Subsequent bioinformatic analysis using predictive algorithms and protein-ligand docking showed that identified proteins possess hypothetical S-nitrosylation sites. Analyzing protein-protein interaction networks enabled us to discover the targets that can directly interact with autophagic proteins, and those that can interact with them indirectly via key multifunctional regulatory proteins. In this study, we show that S-nitrosylation is a key mechanism of NO-mediated regulation of autophagy in wheat roots. A combination of in silico predictive algorithms with a mass spectrometry analysis provides a targeted approach for the identification of S-nitrosylated proteins.

Atherosclerosis (AS) is a chronic progressive disease caused by various factors, and causes various cerebrovascular and cardiovascular diseases (CVDs). Reducing the plasma levels of low-density lipoprotein-cholesterol (LDL-C) is the primary goal in preventing and treating AS. Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) plays a crucial role in regulating LDL-C metabolism. Panax notoginseng has potent lipid-reducing effects and protects against CVDs, and its saponins induce vascular dilatation, inhibit thrombus formation, and are used in treating CVDs. However, the anti-AS effect of the secondary metabolite, 20(S) -protopanaxatriol (20(S)-PPT), remains unclear. In this study, the anti-AS effect and molecular mechanism of 20(S)-PPT were investigated in vivo and in vitro by western blotting, real time-polymerase chain reaction (RT-PCR), Enzyme-linked Immunosorbent Assay (ELISA), immunofluorescence staining, and other assays. The in vitro experiments revealed that 20(S)-PPT reduced the levels of PCSK9 in the supernatant of HepG2 cells, upregulated low density lipoprotein receptor (LDLR) protein levels, promoted LDL uptake by HepG2 cells, and reduced PCSK9 mRNA transcription by upregulating the levels of FoxO3 protein and mRNA and decreasing the levels of HNF1α protein and mRNA. The in vivo experiments revealed that 20(S)-PPT upregulated aortic αSMA expression, increased the stability of atherosclerotic plaques, and reduced aortic plaque formation induced by a high-cholesterol fed in ApoE-/- mice (HCF group). Additionally, 20(S)-PPT reduced the aortic expression of CD68, reduced inflammation in the aortic root, and alleviated the hepatic lesions in the HCF group. The study revealed that 20(S)-PPT inhibited LDLR degradation via PCSK9 to alleviate AS.

Sepsis is a serious and life-threatening medical emergency associated with dysregulated host immune responses to infection. Like cerebral vascular or acute cardiovascular incidents, sepsis is considered a time-dependent condition having severe and long-term consequences on human health. Apart from organ support, prompt administration of appropriate antimicrobial therapy is crucial to limit the burden of complications related to sepsis in ICU patients. The management of septic patients requires comprehensive and multi-disciplinary strategies for an adequate diagnosis. Most of the ICU population receives empirical antibiotic therapy without having a confirmed diagnosis. The misuse of antibiotics in intensive care units may increase the possibility of developing multidrug resistance along with considerable ecological side effects. The first doses of empirical anti-microbial therapy are slightly higher, regardless of the presence or absence of organ dysfunction, which may upregulate the production of circulating pro-and-anti-inflammatory mediators, having negative effects on the general well-being of the patients. This notion supports the introduction of individualized antimicrobial approaches based on local patterns of resistance to ensure the appropriate dosage of empirical therapy, as well as to limit the emergence of multidrug resistance in advanced-care patients. The adequacy and treatment duration must be viewed at regular intervals for effective de-escalation, and novel diagnostic approaches must be introduced to improve the quality of care in the ICU population.

Till date there are three full length COVID 19 virus genome sequences available from India. The earlier two were reported from Kerala, Southern India and the more recent one has been reported from Gujarat, western part of India. In this paper we report two novel mutations in the Spike protein sequence of Gujarat’s isolate. These mutations are based on comparison with the original Wuhan sequence. The two mutations have been found to be located just upstream and downstream of the receptor binding domain (RBD). Out of these two one has also been found to affect the secondary structure of the S1 domain. Since both of these mutations lie near the receptor binding domain, they might influence the spike receptor interactions by changing the conformation of the spike protein S1 domain. These mutations are uniquely placed and might be important in the context of vaccine engineering and therapeutic interventions.

Staphylococcus aureus (S. aureus) is recognized worldwide as one of the major agents of dairy cow intra-mammary infections. This microorganism can express a wide spectrum of pathogenic factors used to attach, colonize, invade and infect the host. The present study evaluated 120 isolates from eight different countries that were genotyped by RS-PCR and investigated for 26 different virulence factors to increase the knowledge on the circulating genetic lineages among the cow population with mastitis. New genotypes were observed for South African strains while for all the other countries new variants of existing genotypes were detected. For each country, a specific genotypic pattern was found. Among the virulence factors, fmtB, cna, clfA and leucocidins genes were the most frequent. The sea and sei genes were present in seven out of eight countries; seh showed high frequency in South American countries (Brazil, Colombia, Argentina), while sel was harboured especially in one Mediterranean country (Tunisia). The etb, seb and see genes were not detected in any of the isolates, while only two isolates were MRSA (Germany and Italy) confirming the low diffusion of methicillin resistance microorganism among bovine mastitis isolates. This work demonstrated the wide variety of S. aureus genotypes found in dairy cattle worldwide. This condition suggests that considering the region of interest might help to formulate strategies for reducing the infection spreading.

With the aim to develop novel scaffolds for sustained release of drugs, we initially developed an easy approach for the synthesis of α,ω-homobifunctional mercaptoacyl poly(alkyl oxide)s. This was based on the esterification of the terminal hydroxyl groups of poly(alkyl oxide)s with suitably S-4-methoxytrityl (Mmt) protected mercapto acids, followed by removal of the acid labile S-Mmt group. This method allowed the efficient synthesis of the title compounds in high yield and purity, which were further used in the development a thioether cross-linked liposome scaffold, by thia-Michael reaction of the terminal thiol groups with preformed nano-sized liposomes bearing maleimide groups on their surface. The reaction process was followed by 1H-NMR, using a Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion NMR experiment (1H-NMR CPMG), which allowed real-time monitoring and optimization of the reaction process. The thioether cross-linked liposomal scaffold that was synthesized was proven to preserve the nanosized characteristics of the initial liposomes and allowed sustained release of calcein (which was used as a chromophore), providing evidence for the efficient synthesis of a novel drug release scaffold consisted of nanoliposome building blocks.

Recently, some authors have claimed that we may live in one of a pair of universes in which one is expanding receding from the Big Bang and its partner is contracting and moving towards the Big Bang. We show that near a black hole binary system, this event may be occurring. If we suppose that there is a N dimensional brane which contains many smaller k dimensional branes and black holes, there is a possibility that the curved space times near black holes act like mirrors. This is because these space-times contain two regions such that the branes in the one region have opposite quantum numbers with respect to the branes in the other region. Also, if branes in one region are expanding and go away from a point state and the Big Bang, anti-branes in the other region are contracting and moving towards the point state and the Big Bang. If black holes join and form a binary system, then their states become similar to two mirrors that are facing each other and producing many images themselves of smaller branes and even black holes in the binary system. Summing over all branes and images give the CPT system. Dark energy could be a result of the images of observed matter. Comparing the masses of the observed objects and dark energy, the angle between cosmic mirrors like black hole binary systems could be determined.

Image fusion is the process of combining multiple input images from single or multiple imaging modalities into a fused image, which is expected to be more informative for human or machine perception as compared to any of the input images. In this paper, we propose a novel method based on deep learning for fusing infrared images and visible images, named the LBP-based proportional input generative adversarial network (LPGAN). In the image fusion task, the preservation of structural similarity and image gradient information is contradictory, and it is difficult for both to achieve good performance at the same time. To solve this problem, we innovatively introduce Local Binary Patterns (LBP) into Generative Adversarial Networks (GANs), which effectively utilize the texture features of the source images, so that the network has stronger feature extraction ability and anti-interference ability. In the feature extraction stage, we introduce a pseudo-siamese network for the generator to extract the detailed features and the contrast features. At the same time, considering the characteristic distribution of different modal images, we propose a 1:4 scale input mode. Extensive experiments on the publicly available TNO dataset and CVC14 dataset show that the proposed method achieves the state-of-the-art performance. We also test the universality of LPGAN through the fusion of RGB and infrared images on the RoadScene dataset. In addition, LPGAN is applied to multi-spectral remote sensing image fusion. Both qualitative and quantitative experiments demonstrate that our LPGAN can not only achieve good structural similarity, but also retain rich detailed information.

In this paper after introducing a model of binary data matrix (BDM) for physical parameters of an evolving system (of particles), we develop a Hilbert space as an ambient space to derive induced metric tensor on embedded parametric manifold identified by associated joint probabilities of particles observables (parameters). Parameter manifold assumed as space-like hypersurface evolving along time axis, an approach that resembles 3+1 formalism of ADM and numerical relativity. We show the relation of endowed metric with related density matrix. Identification of system density matrix by this metric tensor, leads to the equivalence of quantum Liouville equation and metric compatibility condition while covariant derivative of metric tensor has been calculated respect to Wick rotated time or spatial coordinates. After deriving a formula for expected energy per particles, we prove the equality of this expected energy with local scalar curvature of related manifold. We show the compatibility of BDM model with Hamilton-Jacobi formalism and canonical forms. On the basis of the model, I derive the Ricci flow like dynamics as the governing dynamics and subsequently derive the action of BDM model and Einstein field equations. Given examples clarify the compatibility of the results with well-known principles such as equipartition energy principle and Landauer’s principle. This model provides a background for geometrization of quantum mechanics compatible with curved manifolds and information geometry. Finally, we conclude a “bit density principle” which predicts the Planck equation, De Broglie wave particle relation, , Beckenstein bound and Bremermann limit.

The editorial explores the realm of emerging translational research in neurology and psychiatry, providing insights into various subjects, including neurodegenerative disorders and innovative therapeutic methods. The main objective is to study neurological and psychiatric disorders, such as Alzheimer's disease, with a particular emphasis on techniques for neural regeneration and repair. The editorial highlights the importance of taking a comprehensive approach to studying and treating complex neurological and psychiatric conditions. This involves thoroughly reviewing research papers on the causes, development, biomarkers, and treatment options for these conditions. The editorial emphasizes the necessity of using multidisciplinary and integrative methods to gain a deeper understanding and improve the treatment of these conditions. The development of an animal model for recurrent primary dysmenorrhea showcases the innovative techniques employed in the investigation of gynecological disorders, illustrating the capacity of translational research to connect fundamental scientific knowledge with practical medical applications. The cooperative endeavors of researchers and clinicians emphasized in this editorial lay the foundation for revolutionary advancements that hold the potential to enhance outcomes for individuals afflicted with neurological and psychiatric disorders globally.

Recent research has implicated the gut microbiota in the development of lymphoma. Dysbiosis of the gut microbial community can disrupt the production of gut microbial metabolites, thereby impacting host physiology and potentially contributing to lymphoma. Dysbiosis-driven release of gut microbial metabolites such as lipopolysaccharides can promote chronic inflammation, potentially elevating the risk of lymphoma. In contrast, gut microbial metabolites, such as short-chain fatty acids, have shown promise in preclinical studies by promoting regulatory T-cell function, suppressing inflammation, and preventing lymphoma. Another metabolite, urolithin A, exhibited immunomodulatory and antiproliferative properties against lymphoma cell lines in vitro. While research on the role of gut microbial metabolites in lymphoma is limited, this article emphasizes the need to comprehend their significance, including therapeutic applications, molecular mechanisms of action, and interactions with standard chemotherapies. The article also suggests promising directions for future research in this emerging lymphoma and gut microbiome investigation field.

Systemic lupus erythematosus (SLE) is a prevalent autoimmune condition, yet its alignment with a specific host immunological pathway remains unclear. The THαβ host immunological pathway, recognized for its defense against viruses and prions, has recently emerged as a response to DNA, RNA, and protein pathogens. SLE patients often produce anti-double strand DNA antibodies and anti-nuclear antibodies, suggesting a potential association with the THαβ host immune reaction. Throughout the course of SLE, elevated levels of type 1 interferons, type 3 interferons, interleukin-10, IgG1, and IgA1 are commonly observed. These cytokines and antibody isotypes are indicative of the THαβ host immunological pathway. Similarly, Myasthenia gravis, Grave’s disease, Graft versus host disease, autoimmune hemolytic anemia, immune thrombocytopenia, dermatomyositis, and Sjogren’s syndrome are also linked to THαβ-related type 2 hypersensitivities. Considering the potential association of these diseases with dysregulated THαβ immune responses, therapeutic strategies such as anti-interleukin-10 or anti-interferons α/β could be explored to manage these disorders effectively.

There has been significant increase of studies investigating plasma biomarkers of Alzheimer’s and their relationship to cognitive functioning. The impact of ethnicity on this relationship has not been extensively studied. The current research investigated the relationship between the plasma biomarkers of total tau, Aβ40, Aβ42 and NfL and neuropsychological test performance in a bi-ethnic sample of cognitively unimpaired, older community dwelling adults. The 1326 cognitively unimpaired participants drawn from The Health & Aging Brain Study – Health Disparities (HABS-HD) study included 765 Mexican American participants and 860 non-Hispanic White participants with complete plasma biomarkers and neuropsychological testing. Plasma samples were assayed using Simoa technology. Significant differences in concentrations were found for all of the plasma biomarkers. NHWs had significantly higher levels of each of the biomarkers with a lower Aβ42/ Aβ40. With none of the biomarkers related to performance on any of the neuropsychological tests. For MAs, Aβ40 was the only biomarker that was significantly related to neuropsychological test performance. Aβ40 levels were negatively related to performance on Trails A, Trails B and Digit Symbol Substitution. Results suggest that the relationship of these biomarkers to cognitive functioning is impacted by ethnicity and may be domain specific.

Radish (Raphanus sativus L.), a root vegetable belonging to the Brassicaceae family, is considered as one of the representative crops displaying sporophytic self-incompatibility (SSI). The utilization of a self-incompatibility system in F1 breeding can improve the efficiency of cross combinations, leading to a reduction in breeding time and aiding in the development of novel F1 varieties. The successful implementation of this system necessitates the rapid and accurate identification of S haplotypes in parental lines. In this study, we identified a total of 9 S haplotypes among 22 elite radish lines through Sanger sequencing. Subsequently, we obtained sequences for showing 95% similarity to 9 S haplotypes, along with sequences identified by other researchers using BLAST. Following this, multiple sequence alignment (MSA) was conducted to identify SRK and SLG sequence similarities, as well as polymorphisms within the class I, II groups. Subsequently, S haplotype-specific marker sets were developed, targeting polymorphic regions of SRK and SLG alleles. These markers successfully amplified each of 9 S haplotypes. these markers will play a crucial role in the rapid and precise identification of parental S haplotypes in the radish F1 breeding process, proving instrumental in the radish F1 purity test.

Background: Crohn’s disease (CD) and ulcerative colitis (UC) are well defined phenotypes of chronic inflammatory bowel diseases (IBD). A mechanism of inflammation in these diseases is partially controlled by intestinal dendritic cell (DC). In this study we observed a mature CD83+DC in colonic bioptic samples, and its correlation with disease phenotype and activity. Methods: There were 219 subjects included in the study: 100 with UC, 44 with CD and 75 healthy subjects. Colonic biopsy specimens were incubated with primary antibody Anti-CD83. Intraepithelial CD83+DC were counted per 100 enterocytes. Presence of CD83+DC was analysed according type of IBD, histopathologic inflammation activity and treatment outcome. Results: The presence of mature CD83+DCs (0, ≥1) significantly differed among disease types of IBD (p=0.001), histologic inflammation activity (p=0.049) and applied therapy (p=0.001). The odds for CD83+DC presence was 5.2 times higher in CD group than in control/UC group. The odds for CD83+DC presence was 2.6 times higher in subjects without inflammation or chronic inflammation than in acute inflammation. It was also 3.7 times higher in subjects without therapy. The cut-off value 0.5 CD83+DC (Rock analysis area=0.699; SE 0,046;p<0.001;95%CI:0.609-0.788) had been assessed as a differentiation marker between UC and CD. Conclusion: Presence of CD83+DC could be used as a possible parameter in distinction between UC and CD, as well as predictor of inflammation activity and treatment outcome.

Coupling the Maxwell tensor to the Riemann-Christoffel curvature tensor is shown to lead to a geometricized theory of electrodynamics. While this geometricized theory leads directly to the classical Maxwell equations, it also extends their physical interpretation by giving charge density, mass density and the four-velocity that describes their motions geometric definitions. Assuming the existence of a conserved energy-momentum tensor, all solutions to the geometricized theory of electrodynamics developed here are shown to be consistent with the emergence of gravity obeying the General Relativity field equation augmented by a term that mimics the properties of dark matter and/or dark energy. Finally, due to the symmetries of the theory, the properties and phenomenology of antimatter emerge in solutions.

Brown-Séquard Syndrome (BSS) is a rare spinal cord injury characterized by asymmetrical motor and sensory dysfunction. Trauma to the spinal cord, particularly the hemi section, is the primary cause. Diagnosis involves a thorough medical history, physical examination, and imaging studies. Treatment focuses on stabilization, rehabilitation, and potential emerging therapies. This article provides a comprehensive overview of BSS, including its causes, symptoms, diagnosis, and treatment.

This article deals with the queueing-inventory system, composed of c junior servers, a senior server, two finite waiting halls, and an infinite orbit. On occasion, junior servers encounter challenges during customer service. In these instances, they approach the senior server for guidance in resolving the issue. Suppose the senior server is engaged with another junior server. The approaching junior servers await their turn in a finite waiting area with a capacity of c for consultation. Concerning this, we study the performance of junior servers approaching the senior server in the retrial queueing-inventory model with the two finite waiting halls dedicated to the primary customers and the junior servers for consultation. We formulate a level-dependent QBD process and solve its steady-state probability vector using Neuts and Rao’s truncation method. The stability condition of the system is derived, and the R matrix is computed. Optimum total cost has been obtained, and sensitivity analyses, which include expected total cost, waiting time of customers in waiting hall and orbit, number of busy servers, and fraction of successful retrial rate of the model, are done numerically.

In the present paper, we introduced a quadratically convergent Newton’s like normal S2 iteration method free from the second derivative for the solution of nonlinear equations permitting 3 f'(x) = 0 at some points in the neighborhood of the root. Our proposed method works well 4 when the Newton method fails. Numerically it has been verified that the Newton’s like normal 5 S-iteration method converges faster than Fang et al. method [A cubically convergent Newton-type 6 method under weak conditions, J. Compute. and Appl. Math., 220 (2008), 409-412]. We studied 7 different aspects of normal S-iteration method. Lastly, fractal patterns support the numerical 8 results and explain the convergence, divergence, and stability of method.

The basic idea is to expand the completed zeta function $\xi(s)$ in MacLaurin series (infinite polynomial), which can be further expressed as infinite product (Hadamard product) by conjugate complex roots. Finally, the functional equation $\xi(s)=\xi(1-s)$ leads to $(s-\alpha_i)^2 = (1-s-\alpha_i)^2, i \in \mathbb{N}$ with solution $\alpha_i= \frac{1}{2}, i \in \mathbb{N}$, where $\alpha_i$ are the real parts of the zeros of $\xi(s)$, i.e., $s_i =\alpha_i\pm j\beta_i, i\in \mathbb{N}$. Therefore, a proof of the Riemann Hypothesis is achieved.

Lipid metabolism is clearly associated to Parkinson´s disease (PD). Although lipid homeostasis has been widely studied in multiple animal and cellular models as well as in blood derived from PD individuals, the cerebrospinal fluid (CSF) lipidomic profile in PD remains largely unexplored. In this study, we have characterized the CSF lipidomic imbalance between neurologically intact controls (n=10) and PD subjects (n=20). The combination of dual extraction with ultra-performance liquid chromatography-electrospray ionization quadrupole-time-of-flight mass spectrometry (UPLC-ESI-qToF-MS/MS) allowed to monitor 257 lipid species across all samples. Complementary multivariate and univariate data analysis pointed out that glycerolipids (mono-, di-, and triacylglycerides), saturated and mono/polyunsaturated fatty acids, primary fatty amides, glycerophospholipids (phosphatidylcholines, phosphatidylethanolamines), sphingolipids (ceramides, sphingomyelins), N-acylethanolamines and sterol lipids (cholesteryl esters, steroids) were significantly increased in the CSF of PD compared to control group. These results, despite the limitation of being obtained in a small population, demonstrate and extensive CSF lipid remodelling in PD, shedding new light on the deployment of CSF lipidomics as a promising tool to identify potential lipid markers as well as discriminatory lipid species between PD and other atypical parkinsonisms.

The search for novel brewing strains from non-brewing environments represents an emerging trend to increase genetic and phenotypic diversities in brewing yeast culture collections. Another valuable tool is hybridization, where beneficial traits of individual strains are combined in a single organism. This has been used successfully to create de novo hybrids from parental brewing strains by mimicking natural Saccharomyces cerevisiae ale x Saccharomyces eubayanus lager yeast hybrids. Here, we integrated both these approaches to create synthetic hybrids for lager fermentation using parental strains from niches other than beer. Using a phenotype-centered strategy, S. cerevisiae sourdough strains and the S. eubayanus x Saccharomyces uvarum strain NBRC1948 (also referred to as Saccharomyces bayanus) were chosen for their brewing aptitudes. We demonstrated that, in contrast to S. cerevisiae x S. uvarum crosses, hybridization yield was positively affected by time of exposure to starvation, but not by staggered mating. In laboratory-scale fermentation trials at 20°C, one triple S. cerevisiae x S. eubayanus x S. uvarum hybrid showed a heterotic phenotype compared with the parents. In 2L wort fermentation trials at 12°C, this hybrid inherited the ability to consume efficiently maltotriose from NBRC1948 and, like the sourdough S. cerevisiae parent, produced appreciable levels of the positive aroma compounds 3-methylbutyl acetate (banana/pear), ethyl acetate (general fruit aroma) and ethyl hexanoate (green apple, aniseed, and cherry aroma). Based on these evidences, the phenotype-centered approach appears promising for design of de novo lager beer hybrids and may help to diversify aroma profiles in lager beers.

The novel coronavirus (2019-nCoV) is a human and animal pathogen recently emerged in the city of Wuhan in Hubei province of China, causing a spectrum of severe respiratory illnesses. Corona viruses makes entry in to human cells through its spike (S) protein that binds to cell surface receptors. Wide spread of 2019-nCoV has been attributed to relatively high affinity of S protein to its receptor. Although S protein is a highly importantdrug target, unavailability of a high-resolution crystal structure and solvent accessible binding surface has made it a tedious target for current rapid virtual screening. A homology model of the receptor binding domain (RBD) of 2019 -n CoV S protein that is reasonably acceptable for drug screening was prepared using a high resolution crystal structure of SARS corona virus (SARS CoV)S protein. Data obtained from RBD- receptor docking experiments and published molecular dynamics experiments were used to map a RBD-receptor interaction hotspot that can be used for designing small molecule inhibitors. The hot spot was then used for virtual screening of more than 3000 drugs approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Two anthracycline class drugs (zorubicin and aclarubicin) and a food dye (E 155) were predicted to be potent inhibitors of RBD – receptor interaction. Results of present study provide evidence for the potential of these compounds asprophylactic medications or for use to reduce disease severity of COVID -19.

Longevity risk constitutes an important risk factor for life insurance companies and it can be managed through longevity-linked securities. The market of longevity-linked securities is at present far from being complete and does not allow to find a unique pricing measure. We propose a method to estimate the maximum market price of longevity risk depending on the risk margin implicit within the calculation of the technical provisions as defined by Solvency II. The maximum price of longevity risk is determined for a survivor forward (S-forward), an agreement between two counterparties to exchange at maturity a fixed survival-dependent payment for a payment depending on the realized survival of a given cohort of individuals. The maximum prices determined for the S-forwards can be used to price other longevity-linked securities, such as q-forwards. The Cairns-Blake-Dowd model is used to represent the evolution of mortality over time, that combined with the information on the risk margin, enables us to calculate upper limits for the risk-adjusted survival probabilities, the market price of longevity risk and the S-forward prices. Numerical results can be extended for the pricing of other longevity-linked securities.

S-licarbazepine was prepared by asymmetric reduction of oxcarbazepine with interface-assembled carbonyl reductase at the interface of oil/water biphasic system. The carbonyl reductase was conjugated with polystyrene in the surface of toluene/Tris-HCl biphasic system and formed a surfactant-like structure. The conversion and enantiometric excess of S-licarbazepine reached 97.39% and 99.6% when 3.97 mmol/L oxcarbazepine was reduced by interface-assembled carbonyl reductase with 60 g/L ethanol as co-substrate in toluene/Tris-HCl(12.5:10) biphasic system at 30 °C, 180 rpm for 6 h.

The port environments have some structures that still need regular control. However, the nature of these environments presents a number of challenges in determining an accurate vehicle position and consequently performing successful image similarity detection. These scenarios, however, can have poor visibility conditions and are highly dynamic, making place recognition difficult because the appearance of a place can change over time. Under these operational conditions, imaging sonars are a promising solution. There are some factors that affect the quality of the captured images, but the fact that they do not suffer from haze is a plus. Therefore, in this paper, a purely acoustic similarity detection method based on forward-looking sonar (FLS) data is proposed to overcome the inherent perceptual problems in a port scenario. Considering the lack of available data in this context and to facilitate the variation of environmental parameters and sensor configurations, a port scenario was simulated using the Stonefish simulator. Experiments were conducted on predefined trajectories near structures. The place recognition approach performs better compared to the results obtained with optical imagery. In general, it provides a good compromise in terms of distinctiveness and achieves a performance of 87.5% when appropriate constraints and assumptions are made.

Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants in topics surrounding politics, climate, the economy and other areas where an agreement is required. There are multiple approaches to investigating the scenarios in which polarization occurs and given that polarization is not a new phenomenon but that its virality may be supported by the low cost and latency messaging offered by online social media platforms; an investigation into the intrinsic dynamics of online opinion evolution is presented for complete networks. Extending a model which utilizes the Binary Voter Model (BVM) to examine the effect of the degree of freedom for selecting contacts based upon homophily, simulations show that different opinions are reinforced for a period of time when users have a greater range of choice for association. The facility of discussion threads and groups formed upon common views further delays the rate in which a consensus can form between all members of the network. This can temporarily incubate members from interacting with those who can present an alternative opinion where a voter model would then proceed to produce a homogeneous opinion based upon pairwise interactions.

We study here what can be learned from our experience with COVID-19 vaccination for an initially naïve population, that can inform planning for vaccination against the next novel, highly transmissible pathogen. We focus on the first two pandemic years (wild strain through Delta), because after the Omicron wave in early 2022, few people were still SARS-CoV-2-naïve. Almost all were vaccinated, infected, or often both. We review the evidence on COVID-19 vaccine effectiveness (VE), waning effectiveness over time, and what we should expect about VE and waning from a future pathogen. As a basis for our analysis, we conducted a PRISMA-compliant review of all studies on PubMed through August 15, 2022 reporting VE against four endpoints: any infection, symptomatic infection, hospitalization, and death, for the four principal vaccines used in developed Western countries (BNT162b2, mRNA1273, Ad26.CoV2.S, and ChAdOx1-S). The mRNA vaccines (BNT162b2, mRNA1273) had high initial VE against all endpoints but protection waned after approximately six months, with BNT162b2 declining faster than mRNA1273. Both mRNA vaccines initially outperformed the viral vector vaccines. A third “booster” dose, roughly six months after the primary doses, substantially reduced symptomatic infection, severe disease, and mortality, and in hindsight should be seen as part of the normal vaccination schedule.

Defining integrals over volume element in curved spacetime together with the mass and energy densities within that region of spacetime is apparently equivalent to the given energy and mass of that body or particle. With this in mind equations involving energies and mass can be rewritten in terms of their densities and the integral over the volume element. The idea find its place in the Hamiltonian formulations, and can be carried over into quantum mechanical frameworks systematically accounting for the effect of spacetime volume structures and gravity on dynamics of quantum systems. This article briefly explores this concept and runs through various frameworks and equations relevant to this idea, particularly the schrodinger-Newton equation and discusses the cosmological constant as a vacuum energy density.

Ecuador is an important center of biodiversity of the plant family Amaryllidaceae, specially the subfamily Amaryllidoideae, known as a source of important bioactive molecules. The aim of this study was to assess the chemical and biological potential of four different species of Amaryllidoideae collected in Ecuador: Urceolina formosa, Urceolina ruthiana, Clinanthus incarnatus, and Stenomesson aurantiacum. Sixteen alkaloids were identified in the bulb extract of these species by GC-MS, which the extract of S. aurantiacum exhibiting the greatest structural diversity. The potential of these three genera against Alzheimer’s disease was evaluated by measuring their AChE and BuChE inhibitory activity, revealing that C. incarnatus and U. formosa (from Sucumbíos province) showed the best results with IC50 values of 1.73 ± 0.25 and 30.56 ± 1.56 g·ml-1, respectively. Molecular dynamic assays were conducted to elucidate the possible interactions that occurs among 2-hydroxyanhydrolycorine and AChE enzyme, suggesting some similarity with those observed for galanthamine. This study enhances our understanding of the biodiversity of Amaryllidoideae species from Ecuador, highlighting their potential as a source of chemical compounds with pharmaceutical potential.

Alzheimer's Disease (AD) presents a significant challenge in the wake of its multifaceted nature, characterized by cognitive decline, memory impairment, and neuroinflammation. Despite extensive research, effective pharmacological interventions remain elusive, prompting exploration into non-pharmacological approaches. Microcurrent therapy (MC), utilizing imperceptible currents, has emerged as a potent clinical protocol. While previous studies have focused on its therapeutic effects, this study investigates its impact on neuronal damage and neuroinflammation in an AD mouse model, specifically addressing potential side effects. Utilizing 5xFAD transgenic mice, we examined the effects of MC therapy on neuronal integrity and inflammation. Our findings suggest that MC therapy attenuates memory impairment and reduces neurodegeneration, as evidenced by improved performance in memory tests and preservation of neuronal structure. Additionally, MC therapy significantly decreases amyloid-beta (Aβ) plaque deposition and inhibits apoptosis, indicating its potential to mitigate AD pathology. Our study discovered that MC therapy effectively reduces glial activation by inhibiting the TLR4-MyD88-NFκB pathway, consequently leading to decreased levels of inflammatory factors TNF-α, IL-1β, and IL-6, thus implicating TLR4 in neurodegenerative disease-related neuroinflammation. Furthermore, while our study did not observe significant adverse effects, further clinical trial into potential side effects and neuroinflammatory responses associated with MC therapy is warranted.

In Mexico viticulture represents the second source of employment in the agricultural area after the fruit and vegetable sector. In developed countries, remote sensing is widely used for vineyard monitoring, however, this tool is barely used in developing countries of Iberoamerica. In this re-search, our overall objective is to characterize two vineyards in the state of Queretaro (Mexico) using Sentinel-2 and meteorological data, specifically spectral and thermal indices. Results showed that spectral indices obtained from Sentinel-2 bands have characterized adequately the phenolog-ical evolution of the different varieties of the vineyards. The Modified Soil-Adjusted Vegetation Index (MSAVI) was adequately used to discriminate the first stages of vineyards, while the Nor-malized Difference Vegetation Index (NDVI) was useful to monitor vineyards during the rest stages of vineyards. Thermal indices have shown that the best grape varieties were those that can adapt to both cooler and warmer temperatures, have a reasonable ripening period, and can produce wines with balanced acidity and flavors. In conclusion, the combination of meteorological (including thermal indices) and remote sensing data (NDVI and MSAVI) provide information for choosing the suitable grape variety for this region.

Entropy as a mathematical concept is the first of its own kind, and second to none. Barely one or two papers in literature have investigated fractal dimensions of very basic entropies, such as Shannon, Tsallis, and Rényi entropic expressions. This was a thoughtful inspiration to delve into a step forward towards a unified information- theoretic fractal theory. The storytelling of this current paper starts by introducing my third entropy formula, namely Ismail’s entropy, , as a novel generalization to Shannonian entropy with a visionary link to both long- and short-range interactions, (LRIs), (SRIs) respectively. Clearly, this would generate a fourfold unification with statistical mechanics as well as contemporary physics. Hence, this adds more credibility and weight for this study. The fractal dimension of , is identified in this paper. As an essential part of this work, it was influential to spotlight the importance of fractal geometry to space industry as well as education, which is crucial to develop our societies. Thus, some potential fractal applications to CubeSat Technologies and Education are highlighted. So, will the deep search for more ground-breaking research has come to an end. Certainly, not. This was another inspiration to propose new open problems to widen research gates to the scientific community for more research pathways. Consequently, the paper ends with closing remarks combined with some challenging open problems and the next phase of research.

Vectorial Boolean functions and codes are closely related, and each corresponding domain gives been to each other. On the one hand, various requirements of binary linear codes are needed for their theatrical interests but, more importantly, for their practical applicants (such as few-weight codes or minimal codes for secret sharing, locally recoverable codes for storage, etc.). On the other hand, various criteria and tables have been introduced to analyse the security of S-boxes that are related to vectorial Boolean functions, such as the Differential Distribution Table (DDT), the Boomerang Connectivity Table (BCT), and the Differential-Linear Connectivity Table (DLCT). In previous years, two new tables have been proposed for which the literature was pretty abundant: the $c$-DDT to extend the DDT and the $c$-BCT to extend the BCT. In the same vein, we propose extended concepts to study further the security of vectorial Boolean functions, especially the $c$-Walsh transform, the $c$-autocorrelation, and the $c$-differential-linear uniformity, and its accompanying table, the $c$-Differential-Linear Connectivity Table ($c$-DLCT). We study these properties of the novel functions at their optimal level concerning these concepts and describe the $c$-DLCT of the crucial inverse vectorial (Boolean) function case. Finally, the derived functions could lead to new families of binary minimal codes, as the recent achievements on minimal codes from low differential uniformity. We draw new avenues for future research toward linear code designs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents a serious threat to public health. The spike (S) glycoprotein of SARS-CoV-2 mediates viral entry into host cells and is heavily glycosylated. In this study, we systemically analyzed the roles of 22 putative N-linked glycans in SARS-CoV-2 S protein expression, membrane fusion, viral entry, and stability. Using α-glycosidase inhibitors, castanospermine and NB-DNJ, we confirmed that disrupting the N-linked glycosylation process blocked the maturation of the S protein, leading to impairment of S protein-mediated membrane fusion. Single substitution of each of the 22 N-linked glycosylation sites with glutamine revealed that 9 out of the 22 N-linked glycosylation sites were critical for S protein folding and maturation, resulting in reduced S protein-mediated cell-cell fusion and viral entry. Of note, N1074Q mutation markedly affected S protein stability and induced significant receptor-independent syncytium (RIS) formation in HEK293T/hACE2-KO cells, and removal of the furin-cleavage site partially compensated instability of N1074Q mutation. Although the corresponding mutation in the SARS-CoV S protein (N1056Q) did not induce RIS in HEK293T cells, the mutants N669Q and N1080Q exhibited increased fusogenic activity and induced syncytia formation in HEK293T cells. Therefore, N-glycans on the SARS-CoV and SARS-CoV-2 S2 subunits are of great importance in maintaining the prefusion state of the S protein. The study revealed the critical roles of N-glycans in S protein maturation and stability, which have implications for the design of vaccines and anti-viral strategies.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of corona-virus disease 19 (COVID-19) and employs angiotensin-converting enzyme 2 (ACE2) as the recep-tor. Although the expression of ACE2 is crucial for cellular entry, we found that the interaction of ACE2 with the Spike (S) protein in the same cells led to its downregulation through degradation in the lysosomal compartment via the endocytic pathway. Interestingly, the ability of the S protein from previous variants of concern (VOCs) to downregulate ACE2 was variant-dependent and correlated with disease severity. The S protein from the Omicron variant, associated with milder disease, exhibited a lower capacity to downregulate ACE2 than that of the Delta variant, which is linked to a higher risk of hospitalization. Chimeric studies between the S proteins from the Delta and Omicron variants revealed that both the receptor-binding domain (RBD) and S2 subunit played crucial roles in the reduced ACE2 downregulation activity observed in the Omicron var-iant. In contrast, three mutations (L452R/P681R/D950N) located in the RBD, S1/S2 cleavage site, and HR1 domain were identified as essential for the higher ACE2 downregulation activity ob-served in the Delta variant than that in the other VOCs. Our results suggested that dysregulation of the renin-angiotensin system due to the ACE2 downregulation activity of the S protein of SARS-CoV-2 may play a key role in the pathogenesis of COVID-19.

Coagulase-Negative Staphylococci (CoNS) are commensal on human body surfaces and for years, they were not considered a cause of bloodstream infection and were often regardered as contamination. However, the association of CoNS with nosocomial infection is increasingly recognized. The insertion of cannulas and intravascular catheters represents the first source of CoNS entry into the bloodstream, causing bacteremia and sepsis. They owe their pathogenic power to their ability to produce biofilms on surfaces, such as medical devices. In this study, we evaluate the adhesive capacity of CoNS isolated from blood cultures by comparing spectrophotometric phenotypic assay with genotypic analysis based on the evidence of the ica operon. We retrospectively reviewed the database of CoNS isolated from blood cultures, that were considered to be responsible for 361 bloodstream infections. Among them, we selected 89 ones who had full records. Our data show that S. epidermidis was the predominant species isolated, and with greater adhesive capacities, especially those with the complete operon. Knowing the adhesive capabilities of a microorganism responsible for sepsis can be useful in implementing appropriate corrective and preventive measures, as conventional antibiotic therapy cannot effectively eradicate biofilms.

Staphylococcus aureus are commensal bacteria present on skin and mucosae in both humans and animals, but they can also be found in food, water and in various environments. They are also considered a major pathogen having a great morbidity leading to a wide range of infections. They are included in the list of most virulent and antimicrobic resistant bacterial pathogens (ESKAPE, Escherichia coli, Staphylococcus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterococcus faecalis and faecium)) by the Center for Disease Control and Prevention (CDC), and S. aureus is part of the worldwide threat represented by the presence of antimicrobial resistance (AMR). The outcomes of an epidemiological investigation on 26,430 S. aureus isolates from a global public database (NPDIB; NCBI Pathogen Detection Isolate Browser) support the evidence of significant differences in the distribution of isolates and ARGs (Antimicrobial Resistance Genes) clusters among geographical areas of origin and among sources of the isolates. Moreover, the ARGs cluster patterns suggest an association between the isolates from human and animal populations. This outcome and the large diffusion of the pathogens among human and animal populations support the importance of gaining information on the epidemiology of these infections with a One Health approach.

Recently, we demonstrated the validity of anomalous numbers law, known as Newcomb-Benford´s law, at the mammalian neuromuscular transmission, considering different extracellular calcium concentrations . The present work continues to examine how alterations in extracellular solution modulate the first digit law in the context of the spontaneous release of acetylcholine from the neuromuscular junction. We investigated if the intervals of miniature potentials collected at the neuromuscular junction obey the law in a hyperkalemic environment. The analysis showed that the interval between the miniature potentials at high potassium concentrations follows Newcomb-Benford´s law. Also, our data allowed us to uncover a conformity fluctuation as a function of the number of intervals of the miniature potentials. Finally, we discuss the biophysical implications of the present findings.

Polymyositis is a rare condition with an unknown etiology occurring more frequently in adult women. There is a lack of evidence on the coexistence of PM and CMV infection in a patient with Hashimoto Thyroiditis hypothyroidism. However, the increasing incidence of CMV infection and autoimmune diseases overlapping points out a relationship, while the association direction remains unclear. Case outline: A 32-year-old woman recently treated for HT hypothyroidism was admitted to the hospital two weeks after being treated for common flu by the family doctor, complaining about a worsening condition with muscle pain, weakness, frequent falls, and fatigue. The first tests showed a normalized thyroid function, with elevated values of troponin and serum creatinine kinase (KC). The immunological tests revealed the presence of a high titer of CMV IgG antibodies and raised levels of CMV DNA. Pelvis MRI images demonstrated markedly elevated signals on the STIR sequences in the pelvis, thighs, and calves, indicating active and severe multifocal myositis. The diagnosis of PM was confirmed with the muscle biopsy on day 7 of hospitalization. The patient showed significant improvements within two weeks after the medical therapy and physiotherapy.

The humoral response of the COVID-19 vaccine varies from person to person. It largely depends on prior SARS-CoV-2 infection, obtaining an adequate immune response, and leaving a trace of changing antibody concentration over time. We retrospectively analyzed five clinical cases from selected patients and employees of the oncology hospital. All mild COVID-19 convalescents received the BNT162b2-Comirnaty mRNA vaccine three or four times. The levels of SARS-CoV-2 IgM- and IgG-specific antibodies, as well as S-RBD antibodies, were analyzed for two years. The concentration of antibodies was assessed in the laboratory using the chemiluminescent immunoassay CLIA, MAGLUMI. Results: (1) Active autoimmune disease stabilized the level of IgG-specific antibodies after systemic mRNA vaccination for at least six months. (2) Post-vaccination IgG and S-RBD levels decreased when vaccination was performed within three months of onset. (3) The booster dose administered only increased the S-RBD antibody levels. Declining IgG-specific antibodies were observed. (4) The S-RBD IgG levels were not correlated with the SARS-CoV-2 IgG levels in the vaccinated convalescents. (5) Subsequent reinfection with SARS-CoV-2 after vaccination three times released a more significant specific antibody response. Based on the collected data, we suggest that monitoring S-RBD antibodies is sensitive but not equivalent to a specific humoral response for SARS-CoV-2 IgG. We suggested that administering at least three doses of the mRNA vaccine should serve as the basis for immunization. The three-month interval may be the best alternative to an immunization schedule for non-immunocompromised people.

The relationship between Parkinson's disease (PD), the second most common neurodegenerative disease after Alzheimer's disease, and palmitoylation, a post-translational lipid modification, is not well understood. In this study, we have analyzed the differential palmitome present in the cerebral cortex of PD patients compared to controls (n=4 per group) to better understand the role of protein palmitoylation in PD and the pathways altered in this disease. Data-mining of the cortical palmitome from PD patients and controls has allowed to: i) detect a set of 150 proteins with altered palmitoylation in PD subjects in comparison with controls, ii) describe the biological pathways and targets predicted to be altered by these palmitoylation changes, and iii) depict the overlap between the differential palmitome identified in our study with protein interactomes of the PD-linked proteins α-synuclein, LRRK2, DJ-1, PINK1, GBA and UCHL1. In summary, we have partially characterized the altered palmitome in the cortex of PD patients which is predicted to impact cytoskeleton, mitochondrial and fibrinogen functions, as well as cell survival. Our study points out that protein palmitoylation could have a role in the pathophysiology of PD, and that comprehensive palmitoyl-proteomics offers a powerful approach for elucidating novel cellular pathways modulated in this neurodegenerative disease.

From the hospital wastewater, a novel bacteriophage was isolated and characterized. According to characterization properties, this bacteriophage belongs to the Siphoviridae family, the maximum bacteriophage titer was recorded at 37°C and a pH of 7.2, had a 44,789 bp linear double-strand DNA genome, and within the genome sequence, there are 61 genes, all of which are encoded into proteins. Although this bacteriophage does not have any virulence factors or antimicrobial resistance genes and had specific lytic activity against some antimicrobial resistance S. aureus clinical isolates.

Abstract The present work was designed to investigate antiviral potential of novel mono and oligomeric Chitosan derivatives through in-silico approaches to find potent broad-spectrum anti-viral and promising drug candidates against SARS-CoV-2 and augmentation of their mode of action. Chitosan biopolymer and its derivatives were screened virtually against spike glycoprotein and human ACE2 receptor of nCoV-19. HTCC a polymeric Chitosan has been reported to interact with the corona viral Spike (S) protein and blocks its interaction with ACE2 receptor. Better biocompatibility, structural correlations, variation in degree of decetylation and molecular weight of modified Chitosan derivatives are the key attributes for enhancement of anti-viral activity. The Chitosan derivatives constructively interact with viral S protein. N-Carboxy methyl Chitosan (NCMC) among the Chitosan derivatives displayed efficient binding affinity. NCMC, when compared to mHTCC, a monomeric Chitosan for its interaction with the S protein, RBD site and ACE2 receptor, displayed efficient binding affinity with binding energy of -7.9, -6.3 and -7.4; -6.2, -4.8 and -5.5 Kcal/mol respectively. The interaction of S protein with ACE2 and ligand mHTCC-S protein complex and NCMC-S protein complex with ACE2 was calculated through flexible docking resulted in efficient reduction of binding energy from -901.2kJ/mol to -765.06kJ/mol and-814.72kJ/mol respectively, elucidated that the binding affinity of the viral S protein for its receptor ACE2 decreases in the presence of NCMC/mHTCC. The computational study envisages the antiviral efficiency of NCMC, mHTCC and biocompatible Chitosan derivatives for the first time,as preventive intervention against Covid-19.

Critical care of neonates involves substantial usage of antibiotics and exposure to multidrug resistant (MDR) nosocomial pathogens. These pathogens are often exposed to sub-MIC doses of antibiotics which might result in a range of physiological effects. Therefore, to understand the outcome of sub-inhibitory dosage of antibiotics on Staphylococcus populations, nasal swab specimens were collected from 34 neonates admitted to the Sick Newborn Care Unit between 2017-2018, a total of 41 non-repetitive isolates were included in this study. Staphylococcus haemolyticus was the prevalent species (58.54%) with high non-susceptibility to cefotaxime (CTX) (79.16%), gentamicin (87.50%), and meropenem (54.17%). Biofilm forming abilities of S. haemolyticus isolates in the presence of sub-optimal CTX (30μg/mL), the predominantly prescribed β-lactam antibiotic, were then determined by crystal violet assays and extracellular DNA (eDNA) quantitation. CTX was found to significantly enhance biofilm production among the non-susceptible isolates (p-valueWilcoxin test- 0.000008) with increase in eDNA levels (p-valueWilcoxin test- 0.000004). Additionally, no changes in non-susceptibility were observed among populations of two MDR isolates, JNM56C1 and JNM60C2 after >500 generations of growth in the absence of antibiotic selection in vitro. These findings demonstrate that sub-MIC concentration of CTX induces biofilm formation and short-term non-exposure to antibiotics does not alter non-susceptibility among S. haemolyticus isolates.

This single-blind and cross-sectional study evaluated the role of Rho-kinase (ROCK) as a biomarker of the cardiovascular remodelling process assessed by echocardiography in competitive long-distance runners (LDR) during the training period before a marathon race. Thirty-six healthy male LDR (37.0±5.3 years; 174.0±7.0 height; BMI: 23.8±2.8; VO2-peak: 56.5±7.3 mL·kg-1·min-1) were separated into two groups according to previous training level: high-training (HT, n=16) ≥100 km·week-1 and low-training (LT, n=20) ≥70 and &lt;100 km·week-1. Also, twenty-one healthy nonactive subjects were included as a control group (CTR). A transthoracic echocardiography was performed and ROCK activity levels in circulating leukocytes were measured at rest (48-hr without exercising) the week before the race. HT group showed higher left ventricular mass index (LVMi) and left atrial volume index (LAVi) than other groups (p&lt;0.05, for both), also higher levels of ROCK activity were found in LDR (HT=6.17±1.41 vs CTR=1.64±0.66 (p&lt;0.01); vs LT=2.74±0.84; (p&lt;0.05)). In LDR a direct correlation between ROCK activity levels and LVMi (r=0.83; p&lt;0.001), and LAVi (r=0.70; p&lt;0.001) were found. In conclusion, in male competitive long-distance runners, the load of exercise implicated in marathon training is associated with ROCK activity levels and the left cardiac remodelling process assessed by echocardiography.

The most common form of mixed dementia (MixD) is constituted by abnormal protein deposits associated with Alzheimer´s disease (AD) that coexist with vascular disease. Although olfactory dysfunction is considered a clinical sign of AD-related de-mentias, little is known about the impact of this sensorial impairment in MixD at molecular level. To address this gap in knowledge, we have assessed olfactory bulb (OB) proteome-wide expression in MixD subjects (n=6) respect to neurologically intact controls (n=7). Around 9% of the quantified proteins were differentially expressed, pinpointing aberrant proteostasis involved in synaptic transmission, nucleoside monophosphate and carbohydrate metabolisms and neuron projection regeneration. In addition, net-work-driven proteomics revealed a modulation in cell-survival related pathways such as ERK, AKT and PDK1-PKC axis. Part of the differential OB protein set was not specific of MixD, being also deregulated across different tauopathies, synucleinopathies and tardopathies. However, the comparative functional analysis of OB proteome data between MixD and pure AD pathologies deciphered commonalities and differences between both related phenotypes. Finally, olfactory proteomics allowed to propose serum Prolow-density lipoprotein receptor-related protein 1 (LRP1) as a candidate marker to differentiate AD from MixD phe-notypes.

Since December 2019, the worldwide spread of COVID-19 has brought the majority of the world to a standstill, affecting daily lives as well as economy. Under these conditions, it is imperative to develop a cure as soon as possible. On account of some of the adverse side effects of the existing conventional drugs, researchers all around the world are screening natural antiviral phytochemicals as potential therapeutic agents against COVID-19. This paper aims to review interactions of some specific phytochemicals with the receptor binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2 and suggest their possible therapeutic applications. Literature search was done based on the wide array of in-silico studies conducted using broad spectrum phytochemicals against SARS-CoV-2 and other viruses. We shortlisted 26 such phytochemicals specifically targeting the S protein and its interactions with host receptors. To validate the previously published results, we also conducted molecular docking using the AutoDockVina application and identified 6 high potential phytochemicals for therapeutic use based on their binding energies. Besides this, availability of these compounds, their mode of action, toxicity data and cost-effectiveness were also taken into consideration. Our review specifically identifies 6 phytochemicals that can be used as potential treatments for COVID-19 based on their availability, toxicology results and low costs of production. However, all these compounds need to be further validated by wet lab experiments and should be approved for clinical use only after appropriate trials.

Glyceraldehyde 3–phosphate dehydrogenase (GAPDH) is a key glycolytic enzyme, which is crucial for the breakdown of glucose to provide cellular energy. Over the past decade, GAPDH has been reported to be one of the most prominent cellular targets of post-translational modifications (PTMs), which divert GAPDH towards different non-glycolytic functions. Hence, it is termed a moonlighting protein. During metabolic and oxidative stress, GAPDH is a target of different oxidative PTMs (oxPTM), e.g. sulfenylation, S-thiolation, nitrosylation and sulfhydration. These modifications alter the enzyme’s conformation, subcellular localization and regulatory interactions with downstream partners, which impact its glycolytic and non-glycolytic functions. In this review, we discuss the redox regulation of GAPDH by different redox writers, which introduce the oxPTM code on GAPDH to instruct a redox response; the GAPDH readers, which decipher the oxPTM code through regulatory interactions and coordinate cellular response via the formation of multi-enzyme signaling complexes; and the redox erasers, which are the reducing systems that regenerate the GAPDH catalytic activity. Human pathologies associated with the oxidation-induced dysregulation of GAPDH are also discussed, featuring the importance of the redox regulation of GAPDH in neurodegeneration and metabolic disorders.

Spike (S) protein of Coronaviruses help in receptor attachment and virus entry into the host cells. While S protein is required for virus entry, it is also important as an immunogen as it is the most accessible part of the virus architecture. S protein form knob like structures (viral spikes) protruding outwards in the form of homotrimers containing an S1 and S2 as monomers. Mutations in structural proteins of virus play crucial role in determining virulence and also in many instances influencing emergence of antibody escape variants and cellular tropism. In this paper we have performed in depth analyses of spike protein sequences from various parts of the world and tried to correlate the data with possible functional relevance of such mutations.

Much of the debate on Plan S seems to concentrate on how to make toll access journals open access, taking for granted that existing open access journals are Plan S compliant. We suspected this was not so, and set out to explore this using DOAJ's journal metadata. We conclude that an overwhelmingly large majority of open access journals are not Plan S compliant, and that it is small HSS publishers not charging APCs that are least compliant and will face major challenges with becoming compliant. Plan S need to give special considerations to smaller publishers and/or non-APC-based journals.

Adlay seed samples were collected from 3 adlay growing regions (Yeoncheon, Jeonnam and Eumseong regions) in Korea during 2012. Among all the samples collected, 400 seeds were tested for fungal occurrence by standard blotter and test tube agar methods and different taxonomic groups of fungal genera were detected. The most predominant fungal genera encountered were Fusarium, Phoma, Alternaria, Cladosporium, Curvularia, Cochliobolus and Leptosphaerulina. The occurrence of Fusarium species were 45.6% and based on the combined sequences of two protein coding genes, EF-1a, Beta-tubulin and phylogenetic analysis, 10 species were characterized as F. incarnatum (11.67%), F. kyushense (10.33%), F. fujikuroi (8.67%), F. concentricum (6.00%), F. asiaticum (5.67%), F. graminearum (1.67%), F. miscanthi (0.67%), F. polyphialidiom (0.33%), F. armeniacum (0.33%) and F. thapsinum (0.33%). The ability of these isolates to produce mycotoxins fumonisin (FUM) and zeralenone (ZEN) were tested by ELISA quantitative analysis method. The result revealed that fumonisin (FUM) was produced only by F. fujikuroi and zeralenone (ZEN) by F. asiaticum & F. graminearum. Mycotoxigenic species were then examined for their morphological characteristics to confirm their identity. Morphological observations of the species correlated well with their molecular identification and confirmed as F. asiaticum, F. fujikuroi and F. graminearum.

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPP) in Gyeongsangbuk-do and to develop effective cost and risk management strategies. The study collected data by conducting an online survey of 244 stakeholders. Binary logistic regression was used to analyze the impact of various variables on cost deviation, in-cluding project management risk (PMR), project costing and execution risk (PCER), project exe-cution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMC), and construction project subcontractor and safety man-agement (CPSSM). The results showed that PMR (OR=3.744, 95% C.I. [1.657, 8.457]), PCER (OR=5.068, 95% C.I. [2.236, 11.484]), PESR (OR=3.447, 95% C.I. [1. 853, 6.413]), CPR (OR=2.292, 95% C.I. [1.020, 5.151]), PCSR (OR=4.817, 95% C.I. [2.250, 10.317]), PMC (OR=2.954, 95% C.I. [1.452, 6. 013]), and CPSSM (OR=2.419, 95% C.I. [1.297, 4.515]) had statistically significant effects on cost deviation. In particular, PMR, PCER, and PESR were identified as the main causes, and the effects of additional factors such as CPSSM were also important. The developed predictive model plays an important role in helping stakeholders of NDPP to manage risks in advance and take appro-priate preventive measures to ensure the success of the project. This study empirically supports the theoretical hypotheses of previous studies and provides a clear understanding of the causes of cost deviation in NDPP, which provides important insights for strategic decision-making and provides a new perspective on risk management.

Hyperspectral image and LiDAR image fusion plays a crucial role in remote sensing by capturing spatial relationships and modeling semantic information for accurate classification and recognition. However, existing methods, like Graph Convolutional Networks (GCNs), face challenges in constructing effective graph structures due to variations in local semantic information and limited receptiveness to large-scale contextual structures. To overcome these limitations, we proposed a invariant attribute-driven binary bi-branch classification (IABC) method which is a unified network that combines binary Convolutional Neural Network (CNN) and GCN with invariant attributes. Our approach utilizes a joint detection framework that can simultaneously learn features from small-scale regular regions and large-scale irregular regions, resulting in an enhanced structured representation of HSI and LiDAR images in the spectral-spatial domain. This approach not only improves the accuracy of classification and recognition but also reduces storage requirements and enables real-time decision-making, which is crucial for effectively processing large-scale remote sensing data. Extensive experiments demonstrates the superior performance of our proposed method in hyperspectral image analysis tasks. The combination of CNNs and GCNs allows for accurate modeling of spatial relationships and effective construction of graph structures. Furthermore, the integration of binary quantization enhances computational efficiency, enabling real-time processing of large-scale data. Therefore, our approach presents a promising opportunity for advancing remote sensing applications using deep learning techniques.

In the article, we are trying to find a general law that describes the physical properties of a complex compound through the same physical properties of compound elements. For metal alloys operated under extreme conditions - neutron and proton irradiations and thermal heating, the mechanical properties of these alloys and their elements have been studied. It turned out that the ultimate tensile strength of tantalum alloys used in the design of space reactors can be expressed in terms of the weighted sum of the ultimate tensile strengths of its elements in the range of neutron doses: (0 - 0.96) displacement per atom (dpa) for Ta–10W alloy and (1.4 - 1.7) dpa for T–111 alloy with a neutron energy of more than 0.1 MeV. For tungsten binary alloys used in the design of fusion reactors, the Vickers hardness can also be expressed in terms of the weighted sum of the Vickers hardnesses of the alloy elements in the range of proton irradiation doses: (0 - 0.05) dpa for W-1%Re alloy, (0.05 - 0.2) dpa for W-3%Re alloy and (0.05 - 1) dpa for W-1%Ta with a proton energy of 1 MeV.

In any region of a space, the gravitational field cannot be eliminated. The speed of light in a vacuum has never been observed and cannot be observed with current technology. Till now, only the speed of light in a gravitational field has been observed. It results in that all the observed speed of light are always being varied by the gravity. Here, it is presented that light could be dispersion in a gravitational field analogous to the dispersion of light in the Newtonian prism experiment. The relativistic mass density on the surface of a neutron star is on the level of 10¹⁷kg/m³ while on the surface of the Earth is only 10^-7kg/m³, the effect of the gravitational field acting on the speed of light by a neutron star is much larger than that by the Earth. Therefore, the dispersion of light in strong gravitational field could be generally observed from the image of a star and it should have been observed through the double-image gravitational lensing and the spectroscopic binary system. And, it should affect the observed numbers, spectrogram, size and distance of the celestial objects.

Starting from a very simple economic scenario, we build on it a game and then we introduce a general strategy able to reduce a regression problem to an equivalent binary classification problem. This reduction scheme (that we call adaptive reduction or also dynamic reduction) can be also used to derive a new boosting algorithm for regression problems named bOOst^d. The bOOst^d algorithm is very simple to implement, and it can use any learning algorithm with no priori assumptions. We present a conjecture for bOOst^d performances, which ensures a little error on training set. More important we can also provide a very good theoretical upper bound for the generalization error. We give a set of preliminary experimental results that seems to confirm our conjecture for bOOst^d performances on training set and the theoretical assumptions for the generalization error. We also provide a possible justification of why boosting often does not overfit. Finally, we leave some open problems and argue that in the future an adaptive single boosting (with an unique code) algorithm for binary, multi class and regression problems can be derived.

Parkinson’s disease (PD) is the second most common degenerative disease which may cause blood pressure abnormalities due to autonomic dysfunction. Early morning rise of blood pressure which is called morning surge is found to be related with some cardiovascular diseases when it is exaggerated. We wanted to search the relation of Morning blood pressure surge (MBPS) and inflammation in PD. Method: Ambulatory blood pressure monitoring for 24 hours, fibrinogen to albumin ratio, hs-CRP are used in this retrospective study. Fifty idiopathic PD patients and 50 age and sex matched control cases were included. MBPS, it has been defined as the difference between morning BP (measured 2 hours after awakening) and the lowest night-time BP. Body mass index (BMI) is used as an independent variable. Results: Median value of MBPS for PD group (21,63) was significantly different from the control group values (18,63) (p

Alzheimer´s disease (AD) is characterized by the brain deposition of senile plaques composed by amyloid-β peptides (Aβ) that increase inflammation. An endogenous peptide derived from the insulin-like growth factor (IGF)-I, glycine-proline-glutamate (GPE) has IGF-I-sensitizing and neuroprotective actions. Here, we examined the effects of GPE on Aβ levels and hippocampal inflammation generated by the intracerebroventricular infusion of Aβ25-35 during 2 weeks (300 pmol/day) in ovariectomized rats and the signaling-related pathways and levels of Aβ-degrading enzymes associated with these GPE-related effects. GPE prevented the Aβ-induced increase in the phosphorylation of p38 mitogen-activated protein kinase and the reduction in activation of signal transducer and activator of transcription 3, insulin receptor substrate-1 and Akt, as well as on interleukin (IL)-2 and IL-13 levels in the hippocampus. The functionality of somatostatin, measured as the percentage of inhibition of adenylate cyclase activity and the levels of insulin-degrading enzyme were also preserved by GPE co-treatment. These findings indicate that GPE co-administration may protect from Aβ insult by changing hippocampal cytokine content and somatostatin functionality through regulation of leptin- and IGF-I-signaling pathways that could influence the reduction in Aβ levels through modulation of levels and/or activity of Aβ proteases.

With the increasing occurrence of rotator cuff injuries every year, there is a great need for a reliable treatment option. Wharton’s Jelly contains several components that can positively impact the replacement and repair of musculoskeletal defects. The overall objective of this study is to evaluate the improvement of patient-reported pain scales after applying Wharton’s Jelly (WJ) in rotator cuff defects. Eighty-seven patients with rotator cuff defects who failed at least eight weeks of conservative treatment were selected from the retrospective repository. 2cc of WJ flowable allograft was applied to the specific affected anatomy, the most common being supraspinatus tendon, biceps tendon insertion, labral tear, and subscapularis tear. No adverse reactions were reported. Statistically significant improvements were found from the initial to Day 90 in all scales. Patient satisfaction was calculated using minimal clinically important differences. No statistically significant differences were found in mean changes between gender, BMI, and age. Scanning Electron Microscopy images reveal the similarities between the collagen matrix in WJ and the rotator cuff. The significant improvement in patient outcomes coincides with current literature analyzing WJ applications with other structural defects around the body. WJ is a promising alternative for musculoskeletal defects when the standard of care fails.

Cow’s Milk (CM) is a healthy food consumed worldwide by individuals of all ages. Unfortunately, 'lactase deficient' individuals cannot digest milk's carbohydrate lactose depriving themselves of highly beneficial milk proteins like casein, lactoalbumin and lactoglobulin, due to lactose intolerance (LI), while other individuals develop cow milk allergy specifically against these proteins (CMPA). The management of these conditions is distinctly different and an inappropriate diagnosis or treatment may have significant implications for the patients, especially if they are infants or very young children, resulting in unnecessary dietary restriction or avoidable adverse reactions. Omics technologies play a pivotal role in elucidating the intricate interactions between nutrients and the human body, spanning from genetic factors to the microbiota profile and metabolites. This comprehensive approach enables the precise delineation and identification of distinct cohorts of individuals with specific dietary requirements, so that tailored nutrition strategies can be developed. This is what is called personalized nutrition or precision nutrition (PN), the area of nutrition that focuses on the effects of the nutrients over the genome, proteome and metabolome, promoting well-being and health, preventing diseases, reducing chronic disease incidence, and so increasing life expectancy. Here, we report the scientific community opinion proposing to replace the approach “one size fits all” with tailor-made nutrition programs, designed by integrating nutrigenomic data together with clinical parameters and microbiota profiles, taking into account the individual lactose tolerance threshold and needs in terms of specific nutrients intake. This customized approach could help LI patients to improve their quality of life, overcoming depression or anxiety, often resulting from the individual perception of this condition as different from a normal state.

This research proposes an algorithm to sign messages using the ElGamal asymmetric cryptosystem, called: Digital signature algorithm based on ElGamal, Diffie-Hellman protocol and the number π (DSAπ). This proposal has a high level of security like the DSA standard, in addition, execution times are reduced in relation to it. The Diffie-Hellman protocol and the number π were used in the construction of the digital signature algorithm in conjunction with the Hash-Sha-512 function. Some experiments are presented to provide evidence that the bits on the right side of the decimal point of π appear randomly, such as: a color image was constructed of a string of consecutive bits chosen at random, of the number π. Subsequently, parameters such as: entropy, correlation, discrete Fourier transform, goodness-of-fit test χ2 were evaluated. It is mentioned that an S-box 8×8 is involved in the signature. The sensitivity of the signature was measured, that is, when small changes are made to the sender’s private key, or small changes to the message. Finally, an image was constructed using the signatures of random texts, and subsequently the randomness of its pixels was obtained, to verify that there is no relationship between the different signatures.

Intrusion detection is generally carried out by matching network traffic patterns with known attack patterns or by identifying abnormal network traffic patterns. One statistical methodological approach used in intrusion detection is Statistical Process Control (SPC) by constructing a control chart. Hotelling’s T2 control chart is a multivariate control chart commonly used to monitor the mean process. The performance of the T2 chart in monitoring mean shifts can be increased if a robust estimator is utilized. Based on previous research, T2 based on the Fast-MCD estimator has good performance in monitoring low to medium outlier contaminated data. Therefore, the MRCD estimator can be used to detect intrusion. On the other hand, this research focuses on developing a bootstrap-based robust Hotelling’s T2 charts with Fast-MCD and MRCD estimators for evaluating performance in detecting intrusion on intrusion detection datasets. Based application of UNSW-NB15, the proposed chart has better performance than the conventional T2 and Fast-MCD-based T2 despite the longer execution time.

The Sidi Bou Othmane (SBO) pegmatite district is in the Central Jebilet massif, Occidental Meseta domain, Morocco. The SBO district is hosted essentially in a volcano-sedimentary series composed of the Late-Devonian Sarhlef shales. Pegmatite bodies crop out as dykes, which are oriented from N-S to E-W and are generally variably deformed with ductile and/or brittle structures with ante, syn- or post kinematic criteria. Petrographic observations of pegmatite dykes show that feldspars (i.e., albite, microcline) are the most abundant mineral phases, followed by quartz, micas, with tourmaline and accessory mineral as garnet, and zircon and secondary minerals as clinochlore, sericite, and illite. The geochemical study indicates that, according to the major pegmatite elements dykes of SBO have mainly a S-type granitic composition and are peraluminous granite with calc-alkalic affinity. The study of trace elements pointed out that SBO pegmatite formed under post-orogenic syn-collision context during the Variscan orogeny, by the partial melting of argilliferous sediment and can be ascribed to the muscovite-bearing pegmatite; moreover, they have a good potential on ceramic and contain minerals, such as feldspar, recently assessed as Critical raw materials by European Union.

The work is devoted to the development of methods for constructing asymptotic formulas as x→∞ of a fundamental system of solutions of linear differential equations generated by a symmetric two-term differential expression of odd order. The coefficients of the differential expression belong to classes of functions that allow oscillation (for example, those that do not satisfy the classical Titchmarsh-Levitan regularity conditions). As a model equation, the 5th order equation i2p(x)y′′′′′+p(x)y′′′′′+q(x)y=λy, for which various cases of behavior of the coefficients p(x),q(x), is investigated. New asymptotic formulas are obtained for the case when the function h(x)=−1+p−1/2(x)∉L1[1,∞) significantly influences the asymptotics of solutions to the equation. The case when the equation contains a nontrivial bifurcation parameter is studied.

It is important to develop new antibacterial drugs since the emergence of bacterial resistance to available antibiotics. Metal nanoparticles have the potential to combat antibiotic resistance and are effective antibacterial agents. Here, we demonstrate the biogenic production of zinc nanoparticles using Rhododendron arboreum stem bark. The biosynthesized ZnNPs were characterized through different analytical techniques such as UV-vis, FTIR, EDX, SEM, and XRD. Clinical isolates such as E. coli, S. aureus, and K. pneumonia were used to check the antibacterial efficacy of the biosynthesized zinc nanoparticles. The MIC and MBC values against K. pneumonia, S. aureu, and E. coli were found to be 34±0.21 and 11.71±0.47, 47±0.11 and 23.86±0.84 and 94±0.18 and 40.43±0.16 µg/mL, respectively. It dramatically decreased the integrity of the cell membrane and markedly increased the permeability of both inner and outer membranes. The green synthesized ZnNPs have good catalytic activity. It degraded 65% of methyl orange dye within 6h when the mixture was kept in direct sunlight, thus demonstrating good photodegradation potential and can be employed as a good photocatalyst. According to these results, biosynthesized zinc nanoparticles could be a potential therapy option for controlling bacterial pathogenesis and an effective photocatalyst for the elimination of hazardous water contaminants.

Following on from work already carried out in our laboratory on a new biomass-derived green solvent, eucalyptol, we are now turning our attention to sabinene as a new green solvent. Sabinene is also derived from biomass. We have shown that it can be used as such or distilled to synthesize thiazolo[5,4-b]pyridine heterocycles by thermal or microwave activation. This new solvent was compared with various conventional and green solvents. The conditions were optimized to enable us to carry out the syntheses in good yields, and we were able to show that sabinene, a natural bicyclic monoterpene, could be used effectively as a solvent.

Perinatal stress experienced by mothers of very premature newborns may influence the mother’s milk and the infant’s intestinal microbiota. This prospective study of mothers of very preterm infants fed with mother´s own milk (MOM) was carried out in a tertiary hospital over a 2-year period. Assessment of maternal stress in 45 mothers of 52 very preterm newborns using the parental stress scale (PSS:NICU) that revealed an inverse relationship between stress and MOM production in the first days of life (p=0.012). The greatest contributor to stress was the one related to the establishment of mother-child bond. Maternal stress was lower in mothers in whom the kangaroo method was established early (p=0.011) and in those with a higher educational level (p=0.032). Levels of fecal calprotectin (FC) decrease with the passage of days and were directly correlated with birthweight (p=0.044). FC levels 7 days post-delivery were lower in newborns that received postnatal antibiotics (p=0.027). High levels of maternal stress resulted in progressive decreases and increases in the proportions of Firmicutes and Proteobacteria species, respectively, over 15 days post-delivery, both in MOM and in fecal samples from premature newborns. These findings underscore the importance of recognizing and appropriately managing maternal stress in neonatal units, given its marked influence on both the microbiota of maternal milk and the intestinal microbiota of premature newborns.

Currently, a wide variety of velocity profiles are used in motion control. Thus, this paper compares the energy consumption of three parabolic, trapezoidal, and S-curve profiles. We studied the case of using embedded systems since they are a powerful solution to monitor and coordinate the movement of devices and machinery in various industries combined with motion control applications. These integrated systems allow precise and efficient control of motors and actuators through control and feedback algorithms. In addition, we propose an alternative methodology for implementing motion controllers using an Advanced RISC Machine (ARM) microcontroller, which computes the trajectory and the control action in real-time. We conducted an experiment using a linear plant composed of a direct current (DC) motor coupled to an endless screw where a carriage is mounted that can move mechanically along a rail a distance of 1.16m. In addition, a 4096 pulses per revolution (PPR) encoder is connected to the motor to measure position and angular velocity, which compute the distance the carriage has moved in meters. A current sensor is used to assess the energy consumption, and 40 tests for each profile were carried out to compare the energy consumption for the three-motion profiles considering cases with and without load on the carriage.

A simulation test system for the two-dimensional (2D) fuze overload loading process was designed to address the loading issues of recoil overload and centrifugal overload in fuze safety and arming (S&amp;A) devices. By incorporating centrifuge rotation energy storage, impact acceleration simulation, and equivalent centrifugal rotation simulation, a block equipped with a fuze S&amp;A device was accelerated instantly upon being impacted by a centrifuge-driven impact hammer, simulating recoil overload loading. The impact hammer was retracted instantaneously by adopting an electromagnetic brake, which resulted in the centrifugal rotation of the block around its track, to simulate the centrifugal overload loading. The dynamic equations of the simulation test system and the equations of impact hammer motions were established, whereby the rotation speed of the centrifuge and the braking force of the electromagnetic brake were calculated and selected. A dynamic model of the collision between the impact hammer and block was established using ANSYS/LS-DYNA software for simulation analysis. The acceleration curves of the recoil overload and centrifugal overload with variations in the centrifuge speed, cushion material, and buffer thickness were obtained, which verified the feasibility of the proposed loading simulation method. 2D overload loading simulation tests were performed using the developed simulation system, and the acceleration curves of the recoil overload and centrifugal overload were measured. The test results indicated that the proposed system can accomplish 2D overload loading simulations for a recoil overload of several 10000 g and centrifugal overload of several 1000 g.

A newly UHPLC-MS/MS method development and validation for S-Allyl Cysteine was used to evaluate the comparative pharmacokinetic parameters. SC PLGA NPs were developed by the emulsion solvent evaporation method. SC PLGA NPs showed their drug loading and encapsulation efficiency i.e. 5.13±0.10% and 82.36±4.01%, respectively. SC PLGA NPs showed a spherical morphology on an average size (134.8±4.61nm), PDI: 0.277±0.004, and −25.3±1.03mV zeta-potential is suitable for oral delivery. Development and validation of the UHPLC-MS/MS bioanalytical method were performed successfully for PK-parameters examinations with 1.219-minutes RT, MS (162.00/73.10), and a total run-time was 2.0-minutes. 1.0–1000.0ng/mL was a linear-range with inter & intra-day accuracy (92.55–99.40%) followed by precision (1.88–4.23%). SC PLGA NPs oral bioavailability was significantly higher (**p<0.01) as compared to SC-S treated groups (iv & oral). We found that the antimicrobial activity of SC PLGA NPs was more effective than pure S-Allyl-L-Cysteine with significant results (p<0.01) as compared to SC-S. SC PLGA NPs showed fitted physicochemical and enhanced antimicrobial properties which can be helpful for oral administration. On the basis of our observations, SC PLGA NPs suggested the highest potential for the improvement of oral bioavailability with a sustained and controlled release of S-Allyl-L-Cysteine delivery.

Pseudomonas aeruginosa (P. aeruginosa) is an opportunistic pathogen and is the leading cause of infection in patients with cystic fibrosis (CF). The ability of P. aeruginosa to evade host responses and develop into chronic infection causes significant morbidity and mortality. Several mouse models have been developed to study chronic respiratory infections induced by P. aeruginosa, with the bead agar model being the most widely used. However, this model has several limitations, including the requirement for surgical procedures and high mortality rates. Herein, we describe novel and adapted biologically relevant models of chronic lung infection caused by P. aeruginosa. Three methods are described, a clinical isolate infection model, utilizing isolates obtained from patients with CF, an incomplete antibiotic clearance model, leading to bacterial bounce-back and the establishment of chronic infection, and an adapted water bottle chronic infection model. These models circumvent the requirement for surgical procedure and importantly, can be induced with clinical isolates of P. aeruginosa and in wild-type mice. We also demonstrate successful induction of chronic infection in the transgenic βENaC murine model of CF. We envisage that the models described will facilitate the investigations of host and microbial factors, and the efficacy of novel antimicrobials, during chronic P. aeruginosa respiratory infections.

The research is a deep study of the CBOE Volatility Index (VIX), which represent the market sentiments of the S & P 500 Index (SPX) over a period of 33 years. It evaluates how the two indexes perform in the stock market crash and how reliable VIX is in predicting market sentiments. The research distributes the market rally in two forms, and one is a trust rally, when investors are happy to see the market in a stable form, and investors' sentiments are positive towards the stock market. Second is a fear rally, where investors' sentiments are negative, and their outlook is bearish for various reasons. It observes the pattern of rallies, like the longest trust or fear rally, in which year and its duration. The research analyzes data to reach a meaningful conclusion and various inferences that can be drawn from the study of historical data.

Methyl Salicylate (MS), the principal constituent of Wintergreen oil (WO) was obtained from acetyl salicylic acid (ASA) by sequential transesterification-esterification reaction promoted by NbCl5for the first time. The reagents were added simultaneously, and the reaction process involved the transesterification and esterification reactions, which were accompanied by thin layer chromatography and gas chromatography. The conversion rate via GC was 100%, and the MS yield was 94%. A cytotoxicity of 50% and 64% for cultured S. aureus and metastatic melanoma cells, respectively, was observed for a concentration of 0.6 mg/mL, whereas no cytotoxicity for non-tumor cells was observed for this concentration, and it is considered to be the optimum concentration.

In response to the new concept of the impact of total climate production factors on plant phenology, this study will verify the feasibility of simulating plant phenology and triggering thresholds based on total climatic production factors by using the phenological and meteorological observation data of S. krylovii plant from 1985 to 2018 at the Xilinhot National Climate Observatory of China Meteorological Administration. The results indicate that the total climate production factors influencing plant phenological changes can be well used for phenological simulation and its triggering thresholds. The mutation of cumulative climate production potential based on total climate production factors can effectively indicate the green-up date and the wilting date of S. krylovii plant, and their triggering thresholds depend on the parameters of climate resource change and plant biology, which are (0.085, –5.363) and (0.086, –27.620), respectively. The cumulative climate production potential based on total climate production factors can effectively indicate the heading date of S. krylovii plant, and its triggering thresholds also depends on the parameters of climate resource change and plant biology, which is (394.632，–38026.268). Furthermore, the results support the viewpoint that the climate abrupt changes determine the beginning and the ending of plant growth, while the accumulative climate resources determine the other phenological dates. This study provides new ideas for the study of plant phenology.

With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need and significance for the development of novel image encryption algorithms is unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps, utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage, a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. However, the main advantages of this work are: (1) The attained width of the key space; and (2) The achieved efficiency in software implementation. The superior key space of 2^{2551} is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of the utilization of the single neuron model, as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite.

From the merge of arts and crafts towards a practice for mass production of desirability, consumption and product development in a capitalist economy of scale, design has lost its natural ability of problem comprehension and tension alleviation. The modern world needs the creativity, flexibility, and responsiveness embedded into design practices, mostly when a behavioural change, either individual or organizational, is intended. Still, the informality nature of the field is creating a gap between the study, research, and industrial design practice. Here it is presented the Biology of Creativity Model (BoC) which is a design-by-analogy method that promotes an empowered design practice through analysis of mostly biology reference texts for enhanced creativity and innovation performance in a diverse array of contexts.

Cotton is one of the most important economic crops in the world, whereas insect attacks is a prime cause of its losses on yield and quality. Despite it is important, little is known about the mechanism of cotton response to insect. In this study, we simulated insect feeding by applying insect oral secretions (OS) to wounds, and combined transcriptome and metabolome analysis to comprehensively investigate how OS from two major pest species (Helicoverpa armigera and Spodoptera litura) affect cotton defense responses. Obvious differences were observed that 12,668 and 13,379 genes differently expressed respectively in cotton after being treated with different OS when compared with wounding along. Upon the addition of OS, JA-signaling pathway were rapidly and strongly induced, however SA-biosynthesis related gens were significantly down-regulated. By constructing the co-expression gene network, we identified a hub gene which encoding a leucine-rich repeat receptor kinase may play important role in recognition and signal transduction at early stage. We also found that OS from different insect species altered abundance of flavonoid related compound with different patterns. Interestingly, Gossypol which is a well-known anti-insect compound was kept a relative low content after OS application relative to wounding which implied the existence of the suppression effects of OS to cotton defense response. This study illustrated the transcriptional and metabolic changes of cotton in responding to OS from two chewing insect species, identified potential key gene during the interaction process and finds the evidence for OS’s inhibition effects on cotton defense response.

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

In recent, Chae found that, at weak gravitational acceleration g_N≲10⁻⁹ms⁻², the observed orbit of the wide binary stars is not accordant with current theory of binary star. Here, we present, this finding should be an observational evidence for that Newtonian theory of orbit perturbation is still valid in galactic scale.

Clustering algorithms for multi-database mining (MDM) rely on computing $(n^2-n)/2$ pairwise similarities between $n$ multiple databases to generate and evaluate $m\in[1, (n^2-n)/2]$ candidate clusterings in order to select the ideal partitioning which optimizes a predefined goodness measure. However, when these pairwise similarities are distributed around the mean value, the clustering algorithm becomes indecisive when choosing what database pairs are considered eligible to be grouped together. Consequently, a trivial result is produced by putting all the $n$ databases in one cluster or by returning $n$ singleton clusters. To tackle the latter problem, we propose a learning algorithm to reduce the fuzziness in the similarity matrix by minimizing a weighted binary entropy loss function via gradient descent and back-propagation. As a result, the learned model will improve the certainty of the clustering algorithm by correctly identifying the optimal database clusters. Additionally, in contrast to gradient-based clustering algorithms which are sensitive to the choice of the learning rate and require more iterations to converge, we propose a learning-rate-free algorithm to assess the candidate clusterings generated on the fly in a fewer upper-bounded iterations. Through a series of experiments on multiple database samples, we show that our algorithm outperforms the existing clustering algorithms for MDM.

Local binary pattern is one of the visual descriptors and can be used as a powerful feature extractor for texture classification. In this paper, a novel representation for face recognition is proposed, called it Bilateral Line Local Binary Patterns (BL-LBP). This scheme is an extension of Line Local Binary Patterns descriptors in the statistical learning subspace. The present bilateral descriptors are fused with an ensemble learning of calibrated SVM models. The performance of this scheme is evaluated using 5 standard face databases. It is found that it is robust against illumination variation, diverse facial expressions and head pose variations and its recognition accuracy reaches 98 percent, running on a mobile device with a processing speed of 63 ms per face. Results suggest that our proposed method can be very useful for the vision systems that have limited resources where the computational cost is critical.

In this paper, we observe that if X is a set and (Bin(X), □) is the semigroup of binary systems on X, then its center ZBin(X) consists of the locally-zero-semigroups and that these can be modeled as (simple) graphs and conversely. Using this device we show that we may obtain many results of interest concerning groupoids by reinterpreting graph theoretical properties and at the same time results on graphs G may be obtained by considering them as elements of centers of the semigroups of binary systems (Bin(X), □) where X = V(G), the vertex set of G.

This paper presents novel feature descriptors and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI) of breast cancer histology slides. Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level and to use simple, yet robust feature descriptors that can provide accurate classification of the slides. We propose two types of feature descriptors that encode important information about staining patterns and the percentage of staining present in ImmunoHistoChemistry (IHC) stained slides. The first descriptor is called a characteristic curve which is a smooth non-increasing curve that represents the variation of percentage of staining with saturation levels. The second new descriptor introduced in this paper is an LBP feature curve which is also a non-increasing smooth curve that represents the local texture of the staining patterns. Both descriptors show excellent interclass variance and intraclass correlation, and are suitable for the design of automatic HER2 classification algorithms. This paper gives the detailed theoretical aspects of the feature descriptors and also provides experimental results and comparative analysis.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) &gt; MRI (2.14 ± 0.08) &gt; EEG (1.87 ± 0.09) &gt; SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) &gt; MRI (0.518) &gt; EEG (0.446) &gt; SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) &gt; MRI (2.558) &gt; EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

We consider boundary value problems for a nonlinear mass transfer model, which generalizes the classical Boussinesq approximation, under inhomogeneous Dirichlet boundary conditions for the velocity and the substance’s concentration. It is assumed that the leading coefficients of viscosity and diffusion and the buoyancy force in the model equations depend on concentration. We develop mathematical apparatus of studying inhomogeneous boundary value problems under consideration. It is based on using of a weak solution of the boundary value problem and construction of liftings of the inhomogeneous boundary data. They remove the inhomogeneity of the data and reduce original problems to equivalent homogeneous boundary value problems. Based on this apparatus we will prove the theorem of the global existence of a weak solution to boundary value problem under study and establish important properties of the solution. In particular, we will prove the validity of the maximum principle for the substance’s concentration. We will also establish sufficient conditions for the problem data, ensuring the local uniqueness of weak solutions.

In 2011, by 1.3 mm wavelength VLBI radio wave observations of the SgrA*, Fish, V. L. et al showed that the emissions tightly related to the formation of a black hole shadow have a remarkably large time-varying feature within a region of less than 50 μas. The present paper suggests that the origin of the time variation in the observed emission is due to effects of the orbital motion of the existing super-massive black hole binary orbiting at SgrA* with a period of 2150±2.5 s. This suggestion is based on observations of decameter radio wave pulses from SgrA*. We show a good correlation between the time variation in the coherent flux density of the VLBI results and the time variation model of estimated emission intensities based on the periodic motion of the super-massive black hole binary by applying parameters deduced from the decameter radio wave pulse observation model (DRWP-Model). With further confirmation by Fourier analyses of the potential periodicity of the VLBI data that show the same periods of DRWP Model, we conclude that the time variation detected by the 1.3 mm wavelength radio wave VLBI is evidence of an existing super-massive black hole at Sgr A*.

Mass plays a strange multiple role in classical physics. This results in a difference between gravity and all other forces - a difference that stood at the beginning of Einstein's development of his general theory of relativity. The equivalence principle (EP) deals with homogenious gravitational fields, which, in fact, don‘t exist in nature. There is only an approximation for this field in Einstein-Lift possible for local situations. Nevertheless this EP can be true, because in classical formal binary logic there can be formulated a true conclusion from a wrong premise or assumption.

Influenza virus transcription is catalyzed by the viral RNA-polymerase (FluPol) through a cap-snatching activity. The snatching of the cap of cellular mRNA by FluPol is preceded by its binding to the flexible C-terminal domain (CTD) of the RPB1 subunit of RNA-polymerase II (Pol II). To better understand how FluPol brings the 3’-end of the genomic RNAs in close proximity to the host-derived primer, we hypothesized that FluPol may recognize additional Pol II subunits/domains to ensure cap-snatching. Using binary complementation assays between the Pol II and FluPol subunits and their structural domains, we revealed an interaction between the N-third domain of PB2 and RPB4. This interaction was confirmed by a co-immunoprecipitation assay and found to occur with the homologous domains of influenza B and C FluPols. Residues [1-72] of RPB4 were found critical in this interaction. Numerous punctual mutants generated at conserved positions between influenza A, B and C FluPols in the N-third domain of PB2 exhibited strong transcriptional activity defect. These results suggest that FluPol interacts with several domains/subunits of Pol II, the CTD to bind Pol II initiating host transcription and a second on RPB4 to locate FluPol at the proximity of the 5’-end of nascent host mRNA.

The storage of biochemical information, which is a prerequisite for the development of the first cell, is an unsolved problem affecting all concepts of the origin of life. However, if the protected environment in the continental crust is taken into account, completely new possibilities emerge for identifying processes that may have been crucial for the formation of the first cell. Under this background, we can hypothesize that, before cellular life began, a self-sustaining cycle of molecular reaction steps with information storage in RNA existed outside of a cell. This cycle was made possible in an open system bound to gas-permeable tectonic fracture zones with a high proportion of CO2 and N2. The formation of peptides and vesicles in supercritical CO2 and the chemical evolution of peptides have already been proven for the upper continental crust. Further considerations include the interactions of vesicles with catalytic peptides and the emergence of proto-tRNA. In combination with the formation of proto-tRNA synthetases, which consist of only two amino acid species and associated proto-tRNAs, the first RNA as an information storage system could have been formed with the information of proto-enzymes.

The article presents the author's results of studying hidden rules of structural organizations of long DNA sequences in eukaryotic and prokaryotic genomes. The results concern some rules of percentages (or probabilities) of n-plets in genomes. To reveal such rules, the author considers genomic DNA nucleotide sequences as multilayers sequences of n-plets and studies the percentage contents of n-plets in different layers. Unexpected rules of invariance of total sums of percentages in certain tetra-groupings of n-plets in different layers of genomic DNA sequences are revealed. These discovered rules are candidates for the role of universal genomic rules. A tensor family of matrix representations of interrelated DNA-alphabets of 4 nucleotides, 16 doublets, 64 triplets, and 256 tetraplets is used in the study. This matrix approach allows revealing algebraic properties of the mentioned genetic rules of probabilities, which are useful for developing algebraic and quantum biology. Some analogies of the discovered genetic phenomena with phenomena of Gestalt psychology are noted and discussed. The author connects the received results about the genomic percentages rules with a supposition of P. Jordan, who is one of the creators of quantum mechanics and quantum biology, that life's missing laws are the rules of chance and probability of the quantum world. Additional attention is paid to the algebraic features of the system of structured DNA alphabets and their relationship with the methods of algebraic holography, known in the technique of processing discrete signals. The concept of algebraic-holographic genetics is being developed for the understanding of inherited holographic properties of organisms.

This paper presents a discrete compartmental Susceptible-Exposed-Infected-Recovered/Dead (SEIR/D) model to address the expansion of Covid-19 pandemic. When time passes, the status of the cells is determined by binary rules that update following both a neighbourhood and a delay pattern. The model assumes the environmental parameters have a crucial impact on the expansion of the disease so a grid is assigned to each parameter to model the single effect caused by this parameter. The expansion is then the weighted sum of all the grids. This proposal shows how the grid architecture, along with an update rule and a neighbourhood pattern is a valuable tool to model the pandemic expansion. This model has already been analyzed in previous works and compared with the corresponding continuous models solved by ordinary differential equations (ODE), coming to find the homologous parameters between both approaches. Thus, it has been possible to prove that the combination neighborhood-update rule is responsible for the rate of expansion and recovering/death of the illness. The delays (between Susceptible and Asymptomatic, Asymptomatic and Infected, Infected and Recovered/Dead) may have a crucial impact on both the peak of Infected and the Recovery/Death rate. This theoretical model has been successfully tested in the case of the dissemination of information through mobile social networks and in the case of plant pests.

Motivated by diffraction experiments on the $\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$ reconstructed Si(111) due to deposition of rare earth elements (Dy, Tb) and silicide formation we analyse the splitting and non-splitting of superstructure spots. For this purpose, we model diffraction patterns for one dimensional structures generated by the binary surface technique and use supercell models to keep the analysis simple. Diffraction pattern are calculated in the framework of the kinematical diffraction theory and they are analyzed as a function of the domains and domain boundaries. Basic properties of the diffraction pattern are analyzed for model systems of a two-fold and a three-fold periodicity. The rules derived from these calculations are applied to the "real-world" system of Si(111)-($\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$)-RESi$2_{}$ (RE = Dy or Tb). Depending on the combination of domains and domain boundaries of different types a plethora of different features are observed in the diffraction patterns. These are analyzed to determine the sizes of both domain boundaries and domains from experimentally observed splitting of specific superstructure spots.

Amidst worsening climate change, drought stress imperils global agriculture, jeopardizing crop yields and food security, necessitating urgent exploration of sustainable methods like biopriming, harnessing beneficial microorganisms to bolster plant resilience. Recent research has revealed diverse biological compounds with versatile applications produced by Schizophyllum commune, rendering this fungus as a promising contender for biopriming applications. For the first time this study aimed to investigate,the potential of S. commune exo- (EPSH) and intra-PSH (IPSH), isolated from two strains: Italian (ITA) and Serbian (SRB) under submerged cultivation, in enhancing the resilience of Pisum sativum L. seeds through biopriming technique. Testing of seed quality of bioprimed, hydroprimed, and unprimed seeds was done using a germination test, under optimal and drought conditions. In optimal conditions, the IPSH SRB increased germination energy by 5.50% compared to the control, while the highest percentage of germination (94.70%) was shown after biopriming with PSH isolated from the ITA strain. Additionally, all assessed treatments resulted in a boost in seedling growth and biomass accumulation, where the ITA strain demonstrated greater effectiveness in optimal conditions, whereas the SRB strain showed superiority in drought conditions. The drought tolerance indices increased significantly in response to all examined treatments during the drought, with EPSH ITA (23.00%) and EPSH SRB (24.00%) demonstrating the greatest effects. Results demonstrate a significant positive influence of fungal PSH, indicating their potential as biopriming agents and offers insights into novel strategies for agricultural resilience in the face of changing environmental conditions.

A difficult open problem that has never been fully resolved in the literature to date is the behaviour of the (TDCDP) third approximation. As a giant step towards modern control theory, this cutting-edge paper will advance control theory and other relevant inter-disciplinary subjects. Because control theory is important in industry and engineering, this study will be especially beneficial to anyone working in these disciplines who wish to understand more about recent advances in control theory settings. In contrast, the wealth of applications of Fokker Planck Kolmogorov (FPK) equations numerous disciplines As a result, the study instantly gains more taste and credibility. At the end of the paper, there are several challenging open problems, some concluding remarks, and recommendations for further investigation.

Our starting point is the covariant coordinate transformation equation of a relativistic positioning system in Minkowski space-time, which maps the receiver’s emission coordinates (proper times broadcast by the emitters) to its coordinates in some inertial reference frame. Bancroft’s analytical (closed-form) solution to the basic pseudorange navigation equations with four emitters is recovered and the subjacent elements are geometrically interpreted. The case of four static beacons is analized as a clarifying situation.

This article addresses the urbanization model in valley bottom areas in the city of São Paulo, an-alyzed in its urban planning and socio-environmental aspects, and examines the hydrological impacts triggered by its implementation. It argues that sustainable occupation of urbanized hy-drographic basins should be based on environmental criteria in order to attain a sustainable water management regime that can ensure urban and environmental resilience. In the “Introduction,” the article emphasizes that urbanization in São Paulo has neglected the natural features of river basins, promoting the channeling of watercourses, which resulted in floods and inundations. “Theoretical Basics” brings in key concepts related to the environmental approach of drainage infrastructure with gray and green-blue systems. “Methods” details our qualitative research, bibliographical analyzes, referential case studies, and cartographical analyzes (geoprocessing), focusing on a case study in the Jaguaré creek basin. “Results” includes guidelines and recom-mendations for an urbanization model adjusted to valley bottom areas, applicable to new patterns of urban occupation or to the adjustment of existing patterns. “Discussion” explores the concept of “local sustainable self-development,” and “Conclusions” highlights the importance of an inte-grated, multisectoral, and sustainable planning, adjusted to the characteristics of river basins in valley bottom areas, promoting a socially responsible urban occupation, especially in the face of climate change.

. Interconnected control systems (ICS) widely apply to various technical systems. ICS has a complex description. Therefore, simplified models use, which the specifics of an object do not always reflect. So, the problem of synthesizing mathematical models is topical. The work purpose is to develop an approach to obtaining models in conditions of incomplete a priori information. We use an adaptive approach. As examples, two-channel systems (TCS) with cross-links and identical channels consider, and a method for mathematical model design. We consider the system with asymmetric cross-links and evaluate their impact on properties of an adaptive identification system. Approach proposed to assessing the TCS identifiability with cross-links. The excitation constancy influence on TСS parameter estimates is studied. A generalization of the proposed approach is given for an interconnected system.

Smoker’s paradox usually refers to the common observation of a favourable outcome of smoker patients in acute myocardial infarction. The interpretation of this phenomenon is still controversial and not fully explained. We aimed at assessing whether smoking could be associated with mortality in a large cohort of prospectively enrolled patients with ST segment elevation myocardial infarction (STEMI) referred to primary percutaneous coronary intervention (pPCI). From April 2006 to December 2018 a population of 2456 STEMI patients treated with primary PCI were prospectively enrolled in the MATRIX registry. Ischemic time, clinical, demographics, angiographic data and 1-year follow-up were collected. Among 2546 patients admitted with STEMI 1007 (41%) were current smokers. Smokers were 10 years younger and had lower crude in-hospital and 1-year mortality (1.5% vs 6%, p&lt;0.0001 and 5% vs 11%, p&lt;0.0001), shorter ischemic time (203 [147-299] vs 220 [154-334] minutes, p=0.002) and shorter decision time (60 [30-135] vs 70 [36-170] minutes, p=0.0063). After propensity-matching, age, cardiogenic shock and low TIMI score were associated with in-hospital mortality, while smoking habit was still associated with reduced mortality. Smoking was also associated with reduced death rate at 1-year follow-up (HR 0.54, 95% CI [0.37 - 0.78]; p&lt;0.001). Our data show a protective link between smoking status and mortality in patients with STEMI, the so called “smoker’s paradox”. This could be explained not only by the shorter ischemic time and younger age of the smoking population but also by a specific pathogenetic effect of smoking underlying the onset of STEMI and response to therapies.