The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

Recent reports suggest that the clinical course of coronavirus disease 2019 (COVID-19) in previously healthy children is usually milder as compared to adults. However, children with comorbid conditions such as diabetes are at increased risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as well as morbidity and mortality due to COVID-19. Experience in adults with diabetes shows that they are prone to faster metabolic decompensation, develop diabetes-related complications, and have a poor prognosis when hospitalized with COVID-19. Data on children are limited. The aim of this mini-review is to discuss the possible risks to children and adolescents with diabetes during the current pandemic and the special considerations in management in those affected with COVID-19. The challenges for children who develop new-onset type 1 diabetes during the COVID-19 lockdown, especially in accessing healthcare, are also discussed.

Neurological involvement following COronaVIrus Disease 19 (COVID-19) is thought to have a neuroinflammatory etiology. Co-ultraPEALut (an antiinflammatory molecule) and luteolin (an antioxidant) yielded promising results as neuroinflammation antagonists. This study aimed at describing cognitive impairment in post-COVID patient treated with co-ultraPEALut. Montreal Cognitive Assessment (MoCA), Prospective-Retrospective Memory Questionnaire (PRMQ), Fatigue Severity Scale (FSS) and a subjective evaluation were administered at baseline and after 10 months. Co-ultraPEALut-treated patients were retrospectively compared with controls. 26 co-ultraPEALut-treated patients showed significant improvement in PRMQ (T0: 51.94±10.55, T1: 39.67±13.02, p

Evaluation of the usefulness of [18F]FDG-PET/CT in the short-term follow-up of patients admitted for COVID-19 pneumonia and to explore the association of findings with clinical prognostic markers. Prospective study included 20 patients admitted to hospital with COVID-19 pneumonia between November 2020 and March 2021. Clinical and laboratory test findings were gathered at admission, 48-72h post-admission, and 2-3 months post-discharge. [18F]FDG-PET/CT and respiratory function tests were performed at 2-3 months post-discharge. Lung volumes (TLC), spirometry (FVC, FEV1), lung diffusion capacity for carbon monoxide (DLCO), and respiratory muscle strength were measured. PET/CT images were qualitatively and semi-quantitatively interpreted. Volumetric [18F]FDG-PET/CT results were correlated with laboratory test and respiratory parameters. Eleven [18F]FDG-PET/CT (55%) were positive. The main finding was hypermetabolic lymphade-nopathy in the mediastinum (90.9%). SUVpeak of the target mediastinum lesion was correlated with neutrophil and lymphocyte counts. Eleven (55%) patients had impaired respiratory function, most frequently a reduced DLCO (35%). SUVpeak was positively correlated with %predict-ed-DLCO values. Pulmonary TLG was negatively correlated with %predicted-DLCO and TLC values. In the short-term follow-up of patients hospitalized for COVID-19 pneumonia, [18F]FDG-PET/CT findings revealed significant detectable inflammation in lungs and mediastinal lymph nodes that correlated with pulmonary function impairment in more than half of the patients.

M-polynomial of different molecular structures helps to calculate many topological indices. A topological index of graph G is a numerical parameter related to G which characterizes its molecular topology and is usually graph invariant. In the field of quantitative structure-activity (QSAR) quantitative structure-activity structure-property (QSPR) research, theoretical properties of the chemical compounds and their molecular topological indices such as the Zagreb indices, Randic index, Symmetric division index, Harmonic index, Inverse sum index, Augmented Zagreb index, multiple Zagreb indices etc. are correlated. In this report, we compute closed forms of M-polynomial, first Zagreb polynomial and second Zagreb polynomial of Octagonal network. From the M-polynomial we recover some degree-based topological indices for Octagonal network. Moreover, we give a graphical representation of our results.

The thionamide antithyroid drugs were discovered largely following serendipitous observations by numerous researchers in the 1940s who found that sulfhydryl-containing compounds were goitrogenic in animals. Prof. Edwin B. Astwood was the first to use these compounds to treat hyperthyroidism. In this review, we summarize the history of the development of these drugs and the coordination possibility of 2-thiouracil and its derivatives, as well as the biological activities of some of its complexes. Some of them are used as agents for the treatment of tuberculosis, and arthritis, others have bactericidal and fungicidal activity, the third cytotoxic properties, and could be used to treat various types of cancer.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

The COVID-19 pandemic over the past years has shown a great need for rapid, low-cost and on-site detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, an aptamer-based colloidal gold nanoparticle lateral flow test strip was well developed to realize the visual detection of wild type SARS-CoV-2 spike protein (SP) and multiple variants. Under the optimal reaction conditions, a low detection limit of SARS-CoV-2 S protein of 0.68 nM was acquired, and the actual detection recovery was 83.3% to 108.8% for real world samples. This suggests a potential tool for the prompt detection of SARS-CoV-2 with good sensitivity and accuracy, and a new method for the development of alternative antibody test strips for the detection of other viral targets.

Carnivore protoparvovirus 1 (CPPV-1) is a DNA virus causing gastrointestinal disease and immunosuppression in various terrestrial carnivores. Domestic dogs and cats are considered the primary CPPV-1 reservoirs. The habitat overlaps of wild carnivores and free-roaming dogs increases the threat of CPPV-1 transmission between them. This study explored the CPPV-1 distribution among wild carnivores through PCR screening and compared the DNA sequences of the partial capsid protein (VP2) between wild and domestic carnivores. In total, 181 samples were screened for the CPPV-1 VP2 gene, including 32 masked palm civets (Paguma larvata), 63 Chinese ferret badgers (Melogale moschata), and 86 crab-eating mongooses (Herpestes urva), from 2015 to 2019 in Taiwan. The average prevalence of CPPV-1 was 17.7% (32/181), with the highest prevalence in masked palm civets (37.5%). In addition, a masked palm civet was coinfected with two CPPV-1 strains. Among the 33 partial VP2 gene sequences, 23 were identical to sequences amplified from domestic dogs and cats in Asia and the remaining 10 were identified for the first time. This study demonstrated that CPPV-1 has circulated between domestic and wild carnivores in rural Taiwan. Therefore, further population control and health management of free-roaming domestic carnivores are recommended.

Let be a power function $f_{r,M}(s)$ defined for every $s$ within the finite set $M$ as follows $$f_{r,M}(s)= \begin{cases} s^r, \ &s\in M,\\ 0, \ &\mathrm{otherwise}. \end{cases} $$ Let a discrete convolution of $f_{r,M}(s)$ be denoted as follows $\mathrm{Conv}_{r,M}[n]=(f_{r,M}*f_{r,M})[n]$. Let a real coefficients $A_{m,j}$ be given by the following recurrence $$ A_{m,j} = \begin{cases} 0, & \mathrm{if } \ j<0 \ \mathrm{or } \ j>m, \\ (2j+1)\binom{2j}{j} \sum_{d=2j+1}^{m} A_{m,d} \binom{d}{2j+1} \frac{(-1)^{d-1}}{d-j} B_{2d-2j}, & \mathrm{if } \ 0 \leq j < m, \\ (2j+1)\binom{2j}{j}, & \mathrm{if } \ j=m. \end{cases} $$ In this paper we show that for every $n>0$ the following odd-power identities involving coefficients $A_{m,j}$ and convolution transform $\mathrm{Conv}_{r,M}[n]$ hold $$ \begin{split} n^{2m+1}+1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{N}}[n],\\ n^{2m+1}-1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{Z}_{>0}}[n],\\ n^{2m+1}&=\sum_{r=0}^{m}A_{m,r}\sum_{k=1}^{n} k^r(n-k)^r\\ &=\sum_{r=0}^{m}A_{m,r}\sum_{k=0}^{n-1} k^r(n-k)^r. \end{split} $$

Individuals diagnosed with systemic arterial hypertension (SAH) are considered risk groups for COVID-19 severity. This study assessed differences in cardiac autonomic function (CAF) and functional capacity (CF) in SAH individuals without COVID-19 infection compared to SAH individuals post-COVID-19. Participants comprised 40 SAH individuals aged 31 to 80 years old, grouped as SAH with COVID-19 (G1; n=21) and SAH without COVID-19 (G2; n=19). CAF was assessed via heart rate variability (HRV), measuring R-R intervals during a 10-minute supine period. Four HRV indices were analyzed through symbolic analysis: 0V%, 1V%, 2LV%, and 2UV%. FC assessment was performed by a 6-minute walk test (6MWT). G1 and G2 showed no difference between significant age, anthropometric, clinical and medication. G2 exhibited superior 6MWT performance, covering more distance (522±78 vs. 465±59 meters, p&lt;0.05). Specifically, G2 demonstrated a moderate, positive correlation between 6MWT and the 2LV% index (r=0.58; p&lt;0.05). Shorter walking distances were observed during 6MWT in SAH individuals post-COVID-19. However, the study did not find impaired cardiac autonomic function in SAH individuals post-COVID-19 compared to those without. This suggests that while COVID-19 impacted FC, CAF remained relatively stable in this population.

The urgent need to improve performance in the construction industry has led to the adoption of many innovative technologies. 3D laser scanners are amongst the leading technologies being used to capture and process assets or construction project data for use in various applications. Due to its nascent nature, many questions are still unanswered about 3D laser scanning, which in turn contribute to the slow adaptation of the technology. Some of these include the role of 3D laser scanners in capturing and processing raw construction project data. How accurate is the 3D laser scanner or point cloud data? How does laser scanning fit with other wider emerging technologies such as Building Information Modelling (BIM)? This study adopts a proof-of-concept approach, which in addition to answering the afore-mentioned questions, illustrates the application of the technology in practice. The study finds that the quality of the data, commonly referred to as point cloud data is still a major issue as it depends on the distance between the target object and 3D laser scanner’s station. Additionally, the quality of the data is still very dependent on data file sizes and the computational power of the processing machine. Lastly, the connection between laser scanning and BIM approaches is still weak as what can be done with a point cloud data model in a BIM environment is still very limited. The aforementioned findings reinforce existing views on the use of 3D laser scanners in capturing and processing construction project data.

Previous studies found high but very variable levels of tetranor-PGEM and PGD-M (urine metabolites of prostaglandin (PG) E2 and PGD2, respectively) in persons with cystic fibrosis (pwCF), which correlated with the severity of the CF transmembrane receptor (CFTR) genetic alteration. This study aims to assess the potential role of cyclooxygenase (COX)-1 and COX-2 genetic polymorphisms in the variability of PG production, and determine the potential role of PG metabolites as markers of symptoms severity and imaging findings. Thirty healthy subjects and 103 pwCF were included in the study. Clinical and radiological CF severity was evaluated using clinical scoring methods and the extent of bronchiectasis and air trapping were assessed by chest computed tomography (CT). Urine metabolites were measured using liquid chromatography/tandem mass spectrometry. The presence of variants in the COX-1 gen (PTGS1 639 C>A, PTGS1 762+14delA, and COX-2 gen: PTGS2-899G>C (-765G>C) and PTGS2 (8473T>C) were analysed. PGE-M and PGD-M urine concentrations were significantly higher in pwCF than in healthy controls. There were also statistically significant differences between clinically mild and moderate disease and severe disease. Patients with bronchiectasis and/or air trapping had higher PGE-M levels than patients without these complications. The four polymorphisms did not associate with clinical severity, air trapping, bronchiectasis, or urinary PG levels. Taken together, the present study suggests that urinary PG level testing can be used as a biomarker of CF severity. We found no relationship between COX-1 and COX-2 genetic polymorphisms in the variability of PG production.

Aiming at the limitations of single-functionality, limited applicability, and complex designs prevalent in current metasurfaces, we propose a terahertz multifunctional and multiband tunable metasurface utilizing a VO2-metal hybrid structure. This metasurface structure comprises a top VO2-metal resonance layer, a middle polyimide dielectric layer, and a gold film reflective layer at the bottom. This metasurface exhibits multifunctionality, operating independently of polarization and incident angle. The varying conductivity states of the VO2 layers, enable the metasurface to achieve various terahertz functionalities, including single-band absorption, broadband THz absorption, and multiband perfect polarization conversion for linear (LP) and circularly polarized (CP) incident waves. Finally, we believe that the functional adaptability of the proposed metasurface expands the repertoire of options available for future terahertz device designs.

The developments of confirmed daily Sars-CoV-2 infections can be modeled a posteriori in a comparatively simple and satisfactory way by means of a special exponential function: its exponential coefficient varies exponentially with time itself. This property enables the function to directly simulate the „daily case“ curve fragments observed for the first waves of the current epidemics in a number of counties and countries. Linear combinations of two or more of the functions allow for the modeling of the complete curves observed in the vast majority of all regions for which case number developments have been tabulated.

A timely inventory of agricultural areas and crop types is an essential requirement for ensuring global food security. Satellite remote sensing has proven to be an increasingly more reliable tool to identify crop types. With the Copernicus program and its Sentinel satellites, a growing source of satellite remote sensing data is publicly available at no charge. Here we use joint Sentinel-1 radar and Sentinel-2 optical imagery to create a crop map for Belgium. To ensure homogenous radar and optical input across the country, Sentinel-1 12-day backscatter composites were created after incidence angle normalization, and Sentinel-2 NDVI images were smoothed to yield dekadal cloud-free composites. An optimized random forest classifier predicted the 8 crop types with a maximum accuracy of 82% and a kappa coefficient of 0.77. We found that a combination of radar and optical imagery always outperformed a classification based on single-sensor inputs, and that classification performance increased throughout the season until July, when differences between crop types are largest. Furthermore we showed that the concept of classification confidence derived from the random forest classifier provided insight in the reliability of the predicted class for each pixel, clearly showing that parcel borders have a lower classification confidence. We concluded that the synergistic use of radar and optical data for crop classification led to richer information increasing classification accuracies compared to optical-only classification. Further work should focus on object-level classification and crop monitoring to exploit the rich potential of combined radar and optical observations.

In this paper, the integrated performance of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and a supplementary supercritical-CO2 (sCO2) Brayton cycle is analyzed. The aim is to leverage the high efficiency supplementary sCO2 cycle to increase net generation and energy efficiency from the existing biomass boiler. Two sCO2 heater configurations situated within the flue gas flow path are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. A quasi-steady-state 1D model was developed to simulate the integrated cycle, including detailed component characteristics for the Rankine and Brayton cycles. The model solves the mass, energy, momentum, and species balance equations. The system is analyzed for three cases: (i) the existing Rankine cycle without the sCO2 integration, (ii) with the single convective-dominant sCO2 heater configuration, and (iii) the dual sCO2 heater configuration. The results show the required rate of overfiring for the sCO2 configurations, with a 15.3% increase in fuel flowrate resulting in an additional 21.2% in net power output. The model quantifies the impact of the sCO2 heaters, with reduced heat uptakes for downstream boiler heat exchangers. Furnace water wall heat uptake increased due to overfiring, offsetting the reduced heat uptakes at downstream evaporative heat exchangers. The dual configuration has more impact on Rankine cycle operation due to the radiative sCO2 heater placement in front of the second superheater, absorbing some of the direct radiation from the furnace.

Satellite Crop Detection technologies are focused on detection of different types of crops on the field in the early stage before harvesting. Crop detection is usually done on a time series of satellite data by classification of the desired fields. Currently, data obtained from Remote Sensing (RS) are used to solve tasks related to the identification of the type of agricultural crops, also modern technologies using AI methods are desired in the postprocessing part. In this challenge Sentinel-1 and Sentinel-2 time series data were used due to their periodic availability. Our focus was to develop methodology for classification of time series of Sentinel 2 and Sentinel 1 data and compare how accuracy of classification can be increased, but also how to guarantee availability of data. We analyse phenology of single crops and on the basis of this analysis we started to provide crop classification. Original crop classifications were made from Enhanced Vegetation Index (EVI) layers made from Sentinel-2 time-series data and then we added also . To increase accuracy we also integrate into the process parcel borders and provide classification of fields..

Detection of PLA2R and THSD7A among primary membranous glomerulonephritis (MGN) patients transformed the diagnosis, treatment monitoring and prognosis. Anti-PLA2R can be detected in 70-90% of primary MGN patients while anti-THSD7A in 2-3% of anti-PLA2R negative primary MGN patients depending on the technique used. Serum and urine samples are less invasive and non-invasive respectively and can detect the presence of anti-PLA2R and anti-THSD7A with higher sensitivity and specificity, significant in patients’ monitoring and prognosis better than exposing patients to frequent biopsy which is an invasive procedure. Different techniques of detection of PLA2R and THSD7A in patients’ urine and sera were reviewed with the aim of providing newer and alternative techniques. We proposed the use of biomarkers (PLA2R and THSD7A) in making the diagnosis, treatment decision and follow up of patients with primary MGN. We also reviewed other prognostic renal biomarkers like retinol binding protein (RBP) and beta-2 microglobulin in order to detect progression of renal damage for early intervention.

This study investigated the factors affecting consumers’ acceptance to use cashless payment services in Malaysia through the construction of the Cashless Society Acceptance (CSA) model. The Technology Readiness Index 2.0 and Unified Theory of Acceptance and Use of Technology 2 were employed to create the CSA model. A total of 434 questionnaires were collected from Malaysian consumers, aged 18 years and above. The results show that Perceived Usefulness, Perceived Ease of Use, and Discomfort have the most significant influence on the consumers’ acceptance of cashless payment services with R-square of 71.4%.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

Chronic diseases, such as type 2 diabetes (T2D), are difficult to manage because they demand continuous therapeutic review and monitoring. Beyond achieving the target HbA1c, new guidelines for the therapy of T2D have been introduced with the new groups of antidiabetics (GLP-1ra and SGLT2-in). Despite new guidelines, clinical inertia, that can be caused by physicians, patients or healthcare system, results in T2D not being effectively managed. This opinion paper explores the shift in T2D treatment, challenging assumptions and evidence-based recommendations, particularly for family physicians, considering the patient's overall situation in decision-making. We looked for the possible reasons of clinical inertia and poor application of guidelines in the management of T2D. Guidelines for antidiabetic drugs should be more precise, providing case studies and clinical examples to define clinical contexts and contraindications. Knowledge communication can improve confidence and should include clear statements on areas of decision-making not supported by evidence. Precision medicine initiative in diabetes aims to identify subcategories of T2D patients (including frail patients) using clustering techniques from data science applications, focusing on CV and poor treatment outcomes. Clear, unconditional recommendations for personalized T2D management may encourage drug prescription, especially for family physicians dealing with diverse patient contexts and clinical settings.

Type 2 Diabetes Mellitus (T2DM) is associated with a high risk of atherosclerotic cardiovascular (CV) disease. Contributing pathophysiologic factors include endothelial dysfunction caused by excessive production of reactive oxygen species (ROS), increased activity of nuclear factor kB (NFkB), altered macrophage polarization, and reduced synthesis of endothelial progenitor cells (EPC). Consequently, there can be a potentially rapid progression of the atherosclerotic disease with a higher propensity to unstable plaque, leading to increased cardiovascular mortality. Management is aimed at prevention, early diagnosis, and treatment of hyperglycemia and vascular complications. Innovative therapeutic approaches for T2DM seek to customize the antidiabetic treatment to each patient in order to optimize glucose-lowering effects, minimize hypoglycemia and adverse effects, and prevent cardiovascular events. The newer drugs (Glucagon Like Peptide-1 Receptor Agonists, GLP-1 RAs; Sodium GLucose coTransporter-2 inhibitors, SGLT2is; DiPeptidyl Peptidase-4 inhibitors, DPP4is) impact body weight, lipid parameters, and blood pressure, as well as endothelial function, inflammatory markers, markers of oxidative stress, and subclinical atherosclerosis. The present review summarizes the results of trials that evaluated the cardiovascular safety of these drugs and found them to be safe from the CV standpoint.

The aim of this study was to examine oxidative stress and low level of alpha-1-antitrypsin (A1AT) in primary Sjögren's syndrome (pSS), and evaluate the associated autoreactivity against unmodified and their 4-hydroxy-2-nonenal (HNE)-modified peptides with pSS. Two differentially expressed proteins, alpha-1-acid glycoprotein 1 (A1AG1) and A1AT, exhibited 2-fold differences, and their HNE modifications were identified by depleted-albumin and immunoglobulin G (IgG) serum protein, in-solution digestion, in-gel digestion, and nano-LC-MS/MS from pSS patients and age-matched healthy controls (HCs). Furthermore, levels of proteins, confirmation of HNE modifications, HNE-protein adducts and autoreactivity against unmodified and their HNE-modified peptides were further validated. Levels of the HNE-protein adduct and A1AG1 were significantly higher in pSS patients than HCs, but levels of A1AT were significantly lower in pSS patients compared to HCs. Only the HNE modification of A1AT was confirmed. Further, concentrations of anti-A1AT^50-63 IgG and anti-A1AT^50-63 HNE IgA were significantly lower in pSS patients than HCs. Our study suggests that elevated HNE-protein adduct, oxidative stress, level [odds ratio (OR) 4.877, p = 0.003], lowered A1AT level (OR 3.910, p = 0.010) and a decreased level of anti-A1AT^50-63 IgG (OR 3.360, p = 0.010) showed an increased risk in pSS patients compared to HCs, respectively.

2-(Adamantan-1-yl)-2H-isoindole-1-carbonitrile (1) has been identified as a neurobiological fluorescent ligand that may be used to develop receptor and enzyme binding affinity assays. Compound 1 was synthesised using an optimised microwave irradiation reaction and crystallised from ethanol. Crystallization occurred in the orthorhombic space group P212121 with unit cell parameters: a = 6.4487(12) Å, b = 13.648(3) Å, c = 16.571(3) Å, V = 1458(5) Å3, Z = 4. Density functional theory (DFT) (B3LYP/6-311++G (d,p)) calculations of 1 were carried out. Results showed that the optimised geometry is similar to the crystal structure parameters with a root-mean-squared deviation of 0.143 Å. Frontier molecular orbital energies and net atomic charges are discussed with a focus on potential biological interactions. Docking experiments within the active site of the neuronal nitric oxide synthase (nNOS) protein crystal structure were carried out and analysed. Important binding interactions between the DFT optimised structure and amino acids within the nNOS active site were identified that explain the strong NOS binding affinity reported. Fluorescent properties of 1 were studied using aprotic solvents of different polarities. Compound 1 showed the highest fluorescence intensity in polar solvents with excitation and emission values of 336 nm and 380 nm, respectively.

A single Cancer immunotherapy has ushered in a transformative era in oncology, bringing forth unprecedented promise and opportunities. However, even with its significant breakthroughs, the domain faces the continual issue of treatment resistance. Such resistance not only restricts the broad effectiveness of these pioneering treatments but also highlights the imperative need for further research. Delving into the complex world of cancer immunotherapy resistance, we identify a range of mechanisms, from primary and secondary resistance to the notable effects of genetic and epigenetic variables, and the pivotal importance of the tumor microenvironment (TME). Additionally, we emphasize the need for innovative strategies to mitigate this resistance, including combination treatments, customized immune checkpoints, and instantaneous monitoring. By advocating for these cutting-edge methods, we foresee a direction that incorporates personalized healthcare, enhanced treatment options, and a steadfast dedication to the welfare of patients. Through a comprehensive and diverse approach, we aim to address the hurdles posed by resistance, elevating cancer immunotherapy as a symbol of hope for patients worldwide.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

The 32CA reactions of a series of pairs of bent three-atom-components (B-TACs) and linear TACs (L-TACs) towards electrophilic dicyanoethylene (DCE) have been studied within the Molecular Electron Density Theory in order to understand their different reactivity. ELF analysis indicates that while pseudodiradical B-TACs change their electronic structure to pseudoradical or carbenoid L-TACs upon dehydrogenation, zwitterionic B-TACs experience no remarkable change. Analysis of the CDFT indices indicates that five of the nine studied TACs have a strong nucleophilic character, thus participating in polar reactions towards electrophilic ethylenes. The activation energies of the 32CA reactions of the nine TACs towards electrophilic DCE range from 0.6 to 22.0 kcal·mol-1, which are by between 2.0 and 10.1 kcal·mol-1 lower than those involved in the non-polar 32CA reactions with ethylene. In general, B-TACs are more reactive than their L-TAC counterparts. A change of the regioselectivity is found in these polar 32CA reactions; in general, while B-TACs are meta regioselective, L-TACs are ortho regioselective. Analysis of the geometrical parameters indicates that at all TSs, the formation of the single bond involving the most electrophilic C4 carbon of DCE is more advanced than that involving the C5 one. A change of the asynchronicity in the reactions involving B-TACs and L-TACs is also found.

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

The open-bundle structure of cytochrome c’ as an unfolding intermediate was determined by small-angle neutron scattering experiment (SANS). The four-α-helix bundle structure of Cyt c’ at neutral pH was transited to an open-bundle structure (at pD ~13), which is a joint-clubs consisting of four clubs (α-helices) connected by short loops. The compactly folded structure of Cyt c’ (radius of gyration, Rg = 18 Å for the Cyt c’ dimer) at neutral or mildly alkaline pD transitioned to a remarkably larger “open-bundle” structure at pD ~13 (Rg = 25 Å for the Cyt c’ monomer). Cyt c’ adopts an unstructured random coil structure at pD = 1.7 (Rg = 25 Å for the Cyt c’ monomer). Numerical partial scattering function analysis (joint-clubs) and ab initio modelling gave structures similar to the “open-bundle”, which retains the α-helices but loses the bundle structure.

Easy to use satellite-based water quality visualizations are needed for monitoring and understanding coastal and inland waters, but to date, no publicly accessible real-time global visualization system was in place. Here we introduce the Ulyssys Water Quality Viewer (UWQV), a Sentinel Hub EO Browser Custom script designed for qualitative views of aquatic chlorophyll and suspended sediment concentrations. The viewer avoids unmixing of the chlorophyll and suspended sediment spectral signal by visualizing these parameters together, with high concentrations of suspended sediment obscuring chlorophyll if present. Cloud masking uses the Hollstein and Braaten algorithms (existing EO Browser custom script code), additionally water surfaces are masked using the Normalized Differential Water Index. Chlorophyll is estimated using reflectance line height-based indicators such as fluorescence line height and maximum chlorophyll index. Suspended sediment is visualized based on single-band reflectances at 620 or 700 nm. Data sources are Sentinel-2 and Sentinel-3 images, allowing either 20 m spatial resolution or up to daily imaging. This visualization system is easy to operate and interpret, and combined with the data service capacity of the Sentinel Hub, it is expected that UWQV will contribute to monitoring of remote water bodies and to our overall understanding of physical limnology and aquatic ecology.

Our environment has been significantly impacted by man-made pollutants, primarily due to industries make substantial use of synthetic chemicals, resulting in significant environmental consequences. In this research investigation, the co-precipitation approach was employed for the synthesis of cellulose-based ferric oxide (Fe₂O₃/cellulose) and copper oxide nanoparticles (CuOx-NPs). Scanning electron microscopy (SEM) analyses were conducted to determine the properties of the newly synthesised nanoparticles. Furthermore, the synthesized nanoparticles were employed for eliminating chromium from aqueous media under various conditions, including temperature, contact time, adsorbent concentration, adsorbate concentration, and pH. Additionally, the synthesised materials were used to recover Cr(VI) ions from real samples, including tap water, seawater, and industrial water, and the adsorptive capacity of both materials evaluated under optimal conditions. The synthesis of Fe₂O₃/cellulose and CuOx-NPs proved to be effective, as indicated by the outcomes of the study.

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has high infectivity in humans, attributed to the strong affinity of its spike (S) protein to human angiotensin-converting enzyme 2 (ACE2). Here, we analyzed the structural similarity of the S protein between SARS-CoV-2 and other SARS-related coronaviruses (CoVs). Methods We performed multiple alignment analysis of nine amino acid sequences of CoV S proteins from NCBI with MAFFT web-based software, followed by phylogeny analysis. Three-dimensional structure modeling was performed by SWISS-MODEL. We calculated the template modeling score between the S protein of SARS-CoV-2 and that of other SARS-related CoVs. Results The S1 domain of the unclassified CoV RaTG13 (the host of which is the intermediate horseshoe bat) was structurally very similar to that of SARS-CoV-2, implying that RaTG13 could be the origin of SARS-CoV-2. In addition, the folding property of the entire S protein was nearly the same between SARS-CoV-2 and RaTG13 after the PRRA amino acid insertion was removed from SARS-CoV-2. Conclusions RaTG13 could have a high binding affinity to ACE2, similar to SARS-CoV-2, and it is therefore highly likely to infect other animals. Therefore, massive research and monitoring of CoVs in animals is necessary to prevent future COVID-19-like disasters.

Gelephu, located in the Himalayan region, has experienced one of the strongest development activities due to the suitable topography and geographic location, which has led to rapid urbanization. The main objective of the study is to perform land use land cover (LULC) mapping for Gelephu for 2016 and 2023 by a Random Forest (RF) classifier, using the Semi-automatic Classification Plugin (SCP) in QGIS and identify LULC changes. Furthermore, the study assessed the vegetation change dynamics within the study area by analysing the Normalized Difference Vegetation Index (NDVI) for 2016 and 2023. Additionally, the study characterized the resulting LULC change for Gelephu Thromde, a sub-administrative municipal entity, as a result of the notable intensity of the infrastructure development activities. The current study used a framework to collect Sentiniel-2 satellite data, which was then used for pre- and post-processing to create LULC and NDVI maps. The classification model achieved high accuracy, with an area under the curve (AUC) of up to 0.89. The corresponding LULC and NDVI statistics were analysed to determine the current status of the LULC and vegetation indices, respectively. The LULC change analysis reveals urban growth of 5.65% and 15.05% for Gelephu and Gelephu Thromde, respectively. The NDVI assessment shows significant deterioration in vegetation health with a 75.11% loss of healthy vegetation in Gelephu between 2016 and 2023. This research provides the first version of LULC and NDVI maps of Gelephu. The analysis results indicate possible future implications on sustainable development management in Gelephu Bhutan.

In this study, we introduce a novel framework for the estimation of residual renal function (RRF), based on the population compartmental kinetic behavior of Beta 2 Microglobulin (B2M) and its dialytic removal. Using this model, we simulated a large cohort of patients with various levels of RRF receiving either conventional high-flux hemodialysis or on-line hemodiafiltration. These simulations were used to estimate a novel population kinetic (PK) equation for RRF (PK-RRF) that was validated in an external public dataset of real patients. We assessed the performance of the resulting equation(s) against their ability to estimate urea clearance using cross-validation. Our equations derived entirely from computer simulations and advanced statistical modeling, and had extremely high discrimination (AUC 0.808 – 0.909) when applied to a human dataset of measurements of RRF. A clearance-based equation that utilized pre and post dialysis B2M measurements, patient weight, treatment duration and ultrafiltration had higher discrimination than an equation previously derived in humans. Furthermore, the derived equations appeared to have higher clinical usefulness as assessed by Decision Curve Analysis, potentially supporting decisions that for individualizing dialysis frequency in patients with preserved RRF.

Inhibition of the binding of enveloped viruses surface glycoproteins to host cell receptor(s) is a major target of vaccines and constitutes an efficient strategy to block viral entry and infection of various host cells and tissues. Cellular entry usually requires fusion of the viral envelope with host plasma membranes. Such entry mechanism is often preceded by “priming” and/or “activation” steps requiring limited proteolysis of the viral surface glycoprotein to expose a fusiogenic domain for efficient membrane juxtapositions. The 9-membered family of Proprotein Convertases related to Subtilisin/Kexin (PCSK) serine proteases (PC1, PC2, Furin, PC4, PC5, PACE4, PC7, SKI-1/S1P and PCSK9) participate in post-translational cleavages and/or regulation of multiple secretory proteins. The type-I membrane-bound Furin and SKI-1/S1P are the major convertases responsible for the processing of surface glycoproteins of enveloped viruses. Stefan Kunz has considerably contributed to define the role of SKI-1/S1P in the activation of arenaviruses causing hemorrhagic fever. Furin was recently implicated in the activation of the spike S-protein of SARS-CoV-2 and Furin-inhibitors are being tested as antivirals in COVID-19. Other members of the PCSK-family are also implicated in some viral infections such as PCSK9 in Dengue. Herein, we summarize the various functions of the PCSKs and present arguments whereby their inhibition could represent a powerful arsenal to limit viral infections causing the present and future pandemics.

SARS-CoV-2 is the Coronavirus responsible for the COVID-19 pandemic. Even though we are no more in a pandemic situation, people are getting infected some of them needing hospitalization, and a few of them die. Methods: We did a retrospective study including 445 patients who accessed the Emergency Section of Policlinico Umberto I, Rome, Italy, where they had routine blood exams. In this study, we concentrated on the complete blood count, creatinine, and azotemia. The data was analyzed using ANOVA, Spearman correlation, and ROC analysis. They were divided into four groups based on their outcome: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients who after admission to the emergency section were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency section required intensive assistance); (4) the deceased group (patients that after the admission in the emergency section had a fatal outcome). Results: We found significant changes for creatinine, azotemia, hematocrit, mean corpuscular hemoglobin concentration, basophils, monocytes, red blood cell distribution width, hemoglobin, hematocrit, and red blood cell numbers by ANOVA according to their outcomes, particularly for the deceased group. Also, we found outcome correlations for eosinophils, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, lymphocyte, neutrophil, platelet, and red blood cell number and red blood cell distribution width. Conclusions: This study discloses an association between “classical” routine blood biomarkers and the severity of outcomes in Omicron patients.

Good hand hygiene has proven to be essential in reducing the uncontrolled spread of human pathogens. Cold atmospheric plasma (CAP) may provide an alternative to disinfecting hands with ethanol-based handrubs when hand washing facilities are unavailable. CAP can be safely applied to the skin if the energy is well controlled. In this study, RF and DC plasma sources was built with a pin-to-mesh electrodes configuration inside a fused silica tube of 5 mm of inner diameter. Microbiological assays based on EN 13697:2015+A1:2019 using Escherichia coli DSM 682 or Staphylococcus epidermidis DSM 20044 were used to examine the antimicrobial effect of various plasma conditions. Metal and silicone disks that model skin were used as inoculation matrices. The prototype air radio frequency (RF) CAP achieved significant disinfection in the MHz range on stainless steel and silicone substrates. This is equivalent to half the performance of direct current CAP, which is only effective on conductive substrates. Using only electricity and air CAP could, with further optimization, replace or complement current hand disinfection methods, and mitigate the economic burden of public health crises in the future.

Overhydration (OH) is a prevalent medical problem occuring in patients with kidney failure, but a specific marker has still not been found. Currently, clinicians employ techniques such as bioimpedance spectroscopy (BIS), ultrasound (US) markers of fluid overload or markers of heart and kidney function such as NT-pro-BNP, GFR or creatinine levels. New serum markers, including but not limited to Ca-125, Galectin-3 (Gal-3), Adrenomedullin (AMD) and Urocortin-2 (UCN-2), are presently under research, displaying promising results. The necessity to ascertain a more precise marker of overhydration is urgent mainly because physical examination is exceptionally imprecise. Signs and symptoms of fluid overload, like edema or gradual increase of body mass, are not always present, notably in patients with chronic kidney disease. This review paper summarizes actual knowledge of a patient's hydration status estimation, focusing specifically on kidney diseases.

Acid proteins capable of nucleating Ca2+ and displaying aggregation capacity play key roles in the formation of calcium carbonate biominerals. EF-hands are among the largest Ca2+-binding motif in proteins. Gad m 1, an Atlantic cod β-parvalbumin isoform, is a monomeric EF-hand protein that acts as a Ca2+ buffer in fish muscle and is able to form amyloids under acidic conditions. Since nucleating Ca2+ protein have a propensity to form extended β-strand structures, we wondered whether amyloid assemblies of a protein containing refolded EF-hand motifs were able to influence the in vitro calcium carbonate crystallization. Here we have used the Gad m 1 chain as model to generate monomeric and amyloid assemblies and analyze their effect on in vitro calcite formation. We found that only amyloid assemblies alter calcite morphology.

Currently, SARS-CoV-2 has evolved into various variants, including the numerous highly mutated Omicron sub-lineages, significantly increasing immune evasion ability. The development raises concerns about possibly diminished effectiveness of available vaccines and antibody-based therapeutics. Here, we describe those representative categories of broadly neutralizing antibodies (bnAbs) that retain prominent effectiveness against emerging variants including Omicron sub-lineages. The molecular characteristics, epitope conservation, and resistance mechanisms of these antibodies are further detailed, aiming to offer suggestion or direction for the development of therapeutic antibodies, and facilitate the vaccine design with broad-spectrum potential.

The COVID-19 pandemic was associated with increases in some healthcare-associated infections. We investigated the impact of the pandemic on rates and molecular epidemiology of Clostridioides difficile infection (CDI) within one VA Hospital. We anticipated that the potential widespread use of antibiotics for pneumonia during the pandemic might increase CDI rates given that antibiotics are a major risk for CDI. Hospital data on patients with CDI and recurrent CDI (rCDI) were reviewed pre-COVID-19 pandemic (2015 to 2019) and during the pandemic (2020 - 2021). Restriction endonuclease analysis (REA) strain typing was performed on CD isolates recovered from stool samples collected from 10/2019 – 3/2022. CDI case numbers declined 43.2% in 2020 – 2021 compared to the annual mean over the previous 5 years. Stool test positivity rate was also lower during the COVID-19 pandemic (14.3% vs. 17.2%; P = 0.013). Although inpatient volume declined, rates of CDI among inpatients were reduced by 34.2% in 2020 – 2021. Mean monthly cases of rCDI also declined significantly after 2020 [3.38 (95% CI: 2.89 – 3.87) vs. 1.92 (95% CI: 1.27 – 2.56); P = &lt;0.01]. Prior to the pandemic, REA group Y was the most prevalent CD strain among the major REA groups (27.3%). During the first wave of the pandemic from March 8, 2020, through June 30, 2020, there was an increase in the relative incidence of REA group BI (26.7% vs. 9.1%. After adjusting for CDI risk factors, a multivariable logistic regression model revealed that odds of developing an REA group BI CDI increased during the first pandemic wave (OR 6.41, 95% CI: 1.03 – 39.91) compared to the pre-pandemic period. In conclusion, the incidence of CDI and rCDI decreased significantly during the initial waves of the COVID-19 pandemic. In contrast, REA BI (Ribotype 027), a virulent, previously epidemic CD strain and frequently associated with hospital transmission and outbreaks, reappeared as a prevalent strain during the first wave of the pandemic.

Abstract: The purpose of this study was to understand the role of infection in the origin of chromosomal anomalies linked to neurodevelopmental disorders. In patients with neurodevelopmental disorders, DNA’s from viruses and bacteria including known teratogens were tested against chromosome anomalies known to cause the disorders. Results support a theory that parental infections disrupt elaborate multi-system gene coordination needed for neurodevelopment. Genes essential for neurons, lymphatic drainage, immunity, circulation, angiogenesis, barriers, structure, and chromatin activity were all found close together in polyfunctional clusters that were deleted in neurodevelopmental disorders. These deletions account for immune, circulatory, and structural deficits that accompany neurologic deficits. In deleted clusters, specific and repetitive human DNA matched infections and passed rigorous artifact tests. In some patients, epigenetic driver mutations were found and may be functionally equivalent to deleting a cluster or changing topologic chromatin interactions because they change access to large chromosome segments. In three families, deleted DNA sequences were associated with intellectual deficits and were not included in any database of genomic variants. These sequences were thousands of bp and unequivocally matched foreign DNAs. Analogous homologies were also found in chromosome anomalies of a recurrent neurodevelopmental disorder. Viral and bacterial DNAs that match repetitive or specific human DNA segments are thus proposed to interfere with highly active break repair during meiosis, and sometimes delete polyfunctional clusters, and disable epigenetic drivers. Mis-repaired gametes produce zygotes containing rare chromosome anomalies which cause neurologic disorders and accompanying non-neurologic signs. Neurodevelopmental disorders may be examples of assault on the human genome by foreign DNA with some infections more likely tolerated because they resemble human DNA segments. Further tests of this model await new technology.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

(1) Background: Patients with type 2 diabetes mellitus (T2DM) are at higher risk of cancer but how these two diseases associate is still debated. The goal was the assessment of the overall incidence of cancer among patients with newly diagnosed T2DM in Hungary. Summarizing, incident T2DM is associated with a significantly higher overall risk of incident cancer, with a reverse correlation of age. Newly registered T2DM patients were suggested to be screened for cancer within 6 months. (2) Methods: A nationwide, retrospective, longitudinal study was performed using a Hungarian database. The incident T2DM and diabetes free Hungarian population were included in the study. The primary endpoints were the overall and site-specific incidence and annual percentage change of the incidence of cancer in both populations. (3) Results: The overall incidence of cancer in patients amounted to 29.4/1000 and 6.6/1000 with or without T2DM, respectively, and the OR (95%CI) of cancer of the T2DM group was 4.32 (4.14-4.53), p&lt;0.0001. The risk of having cancer was age-dependent, having the highest odd in the age group 18-39. The incidence of cancer was declining in the non-diabetic but was unchanged in T2DM population. The average lag time of diagnosing a cancer after the detection of T2DM was 3.86 months.; (4) Conclusions: Iincident T2DM is associated with a significantly higher overall risk of incident cancer, with a reverse correlation of age. Newly registered T2DM patients were suggested to be screened for cancer within 6 months.

In this review, we outline our current understanding of the mechanisms involved in the absorption, storage, and transport of dietary vitamin A to the eye, the trafficking of rod opsin protein to the photoreceptor outer segments, which encompasses the logistical backbone required for visual function. Two key mechanisms of this process are emphasized in this manuscript: Ocular and systemic vitamin A membrane transporters, and rhodopsin transporters. Understanding the complementary mechanisms responsible for the generation and proper transport of the retinylidene opsin to the photoreceptor outer segment will eventually shed light on the importance of genes encoded by these proteins, and their relationship on normal visual function and in the pathophysiology of retinal degenerative diseases.

Mangrove plant seedling cultivation is crucial for the protection, management and restoration of mangrove ecosystem. In this study, we focused on Kandelia obovata, a typical mangrove, and evaluated nursery cultivation with different combinations of three salinity levels (S1: 0 ppt, S2: 10 ppt, and S3: 20 ppt), three genealogies (EZD, JX, and YZ), and five growth media (M1: 100% loess, M2: 100% sandy, M3: 50% loess + 50% sandy, M4: 40% loess + 40% sandy + 20% peat, and M5: 40% loess + 40% sandy + 20% coir), by measuring the growth parameters such as mortality rate, seedling height, diameter, and biomass partition. These growth indexes were significantly affected by salinity and medium, and genealogies also had significant effects on mortality rate and biomass accumulation. S2 or S3 both had lower mortality and higher growth indexes than S1. M1 was the medium that increased seedlings height, diameter and biomass the most and had the lowest death rate. EZD and JX were also higher levels than YZ in these indicators, but the difference between them was not obvious. S3, M1, and EZD consistently performed well in fuzzy evaluation and quality assessment. Furthermore, combinations involving these treatments also produced highly favorable results. These results furnish both a theoretical and practical foundation for advancing nursery cultivation techniques and germplasm breeding of K. obovata in mangroves.

The skeletal muscle plays a critical role in regulating systemic blood glucose homeostasis. Impaired skeletal muscle glucose homeostasis associated with type 2 diabetes mellitus (T2DM) has been observed to significantly affect the whole-body glucose homeostasis, thereby resulting in other diabetic complications. T2DM does not only affect skeletal muscle glucose homeostasis, but it also affects skeletal muscle structure and functional capacity. Given that T2DM is a global health burden, there is an urgent need to develop therapeutic medical therapies that will aid in the management of T2DM. Prediabetes is a prominent risk factor of T2DM that usually goes unnoticed in many individuals as it is an asymptomatic condition. Hence, research on prediabetes is essential because establishing diabetic biomarkers during the prediabetic state would aid in preventing the development of T2DM, as prediabetes is a reversible condition if it is detected in the early stages. Literature predominantly documents the changes in skeletal muscle during T2DM, but the changes in skeletal muscle during prediabetes remain unknown. In this review, we seek to review the existing literature on prediabetic and T2DM associated changes in skeletal muscle function.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

This research aims to find out whether the synthetic 1, 2, 4-triazine and its derivatives have antifungal effects and can protect humans from infection with Candida albicans. Molecular docking and molecular dynamic simulation are widely used in modern drug design to target a We are interested in using molecular docking and molecular dynamics modelling to investigate the interaction between the derivatives of 1, 2, 4-triazine and the resulting lanosterol 14 - demethylase (CYP51) of Candida albicans The inhibition of Candida albicans CYP51 is the main goal of our research. The 1, 2, 4-triazine and its derivatives have been docked to the CYP51 enzyme, which is involved in Candida albicans Multidrug Drug Resistance (MDR). Autodock tools were used to identifying the binding affinities of molecules against the target proteins. Compared to conventional fluconazole, the molecular docking results indicated that each drug has a high binding affinity for CYP51 proteins and forms unbound interactions and hydrogen bonds with their active residues and surrounding allosteric residues. The docking contacts were made using a 10 ns MD simulation with nine molecules. RMSD, RMSF, hydrogen bonds, and the Rg all confirm these conclusions. In addition, these compounds were expected to have a favorable pharmacological profile and low toxicity. The compounds are being offered as scaffolds for the development of new antifungal drugs and as candidates for future in vitro testing.

The Xpert® Xpress SARS-CoV-2 and Xpert® Xpress SARS-CoV-2/Flu/RSV tests were rapidly developed and widely used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. In response to emerging genetic variability, a new SARS-CoV-2 target (RNA-dependent RNA-polymerase) has been added to both tests: Xpert® Xpress CoV-2 plus and Xpert® Xpress CoV-2/Flu/RSV plus test. A rapid evaluation of both tests was performed in South Africa, using residual respiratory specimens. Residual respiratory specimens (n=125) were used to evaluate the Xpert® Xpress CoV-2 plus test and included 50 genotyped specimens. The Xpert® Xpress CoV-2/Flu/RSV plus test was assessed using 45 genotyped SARS-CoV-2 specimens, ten influenza A, ten Influenza B and twenty respiratory syncytial virus specimens. Results were com-pared to in-country standard of care tests. Genotyped specimens tested the performance of the test under pressure from circulating SARS-CoV-2 variants of concern. Reference material was included to assess the test limits and linearity. The Xpert® Xpress CoV-2 plus test performance compared to reference results across residual respiratory specimens was good (positive per-centage agreement (PPA)=95.2%, negative percentage agreement (NPA)=95.0%) The Xpert® Xpress CoV-2/Flu/RSV plus test showed good performance across all residual respiratory specimens (PPA=100%, NPA=98.3%). All genotyped variants of concern were detected by both tests. The Xpert® Xpress CoV-2 plus and Xpert® Xpress CoV-2/Flu/RSV plus tests can be used to diagnose SARS-CoV-2, and to diagnose and differentiate SARS-CoV-2, influenza A, influenza B and respiratory syncytial virus respectively. The NPA was lower than the recommended 99%, but was influenced by the low number of negative specimens tested. The variants of concern assessed did not affect test performance. It is recommended that sites perform their own assessments compared to in-country standard of care tests.

Mitochondrial pyruvate dehydrogenase complex (PDHC) is essential for the brain glucose and neurotransmitter metabolism, dysregulated in many pathologies. Using specific inhibitors of PDHC in vivo, we determine biochemical and physiological responses to PDHC dysfunction. Dose dependence of the responses to membrane-permeable dimethyl acetylphosphonate (Ac-PMe2) is non-monotonous. Primary decreases in glutathione and its redox potential, methionine and ethanolamine are alleviated with increasing PDHC inhibition, the alleviation accompanied by physiological changes. Comparison of 39 brain biochemical parameters after administration of four phosphinate and phosphonate analogs of pyruvate at a fixed dose of 0.1 mmol/kg reveals no primary, but the secondary changes, such as activation of 2-oxoglutarate dehydrogenase complex (OGDHC) and decreased levels of glutamate, isoleucine and leucine. The accompanying decreases in RMSSD of ECG and freezing time are most pronounced after administration of me-thyl acetylphosphinate and dimethyl acetylphosphonate. The levels of PDHA1 expression and phosphorylation, sirtuin 3 and total protein acetylation are not significantly changed by the PDHC inhibitors that affect the brain protein succinylation and glutarylation. Thus, decreased production of the tricarboxylic acid cycle substrate acetyl-CoA by inhibited PDHC is compen-sated by increased degradation of amino acids through the cycle with activated OGDHC, increas-ing total protein succinylation and decreasing anxiety indicators.

Praeruptorin A(PA), a naturally existing pyranocumarin, is isolated from the dried root of Peucedanum praeruptorum Dunn. So far the anti-cancer effect and molecular mechanism behind Praeruptorin A action in human cervical cancer HeLa cells remain unknown. In the present study, we find that PA reduces cell proliferation and colony formation of human cervical cancer HeLa cells through inducing cell cycle arrest at G0/G1 phase. PA-upregulated p21 and p27 proteins are observed, accompanied with inhibition of cyclin D1 and S-phase kinase-associated protein 2(Skp2) proteins expression. PA could significantly inhibit migration and invasion of human HeLa cells. Meanwhile, PA significantly reduces invasive protein expression of matrix metalloproteinase-2 (MMP-2), and increases protein expression of tissue inhibitor of metalloproteinase-2 (TIMP-2). PA is observed to possess the capacity in suppressing ERK1/2 activation. PD98059 (ERK specific inhibitor) significantly enhances PA-induced downregulation of MMP-2 expression, and upregulation of TIMP-2 expression. Moreover, we found that PA treatment notably inhibits 12-O-tetradecanoylphorbol-13-acetate(TPA)-upregulated ERK1/2 activation, MMP-2 expression, cellular migration and invasion in human HeLa cells. Taken together, these findings are the first to demonstrate the anti-cancer activity of PA, which may act as a promising therapeutic agent for the treatment of human cervical cancer.

O26 enteropathogenic Escherichia coli (EPEC), possesses a unique pseudocapsule composed of polysaccharides identical to the O antigen in their lipopolysaccharide (LPS) membrane. Therefore, the impact of O26 polysaccharides on the immune evasion mechanisms of capsulated O26 EPEC was investigated. Our findings reveal that the concentration of GlcNAc, an immunodominant unit of O26 polysaccharides capable of activating the MBL (Mannose Biding Lecting) pathway of the complement system, was found to be lower in capsulated EPEC O26 compared to naked shiga toxin-producing E. coli (STEC) O26 strain. It was noted that, unlike the naked STEC strain, the capsulated EPEC O26 strain was protected against lysis by the alternative pathway of the com-plement system by inhibiting C3b adhesion to its bacterial surface. Capsulated EPEC O26 strains were also able to avoid phagocytosis by macrophages. However, the immune evasion provided by the capsule was overcome in the presence of anti-O26 polysaccharide antibodies. Additionally, these antibodies were able to recognize O26 EPEC in the presence of biofilm and inhibit their adhesion to human epithelial cells. Overall, the results indicate that the O26 polysaccharides can generate an effective humoral immune response, making them promising antigens for the de-velopment of a vaccine against capsulated O26 E. coli

SARS-CoV-2, the novel coronavirus behind COVID-19 pandemic is acquiring new mutations in its genome. Although some mutations provide benefits to the virus against human immune response, a number of them may result in their reduced pathogenicity and virulence. By analyzing more than 3000 high-coverage, complete genome sequences deposited in the GISAID database, here I report a unique 28881-28883:GGG>AAC trinucleotide-bloc mutation in the SARS-CoV-2 genome that results in two sub-strains, described here as SARS-CoV-2g (28881-28883:GGG genotype) and SARS-CoV-2a (28881-28883:AAC genotype). Computational analysis and literature review suggest that this bloc mutation would bring 203-204:RG(arginine-glycine)>KR(lysine-arginine) amino acid changes in the nucleocapsid (N) protein affecting the SR (serine-arginine)-rich motif of the protein, a critical region for the transcription of viral RNA and replication of the virus. Thus, 28881-28883:GGG>AAC bloc-mutation is expected to modulate the pathogenicity of the SARS-CoV-2. Remarkably, SARS-CoV-2g and SARS-CoV-2a strains can be linked with the heterogeneity of COVID-19 cases across different regions within and between countries by analyzing existing data. Sequence analysis suggests that severely affected cities, such as Milan, Lombardy, New York, Paris have the predominant presence of SARS-CoV-2g strains, whereas less affected places like Abruzzo, Lyon, Valencia have a relatively higher presence of SARS-CoV-2a, an indication that the latter strain may contribute to the reduced cases of COVID-19. A similar relationship is observed when Netherlands, Portugal are compared with Spain, France and Germany. These analyses suggest that the SARS-CoV-2 has already evolved into a less infective SARS-CoV-2a affecting COVID-19 cases in different regions. The time a country or region needs to acquire SARS-CoV-2a strains may be indicative to the time it would need to overcome the peak of the COVID-19 cases. To confirm these assumptions, prompt retrospective and prospective epidemiological studies should be conducted in different countries to understand the course of pathogenicity of the SARS-CoV-2a and SARS-CoV-2g. Potential drugs can be designed targeting 28881-28883 region of the N protein to modulate virus pathogenicity.

The endocannabinoid system has been found to be pervasive in mammalian species. It has also been described in invertebrate species primitive as the Hydra. Insects apparently are devoid of this otherwise ubiquitous system that provides homeostatic balance to the nervous and immune systems, as well as many other organ systems. The endocannabinoid system (ECS) has been defined to consist of three parts: 1. Endogenous ligands, 2. G-protein coupled receptors (GPCRs), and 3. Enzymes to degrade and recycle the ligands. Two endogenous molecules have been identified as ligands in the ECS to date. These are the endocannabinoids: Anandamide (arachidonoyl ethanolamide) and 2-AG (2-arachidonoyl glycerol). Two G-coupled protein receptors have been described as part of this system, with other putative GPC being considered. Coincidentally, the phytochemicals produced in large quantities by the Cannabis sativa L plant, and in lesser amounts by other plants, can interact with this system as ligands. These plant-based cannabinoids are termed, phytocannabinoids. The precise determination of the distribution of cannabinoid receptors in animal species is an ongoing project, with the canine cannabinoid receptor distribution currently receiving the most interest in non-human animals.

In addition to nucleic acids, various viral proteins are involved in the assembly of virion. If it is possible to create a biologically active agent that leads to the degradation of one of the key proteins for virus assembly and/or destroys the viral factory, then this agent will effectively cope with virus replication. One of these key proteins for the SARS-CoV-2 virus is the nucleocapsid protein (N-protein). As such a bioactive agent, we offer a modular nanotransporter (MNT) developed by us, which, in addition to an antibody mimetic to the N-protein, contains an amino acid sequence for the attraction of the Keap1 E3 ubiquitin ligase. This should lead to the subsequent degradation of the N-protein. We have shown that functional properties of modules within the MNT permit its internalization into target cells, endosome escape into the cytosol, and binding to the N-protein. Using flow cytometry and Western blot, it was demonstrated that significant degradation of N-protein is observed when A549 and A431 cells transformed with N-protein are incubated with the developed MNTs. The proposed MNTs open up a new approach for the treatment of viral diseases.

In patients with schizophrenia, metabolic syndrome is associated with cognitive impairments. We carried out a second analysis of data from a longitudinal trial to examine the relationship between weight gain and cognitive function in patients with first-episode schizophrenia (FES) over the first 6-month antipsychotic treatment. Baseline and 6-month endpoint measurements were taken for both cognitive function and body weight. Linear and logistic regression analyses were applied to investigate the bidirectional relationship between weight gain and cognitive function. Clinically relevant weight gain (CRW) was defined as an increase in body weight ex-ceeding 7%. The final analysis included 337 participants. Lower baseline scores in processing speed (OR=0.837, p=0.007), working memory and attention (OR=0.889, p=0.043), and executive function (OR=0.863, p=0.006) domains were significantly associated with CRW at the 6-month endpoint. After adjusting for confounders, CRW was found to be associated with improvement in the Brief Visuospatial Memory Test (p=0.036). The findings suggest that patients with lower baseline cognitive performance experienced more substantial weight gain. Conversely, weight gain was correlated with cognitive improvements, particularly in the domain of visual learning and memory. This suggested a potential bidirectional relationship between weight gain and cog-nitive function in patients with first-episode schizophrenia.

2-(5,6-diphenyl-1,2,4-triazin-3-yl)pyridinium dichloroiodate (I) (1) was synthesized by reacting 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine with ICl in dichloromethane solution. The structural characterization of 1 by SC-XRD analysis was accompanied by elemental analysis, FT-IR, and FT-Raman spectroscopy measurements.

Leucine-rich α-2 glycoprotein1 (LRG1) is a member of the leucine-rich repeat (LRR) family that was implicated in multiple diseases including cancer, aging and heart failure as well as diabetes and obesity. LRG1 plays a key role in diet-induced hepatosteatosis and insulin resistance by mediating the crosstalk between adipocytes and hepatocytes. LRG1 also promotes hepatosteatosis by upregulating de novo lipogenesis in the liver and suppressing fatty acid β oxidation. In this study, we investigated the association of LRG1 with obesity markers including leptin and other adipokines in adolescents (11-14 years; n=425). BMI-for-age classification based on WHO growth charts was used to define obesity. Plasma LRG1 was measured by ELISA while other markers were measured by multiplexing assay. Median (IQR) of LRG1 levels was higher in obese [30 (25, 38) µg/mL] and overweight [30 (24, 39) µg/mL] adolescents, compared to normal-weight participants [27 (22, 35) µg/mL]. The highest tertile of LRG1 had an OR [95%CI] of 2.55 [1.44, 4.53] for obesity. LRG1 was positively correlated to plasma levels of HsCRP (R=0.2), Leptin (R=0.2) and Chemerin (R=0.24) with p<0.001. Additionally, it was positively associated with plasma level of IL6 (R=0.17) and IL10 (R=0.14) but not TNF-α. In conclusion, LRG1 levels are increased in obese kids and associate with increased levels of adipogenic markers. These results suggest the usefulness of LRG1 as an early biomarker for obesity and its related pathologies in adolescents.

Immune checkpoint inhibitors (ICIs), including anti-programmed cell death 1 ligand 1 (PD-L1) antibodies, are significantly changing treatment strategies for human malignant diseases including oral cancer. Cancer cells usually escape from immune system and acquire proliferative capacity and invasive/metastatic potential. We have focused on the two immune checkpoints, PD-1/PD-L1 and CD47/SIRPα in the tumor microenvironment of oral squamous cell carcinoma (OSCC), and performed a retrospective analysis of the expression of seven immune-related factors (PD-L1, PD-1, CD4, CD8, CD47, CD56 and CD11c), and examined their correlation with clinicopathological status. As a result, there were no significant findings relating seven immune-related factors and several clinicopathological statuses. However, the immune-checkpoint related factors (PD-1, PD-L1, CD47) were highly expressed in non-keratinized epithelium-originated tumors when compared to those in keratinized epithelium-originated tumors. It is of interest that immunoediting via immune checkpoint-related factors was facilitated in non-keratinized sites. Several researchers reported that keratinization of oral mucosal epithelia affected the immune response, but our present finding is the first study to show a difference of the tumor immunity in the originating-epithelium of OSCC, keratinized or non-keratinized. Tumor immunity, an immune escape status of OSCC might be different in the originating-epithelium, keratinized or non-keratinized.

The co-circulation of duck hepatitis A virus subtypes 1 (DHAV-1) and 3 (DHAV-3) in ducklings has resulted in significant economic losses. Because ducklings infected with DHAV-1 or DHAV-3 show similar clinical signs and gross lesions, it is important to discriminate these subtypes as early as possible for better clinical management. On the basis of multiple alignments of the 5′-noncoding region sequences of strains DHAV-1 and DHAV-3, universal and type-specific primers were designed and synthesized. Using the primers in a one-tube reverse transcription-PCR (RT-PCR) assay, reference strains of DHAV-1 and DHAV-3 (isolated over a span of 60 years and covering many different countries) were successfully amplified, indicating that the primer sequences were completely conserved. The amplicon sequences results and the sizes of amplicons from reference DHAV-1 and DHAV-3 isolates correlated completely with their genotypes. Moreover, with this one-tube RT-PCR system, the amplicon sizes of liver samples of reference DHAV-1- or DHAV-3-infected birds matched perfectly with their respective genotypes, as determined by virus isolation and neutralization tests. No other RNA viruses of duck origin were detected with the synthesized primers. The sensitivity of viral RNA detection was 10 pg. With this system, 20% genotype 1, 45% genotype 3, and 9% co-infection of the two genotypes were detected in 55 clinical samples. This novel approach could be used for the rapid genotyping DHAV-1 and/or DHAV-3 infection in routine clinical surveillance or epidemiologic screening.

Gastric inflammation-related disorders are commonly observed digestive system illnesses char-acterized by the activation of proinflammatory cytokines, particularly tumor necrosis factor-α (TNF-α). This results in the induction of cyclooxygenase-2 (COX-2)/prostaglandin E2 (PEG2) and matrix metallopeptidase-9 (MMP-9). These factors contribute to the pathogenesis of gastric in-flammation disorders. We examined the preventive effects of Lonicera japonica Thunb. ethanol ex-tract (Lj-EtOH) on gastric inflammation induced by TNF-α in normal GES-1 cells. The GES-1 cell line was used to establish a model that simulated the overexpression of COX-2/PGE2 and MMP-9 proteins induced by TNF-α, to examine the anti-inflammatory properties of Lj extracts. The re-sults indicated that Lj-EtOH exhibits significant inhibitory effects on COX-2/PEG2 and MMP-9 ac-tivity, attenuates cell migration, and provides protection against TNF-α-induced gastric inflam-mation. The protective effects of Lj-EtOH are associated with the modulation of COX-2/PEG2 and MMP-9 through activation of TNFR–ERK 1/2 signaling pathways as well as the involvement of c-Fos and nuclear factor kappa B (NF-κB) signaling pathways. Based on our findings, Lj-EtOH ex-hibits a preventive effect on human gastric epithelial cells. Consequently, it may represent a novel treatment for the management of gastric inflammation.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) utilizes Angiotensin Converting Enzyme 2 (ACE2) as its main receptor for cell entry. We have bioengineered a soluble ACE2 protein termed ACE2 618-DDC-ABD that has increased binding to SARS-CoV-2 and prolonged duration of action. Here we investigated the protective effect of this protein when administered intranasally to k18-hACE2 mice infected with the aggressive SARS-CoV-2 delta variant. k18-hACE2 mice were infected with the SARS-CoV-2 delta variant by inoculation of a lethal dose (2x104 PFU) and followed for up to 14 days. ACE2-618-DDC-ABD (10mg/kg) or PBS was administered intranasally six hours prior and 24 and 48 hours post viral inoculation. All animals in the PBS-control group had succumbed to the disease on day 7 post infection (0% survival) whereas, by contrast, there was only one casualty in the group that received ACE2-618-DDC-ABD (90% survival). Mice in the ACE2-618-DDC-ABD group had minimal disease as assessed by a clinical score and stable weight and both brain and lung viral titers were markedly reduced. These findings demonstrate the efficacy of a bioengineered soluble ACE2 decoy with extended duration of action in protecting against the aggressive delta SARS-CoV-2 variant. Together with previous work these findings demonstrate the universal protective potential against current and future emerging SARS-CoV-2 variants.

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

Tdp1 and Tdp2 are DNA repair enzymes that repair DNA damages caused by various agents, including anticancer drugs. Thus, these enzymes resist anticancer therapy and could be the reasons of resistance to such widely used drugs as topotecan and etoposide. In the present work, we found compounds capable of inhibiting both enzymes among derivatives of (-)-usnic acid. Both (+)- and (-)-enantiomers of compounds act equally effectively against Tdp1, and only (-)-enantiomers inhibited Tdp2. Surprisingly, the compounds protect HEK293FT wild type cells from the cytotoxic effect of etoposide but potentiate it against Tdp2 knockout cells. We assume that the sensitizing effect of the compounds in the absence of Tdp2 is associated with effective inhibition of Tdp1, which could take over the functions of Tdp2.

We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.

The ceramic sherds from approximately 20 samples of lead-glazed tableware, recovered from diverse archaeological sites, including three repurposed storage pits transformed into dumpsters within the medieval city of Santarém (13th-14th century), underwent a meticulous examination. This investigation utilized techniques such as micro-Raman, ground state diffuse reflectance absorption, and X-ray fluorescence spectroscopies, in addition to X-ray diffraction and stereomicroscopy. A parallel study was conducted on contemporaneous European ceramics (glazed sherds) sourced from archaeological sites dating back to the 13th-15th centuries in Saintonge (France), Ardenne, Zomergem, and Bruges (Belgium), as well as Surrey-Hampshire, Kingston, and Cheam (England). The colour of the ceramic bodies is predominantly white or whitish, with a few exhibiting a vivid red hue. Ceramic sherds with a light paste composition were likely crafted using kaolin clays as raw materials. Analyses of fabric, mineralogical, and elemental composition of the sherds suggest that the majority of Santarém's glazed ceramics were locally or regionally produced, potentially derived from a Pliocene kaolin-rich sand formation. However, this conclusion is not supported by the absence of discovered lead glaze kilns or workshops in Santarém for the late Middle Ages. A distinctive feature from the European workshop ceramics lies in the quartz temper content and fabric.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause potentially life-threatening coronavirus disease (COVID-19). COVID-19 is a multisystem disease and is associated with significant respiratory distress, systemic hyper inflammation, vasculitis and multi-organ failures. SARS-CoV-2 causes deterioration of numerous systems with increasing evidence implying that COVID-19 affects endothelium and vascular function. The endothelium is important for preserving vascular tone and homeostasis. The overactivation and dysfunction of endothelial cells are significant outcomes of severity in patients with COVID-19. The Angiopoietin 1/Tie 2 pathway plays an important role in endothelium quiescence and vessel stability. The disruption of Angiopoietins/Tie balance affects vessel contact barrier and leads to vessel leakage, and this in turn causes endothelial dysfunction. Although vascular instability through SARS-CoV-2 is associated with endothelial dysfunction, it is still not understood if the virus affects Angiopoietin/Tie axis directly or via other mechanisms such as cytokine storm and/or immune response associated with the infection. This review provides an overview of the impact SARS-CoV-2 has on endothelial function and more specifically the Angiopoietin/Tie pathway.

Digital Elevation Model (DEM) is a representation of elevation data that represent terrain with or without overlaying objects of the Earth. It is the ideal and most widely used method for determining topography. DEMs are generated from various techniques such as traditional Surveying, Photogrammetry, InSAR, LiDAR, Clinometry and radargrammetry. It has been observed that mostly LiDAR-generated DEMs provide the best accuracy. The unavailability of LiDAR data in most of the region restricts global researchers from high-resolution and accurate DEMs. The recent launch of ICESat-2 with a 13m beam footprint and 0.7m pulse interval, promises elevations at high orbital precision. Its accuracy is of the order of few centimeters in complex topography, because of this ICESat-2 proves to be a good source to generate high-accuracy DEMs. ICESat-2 provides discrete photon data with elevations of points on the Earth’s surface. Traditional interpolation techniques tend to over-smooth the estimated space and still are unable to justify the complicated continuity in the topographical data. Machine learning algorithms are widely being used to extract patterns and spatial extent in geographic data. To estimate a DEM from ICESat-2 LiDAR point data, machine learning regression algorithms are implemented in this study. The present study has been performed for a plain region of Ghaziabad, Uttar Pradesh, India. Studies have shown that Cartosat-1 DEM V3 R1 product provides an accuracy of the order of 2m in predominantly plain regions, hence taken for this region. Current work focuses on comparing various regression-based machine-learning techniques to interpolate DEM from ICESat-2 data The RMSE of the interpolated DEM resulted from the Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, and Multi-Layer Perceptron Regressor was 7.13m, 7.01m, 7.15m, and 3.76m, respectively when evaluated against the TANDEM-X DEM of the same region. The MLP Regressor is found to perform the best among the four algorithms tested.

The epithelial cell tight junction structure is the site of the transepithelial movement of solutes and water between epithelial cells (paracellular permeability). Paracellular permeability can be divided into two distinct pathways, the Pore Pathway mediating the movement of small ions and solutes and the Leak Pathway mediating the movement of large solutes. Claudin proteins form the basic paracellular permeability barrier and mediate the movement of small ions and solutes via the Pore Pathway. The Leak Pathway remains less understood. Several proteins have been implicated in mediating the Leak Pathway, including occludin, ZO proteins, tricellulin, and actin filaments, but the proteins comprising the Leak Pathway remain unresolved. The properties of the Leak Pathway, such as its molecular mechanism, its regulation, and whether or not it has a size limit, remain controversial. This review will trace the evolution of the Leak Pathway concept from its origins, will discuss the current information about the properties of the Leak Pathway, and will discuss recent research suggesting a possible molecular basis for the Leak Pathway. Based on these findings, we propose a model for the molecular mechanism underlying the Leak Pathway and its regulation.

We developed some questions regarding twin prime conjecture by examining the bounded gaps between composite numbers and explained the relations between the formulas regarding composite numbers. Then we proved the twin prime conjecture to answer the new questions raised by proving the expression: \[ \liminf_{n\to\infty} (c_n_+_1 - c_n) \ge 10. \] In addition, we prove many different approaches have been and it has been proved that there must be a twin prime in the range $(p_k_2\cdot p_k_1, p^2_k_1)$, where $p \neq 2$.

For each non-prime odd number as F=pq , if we consider m/n as an approximation for q/p and choose k=mn , then by proving some lemmas and theorems, we can compute the values of m and n. Finally, by using Fermat’s factorization method for F and 4kF as difference of two non-consecutive natural numbers, we should be able to find the values of p and q. Then we introduce two new and powerful sieves for separating composite numbers from prime numbers.

Executive functioning is a key component involved in many of the processes necessary for effective weight management behavior change (e.g., setting goals). Cognitive behavioral therapy (CBT) and third-wave CBT (e.g., mindfulness) are considered first-line treatments for obesity, but it is unknown to what extent they can improve or sustain executive functioning. This pilot randomized controlled trial examined if a CBT-based generalized weight management intervention would affect executive functioning and executive function-related brain activity in individuals with obesity or overweight. Participants were randomized to an intervention condition (N=24) that received the Noom Weight program or to a control group (N=26) receiving weekly educational newsletters. EEG measurements were taken during Flanker, Stroop, and N-back tasks at baseline and months 1 through 4. After 4 months, the intervention condition evidenced greater accuracy over time and, to some extent, neural markers of executive function (error-related negativity and beta and gamma band powers) compared to the control group on the Flanker and Stroop tasks. The intervention condition also lost more weight than controls (-7.1 pounds vs. +1.0 pounds). Given mixed evidence on whether CBT-based interventions can change markers of executive function, this study contributes preliminary evidence that a multicomponent CBT-based weight management intervention (i.e., that provide both support for weight management and is based on CBT) can help individuals sustain executive function compared to controls.

The main aim of this study was to determine the prevalence of plasmid-mediated colistin resistance mcr-1 to mcr-5 genes among colistin and multi-drug resistant Enterobacterales, Pseudomonas aeruginosa and Acinetobacter sp strains isolated from patients in a tertiary hospital in the city of Toluca, Mexico. 241 strains were included in the study. The presence of mcr genes among these strains was assessed by PCR and sequencing. In the case of mcr-carrying E. coli, further PCR tests were performed to determine the presence of blaCTX-M and whether the strains belonged to the O25b-ST131 clone. Conjugation experiments were carried to assess plasmid-mediated colistin resistance horizontal transmission. 12 strains (5.0%), of which four were E. coli; four, P. aeruginosa; three, K. pneumoniae and one, E. cloacae, were found to be resistant to colistin. Of these strains, two E. coli isolates were found to carry mcr-1. Both mcr-1-carrying E. coli strains were found to co-express blaCTX-M, belong to the O25b-ST131 clone and horizontally transmit their colistin resistance. The results of this study confirm the presence of plasmid-mediated colistin resistance in hospitalized patients in Mexico and demonstrated that the multidrug-resistant O25b-ST131 E. coli clone can acquire mcr genes and transmit such resistance trait to other bacteria.

The theories of quantum mechanics and relativity dramatically altered our understanding of the universe ushering in the era of modern physics. Quantum theory deals with objects probabilistically at small scales, whereas relativity deals classically with motion in space and time. We show here that the mathematical structures of quantum theory and of relativity follow together from pure thought, defined and uniquely constrained by the same elementary ``combining and sequencing'' symmetries that underlie standard arithmetic and probability. The key is uncertainty, which inevitably accompanies observation of quantity and imposes the use of pairs of numbers. The symmetries then lead directly to the use of complex \sqrt{-1} arithmetic, the standard calculus of quantum mechanics, and the Lorentz transformations of relativistic spacetime. One dimension of time and three dimensions of space are thus derived as the profound and inevitable framework of physics.

In the last decade, an increasing awareness was directed to the role of Vitamin D in non-skeletal and preventive roles for chronic diseases. Vitamin D is a key hormone involved in the regulation of calcium/phosphorous balance and it has been implicated in the pathogenesis of inflammation, insulin resistance and obesity. Cholecalciferol (Vitamin D3) and Ergocalciferol (Vitamin D2) are the main form of vitamin D: the active form (1,25-dihydroxyvitamin D) is the result of two hydroxylations that take place in liver, kidney, pancreas and immune cells. Some anti-inflammatory cytokines are produced at higher levels by vitamin D, while some pro-inflammatory cytokines are released at lower levels. Toll-Like Receptor (TLR) expression is increased and a pro-inflammatory state is also linked to low levels of vitamin D. Regardless of how it affects inflammation, various pathways suggest that vitamin D directly improves insulin sensitivity and secretion. The level of vitamin D in the body may change the ratio of pro- to anti-inflammatory cytokines, which would impact insulin action, lipid metabolism, and the development and function of adipose tissue. Many studies have demonstrated an inverse relationship between vitamin D concentrations and pro-inflammatory markers, insulin resistance, glucose intolerance, metabolic syndrome, obesity and cardiovascular disease. It's interesting to note that several long-term studies also revealed an inverse correlation between vitamin D level and the occurrence of diabetes mellitus. Vitamin D supplementation in people has controversial effects, in fact while some studies demonstrated improvements in insulin sensitivity, glucose and lipid metabolism, others revealed no significant effect on glycemic control and inflammation. The aim of this review is to provide insight into the molecular basis of the relationship between vitamin D, insulin-resistance, metabolic syndrome, type 1 and 2 diabetes, gestational diabetes, and cardiovascular diseases.

Apoptosis, also known as the programmed death of cells, is responsible for maintaining the homeostasis of tissues and this function is carried out by caspases. The process of apoptosis is carried out via two distinct pathways: the extrinsic pathway, which is governed by death receptors, and the intrinsic pathway, also known as the mitochondrial pathway. The BCL-2 protein family encoded by the BCL-2 gene, located at the 18q21.33 chromosomal location, is in charge of regulating the intrinsic pathway, which is responsible for inducing cell death via the permeabilization of the mitochondrial membrane and the release of apoptosis - inducing components. The BCL-2 homology (BH1, BH2, BH3, BH4) domains of this family proteins are crucial for their functioning and their common BH domains allow interactions between members of the same family and can also serve as indications of pro- or anti-apoptotic activity. A direct correlation may be shown between the overexpression of BCL-2 and the postponement of cell death. It has been determined that a change in the expression of BCL-2 is the root cause of a variety of malignancies, including lung, breast, melanoma, and chronic lymphocytic leukemia, Multiple Sclerosis, Diabetes. In this review, we discuss the therapeutic potential of regulating BCL-2 family connections and their relevance to health and disease.

Infectious as well as most non-infectious diseases share certain common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors, produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, they produce metabolic alterations that influence the pathogenesis of the disease. In this review we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, which induces migration and infiltration of immune cells in target tissues, and is involved in disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.

Recent advancements in artificial intelligence (AI) and deep learning have revolutionized the field of protein engineering, particularly in the area of de novo protein design. This review article explores the impact of AI-driven approaches on protein design, with a specific focus on the role of structure prediction neural networks, such as AlphaFold and RoseTTAFold. The article discusses the paradigm shift brought about by these networks, which have enabled the design of proteins with unique structures and functions that are not found in nature. The review covers various aspects of AI-driven protein design, including the use of protein language models to harness evolutionary information, the development of de novo protein design workflows utilizing deep learning, and the application of generative models like RFdiffusion and RoseTTAFold All-Atom. The article also highlights the successes and applications of AI-driven protein design across diverse domains, such as enzyme engineering, antibody design, and vaccine development. Additionally, the review identifies current challenges and future directions in the field, emphasizing the need to address limitations in modeling conformational dynamics and designing proteins for in vivo functionality. The article concludes by underscoring the potential of AI-driven protein design to transform various aspects of science and technology, while also acknowledging the importance of interdisciplinary collaboration and the development of robust pipelines for the validation and optimization of designed proteins. Overall, this comprehensive review serves as a valuable resource for researchers and practitioners interested in understanding the current state and future prospects of AI-driven protein design.

The pathogenesis of coronavirus disease 2019 (COVID-19) is associated with a hyperinflammatory response. The mechanisms of SARS-CoV-2-induced inflammation are scantly known. Methylglyoxal (MG) is a glycolysis-derived by-product, endowed with a potent glycating action, leading to the formation of advanced glycation end products (AGEs), the major of which is MG-H1. MG-H1 exerts strong pro-inflammatory effects, frequently mediated by the receptor for AGEs (RAGE). Here, we investigated the involvement of MG-H1/RAGE axis as a potential novel mechanism in SARS-CoV-2-induced inflammation by resorting to human bronchial (BEAS-2B) and alveolar (A549) epithelial cells, expressing different levels of ACE2 receptor (R), exposed to SARS-CoV-2 spike protein 1 (S1). Interestingly, we found in BEAS-2B cells that do not express ACE2-R, that S1 exerted a pro-inflammatory action through a novel MG-H1/RAGE-based pathway. RAGE expression levels in nasopharyngeal swabs from SARS-Cov-2 positive and negative individuals, as well as glyoxalase 1 expression, the major scavenging enzyme of MG, seem to support the results obtained in vitro. Altogether, our findings reveal a novel mechanism involved in the inflammation triggered by S1, paving the way to the study of MG-H1/RAGE inflammatory axis in SARS-CoV-2 infection as a potential therapeutic target to mitigate COVID-19 associated pathogenic inflammation.

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

Regulation (EU) No 305/2011 lays down harmonized conditions for marketing construction products in the European Union. One of its consequences has been the introduction of the product standard EN 50575 and standard EN 130501-6, concerning power, control, and communication cables permanently installed in buildings to prevent the risk of a fire and its consequences. EN 13501-6 provides the reaction to fire classifications for cables, the test methods to be performed, the requirements to meet a specific reaction to fire, and additional classifications for smoke production, flaming droplets, and acidity. EN 60754-2 is the technical standard used to assess acidity, and it defines three classes: a1, a2, and a3 (the less performant), based on pH and conductivity measurements. Due to the release of hydrogen chloride during the combustion, acidity is the weak point of PVC cables, which are not yet capable of achieving the a1 or a2 classes required in specific locations according to a fire risk assessment. EN 13501-6 does not include EN 60754-1. Both EN 60754-1 and EN 60754-2 are common standards for determining halogen gas content, acidity, and conductivity, respectively. They involve the same type of tube furnace but with different heating regimes, final temperatures, and detection methods. EN 60754-2 must be performed at temperatures between 935 – 965 °C. The paper demonstrates that, when EN 60754-2 is carried out with the thermal profile of EN 60754-1 or at 500 °C in isothermal conditions, the evolution of hydrogen chloride changes significantly if potent acid scavengers are utilized in the PVC compounds. The reason lies behind the kinetic of hydrogen chloride release during the combustion of PVC compounds: the higher the temperature or faster the heat release, the quicker hydrogen chloride evolution and the lower the probability for the acid scavenger to trap it. That further highlights the "fragility" of EN 60754-2 as a tool for assessing the risks associated with the release of hydrogen chloride in case of fire

Estrogen decline during menopause is associated with altered metabolism, weight gain and increased risk for cardiometabolic diseases. The gut microbiota also plays a role in the development of cardiometabolic dysfunction and is also subject to changes associated with age-related hormone changes. Phytoestrogens are plant-based estrogen mimics that have gained popularity as dietary supplements for treatment or prevention of menopause-related symptoms. These compounds have the potential to both modulate and to be metabolized by the gut microbiota. Hops (Humulus lupulus L.) contain potent phytoestrogen precursors, which rely on microbial biotransformation in the gut to estrogenic forms. We supplemented ovariectomized (OVX) or sham-operated (SHAM) C57BL/6 mice, with oral estradiol (E2), a flavonoid-rich extract from hops, or a placebo carrier oil to observe effects on adiposity, inflammation, and gut bacteria composition. Hops extract and E2 protected against increased visceral adiposity and liver triglyceride accumulation in OVX animals. Surprisingly, we found no evidence of OVX having a significant impact on the overall gut bacterial community structure. We did find differences in abundance of Akkermansia muciniphila, which was lower with HE treatment relative to the OVX E2 treatment and to placebo in the SHAM group.

This paper presents a proposal for a non-isolated bidirectional converter (NIBC) controlled by a deep neural network (DNN) to enable vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G) charging, which contributes to the development of more efficient and sustainable transportation and energy systems. The DNN controller manages power flow in both directions, making it possible to charge electric vehicles (EVs) and discharge power from EVs to the grid with improved efficiency and performance compared to traditional control methods. The non-isolated topology used in this proposal offers several benefits, including reduced cost, smaller size, and higher efficiency. To train the DNN controller, a large dataset of simulations was used, and the results were validated with a hardware setup. The real-time performance of the DNN controller was compared to a proportional-integral (PI) based controller through simulated results. The findings of the study show that the DNN controller outperforms traditional PI controllers.

Viral infections, such as those caused by Herpes Simplex Virus-1 (HSV-1) and SARS-CoV-2, affect millions of people each year. However, there are few antiviral drugs that can effectively treat these infections. The standard approach in the development of antiviral drugs involves the identification of a unique viral target, followed by the design of an agent that addresses that target. Antimicrobial peptides (AMPs) represent a novel source of potential antiviral drugs. AMPs have been shown to inactivate numerous different enveloped viruses through the disruption of their viral envelopes. However, the clinical development of AMPs as antimicrobial therapeutics has been hampered by a number of factors, especially their structure as peptides. We have examined the antiviral potential of peptoid mimics of AMPs (sequence-specific N-substituted glycine oligomers). These peptoids have the distinct advantage of being insensitive to proteases, and also exhibit increased bioavailability and stability. Our results demonstrate that several peptoids exhibit potent in vitro antiviral activity against both HSV-1 and SARS-CoV-2 when incubated prior to infection. Visualization by cryo-EM shows viral envelope disruption similar to what has been observed with AMP activity against other viruses. This suggests a common or biomimetic mechanism, possibly due to the differences between the phospholipid head group makeup of viral envelopes and host cell membranes. Furthermore, we observed no cytotoxicity against primary cultures of oral epithelial cells, thus underscoring the potential of this class of molecules as safe and effective broad-spectrum antiviral agents.

A total $m$-labelling $\alpha$ on graph $\Gamma$ is called an edge irregular total $m$-labelling if for any two different edges of $\Gamma$, their weights respect to $\alpha$ are distinct, where the weight of any edge is defined as the sum of its label and the labels of its end vertices. We determine the minimum $m$ such that $\Gamma$ can be labelled by an edge irregular total $m$-labelling whenever $\Gamma$ is an odd staircase graph or an even staircase graph.

With the emergence of the novel corona virus SARS-CoV-2 since December 2019, more than 43 million cases have been reported worldwide. This virus has shown high infectivity and severe symptoms in some cases leading to over 1 million deaths globally. Despite the collaborative and concerted research efforts that has been made, no effective treatment for COVID-19 (corona virus disease-2019) is currently available. SARS-CoV-2 uses the angiotensin converting enzyme 2 (ACE2) as an initial mediator for viral attachment and host cell invasion. ACE2 is widely distributed in human tissues including the cell surface of lung cells which represent the primary site of the infection. Inhibiting or reducing cell surface availability of ACE2 represents a promising therapy for tackling COVID-19. In this context, most ACE2–based therapeutic strategies have aimed to achieve this through the use of angiotensin converting enzyme (ACE) inhibitors or neutralizing the virus by exogenous administration of ACE2. However, through this review, we present another perspective focusing on the subcellular localization and trafficking of ACE2. Membrane targeting of ACE2, shedding and its cellular trafficking pathways including internalization are not well elucidated. Therefore, hereby we present an overview on the fate of newly synthesized ACE2, its post translational modifications, what is known of its trafficking pathways. In addition, we highlight the possibility that some of the identified ACE2 missense variants might affect its trafficking efficiency and localization and hence may explain some of the observed variable severity of SARS-CoV-2 infections. Extensive understanding of these processes is necessary to evaluate the potential use of ACE2 as a credible therapeutic target.

Understanding the dynamics of humoral immune responses throughout the COVID-19 pandemic is crucial for optimizing vaccine strategies. This study aimed to investigate the impact of infection and vaccine-induced immunity on the Albanian population from August 2021 to August 2022. Two independent samples from the Albanian general population were analyzed using an ELISA method to assess IgG class anti-Spike (S1) and anti-Nucleocapsid (N) SARS-CoV-2 antibodies. The results revealed a robust immune response among vaccinated individuals with prior COVID-19 infection who received only one vaccine dose. In the 2022 cohort, most individuals who received one vaccine dose achieved comparable seropositivity and antibody levels to those who received two doses. However, individuals aged 61 and over required two or three vaccine doses to reach the same level of immune response as the younger population. Notably, the time elapsed since infection or vaccination did not significantly impact the immune response. These findings highlight the importance of hybrid immunity and suggest that one vaccine dose may be sufficient for most individuals with prior COVID-19 infection. However, additional doses are necessary for optimal protection in older individuals. This study provides unique insights into humoral immune response dynamics that can be used to refine ongoing COVID-19 population vaccination strategies for middle-income countries with low vaccination coverage.

Predicting the outcome of a future game between two National Basketball Association (NBA) teams poses a challenging problem of interest to statistical scientists as well as the general public. In this article, we formalize the problem of predicting the game results as a classification problem and apply the principle of maximum entropy to construct NBA maximum entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs by the NBAME model. The best NBAME model is able to correctly predict the winning team 74.4 percent of the time as compared to some other machine learning algorithms which is correct 69.3 percent of the time.

This paper outlines the evolution of a learning technology interface from a Beta version to launch with educators and its alignment to pedagogical theory, designed to maximise collaboration between teacher and student. It explores how the “co-creation” of curricula via textual sources that underpin teaching and learning can be enhanced through interactive e-books and outlines the challenges involved in this praxis. With a number of stakeholders involved in the live use of the platform (including teachers, students, HE educators, course instructors, curriculum designers and software developers), iterative feedback loops informed real-time design improvements to both the interface and the-ory. This collaboration utilised a design-based research (DBR) approach (Wang and Hannafin, 2005), which is outlined here as explanation of how the tool developed and how iterative feedback helped to reconsider the challenges educators face in implementing pedagogical innovation across differing contexts. We propose how speculative design (Lukens and DiSalvo, 2012) and Activity Theory (Engeström, 1987) workshops can methodologically enhance the planning and evaluation phases inherent to DBR approaches, which involve students to prepare for educators’ innovation. Finally, we conclude with how educators can utilise these design principles using stratified approaches to help prepare organisational approaches for innovation.

The extensive use of carrier-aided smoothing code (CSC) filter has led to reduce the noise level of raw code measurements in GNSS positioning and navigation applications. However, the existing CSC technique is sensitive to the changes of the integer ambiguity and then the smoothing proce-dure needs to be restarted in the presence of cycle-slips. As the Doppler shift is instantaneous ob-servation and immune to cycle-slips, Doppler-aided smoothing code (DSC) algorithm would be more promising in challenged environment. Based on the Hatch-filter, an optimal DSC approach is proposed with the principle of minimum variance. Meanwhile, to inhibit the effect of integral cumulative error of Doppler, a balance factor is adopted to adjust the contributions of raw code and DSC. The noise level of code observable is not only affected by thermal noise, but also limited by systematic bias. Satellite code bias (SCB) has been identified in the raw code observable on each frequency for each BDS-2 satellite. By minimizing the sum of absolute value of residuals, polyno-mial segment fitting algorithm as a function of elevation-angles is applied to establish the SCB cor-rection model based on epoch-differenced Multipath (MP) deviations. Finally, numerical experi-ments demonstrate the validity and efficiency of the refined DSC filter with SCB corrections on each available frequency for BDS-2 un-GEO satellites.

Li₂TiO₃ nanopowders were synthesized by hydrothermal process using anatase TiO₂ and LiOH H₂O as raw materials. Li₂TiO₃ crystallizes in the layered monoclinic structure (space group C2/c) with average crystallite size of 34 nm. Morphology, elemental composition and local structure of products were carried out using HRTEM, FESEM, EDS, Raman and FTIR spectroscopy. Transport properties investigated by d.c. (4-probe measurements) and a.c. (complex impedance spectroscopy) show the activation energy of 0.71 and 0.65 eV, respectively. The ionic transport properties of Li⁺ ions in nanocrystalline Li₂TiO₃ characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) validate the good electrochemical properties of this anode material for lithium-ion batteries.

Wastewater-Based Epidemiology (WBE) is currently used to monitor not only the spread of the pandemic virus SARS-CoV-2 but also for other viruses in endemic conditions, particularly in the absence of syndromic surveillance. Continuous monitoring of sewage requires high costs and significant time investment, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Italy, targeting Human Adenovirus (HAdV), Norovirus Genogroup II (NoVggII), Enterovirus (EV), and SARS-CoV-2. Samples collected at the entrance of treatment plants were concentrated using PEG/NaCl precipitation and viral nucleic acids were extracted and detected by real-time (RT-)qPCR. NoVggII resulted the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. SARS-CoV-2 results compared with data previously collected in the same study area (February 2021 to September 2021) revealed a shift from an epidemic to a pandemic status, likely due to the evolution of variants. In conclusion, WBE, using standardized methods and an efficient monitoring strategy, proves valuable for virus surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decision.

Surface soil moisture (SSM) is a significant factor affecting crop growth. This paper presents a method for retrieving SSM over wheat-covered areas using synergy dual-polarization C-band Sentinel-1 synthetic aperture radar and Sentinel-2 optical data. Firstly, a modified water cloud model (WCM) was proposed to remove the influence of vegetation from the backscattering coefficient of the radar data. The vegetation fraction was then introduced in this WCM, and the vegetation water content (VWC) was calculated using multiple linear regression model. Subsequently, the support vector regression technique was used to retrieve the SSM. This approach was validated using in-situ measurements of the wheat field in Hebi, in the north of Henan Province. The key findings of this study are as follows: (1) Based on vegetation indices obtained from Sentinel-2; the proposed VWC estimation model can effectively eliminate the influence of vegetation; (2) compared with vertical transmit and horizontal receive polarization, vertical transmit and vertical receive polarization is better for detecting changes in SSM at different growth stages of wheat; and, (3) the validation results indicated that the proposed approach, based on Sentinel-1 and Sentinel-2 data, successfully retrieved SSM in the study area.

The rodent collecting duct (CD) expresses a 24p3/NGAL/lipocalin-2 (Lcn2) receptor (Slc22a17) apically to possibly mediate high-affinity reabsorption of filtered proteins by endocytosis, yet its functions remain uncertain. Recently, we showed that hyperosmolarity/-tonicity upregulates Slc22a17 in cultured mouse inner medullary CD cells, whereas activation of toll-like receptor 4 (TLR4) via bacterial lipopolysaccharides (LPS) downregulates Slc22a17. This is similar to the upregulation of Aqp2 by hyperosmolarity/-tonicity and arginine vasopressin (AVP) and downregulation by TLR4 signaling that occur via the transcription factors Nfat5 (TonEBP or OREBP), cAMP-responsive element binding protein (CREB), and nuclear factor-kappa B, respectively. The aim of the study was to determine the effects of osmolarity/tonicity via Nfat5, AVP via CREB and TLR4 signaling on the expression of Slc22a17 and its ligand Lcn2 in the mouse (m) cortical collecting duct cell line mCCD(cl.1). Normosmolarity/-tonicity was 300 mosmol/l whereas addition of 50-100 mmol/l NaCl for up to 72 h induced hyperosmolarity/-tonicity (400-500 mosmol/l). RT-PCR, qPCR, immunoblotting and immunofluorescence microscopy detected Slc22a17 and Lcn2 expression. RNAi silenced Nfat5, and the pharmacological agent 666-15 blocked CREB. Activation of TLR4 occurred with LPS. Similar to Aqp2, hyperosmotic/-tonic media and AVP upregulated Slc22a17 via activation of Nfat5 and CREB, respectively, and LPS/TLR4 signaling downregulated Slc22a17. Conversely, though Nfat5 mediated hyperosmolarity/-tonicity induced downregulation of Lcn2 expression, AVP reduced Lcn2 expression and predominantly apical Lcn2 secretion evoked by LPS, but through a posttranslational mode of action that was independent of cAMP signaling. In conclusion, the hyperosmotic/-tonic upregulation of Slc22a17 in mCCD(cl.1) cells via Nfat5 and by AVP via CREB suggests a contribution of Slc22a17 to adaptive osmotolerance, whereas Lcn2 downregulation could counteract increased proliferation and permanent damage of osmotically stressed cells.

Purpose: The study aimed to investigate if there were any links between liver function biomarkers and immunoglobulins levels in serum, and Toll-like receptors (TLRs) and neuropilin-1 (NRP1) in COVID-19 patients. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) by the receiver operator curve (ROC) analysis for immunoglobulins levels and TLRs expressions. Patients and Methods: This study included 150 patients (100 patients with confirmed COVID-19 and 50 healthy volunteers as a control group). Patients with COVID-19 were subdivided into two groups according to the severity of symptoms (moderate and severe, with 50 patients each). Serum C-reactive protein (CRP), alanine aminotransaminase (ALT), aspartate aminotransaminase (AST), albumin, lactate dehydrogenase (LDH), immunoglobulin (Ig) G, and IgM levels were estimated. TLRs (TLR2 and TLR4) and NRP1 gene expression in blood samples were investigated using quantitative real-time polymerase chain reaction (qRT-PCR). ROC analysis was also applied to determine the accuracy of various detected parameters in predicting the possibility of COVID-19 infection. Results: In COVID-19 patients, serum parameters related to liver function, except serum albumin, CRP, IgG, IgM, and TLR2, TLR4, and NRP1 mRNA expression levels, significantly elevated compared to controls. Severe COVID-19 patients exhibited significantly higher liver enzymes (ALT, AST and LDH), CRP, and TLR2 mRNA expression levels and lower albumin levels than the moderate group. In the moderate and severe groups, ALT, CRP, TLR2, and TLR4 had a significant positive correlation with IgM levels. ALT, AST, LDH, CRP, TLR2, and TLR4 showed a significant positive correlation with IgG levels in both groups. In both the moderate and severe groups, NRP1 expression was found to be significantly correlated with CRP, IgG, IgM, TLR2, and TLR4. In contrast, serum albumin levels exhibited a significant negative correlation with IgG and IgM levels only in the severe group, but they showed a significant negative correlation with TLR2, TLR4, and NRP1 expression in both moderate and severe groups. Serum ALT and AST activities were positively correlated with NRP1 expression in the moderate group but not in the severe group and as well as TLR2 and TLR4 expression in both the moderate and severe groups. ROC analysis indicated that AUC was higher than 0.800 for serum IgM level and TLR4 gene expression in moderate COVID-19 group. Conclusions: The increased liver function biomarkers in serum and NRP1 expression are closely correlated with sustained activations in humoral and innate immune responses during COVID-19 infection. As a result, TLR2, TLR4, and NRP1 could be targets for limiting COVID-19 infection and impairment effects on liver function. Moreover, detection of IgM level in serum and TLR4 expression in blood have a good accuracy in predicting the possibility of infection with COVID-19 in moderate cases.

This study investigated the influence of single nucleotide polymorphisms (SNPs) in genes asso-ciated with the interferon pathway (IFNAR2 rs2236757), antiviral response (OAS1 rs10774671, OAS3 rs10735079), and viral entry (ACE2 rs2074192) on COVID-19 severity and their association with non-alcoholic fatty liver disease (MAFLD). We did not observe a significant association between the investigated SNPs and COVID-19 severity. While the IFNAR2 rs2236757 A allele correlated with higher creatinine levels upon admission and the G allele with lower band neu-trophils upon discharge, these findings require further investigation. The distribution of OAS gene polymorphisms (rs10774671, rs10735079 did not differ between MAFLD and non-MAFLD patients. Our study population's distribution of ACE2 rs2074192 genotypes and alleles differed from the European reference population. Overall, our findings suggest that these specific SNPs may not be major contributors to COVID-19 severity in our patient population, highlighting the potential role of other genetic factors and environmental influences.

Early-season crop-type data are required for a variety of agricultural monitoring and decision-making applications. The early season in this study referred to the prophase and middle of a growth season. Early-season detection of crop types remains challenging because of limited discriminative features, especially for landscapes that are characterized by complex cropping patterns. In fact, different remote-sensing satellites can increase the frequency of data acquisition, which can provide more information in the early season. Moreover, optical and radar sensors have different degrees of sensitivity to crop parameters. Therefore, the integration and application of two types of multitemporal data are of great significance to improve the accuracy and timeliness of crop type detection.In deep learning (DL), convolutional neural network (CNN) and recurrent neural network (RNN) models have great potential for temporal feature extraction. Compared with RNNs, CNNs usually have fewer parameters and are more conducive to determining early-season detection dates of different crop types, which requires a lot of training because of the need to model on different dates. Nevertheless, revisit dates and temporal intervals of different satellites are usually different, resulting in different data acquisition time series; these data cannot be directly used as input for the same convolutional layer. To address this challenge, a Dual-1DCNN was bulit based on the CNN model in this study. Moreover, an incremental training method was used to attain the network on each data acquisition date and obtained the best detection date for each crop type in the early season. A case study for Hengshui City in China was conducted using time series of Sentinel-1A (S1A) and Sentinel-2 (S2). To verify this method, classical methods support vector machine (SVM) and random forest (RF) were implemented. The results demonstrated the following: (1) the Dual-1DCNN extracted discriminative features from S1A and S2 time series at the early season by producing the highest overall accuracy (OA: 87.23%); (2) for summer maize, cotton, and common yam rhizome, the Dual-1DCNN achieved F1 values of 92.39%, 87.71%, and 84.38%, respectively, at the early season (moreover, the early seasons were almost 40, 70, and 80 days before the end of the growth seasons, respectively). These findings suggested that the Dual-1DCNN is promising for the accurate and timely detection of crop types.