Physiological, Agronomic, and Grain Quality Responses of Diverse Rice Genotypes to Various Irrigation Regimes under Aerobic Cultivation Conditions.

Aerobic rice cultivation represents an innovative approach to reduce water consumption and enhance water use efficiency compared to traditional transplanting methods. Simultaneously, cultivating drought-tolerant rice genotypes becomes crucial to ensure their sustainable production under abrupt climate fluctuations. Hence, this study aimed to explore the physiological, agronomic, and grain quality responses of ten diverse rice genotypes to various irrigation levels under aerobic cultivation conditions. A field experiment was performed for two summer seasons of 2019 and 2020 in an arid Mediterranean climate. The irrigation regimes were well watered (13,998 m3/ha), mild drought (10,446 m3/ha), moderate drought (7125 m3/ha), and severe drought (5657 m3/ha). The results revealed considerable variations among rice genotypes under tested irrigation regimes in all physiological, agronomic, and quality traits. According to drought response indices, rice genotypes were classified into three groups (A-C), varying from tolerant to sensitive genotypes. The identified drought-tolerant genotypes (Giza-179, Hybrid-1, Giza-178, and Line-9399) recorded higher yields and crop water productivity with reduced water usage compared to drought-sensitive genotypes. Thus, these genotypes are highly recommended for cultivation in water-scarce environments. Furthermore, their characteristics could be valuable in breeding programs to improve drought tolerance in rice, particularly under aerobic cultivation conditions. The PCA biplot, heatmap, and hierarchical clustering highlighted specific physiological parameters such as relative water content, chlorophyll content, proline content, peroxidase content, and catalase content exhibited robust associations with yield traits under water deficit conditions. These parameters offer valuable insights and could serve as rapid indicators for assessing drought tolerance in rice breeding programs in arid environments.

Effect of mutation and vaccination on spread, severity, and mortality of COVID-19 disease.

Coronavirus disease 2019 (COVID-19) has had different waves within the same country. The spread rate and severity showed different properties within the COVID-19 different waves. The present work aims to compare the spread and the severity of the different waves using the available data of confirmed COVID-19 cases and death cases. Real-data sets collected from the Johns Hopkins University Center for Systems Science were used to perform a comparative study between COVID-19 different waves in 12 countries with the highest total performed tests for severe acute respiratory syndrome coronavirus 2 detection in the world (Italy, Brazil, Japan, Germany, Spain, India, USA, UAE, Poland, Colombia, Turkey, and Switzerland). The total number of confirmed cases and death cases in different waves of COVID-19 were compared to that of the previous one for equivalent periods. The total number of death cases in each wave was presented as a percentage of the total number of confirmed cases for the same periods. In all the selected 12 countries, Wave 2 had a much higher number of confirmed cases than that in Wave 1. However, the death cases increase was not comparable with that of the confirmed cases to the extent that some countries had lower death cases than in Wave 1, UAE, and Spain. The death cases as a percentage of the total number of confirmed cases in Wave 1 were much higher than that in Wave 2. Some countries have had Waves 3 and 4. Waves 3 and 4 have had lower confirmed cases than Wave 2, however, the death cases were variable in different countries. The death cases in Waves 3 and 4 were similar to or higher than Wave 2 in most countries. Wave 2 of COVID-19 had a much higher spread rate but much lower severity resulting in a lower death rate in Wave 2 compared with that of the first wave. Waves 3 and 4 have had lower confirmed cases than Wave 2; that could be due to the presence of appropriate treatment and vaccination. However, that was not reflected in the death cases, which were similar to or higher than Wave 2 in most countries. Further studies are needed to explain these findings.

A study of the possible factors affecting COVID-19 spread, severity and mortality and the effect of social distancing on these factors: Machine learning forecasting model.

BACKGROUNDS: SARS-CoV-2 is affecting different countries all over the world, with significant variation in infection-rate and death-ratio. We have previously shown a presence of a possible relationship between different variables including the Bacillus Calmette-Guérin (BCG) vaccine, average age, gender, and malaria treatment, and the rate of spread, severity and mortality of COVID-19 disease. This paper focuses on developing machine learning models for this relationship. METHODS: We have used real-datasets collected from the Johns Hopkins University Center for Systems Science and Engineering and the European Centre for Disease Prevention and Control to develop a model from China data as the baseline country. From this model, we predicted and forecasted different countries' daily confirmed-cases and daily death-cases and examined if there was any possible effect of the variables mentioned above. RESULTS: The model was trained based on China data as a baseline model for daily confirmed-cases and daily death-cases. This machine learning application succeeded in modelling and forecasting daily confirmed-cases and daily death-cases. The modelling and forecasting of viral spread resulted in four different regions; these regions were dependent on the malarial treatments, BCG vaccination, weather conditions, and average age. However, the lack of social distancing resulted in variation in the effect of these factors, for example, double-humped spread and mortality cases curves and sudden increases in the spread and mortality cases in different countries. The process of machine learning for time-series prediction and forecasting, especially in the pandemic COVID-19 domain, proved usefulness in modelling and forecasting the end status of the virus spreading based on specific regional and health support variables. CONCLUSION: From the experimental results, we confirm that COVID-19 has a very low spread in the African countries with all the four variables (average young age, hot weather, BCG vaccine and malaria treatment); a very high spread in European countries and the USA with no variable (old people, cold weather, no BCG vaccine and no malaria). The effect of the variables could be on the spread or the severity to the extent that the infected subject might not have symptoms or the case is mild and can be missed as a confirmed-case. Social distancing decreases the effect of these factors.

In vitro and in vivo performance modelling and optimisation of different dry powder inhalers: A complementary study of neural networks, genetic algorithms and decision trees.

INTRODUCTION: Aerosol delivery from DPIs could be affected by different factors. This study aimed to evaluate and predict the effects of different factors on drug delivery from DPIs. METHODS: Modelling and optimisation for both in vitro and in vivo data of different DPIs (Diskus, Turbohaler and Aerolizer) were carried out using neural networks associated with genetic algorithms and the results are confirmed using a decision tree (DT) and random forest regressor (RFR). All variables (the type of DPI, inhalation flow, inhalation volume, number of inhalations and type of subject) were coded as numbers before using them in the modelling study. RESULTS: The analysis of the in vitro model showed that Turbohaler had the highest emitted dose compared with the Diskus and the Aerolizer. Increasing flow resulted in a gradual increase in the emitted dose. Little differences between the inhalation volumes 2 and 4 litres were shown at fast inhalation flow, and interestingly two inhalations showed somewhat higher emitted doses than one-inhalation mode with Turbohaler and Diskus at slow inhalation flow. Regarding the in vivo model, the percent of drug delivered to the lung was highly increased with Turbohaler and Diskus in healthy subjects where continuous contour lines were observed. The Turbohaler showed increased lung bioavailability with the two-inhalation modes, the Diskus showed a nearly constant level at both one and two inhalations at slow inhalation. The Turbohaler and Aerolizer showed little increasing effect moving from one to two inhalations at slow inhalation. CONCLUSIONS: Modelling of the input data showed a good differentiating and prediction power for both in vitro and in vivo models. The results of the modelling refer to the high efficacy of Diskus followed by Turbohaler for delivering aerosol. With two inhalations, the three DPIs showed an increase in the percent of drug excreted at slow inhalations.

Bacillus Calmette-Guérin vaccine, antimalarial, age and gender relation to COVID-19 spread and mortality.

COVID-19 is affecting different countries all over the world with great variation in infection rate and death ratio. Some reports suggested a relation between the Bacillus Calmette-Guérin (BCG) vaccine and the malaria treatment to the prevention of SARS-CoV-2 infection. Some reports related infant's lower susceptibility to the COVID-19. Some other reports a higher risk in males compared to females in such COVID-19 pandemic. Also, some other reports claimed the possible use of chloroquine and hydroxychloroquine as prophylactic in such a pandemic. The present commentary is to discuss the possible relation between those factors and SARS-CoV-2 infection.

Modeling and optimization of nebulizers' performance in non-invasive ventilation using different fill volumes: Comparative study between vibrating mesh and jet nebulizers.

BACKGROUNDS: Substituting nebulisers by another, especially in non-invasive ventilation (NIV), involves many process-variables, e.g. nebulizer-type and fill-volume of respirable-dose, which might affect patient optimum-therapy. The aim of the present work was to use neural-networks and genetic-algorithms to develop performance-models for two different nebulizers. METHODS: In-vitro, ex-vivo and in-vivo models were developed using input-variables including nebulizer-type [jet nebulizer (JN) and vibrating mesh nebulizer (VMN)] fill-volumes of respirable dose placed in the nebulization chamber with an output-variable e.g. average amount reaching NIV patient. Produced models were tested and validated to ensure effective predictivity and validity in further optimization of nebulization process. RESULTS: Data-mining produced models showed excellent training, testing and validation correlation-coefficients. VMN showed high nebulization efficacy than JN. JN was affected more by increasing the fill-volume. The optimization process and contour-lines obtained for in-vivo model showed increase in pulmonary-bioavailability and systemic-absorption with VMN and 2 mL fill-volumes. CONCLUSIONS: Modeling of aerosol-delivery by JN and VMN using different fill-volumes in NIV circuit was successful in demonstrating the effect of different variable on dose-delivery to NIV patient. Artificial neural networks model showed that VMN increased pulmonary-bioavailability and systemic-absorption compared to JN. VMN was less affected by fill-volume change compared to JN which should be diluted to increase delivery.

Development of a nanogel formulation for transdermal delivery of tenoxicam: a pharmacokinetic-pharmacodynamic modeling approach for quantitative prediction of skin absorption.

This study investigates potentials of solid lipid nanoparticles (SLN)-based gel for transdermal delivery of tenoxicam (TNX) and describes a pharmacokinetic-pharmacodynamic (PK-PD) modeling approach for predicting concentration-time profile in skin. A 23 factorial design was adopted to study the effect of formulation factors on SLN properties and determine the optimal formulation. SLN-gel tolerability was investigated using rabbit skin irritation test. Its anti-inflammatory activity was assessed by carrageenan-induced rat paw edema test. A published Hill model for in vitro inhibition of COX-2 enzyme was fitted to edema inhibition data. Concentration in skin was represented as a linear spline function and coefficients were estimated using non-linear regression. Uncertainty in predicted concentrations was assessed using Monte Carlo simulations. The optimized SLN was spherical vesicles (58.1 ± 3.1 nm) with adequate entrapment efficiency (69.6 ± 2.6%). The SLN-gel formulation was well-tolerated. It increased TNX activity and skin level by 40 ± 13.5, and 227 ± 116%, respectively. Average Cmax and AUC0-24 predicted by the model were 2- and 3.6-folds higher than the corresponding values computed using in vitro permeability data. SLN-gel is a safe and efficient carrier for TNX across skin in the treatment of inflammatory disorders. PK-PD modeling is a promising approach for indirect quantitation of skin deposition from PD activity data.

Modelling of in-vitro and in-vivo performance of aerosol emitted from different vibrating mesh nebulisers in non-invasive ventilation circuit.

Substituting nebulisers by another in non-invasive ventilation circuit (NIV) involves many process variables which must be adjusted to ensure patient optimum therapy. However, there is a doubt when nebulisers use the same technology. Data mining technology based on artificial neural networks and genetic algorithms were used here to model in-vitro inhalation process and predict bioavailability from inhaled doses delivered by three different vibrating mesh nebulisers (VMNs) in NIV. Modelling of data indicated that in-vitro performance of VMNs was dependent mainly on fine particle fraction, mass median aerodynamic diameter (MMAD), total emitted dose (TED) and to lesser extent on nebuliser type. Ex-vivo model indicated that amount of salbutamol collected on facemask filter was directly affected by TED. In-vivo model showed that amount of salbutamol deposited into the lung (0.5hQ) and amount absorbed systemically (24hQ) were dependent directly on MMAD and TED. Female patients showed higher 24hQ values than males. Nebuliser type affected TED, 0.5hQ but not 24hQ values. Results indicate suitability of VMNs in achieving appropriate in-vitro inhalation performance model. The results also, indicate that the three VMNs are comparable and can be interchanged with no fear of any additional toxicity.

Mucoadhesive niosomal in situ gel for ocular tissue targeting: in vitro and in vivo evaluation of lomefloxacin hydrochloride.

Eradication of ophthalmic infections depends on increasing transcorneal permeation and localizing antibiotics at ocular surface. This study aimed at formulating lomefloxacin HCl (LF) in the form of niosomes and evaluating the in vivo performance of best formula in rabbits' eyes. Vesicles were developed by mixing three surfactants at three molar ratios of 1:1, 1:2 and 1:3 of surfactant to cholesterol. Size, zeta potential, release percentage, transcorneal permeation parameters, stability studies, cytotoxicity and antibacterial activity of niosomes were determined. Niosomes showed encapsulation efficiency of more than 78%, particle size below 500 nm and zeta potential below -43.6. The produced vesicles showed significantly higher amounts of drug permeated across cornea (166%) compared to LF solution. The in vivo study showed 2-5 folds increase in drug concentration in ocular fluids and tissues following administration of niosomes compared to marketed formula (from 3.75 to 10.31 mcg/mL in the cornea). Microbiological studies showed 35 folds increase in the antibacterial activity of LF niosomes compared to free drug; where MBC decreased from 31.25 mcg/mL in case of LF solution to 0.97 mcg/mL for niosomal gel. The formulated niosomes enhanced the ocular bioavailability of LF through increasing transcorneal permeation and localizing drug at site of action.

Topical ketoprofen nanogel: artificial neural network optimization, clustered bootstrap validation, and in vivo activity evaluation based on longitudinal dose response modeling.

OBJECTIVES: This work aimed at investigating the potential of solid lipid nanoparticles (SLN) as carriers for topical delivery of Ketoprofen (KP); evaluating a novel technique incorporating Artificial Neural Network (ANN) and clustered bootstrap for optimization of KP-loaded SLN (KP-SLN); and demonstrating a longitudinal dose response (LDR) modeling-based approach to compare the activity of topical non-steroidal anti-inflammatory drug formulations. METHODS: KP-SLN was fabricated by a modified emulsion/solvent evaporation method. Box-Behnken design was implemented to study the influence of glycerylpalmitostearate-to-KP ratio, Tween 80, and lecithin concentrations on particle size, entrapment efficiency, and amount of drug permeated through rat skin in 24 hours. Following clustered bootstrap ANN optimization, the optimized KP-SLN was incorporated into an aqueous gel and evaluated for rheology, in vitro release, permeability, skin irritation and in vivo activity using carrageenan-induced rat paw edema model and LDR mathematical model to analyze the time course of anti-inflammatory effect at various application durations. RESULTS: Lipid-to-drug ratio of 7.85 [bootstrap 95%CI: 7.63-8.51], Tween 80 of 1.27% [bootstrap 95%CI: 0.601-2.40%], and Lecithin of 0.263% [bootstrap 95%CI: 0.263-0.328%] were predicted to produce optimal characteristics. Compared with profenid® gel, the optimized KP-SLN gel exhibited slower release, faster permeability, better texture properties, greater efficacy, and similar potency. CONCLUSIONS: SLNs are safe and effective permeation enhancers. ANN coupled with clustered bootstrap is a useful method for finding optimal solutions and estimating uncertainty associated with them. LDR models allow mechanistic understanding of comparative in vivo performances of different topical formulations, and help design efficient dermatological bioequivalence assessment methods.

Preparation, optimization, and in vitro simulated inhalation delivery of carvedilol nanoparticles loaded on a coarse carrier intended for pulmonary administration.

Carvedilol (CAR) is a potent antihypertensive drug but has poor oral bioavailability (24%). A nanosuspension suitable for pulmonary delivery to enhance bioavailability and bypass first-pass metabolism of CAR could be advantageous. Accordingly, the aim of this work was to prepare CAR nanosuspensions and to use artificial neural networks associated with genetic algorithm to model and optimize the formulations. The optimized nanosuspension was lyophilized to obtain dry powder suitable for inhalation. However, respirable particles must have a diameter of 1-5 µm in order to deposit in the lungs. Hence, mannitol was used during lyophilization for cryoprotection and to act as a coarse carrier for nanoparticles in order to deliver them into their desired destination. The bottom-up technique was adopted for nanosuspension formulation using Pluronic stabilizers (F127, F68, and P123) combined with sodium deoxycholate at 1:1 weight ratio, at three levels with two drug loads and two aqueous to organic phase volume ratios. The drug crystallinity was studied using differential scanning calorimetry and powder X-ray diffractometry. The in vitro emitted doses of CAR were evaluated using a dry powder inhaler sampling apparatus and the aerodynamic characteristics were evaluated using an Andersen MKII cascade impactor. The artificial neural networks results showed that Pluronic F127 was the optimum stabilizer based on the desired particle size, polydispersity index, and zeta potential. Results of differential scanning calorimetry combined with powder X-ray diffractometry showed that CAR crystallinity was observed in the lyophilized nanosuspension. The aerodynamic characteristics of the optimized lyophilized nanosuspension demonstrated significantly higher percentage of total emitted dose (89.70%) and smaller mass median aerodynamic diameter (2.80 µm) compared with coarse drug powder (73.60% and 4.20 µm, respectively). In summary, the above strategy confirmed the applicability of formulating CAR in the form of nanoparticles loaded on a coarse carrier suitable for inhalation delivery.

Hydrocortisone nanosuspensions for ophthalmic delivery: A comparative study between microfluidic nanoprecipitation and wet milling.

Recently, drug nanosuspensions have shown a potential for ophthalmic delivery. In this study, a hydrocortisone (HC) nanosuspension (NS) was developed using microfluidic nanoprecipitation as a recent, simple and cost-effective bottom-up technique of drug nanonization. For comparison, a second HC NS was prepared by top-down wet milling procedures. The produced nanosuspensions were characterized for particle size, shape and zeta potential. HC nanosuspensions of approximately 300nm particle size were produced by adjusting experimental conditions of the two processing techniques. Results of X-ray diffraction and differential scanning calorimetry revealed that HC maintained the crystalline structure upon milling, while predominant amorphous particles were generated after precipitation. Ocular bioavailability of HC nanosuspensions was assessed in albino rabbits using HC solution as a control. A sustained drug action was maintained up to 9h for the nanosuspensions compared to 5h for the drug solution. The precipitated and milled NS achieved comparable AUC(0-9h) values of 28.06±4.08 and 30.95±2.2, respectively, that were significantly (P<0.05) higher than that of HC solution (15.86±2.7). After 2 months storage at room temperature, the milled HC NS showed good stability with no discernable changes in particle size, whereas the particle size of the precipitated HC NS increased to 440nm.

The morphogenesis of the vasculature in swine fetal skin.

The morphogenesis of the vascular elements in the skin of 45 swine fetuses (German landrace), from 50 to 330 mm crown-to-rump (C-R) length, was described. A simple pattern for the cutaneous vascular networks could be recognized in fetuses ranging from 90 to 100 mm C-R length. In 150 to 170 mm length-fetuses, the cutaneous blood vessel networks were differentiated into a definite pattern of construction. The venous blood drained regionally through the Plexus venosus subpapillaris profundus into the Plexus venosus dermis profundus. Each region ("Unit Vascular Zone") was supplied by more than one R. arteriosus cutaneus . The large branches of R. arteriosus cutaneus were accompanied by 2 satellite veins. At the end of gestation, the vessels of the Plexus venosus dermis profundus exhibited a beaded appearance which indicated the presence of valves.