Effects of Salvadora persica extracts on mice exploratory locomotion activities

The effects of Salvadora persica extracts on mice exploratory locomotor activities and stereotype movements have been determined. Mice injected with Salvadora persica extracts showed significantly low exploratory locomotor activity. The total distance travelled by naive mice injected with saline, during the first 5 min of introduction into an activity cage (Session 1) was 1007 +/- 105 cm/5 min, in contrast to 800 +/- 75, 540 +/- 100 and 330 +/- 55 cm/5 min for naive mice injected i.p. with 5.7, 14.3 and 28.6 ml/kg Salvadora persica extract. The exploratory locomotion of Salvadora persica treated mice declined faster than that of the controls. Mice injected with Salvadora persica extract also showed a significantly lower number of stereotype movements (P less than 0.05). The stereotype movements of the control was 175 +/- 5 movements/5 min and 90 +/- 10, 118 +/- 15 and 35 +/- 11 for mice injected with 5.7, 14.3 and 28.6 ml/kg, Salvadora persica extract, respectively.     

Introduction of cadmium chloride additive to improve the performance and stability of perovskite solar cells

With the increase in the importance of using green energy sources to meet the world''s energy demands, attempts have been made to push perovskite solar cell technology toward industrialization all around the world. Improving the properties of perovskite materials as the heart of PSCs is one of the methods to fabricate favorable photovoltaic (PV) solar cells based on perovskites. Here, cadmium chloride (CdCl₂) was used as an additive source for the perovskite precursor to improve its PV properties. Results indicated CdCl₂ improves the perovskite growth and tailors its crystalline properties, suggesting boosted charge transport processes in the bulk and interfaces of the perovskite layer with electron–hole transport layers. Overall, by incorporation of 1.0% into the MAPbI₃ layer, a maximum power conversion efficiency of 15.28% was recorded for perovskite-based solar cells, higher than the 12.17% for the control devices. The developed method not only improved the PV performance of devices but also boosted the stability behavior of solar cells due to the passivated domain boundaries and enhanced hydrophobicity in the CdCl₂-based devices.

With the increase in the importance of using green energy sources to meet the world''s energy demands, attempts have been made to push perovskite solar cell technology toward industrialization all around the world.     

Evaluation of pulmonary blood flow in bilateral bidirectional Glenn shunts: value of 4‐D flow cardiac magnetic resonance in the evaluation of pulmonary artery confluence stenosis

Bilateral bidirectional Glenn shunts are associated with the risk of developing pulmonary artery bifurcation stenosis, resulting in variable pulmonary blood flow to either lung. This could negatively impact the subsequent stages of the single ventricle palliation pathway. This report highlights the value of 4D flow sequence from the cardiac magnetic resonance imaging in demonstrating the pulmonary blood flow characteristics following a bilateral bidirectional Glenn procedure. Mapping the blood flow pattern and its quantification to each lung provide objective insights into the possible predisposing factors for the development of pulmonary bifurcation stenosis.     

Evaluation of the Effect of the Loading Time on the Microtensile Bond Strength of Various Restorative Materials Bonded to Silver Diamine Fluoride-Treated Demineralized Dentin

The aim of this study was to evaluate the effect of immediate versus delayed loading times on the microtensile bond strength (μTBS) of restorative materials, including resin-based composite (RBC), resin-modified glass ionomer cement (RMGIC) and glass ionomer cement (GIC), that were bonded to silver diamine fluoride (SDF)-treated demineralized dentin. Ninety caries-free extracted premolar teeth were assigned to three groups (n = 30) loaded with RBC, RMGIC and GIC restorative materials. Each group was further divided into three subgroups (n = 10): subgroup A (control specimens), immediate loading of the restorative material on sound dentin; subgroup B, demineralized dentin, SDF treatment and immediate loading of the restorative material; and subgroup C, demineralized dentin, SDF treatment and restorative material loading a week later. One-way ANOVA and Tukey’s post-hoc tests were performed to compare the μTBS values. The RBC exhibited the highest µTBS, followed by RMGIC and GIC. Multiple comparisons showed an increase in the µTBS in the delayed loading groups irrespective of the restorative material used. The majority of the failure modes were adhesive. Delayed loading of RMGIC for 1 week after SDF application showed significantly higher µTBS than that of immediate loading.     

A Comparative Study to Evaluate the Essential Work of Fracture to Measure the Fracture Toughness of Quasi-Brittle Material

In the present work, three different woven composite laminates were fabricated using the hand lay-up method. The woven reinforcement fibres were carbon fibres (CFRP), glass fibres (GFRP-W) and (GFRP-R) in combination with epoxy resin. Then, the central notch specimen tensile test (CNT) was used to measure the fracture toughness and the corresponding surface release energy (GIC). Then, the data were compared with the essential work of fracture (we) values based on the stored energy of the body to obtain a new standard fracture toughness test for composite laminates using relatively simple techniques. In addition to an extended finite element model, XFEM was implemented over a central notch specimen geometry to obtain a satisfactory validation of the essential work of fracture concepts. Therefore, the average values of (GIC) were measured with CNT specimens 25.15 kJ/m², 32.5 kJ/m² and 20.22 kJ/m² for CFRP, GFRP-W and GFRP-R, respectively. The data are very close as the percentage error for the surface release energy measured by the two methods was 0.83, 4.6 and 5.16 for carbon, glass and random fibre composite laminates, respectively. The data for the fracture toughness of XFEM are also very close. The percentage error is 4.6, 5.25 and 2.95 for carbon, glass and random fibre composite laminates, respectively. Therefore, the fundamental work of the fracture concept is highly recommended as a fracture toughness test for composite laminates or quasi-brittle Material.     

Innovative pulmonary targeting of terbutaline sulfate-laded novasomes for non-invasive tackling of asthma: statistical optimization and comparative in vitro/in vivo evaluation

Asthma represents a globally serious non-communicable ailment with significant public health outcomes for both pediatrics and adults triggering vast morbidity and fatality in critical cases. The β₂-adrenoceptor agonist, terbutaline sulfate (TBN), is harnessed as a bronchodilator for monitoring asthma noising symptoms. Nevertheless, the hepatic first-pass metabolism correlated with TBN oral administration mitigates its clinical performance. Likewise, the regimens of inhaled TBN dosage forms restrict its exploitation. Consequently, this work is concerned with the assimilation of TBN into a novel non-phospholipid nanovesicular paradigm termed novasomes (NVS) for direct and effective TBN pulmonary targeting. TBN-NVS were tailored based on the thin film hydration method and Box-Behnken design was applied to statistically optimize the formulation variables. Also, the aerodynamic pattern of the optimal TBN-NVS was explored via cascade impaction. Moreover, comparative pharmacokinetic studies were conducted using a rat model. TBN elicited encapsulation efficiency as high as 70%. The optimized TBN-NVS formulation disclosed an average nano-size of 223.89 nm, ζ potential of −31.17 mV and a sustained drug release up to 24 h. Additionally, it manifested snowballed in vitro lung deposition behavior in cascade impactor with a fine particle fraction of 86.44%. In vivo histopathological studies verified safety of intratracheally-administered TBN-NVS. The pharmacokinetic studies divulged 3.88-fold accentuation in TBN bioavailability from the optimum TBN-NVS versus the oral TBN solution. Concisely, the results proposed that NVS are an auspicious nanovector for TBN pulmonary delivery with integral curbing of the disease owing to target specificity.     

Knowledge and attitudes of physicians toward forensic psychiatry in Saudi Arabia

Objectives:To assess the knowledge and attitudes of physicians of different specialties, including psychiatrists, regarding forensic psychiatry to determine whether further modification or training is needed in the psychiatry residency program.Methods:This cross-sectional study was carried out using a 3-page, 3-section questionnaire containing 21 questions disseminated randomly online via Google forms using social media platforms. The 482 participants were residents, specialists, and consultants of various specialties. The study was conducted between September 2020 and August 2021 in various tertiary hospitals across Saudi Arabia.Results:A total of 482 physicians were recruited. The most common age group was 25-35 years, comprising mostly Saudis (62.4%). Based on the results, “poor” and “good” knowledge of forensic psychiatry was identified in 89% and 11% of the physicians, while “negative” and “positive” attitudes were identified in 16.4% and 83.6% of the physicians.Conclusion:Although the perspective of physicians regarding forensic psychiatry was found to be positive, their knowledge of the topic seems to be lacking.     

Forecasting the Post-Pandemic Effects of the SARS-CoV-2 Virus Using the Bullwhip Phenomenon Alongside Use of Nanosensors for Disease Containment and Cure

The COVID-19 pandemic has the tendency to affect various organizational paradigm alterations, which civilization hasyet to fully comprehend. Personal to professional, individual to corporate, and across most industries, the spectrum of transformations is vast. Economically, the globe has never been more intertwined, and it has never been subjected to such widespread disruption. While many people have felt and acknowledged the pandemic’s short-term repercussions, the resultant paradigm alterations will certainly have long-term consequences with an unknown range and severity. This review paper aims at acknowledging various approaches for the prevention, detection, and diagnosis of the SARS-CoV-2 virus using nanomaterials as a base material. A nanostructure is a material classification based on dimensionality, in proportion to the characteristic diameter and surface area. Nanoparticles, quantum dots, nanowires (NW), carbon nanotubes (CNT), thin films, and nanocomposites are some examples of various dimensions, each acting as a single unit, in terms of transport capacities. Top-down and bottom-up techniques are used to fabricate nanomaterials. The large surface-to-volume ratio of nanomaterials allows one to create extremely sensitive charge or field sensors (electrical sensors, chemical sensors, explosives detection, optical sensors, and gas sensing applications). Nanowires have potential applications in information and communication technologies, low-energy lightning, and medical sensors. Carbon nanotubes have the best environmental stability, electrical characteristics, and surface-to-volume ratio of any nanomaterial, making them ideal for bio-sensing applications. Traditional commercially available techniques have focused on clinical manifestations, as well as molecular and serological detection equipment that can identify the SARS-CoV-2 virus. Scientists are expressing a lot of interest in developing a portable and easy-to-use COVID-19 detection tool. Several unique methodologies and approaches are being investigated as feasible advanced systems capable of meeting the demands. This review article attempts to emphasize the pandemic’s aftereffects, utilising the notion of the bullwhip phenomenon’s short-term and long-term effects, and it specifies the use of nanomaterials and nanosensors for detection, prevention, diagnosis, and therapy in connection to the SARS-CoV-2.     

Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements

The rapid spread of the coronavirus disease COVID-19 has imposed clinical and financial burdens on hospitals and governments attempting to provide patients with medical care and implement disease-controlling policies. The transmissibility of the disease was shown to be correlated with the patient’s viral load, which can be measured during testing using the cycle threshold (Ct). Previous models have utilized Ct to forecast the trajectory of the spread, which can provide valuable information to better allocate resources and change policies. However, these models combined other variables specific to medical institutions or came in the form of compartmental models that rely on epidemiological assumptions, all of which could impose prediction uncertainties. In this study, we overcome these limitations using data-driven modeling that utilizes Ct and previous number of cases, two institution-independent variables. We collected three groups of patients (n = 6296, n = 3228, and n = 12,096) from different time periods to train, validate, and independently validate the models. We used three machine learning algorithms and three deep learning algorithms that can model the temporal dynamic behavior of the number of cases. The endpoint was 7-week forward number of cases, and the prediction was evaluated using mean square error (MSE). The sequence-to-sequence model showed the best prediction during validation (MSE = 0.025), while polynomial regression (OLS) and support vector machine regression (SVR) had better performance during independent validation (MSE = 0.1596, and MSE = 0.16754, respectively), which exhibited better generalizability of the latter. The OLS and SVR models were used on a dataset from an external institution and showed promise in predicting COVID-19 incidences across institutions. These models may support clinical and logistic decision-making after prospective validation.