Abstract: Background: Prediction of human clearance (CL) and subcutaneous (SC) bioavailability are critical aspects of monoclonal antibody (mAb) selection for clinical development. While monkeys are a well-accepted model for predicting human CL, other preclinical species have been less-thoroughly explored. Unlike CL, predicting bioavailability of SC administered mAbs in humans remains challenging as contributing factors are not well understood, and preclinical models have not been systematically evaluated. Methods: Nonclinical and clinical pharmacokinetic (PK) parameters were mined from public and internal sources for rats, cynomolgus monkeys, and humans. Intravenous (IV) and SC PK was determined in Sprague Dawley rats for fourteen mAbs without existing PK data. Together we obtained cross-species data for 25 mAbs to evaluate CL and SC bioavailability relationships among rats, monkeys, and humans. Results: Rat and monkey CL significantly correlated with human CL and supported the use of species-specific exponents for body weight-based allometric scaling. Notably, rat SC bioavailability significantly correlated with human SC bioavailability, while monkey did not. Bioavailability also correlated with clearance. Conclusions: The rat model enables early assessment of mAb PK properties, allowing discrimination among molecules in the discovery pipeline and prediction of human PK. Importantly, rat SC bioavailability significantly correlated with human SC bioavailability, which has not been observed with other species. Rats are cost effective and efficient relative to monkeys and provide a valuable tool for pharmacokinetic predictions in therapeutic antibody discovery.

Abstract: Background: Evaluate the level of physical activity, the levels of oxidative stress and sleep quality of patients with obstructive sleep apnea. Methods: Cross-sectional study with two groups: OSAG (Obstructive Sleep Apnea Group) (n = 15) and CG (Control Group) (n = 22). Both groups completed Pittsburgh Sleep Quality Index (PSQI), the International Physical Activity Questionnaire (IPAQ). To determine the rates of Malondialdehyde (MDA) and Glutathione (GSH), blood was collected. Results: The OSAG presented a higher body mass index (BMI) (32.44 ± 4.79; CG: 27.68 ± 5.36 kg∕m²), higher neck (39.67 ± 3.52; CG: 36.27 ± 3.74 cm) and abdominal circumference (105.4 ± 11.09; CG: 94.45 ± 11.96 cm), and higher levels of MDA (5.18 ± 1.33; CG: 1.18 ± 0.92 nmol∕mL). No significant difference of levels between the groups in GSH (OSAG: 125.99 ± 28.18; CG: 118.44 ± 16.52 μmol/g Hb), IPAQ score (OSAG: 3170 ± 1936; CG: 2907 ± 2411 MET-min∕week) and PSQI categories) was found. Conclusion: Both groups were physically active and had poor sleep quality. However, only OSAG has higher BMI, cervical and abdominal circumference. Conclusions: Both groups were physically active and had poor sleep quality. However, only OSAG has higher BMI, cervical and abdominal circumference.

Abstract: Recent studies on the physiology of LUCA (Last Universal Common Ancestor) associated to molecular dating methods suggest that the ancestor cell appeared very early in the history of the Earth, in a hostile environment, consequence of an intense cosmic bombardment occurred at that time. In the present investigation, the population size of LUCA was estimated by assuming that the ancestor cell had a metabolism similar to the methanogen M. jannaschii fed essentially by H2 and CO2, one of the oldest known metabolism. The cell (wet) mass was evaluated to be approximately 530 fg and the energy per cell required to drive its metabolism and growth was estimated to be around 2:7 10?13 W=cell. If LUCA was fed by the chemical energy available from submarine hydrothermal vents, then its cell population in the Hadean oceans was expected to be around 1:8 1024. Such a value corresponds to approximately ve orders of magnitude less than the present estimated number of prokaryote cells in the Earth's oceans. The study of LUCA's physiology can reveal essential biochemical processes that might be common in extraterrestrial life, guiding the search for biosignatures on other planets.

Abstract: Olive (Olea europaea L.) trees produce many more flowers than fruit. In an “on” year, an adult olive tree may produce as many as 500,000 flowers, but 98% of them will drop before ripening. This waste of resources, better invested in fruit reaching maturation, needs an explanation. Different not mutually exclusive hypotheses elucidating the possible significance of heavy flowering followed by massive and premature fruit abscission are analyzed and confronted based on previously published works as well as on more recent own observations on olive reproductive biology. The results suggest that olive trees selectively abort fruit to increase the quality of the seed in the surviving fruit. A sizable portion of the flowers seems also to enhance the total fitness of the plant by pollen export. On the contrary, the hypotheses alluding to resource limitation, pollination deficits, pollinator attraction or extra flowers constituting an ovary reserve, as the ultimate functions of massive flower production must be rejected in olive. Consequences on olive orchard management are discussed.

Abstract: A majority of free ranging wisent (Bison bonasus L.) populations in Ukraine is critically threatened by the acts of warfare. The only, relatively safe populations, dwell in the Carpathians. One of them - the herd inhabiting Skolyvsky Beskyd National Park, lives in a close proximity to larger herds from Bieszczady Mountains in Poland and National Park Poloniny in Slovakia. Creating conditions for a mutual exchange of individuals within those populations, could secure genetic diversity of the Ukrainian herd in a long term. Such migrations are however limited by permeability of forest corridors, linking herds dwelling across Polish and Slovak borders. Additionally, a border fence along the Ukrainian border effectively prevents any transboundary movements of large mammals. In this paper ecological conditions along national borders of those three countries are analysed, and existing obstacles for animal movements are identified. A concept for the creation a functional metapopulation of wisents, within this transboundary region of the Carpathians is proposed.

Abstract: Water deficit can significantly limit the sustainable production of plants, resulting in reduced growth, development, and flowering. Previous studies have shown that the use of biostimulants improves plant stability and promotes growth under low irrigation conditions. The study aims to evaluate the effects of biostimulators on the growth, development and flowering of tuberose (Polianthes tuberosa L.) under water deficit conditions. The experiment was conducted using a completely randomized design with three replications in pots and eight treatments: four irrigation regimes (100%, 80%, 60%, and 40%), and four biostimulant treatments (foliar application of seaweed extract at concentrations of 500, 1000, and 2000 ppm, humic acid at concentrations of 150, 300, and 600 ppm, inoculation of the bed with mycorrhiza, and a control treatment without biostimulators). The length, diameter, fresh and dry weight of the flower pedicel, the number of leaves per plant, the fresh and dry weight of the leaves, stem and root of each plant, as well as the content of photosynthetic pigments, phenol, proline, carbohydrates and flavonoids were measured. The results of this study showed that the growth and development of tuberoses were positively affected by different irrigation levels and biostimulants. The highest morphological characteristics were observed in plants irrigated at 100% field capacity. In contrast, the irrigation regime treatment of 40% of the field capacity combined with 600 mg/liter of humic acid had the most detrimental effect on plant growth indicators. Under stress conditions, the plant also exhibited increased levels of proline, carbohydrates, and flavonoids, which are commonly used as indicators of stress tolerance.

Abstract: Alkaline stress is one of the major abiotic constraints limiting the plant growth and development. The alkaline tolerance in crop plants is a complex trait regulated by many genes. The genetic basis of alkaline tolerance is largely unknown in soybean. In this study, an integrated strategy of genomic analysis was utilized to elucidate the genetic architecture of alkaline tolerance across the panel of 326 diverse soybean cultivars. Our study revealed 28 SNPs was significantly associated with alkaline tolerance through association mapping using seven GWAS models. By considering the detection of SNPs in multiple environments and GWAS models, the genomic regions of five consistent SNPs were depicted as stable QTLs viz., qAT1, qAT4, qAT14, qAT18 and qAT20. All these five alkaline tolerance QTLs are reported for the first time. By using the in silico analysis, we detected 17 genes within physical intervals of five QTLs as putative candidates. Haplotype alleles of four candidate genes showed significant differences in the regulation of alkaline tolerance-related traits varying from two to four regulating alkaline tolerance from lowest to highest through moderate levels. The outcome of the current investigation can be used in soybean breeding programs for producing cultivars with enhanced alkaline tolerance.

Abstract: Machine learning has witnessed a notable increase in significance within the medical field, primarily due to the increasing availability of health-related data and the progressive enhancements in machine learning algorithms. It can be utilized to formulate predictive models that aid in disease diagnosis, anticipate disease progression, tailor treatment to fulfill individual patient needs and improve the operational efficiency of healthcare systems. The strategic utilization of data can considerably elevate the quality of patient care, reduce healthcare costs, and promote the formulation of personalized and effective medical interventions. The healthcare industry reaps considerable benefits from the meticulous analysis of medical data, as it plays an integral role in promptly identifying diseases in patients. Timely detection of a disease can contribute to effective symptom management and guarantee that appropriate treatment is provided. The pronounced association between evoked potentials (EPs) and Expanded Disability Status Scale (EDSS) scores in individuals diagnosed with multiple sclerosis (MS) indicates that EPs may serve as dependable predictive markers for the progression of disability. Numerous studies have confirmed that variations in somatosensory evoked potentials (SEPs) demonstrate a relationship with EDSS scores, particularly during the early stages of the disease. The present study aims to apply artificial intelligence techniques to identify predictors linked to the progression of Multiple Sclerosis (MS) as assessed by the disability index (EDSS). It is essential to clarify the role of evoked potentials (EPs) in the prognostication of MS. We analyzed empirical data obtained from a medical database of 125 records. Our primary objective is to construct an expert Artificial Intelligence system capable of predicting the EDSS index by applying advanced knowledge-mining algorithms. We have developed intelligent systems that predict the progression of MS utilizing machine learning algorithms, specifically Decision Trees and Neural Networks. In our experimental evaluation, Decision Trees, Neural Networks, and Bayes for EPs achieved accuracies of 88.9%, 92.9%, and 88.2% respectively, which are comparable to MRI which obtained accuracies of 88.2%, 96.0%, and 85.0%. The EPs can be established as predictors of MS with efficacy analogous to that of MRI findings. Further investigation is necessary to validate EPs, which are significantly less expensive, portable, and simpler to administer than MRI, as equally effective as imaging or biochemical methods in functioning as biomarkers for MS.

Abstract: Background: Fluoroquinolone antibiotics are important bactericidal drugs that combat the bacterial infections globally. The emergence of bacterial resistance to this antibiotic class is an overwhelming serious problem in Egypt. Aim of the study: To determine the bacterial genes responsible for the the occurrence resistance to fluoroquinolone antibiotics in different hospitals in Egypt. Methodology: Samples were withdrawn one hundred urinary tract infection (UTI) patients as well as on hundred lower respiratory infection (LRTI) patients in different hospitals in Egypt who were previously administrated different dosage regimens of fluoroquinolone antibiotics. Using antibiotic susceptibility tests along with the bacterial growth spectrophotometric techniques at 600 nm wavelength, the leading bacterial resistant isolates were identified. The major genes responsible for this pattern of resistance were determined exploiting the third generation high throughput sequencing technique using PacBio RS II sequencer with catalog number PacBio RS II manufactured in Pacific Bio-sciences company, USA. Results: The major bacterial isolates along with their fluoroquinolone resistant genes were detected to be Pseudomonas aeruginosa strain GPS containing GPS resistant gene encoding DNA gyrase subunit B, Serratia Marcescens strain GSM containing GSM resistant gene encoding DNA gyrase subunit B and Streptococcus pneumonae strain TAP comprising TAP resistant gene encoding DNA gyrase subunit A. Conclusion: The current study resulted in the discovery of novel fluoroquinolone antibiotic resistant genes in different hospital in Egypt.

Abstract: Background/Objectives: Understanding the behavior of B cells during infection and vaccination is important for determining protective humoral immunity. We evaluated the profile of humoral immunity and B cell pool in individuals who were acutely infected with SARS-CoV-2, recovered from COVID-19, or received two doses of the AZD1222 vaccine. Methods: Peripheral blood mononuclear cells (PBMCs) from these individuals were subjected to in vitro stimulation to promote differentiation of B cells into antibody-secreting cells (ASC), and the ELISpot evaluated the abundance of pan and SARS-CoV-2 Spike S1-reactive IgG+ ASC. Stimulated PBMCs were characterized using flow cytometry. Culture supernatants were assessed for soluble B cell-activating factors. The IgA and IgG for the S1 were evaluated by ELISA. Results: The recovered individuals displayed a robust S1 ASC compared to acute and vaccinated. Although the frequency of total B cells or B-cell subsets did not vary among the groups, plasma cells were increased in naïve and double-negative B cells in the acute, recovered, and vaccinated. Similar IgA and IgG production appeared to be present in the acute and recovered. During vaccination, more IgG is produced than IgA. In acute patients, BAFF levels were positively correlated with total B cells and IgG+ plasma cells, but negatively correlated with IgA+ plasma cells. Conclusions: The vaccination and natural infection with COVID-19 induce a differential profile and functionality of B cells. We suggest that new vaccines against COVID-19 incorporate molecular adjuvants that regulate B lymphocyte functionality and consider the beneficial aspects of the IgA response in addition to IgG.