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This study investigates the impact of exogenous calcium and gamma-aminobutyric acid (GABA) supplementation on rice growth and stress tolerance under white-backed planthopper (WBPH) infestation. We evaluated several phenotypic traits, including shoot/root length, leaf width, tiller number, panicle length, and relative water content, alongside physiological markers such as oxidative stress indicators, antioxidant enzymes activities, hormonal levels, and amino acids biosynthesis. Our results indicate that WBPH stress significantly reduces growth parameters but calcium and GABA supplementation markedly enhance shoot length (by 26% and 36%) and root length (by 38% and 64%), respectively, compared to WBPH-infested plants. Both supplementations also reduced oxidative stress, as evidenced by decreased H2O2 and O2•− levels and a lower electrolyte leakage. Notably, calcium and GABA treatments increased antioxidant enzyme activities, with GABA boosting catalase (CAT) activity by 800%, peroxidase (POD) by 144%, and superoxide dismutase (SOD) by 62% under WBPH stress. Additionally, calcium and GABA enhanced the accumulation of stress hormones (abscisic acid ABA) and salicylic acid (SA) and promoted stomatal closure, contributing to improved water conservation. This study reveals that calcium regulates the GABA shunt pathway, significantly increasing GABA and succinate levels in both root and shoot. Furthermore, calcium and GABA supplementation enhance the biosynthesis of key amino acids and improve ion homeostasis, particularly elevating calcium (Ca), iron (Fe), and magnesium (Mg) levels under WBPH stress. Overall, this study highlights the potential of exogenous calcium and GABA as effective strategies for enhancing rice plant tolerance to WBPH infestation by modulating various physiological and biochemical mechanisms. Further research is warranted to fully elucidate the underlying mechanisms of action.

The negative impacts of soil salinization on ion homeostasis provide a significant global barrier to agricultural production and development. Plant physiology and biochemistry are severely affected by primary and secondary NaCl stress impacts, which damage cellular integrity, impair water uptake, and trigger physiological drought. Determining how transcriptional factors (TFs) and hormone networks are regulated in plants in response to salt stress is necessary for developing crops that tolerate salt. This study investigates the complex mechanisms of several significant TF families that influence plant responses to salt stress, involving AP2/ERF, bZIP, NAC, MYB, and WRKY. It demonstrates how these transcription factors (TFs) help plants respond to the detrimental effects of salinity by modulating gene expression through mechanisms including hormone signaling, osmotic stress pathway activation, and ion homeostasis. Additionally, it explores the hormonal imbalances triggered by salt stress, which entail complex interactions among phytohormones like jasmonic acid (JA), salicylic acid (SA), and abscisic acid (ABA) within the hormonal regulatory networks. This review highlights the regulatory role of key transcription factors in salt-stress response, and their interaction with plant hormones is crucial for developing genome-edited crops that can enhance agricultural sustainability and address global food security challenges.

Designing a pasteurization con dition for sweet lime juice while ensuring microbial safety, enzymatic stability, and high nutritional quality is crucial for satisfying stakeholder demands. The present research investigates the effects of matrix pH, ultrasound treatments, and sequential pulsed light on the microbial population, enzyme activity, and bioactive chemicals in sweet lime juice. The sequential pulsed light (PL: 0.6–0.84 J/cm2) and ultrasound (US: 0.2–0.4 W/cm3) treatments for sweet lime juice were optimized using response surface methodology (RSM). A three-factor full factorial design was used for this purpose. The independent variables encompassed pH (X1), PL effective fluence (X2, J/cm2), and US intensity (X3, W/cm3). The responses assessed included the inactivation of Saccharomyces cerevisiae (Y1, log cfu/mL) and polyphenol oxidase (PPO: Y2 in %) and the retention of vitamin C (Y3, %). The polynomial models were optimized using numerical optimization to attain the maximum desirability value (0.89). The optimized PL + US sample (0.8 J/cm2 + 0.4 W/cm3, respectively) at pH 3.5 resulted in a 5-log cycle reduction in S. cerevisiae count and a 90% inactivation in PPO activity and retained 95% of its vitamin C content. This optimized sample underwent further analysis, including phenolic profiling, assessment of microbial cell morphology, and examination of enzyme conformational changes. After sequential pulsed-light (0.8 J/cm2) and ultrasound (0.4 W/cm3) treatments, yeast cells showed unusual structural changes, indicating additional targets besides membranes. Following PL + US treatment, the PPO composition changed to 2.7 ± 0.1% α-helix, 33.9 ± 0.3% β-sheet, 1.4 ± 0.2% β-turn, and 62 ± 0.7% random coil. Impressively, the optimized PL + US sample maintained a sensory acceptance level similar to that of the untreated sample.

An RP-HPLC method with a UV detector was developed for the simultaneous quantification of diclofenac diethylamine, methyl salicylate, and capsaicin in a pharmaceutical formulation and rabbit skin samples. The separation was achieved using a Thermo Scientific ACCLAIMTM 120 C18 column (Waltham, MA, USA, 4.6 mm × 150 mm, 5 µm). The optimized elution phase consisted of deionized water adjusted to pH = 3 using phosphoric acid mixed with acetonitrile in a 35:65% (v/v) ratio with isocratic elution. The flow rate was set at 0.7 mL/min, and the detection was performed at 205 nm and 25 °C. The method exhibits good linearity for capsaicin (0.05–70.0 µg/mL), methyl salicylate (0.05–100.0 µg/mL), and diclofenac diethylamine (0.05–100.0 µg/mL), with low LOD values (0.0249, 0.0271, and 0.0038 for capsaicin, methyl salicylate, and diclofenac diethylamine, respectively). The RSD% values were below 3.0%, indicating good precision. The overall greenness score of the method was 0.61, reflecting its environmentally friendly nature. The developed RP-HPLC method was successfully applied to analyze Omni Hot Gel® pharmaceutical formulation and rabbit skin permeation samples.

This research focuses on the residential patterns that were traced in Amman in the last decades due to the constant influx of migrants. Therefore, mapping the residential patterns that are emerging was seen important to understand the morphology of the area. A mixed-methods approach was used to identify the typologies emerging into the setting. New residential patterns that called for new strategic thinking were captured and analyzed. Enhancing the new image of “celebrated character” that urges new perception of heterogeneous communities and attracting more sustainable residential attributes towards the neighborhood were the two main outcomes of the study.

Glioblastoma (GBM) is a fatal astrocytic glioma with poor prognosis and treatment resistance. Repurposing potential FDA-approved drugs like anti-psychotics can address the concerns in a timely and cost-effective manner. Epidemiological studies have shown that patients with schizophrenic using anti-psychotics have a low incidence of GBM. Therefore, we aimed to investigate the therapeutic potential of atypical anti-psychotic Iloperidone (ILO) alone and in combination with Temozolomide (TMZ) against GBM. The study assessed the growth inhibitory effect of ILO, TMZ, and their combination (ILO + TMZ) on U-87MG and T-98G cell lines using an MTT assay. The drug interaction coefficient (CDI) was determined, and doses with synergistic effects were used for subsequent experiments, including migratory, invasion, and TUNEL assays. The expressions of DRD2, β-catenin, Dvl2, Twist, and Slug were assessed by RTq-PCR, whereas the β-catenin protein expression was also determined by immunocytochemistry. ILO (p < 0.05) and TMZ (p < 0.01) significantly inhibited the growth of U-87MG cells at all tested doses. The combination of 60 µM of both drugs showed synergistic activity with CDI < 1. The inhibition of migration and apoptosis was more pronounced in the case of combination treatment (p < 0.001). Inhibition of the invading cells was also found to be significant in ILO- and combination-treated groups (p < 0.001). ILO and combination treatment also significantly downregulated the expression of DRD2, while TMZ upregulated the expression (p < 0.001). The expressions of β-catenin (p < 0.001), Dvl2 (p < 0.001), Twist (p < 0.001), and Slug (p < 0.001) were also significantly downregulated in all treatment groups as compared to the vehicle control. The data suggest that ILO possesses strong growth inhibitory activity, possibly due to its effect on DRD2 and β-catenin expression and has the potential to be repurposed against GBM.

Consumer preferences, safety, and sustainability aspects of conventional cosmetic ingredients have contributed to an increase in the demand for natural cosmetic ingredients and products. Naturally derived active cosmetic agents and excipients may come into contact with various naturally occurring and synthetic contaminants throughout the supply chain, and substantiating their safety is essential. This review examines the safety and legislative requirements applicable to natural cosmetic ingredients in the European Union (EU). Cosmetic safety requirements include technical data based on the ingredient profile, presence of hazards and the risks associated with the intended conditions of use. The hazard analysis includes screening for microbial contaminants such as aerobic mesophilic bacteria, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans; chemical contaminants such as lead, cadmium, arsenic, and mercury; and naturally occurring toxins, such as allergens. The toxicological assessment considers both local effects (such as skin sensitisation, eye/skin irritation, and photo-induced effects) and systemic effects (including acute dermal toxicity, sub-acute and sub-chronic toxicity, mutagenicity and carcinogenicity, reproductive toxicity, and toxicokinetics). The EU legislative requirements prohibit the use of animal-based tests for the toxicological evaluation of cosmetic ingredients, paving the way for alternatives termed as New Approach Methodologies (NAMs). The validation of NAMs is critical for their wider usage, and despite advancements, few have been validated, particularly for systemic toxicity testing. The use of NAMs in evaluating the safety of complex natural cosmetic ingredients is further examined.

Our study focused on assessing the effects of three newly identified BRCA1 exon 11 variants (c.1019T>C, c.2363T>G, and c.3192T>C) on breast cancer susceptibility. Using computational predictions and experimental splicing assays, we evaluated their potential as pathogenic mutations. Our in silico analyses suggested that the c.2363T>G and c.3192T>C variants could impact both splicing and protein function, resulting in the V340A and V788G mutations, respectively. We further examined their splicing effects using minigene assays in MCF7 and SKBR3 breast cancer cell lines. Interestingly, we found that the c.2363T>G variant significantly altered splicing patterns in MCF7 cells but not in SKBR3 cells. This finding suggests a potential influence of cellular context on the variant’s effects. While attempts to correlate in silico predictions with RNA binding factors were inconclusive, this observation underscores the complexity of splicing regulation. Splicing is governed by various factors, including cellular contexts and protein interactions, making it challenging to predict outcomes accurately. Further research is needed to fully understand the functional consequences of the c.2363T>G variant in breast cancer pathogenesis. Integrating computational predictions with experimental data will provide valuable insights into the role of alternative splicing regulation in different breast cancer types and stages.

Background: This study aims to understand and describe the clinical impact of SARS-CoV-2 (COVID-19) infection in patients with Hypertrophic Cardiomyopathy (HCM). Methods: A data repository of over 6.6 million patients in a large metropolitan (Chicago IL) healthcare system was queried to identify adults with a history of HCM and COVID-19 infection between 2019 and 2021. Propensity score-matched analysis was performed based on age, sex, BMI, and elements of the cardiovascular history, including tobacco use, hypertension, hyperlipidemia, myocardial injury, and heart failure. Results: Individuals with HCM and COVID-19 infection had more total hospitalizations (41.6 v 23 per 100 persons, p < 0.01), more heart-failure-related hospitalizations (24.2 v 8.7 per 100-persons, p < 0.01), more non-ST elevation myocardial injury (NSTEMI) hospitalizations (8.6 v 4.6 per 100-persons, p < 0.01), and increased mortality (10.8 v 5 per 100-persons, p < 0.01) compared to HCM patients without a history of COVID-19 infection. Patients with HCM and COVID-19 were also noted to have a higher peak CRP when compared to those without prior COVID-19 (Inter-quartile range of 9.0–106.9 v 1.8–21.3, p < 0.01). Conclusions: In patients with HCM, COVID-19 infection is associated with increased incidence of myocardial injury, increased number of total and heart-failure specific hospitalizations, and increased mortality.

Mycobacterium abscessus complex (MABC), a rapidly growing Mycobacterium, is one of the most common causes of non-tuberculous mycobacteria (NTM) infections in the United States of America, and it has been associated with a wide spectrum of infections in immunocompetent and immunosuppressed individuals. Eradicating MABC is very challenging, even with prolonged combination therapies. The management of MABC infections in solid organ transplant (SOT) patients is usually complex given their net state of immunosuppression, associated comorbidities, and potential drug–drug interactions, among other things. In this manuscript, we discussed the antimicrobial management of pulmonary and extrapulmonary MABC infections. In addition, we reviewed promising novel therapies such as clofazimine, omadacycline, bedaquiline, and inhaled tigecycline that could join the existing antimicrobial armamentarium to fight this infection associated with significant morbidity and mortality. However, further studies are needed, especially among the immunocompromised host.

Synapse loss is the principal cause of cognitive decline in Alzheimer’s disease (AD) and related disorders (ADRD). Synapse development depends on the intricate dynamics of the neuronal cytoskeleton. Cofilin, the major protein regulating actin dynamics, can be sequestered into cofilactin rods, intra-neurite bundles of cofilin-saturated actin filaments that can disrupt vesicular trafficking and cause synaptic loss. Rods are a brain pathology in human AD and mouse models of AD and ADRD. Eliminating rods is the focus of this paper. One pathway for rod formation is triggered in ~20% of rodent hippocampal neurons by disease-related factors (e.g., soluble oligomers of Amyloid-β (Aβ)) and requires cellular prion protein (PrPC), active NADPH oxidase (NOX), and cytokine/chemokine receptors (CCRs). FDA-approved antagonists of CXCR4 and CCR5 inhibit Aβ-induced rods in both rodent and human neurons with effective concentrations for 50% rod reduction (EC50) of 1–10 nM. Remarkably, two D-amino acid receptor-active peptides (RAP-103 and RAP-310) inhibit Aβ-induced rods with an EC50 of ~1 pM in mouse neurons and ~0.1 pM in human neurons. These peptides are analogs of D-Ala-Peptide T-Amide (DAPTA) and share a pentapeptide sequence (TTNYT) antagonistic to several CCR-dependent responses. RAP-103 does not inhibit neuritogenesis or outgrowth even at 1 µM, >106-fold above its EC50. N-terminal methylation, or D-Thr to D-Ser substitution, decreases the rod-inhibiting potency of RAP-103 by 103-fold, suggesting high target specificity. Neither RAP peptide inhibits neuronal rod formation induced by excitotoxic glutamate, but both inhibit rods induced in human neurons by several PrPC/NOX pathway activators (Aβ, HIV-gp120 protein, and IL-6). Significantly, RAP-103 completely protects against Aβ-induced loss of mature and developing synapses and, at 0.1 nM, reverses rods in both rodent and human neurons (T½ ~ 3 h) even in the continuous presence of Aβ. Thus, this orally available, brain-permeable peptide should be highly effective in reducing rod pathology in multifactorial neurological diseases with mixed proteinopathies acting through PrPC/NOX.

(1) Introduction: given the high prevalence of metabolic syndrome (MetS) in Saudi Arabia, especially in Jeddah, this study aims to understand the dietary and lifestyle-related risk factors among Jeddah’s non-diabetic adults. (2) Material and Methods: Employing a cross-sectional design, non-diabetic adults were sourced from public healthcare centers. Demographics, lifestyle, and dietary habits were surveyed. Blood pressure, anthropometrics, and fasting blood samples measuring plasma glucose, serum triglycerides, and HDL cholesterol were collected. The age cut-off for MetS was ascertained using the receiver operating characteristic curve. Variables influencing MetS were evaluated using univariate logistic regression, and consequential factors underwent multivariate analysis, adjusted for age and sex. (3) Results: Among 1339 participants, 16% had MetS, with age being the strongest predictor (p < 0.001). The optimal age cut-off was 32 years. For those 32, elevated WC was dominant in both sexes. Univariate logistic regression revealed that higher income and education correlated with lower MetS prevalence, while marriage and smoking were risk factors. Adjusting for age and sex, only very high income had a significant low-risk association (p = 0.034). (4) Conclusion: MetS is notable in the studied group, with age as the pivotal predictor. High income reduces MetS risk, while marital status and smoking could increase it. Since this was a cross-sectional study, cohort studies are needed to validate our findings.

Smart manufacturing needs cognitive computing methods to make the relevant systems more intelligent and autonomous. In this respect, bio-inspired cognitive computing methods (i.e., biologicalization) can play a vital role. This article is written from this perspective. In particular, this article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it cannot get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, but not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like). This characteristic of DBC can help to solve cognitive problems (e.g., pattern recognition). DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, we demonstrate that DBC-1 can solve various cognitive problems, e.g., “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” In addition, using an arbitrary numerical example, we demonstrate that DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” The remarkable thing is that smart manufacturing-based systems (e.g., digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (e.g., machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and enrich their biologicalization.

Background: Shifting the educational system from a traditional to an online context during COVID-19 necessitated several considerations to assure students’ satisfaction with e-learning. Aim: This study aims to explore the factors influencing students’ satisfaction with e-learning during the COVID-19 crisis. In particular, it tests multiple mediations, student factors, and system quality between students’ satisfaction and each course evaluation and instructor’s performance. Methodology: In this cross-sectional study, 258 undergraduate and postgraduate students enrolled in online courses at multiple Malaysian universities were recruited using non-probabilistic purposive sampling. Data were collected using a questionnaire that assessed four factors that influenced students’ satisfaction with e-learning during the COVID-19 crisis (i.e., instructor performance, course evaluation, student factors, and system quality) and analyzed using the partial least squares route structural equation modelling (PLS-SEM). Results: The results indicated that the four factors were significantly associated with students’ satisfaction with e-learning during COVID-19. Student factors and system quality were the most factors predicting students’ satisfaction with e-learning. Findings indicate statistically significant relationships between the instructor’s performance, student factors, course evaluation, and system quality on students’ satisfaction. Furthermore, the results depict that both course evaluation and system quality serially mediate the relationship between instructors’ performance and students’ satisfaction. Conclusion: This study finds that improving and enhancing student factors and system quality is critical for students’ satisfaction with e-learning. Furthermore, e-learning platforms should contain new advances of computer-mediated technologies that enable collaboration, which is a critical factor in the success of e-learning systems.

WNT/β-catenin signaling is essential for colon cancer development and progression. WNT5A (ligand of non-canonical WNT signaling) and its mimicking peptide Foxy5 impair β-catenin signaling in colon cancer cells via unknown mechanisms. Therefore, we investigated whether and how WNT5A signaling affects two promoters of β-catenin signaling: the LGR5 receptor and its ligand RSPO3, as well as β-catenin activity and its target gene VEGFA. Protein and gene expression in colon cancer cohorts were analyzed by immunohistochemistry and qRT-PCR, respectively. Three colon cancer cell lines were used for in vitro and one cell line for in vivo experiments and results were analyzed by Western blotting, RT-PCR, clonogenic and sphere formation assays, immunofluorescence, and immunohistochemistry. Expression of WNT5A (a tumor suppressor) negatively correlated with that of LGR5/RSPO3 (tumor promoters) in colon cancer cohorts. Experimentally, WNT5A signaling suppressed β-catenin activity, LGR5, RSPO3, and VEGFA expression, and colony and spheroid formations. Since β-catenin signaling promotes colon cancer stemness, we explored how WNT5A expression is related to that of the cancer stem cell marker DCLK1. DCLK1 expression was negatively correlated with WNT5A expression in colon cancer cohorts and was experimentally reduced by WNT5A signaling. Thus, WNT5A and Foxy5 decrease LGR5/RSPO3 expression and β-catenin activity. This inhibits stemness and VEGFA expression, suggesting novel treatment strategies for the drug candidate Foxy5 in the handling of colon cancer patients.

Intraoral scanners (IOSs) have become increasingly popular in the field of dentistry for capturing accurate digital impressions of patients’ teeth and oral structures. This study investigates the various factors influencing their accuracy. An extensive search of scholarly literature was carried out via PubMed, utilizing appropriate keywords. Factors evaluated in the included studies were categorized into three primary divisions: those related to the operator, the patient, and the IOS itself. The analysis demonstrated that the accuracy of intraoral scanning is influenced by various factors such as scanner selection, operator skill, calibration, patient’s oral anatomy, ambient conditions, and scanning aids. Maintaining updated software and understanding factors beyond scanner resolution are crucial for optimal accuracy. Conversely, smaller IOS tips, fast scanning speeds, and specific scanning patterns compromise the accuracy and precision. By understanding these factors, dental professionals can make more informed decisions and enhance the accuracy of IOSs, leading to improved final dental restorations.

Cofilactin rod pathology, which can initiate synapse loss, has been extensively studied in rodent neurons, hippocampal slices, and in vivo mouse models of human neurodegenerative diseases such as Alzheimer’s disease (AD). In these systems, rod formation induced by disease-associated factors, such as soluble oligomers of Amyloid-β (Aβ) in AD, utilizes a pathway requiring cellular prion protein (PrPC), NADPH oxidase (NOX), and cytokine/chemokine receptors (CCR5 and/or CXCR4). However, rod pathways have not been systematically assessed in a human neuronal model. Here, we characterize glutamatergic neurons differentiated from human-induced pluripotent stem cells (iPSCs) for the formation of rods in response to activators of the PrPC-dependent pathway. Optimization of substratum, cell density, and use of glial-conditioned medium yielded a robust system for studying the development of Aβ-induced rods in the absence of glia, suggesting a cell-autonomous pathway. Rod induction in younger neurons requires ectopic expression of PrPC, but this dependency disappears by Day 55. The quantification of proteins within the rod-inducing pathway suggests that increased PrPC and CXCR4 expression may be factors in the doubling of the rod response to Aβ between Days 35 and 55. FDA-approved antagonists to CXCR4 and CCR5 inhibit the rod response. Rods were predominantly observed in dendrites, although severe cytoskeletal disruptions prevented the assignment of over 40% of the rods to either an axon or dendrite. In the absence of glia, a condition in which rods are more readily observed, neurons mature and fire action potentials but do not form functional synapses. However, PSD95-containing dendritic spines associate with axonal regions of pre-synaptic vesicles containing the glutamate transporter, VGLUT1. Thus, our results identified stem cell-derived neurons as a robust model for studying cofilactin rod formation in a human cellular environment and for developing effective therapeutic strategies for the treatment of dementias arising from multiple proteinopathies with different rod initiators.

Infected burned skin is a life-threatening condition, which may lead to sepsis. The aims of this work are to formulate a biofilm composed of silver sulfadiazine (SSD), chitosan (CS), and sodium alginate (SA), and to evaluate its wound-healing effectiveness. A full factorial design was used to formulate different matrix formulations. The prepared biofilm was tested for physicochemical, and in vitro release. The optimized formulation is composed of 0.833% of CS and 0.75% of SA. The release of SSD almost reached 100% after 6 h. The mechanical properties of the optimized formula were reasonable. The antibacterial activity for the optimized biofilm was significantly higher than that of blank biofilm, which is composed of CS and SA, p = 1.53922 × 10−12. Moreover, the in vivo study showed a 75% reduction in wound width when using the formulated SSD biofilm compared to standard marketed cream (57%) and the untreated group (0%).

Nanoparticles have emerged as a prominent area of research in recent times, and silver nanoparticles (AgNPs) synthesized via phyco-technology have gained significant attention due to their potential therapeutic applications. Nodularia haraviana, a unique and lesser-explored cyanobacterial strain, holds substantial promise as a novel candidate for synthesizing nanoparticles. This noticeable research gap underscores the novelty and untapped potential of Nodularia haraviana in applied nanotechnology. A range of analytical techniques, including UV-vis spectral analysis, dynamic light scattering spectroscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray powder diffraction, were used to investigate and characterize the AgNPs. Successful synthesis of AgNPs was confirmed through UV-visible spectroscopy, which showed a surface plasmon resonance peak at 428 nm. The crystalline size of AgNPs was 24.1 nm. Dynamic light scattering analysis revealed that silver oxide nanoparticles had 179.3 nm diameters and a negative surface charge of −18 mV. Comprehensive in vitro pharmacogenetic properties revealed that AgNPs have significant therapeutic potential. The antimicrobial properties of AgNPs were evaluated by determining the minimum inhibitory concentration against various microbial strains. Dose-dependent cytotoxicity assays were performed on Leishmanial promastigotes (IC50: 18.71 μgmL−1), amastigotes (IC50: 38.6 μgmL−1), and brine shrimps (IC50: 134.1 μg mL−1) using various concentrations of AgNPs. The findings of this study revealed that AgNPs had significant antioxidant results (DPPH: 57.5%, TRP: 55.4%, TAC: 61%) and enzyme inhibition potential against protein kinase (ZOI: 17.11 mm) and alpha-amylase (25.3%). Furthermore, biocompatibility tests were performed against macrophages (IC50: >395 μg mL−1) and human RBCs (IC50: 2124 μg mL−1). This study showed that phyco-synthesized AgNPs were less toxic and could be used in multiple biological applications, including drug design and in the pharmaceutical and biomedical industries. This study offers valuable insights and paves the way for further advancements in AgNPs research.

Access to clean and safe water is extremely important, not only in Palestine but also worldwide. In the West Bank, groundwater is particularly valuable because of its scarcity and inaccessibility, and, due to the nature of the area’s aquifers, is currently regarded as being at high risk of pollution. Moreover, the water quality in this area is also of wide concern, with its effects being directly linked to human health. Certain parts of the West Bank groundwater suffer from high concentrations of nitrate and potassium. In total, 38.8% of nitrate and 10% of potassium concentrations in well samples exceed the permissible limit set by the WHO and PSI, and, therefore, health problems arise as a limiting factor for life quality and welfare in this region. Moreover, 87.7% of samples are classified as having very hard water. To evaluate the well water in the study area, an assessment was conducted based on the WQI and HHR. Therefore, 49 samples were taken from a group of wells distributed across the study area during the year 2021. The physico-chemical parameters of each sample were analysed. The WQI values showed that 78% of the well samples were of good quality. Moreover, in the classification of the water based on a Piper diagram, 65% of the groundwater was determined to be calcium–magnesium–bicarbonate-type water. Likewise, health risk assessments were evaluated for fluoride and nitrate in drinking water for adults, children, and infants. The main values of the estimated total hazard index (THI) obtained from the analysed data on the health risk assessments revealed a diverse effect on the local population based on age category. The ranges of THI in all sampling locations varied considerably and extended from 0.093 to 3.01 for adults, 0.29 to 3.08 for children, and 0.302 to 3.21 for infants. These results widely indicate that infants are more exposed to health risks.

Rice (Oryza sativa) is a research model for monocotyledonous plants. Rice is also one of the major staple foods and the primary crop for more than half of the world’s population. Increasing industrial activities and the use of different fertilizers and pesticides containing heavy metals (HMs) contribute to the contamination of agriculture fields. HM contamination is among the leading causes that affect the health of rice plants by limiting their growth and causing plant death. Phytohormones have a crucial role in stress-coping mechanisms and in determining a range of plant development and growth aspects during heavy metal stress. This review summarizes the role of different exogenous applications of phytohormones including auxin, cytokinin, gibberellins, ethylene, abscisic acid, strigolactones, jasmonates, brassinosteroids, and salicylic acids in rice plants for mitigating heavy metal stress via manipulation of their stress-related physiological and biochemical processes, and alterations of signaling and biosynthesis of genes. Exogenous administration of phytohormones and regulation of endogenous levels by targeting their biosynthesis/signaling machineries is a potential strategy for protecting rice from HM stress. The current review primarily emphasizes the key mechanistic phytohormonal-mediated strategies for reducing the adverse effects of HM toxicity in rice. Herein, we have provided comprehensive evidence for the effective role of exogenous phytohormones in employing defense responses and tolerance in rice to the phytotoxic effects of HM toxicity along with endogenous hormonal crosstalk for modulation of subcellular mechanisms and modification of stress-related signaling pathways, and uptake and translocation of metals. Altogether, this information offers a systematic understanding of how phytohormones modulate a plant’s tolerance to heavy metals and may assist in directing the development of new approaches to strengthen rice plant resistance to HM toxicity.

Antibiotic resistance in uropathogens has increased substantially and severely affected treatment of urinary tract infections (UTIs). Lately, some new formulations, including meropenem/vaborbactam (MEV), ceftazidime/avibactam (CZA), and ceftolozane/tazobactam (C/T) have been introduced to treat infections caused by drug-resistant pathogens. This study was designed to screen Enterobacteriales isolates from UTI patients and to assess their antimicrobial resistance pattern, particularly against the mentioned (new) antibiotics. Phenotypic screening of extended-spectrum β-lactamase (ESBL) and carbapenem resistance was followed by inhibitor-based assays to detect K. pneumoniae carbapenemase (KPC), metallo-β-lactamase (MBL), and class D oxacillinases (OXA). Among 289 Enterobacteriales, E. coli (66.4%) was the most predominant pathogen, followed by K. pneumoniae (13.8%) and P. mirabilis (8.3%). The isolates showed higher resistance to penicillins and cephalosporins (70–87%) than to non-β-lactam antimicrobials (33.2–41.5%). NDM production was a common feature among carbapenem-resistant (CR) isolates, followed by KPC and OXA. ESBL producers were susceptible to the tested new antibiotics, but NDM-positive isolates appeared resistant to these combinations. KPC-producers showed resistance to only C/T. ESBLs and carbapenemase encoding genes were located on plasmids and most of the genes were successfully transferred to recipient cells. This study revealed that MEV and CZA had significant activity against ESBL and KPC producers.

Colon cancer is the third most common cancer type worldwide in 2020, almost two million cases were diagnosed. As a result, providing new, highly accurate techniques in detecting colon cancer leads to early and successful treatment of this disease. This paper aims to propose a heterogenic stacking deep learning model to predict colon cancer. Stacking deep learning is integrated with pretrained convolutional neural network (CNN) models with a metalearner to enhance colon cancer prediction performance. The proposed model is compared with VGG16, InceptionV3, Resnet50, and DenseNet121 using different evaluation metrics. Furthermore, the proposed models are evaluated using the LC25000 and WCE binary and muticlassified colon cancer image datasets. The results show that the stacking models recorded the highest performance for the two datasets. For the LC25000 dataset, the stacked model recorded the highest performance accuracy, recall, precision, and F1 score (100). For the WCE colon image dataset, the stacked model recorded the highest performance accuracy, recall, precision, and F1 score (98). Stacking-SVM achieved the highest performed compared to existing models (VGG16, InceptionV3, Resnet50, and DenseNet121) because it combines the output of multiple single models and trains and evaluates a metalearner using the output to produce better predictive results than any single model. Black-box deep learning models are represented using explainable AI (XAI).

Acidosis and its associated pathologies predispose patients to develop cardiac arrhythmias and even cardiac arrest. These arrhythmias are assumed to be the result of membrane depolarization, however, the exact mechanism of depolarization during acidosis is not well defined. In our study, the model of quantum tunneling of protons is used to explain the membrane depolarization that occurs during acidosis. It is found that protons can tunnel through closed activation and inactivation gates of voltage-gated sodium channels Nav1.5 that are present in the membrane of cardiac cells. The quantum tunneling of protons results in quantum conductance, which is evaluated to assess its effect on membrane potential. The quantum conductance of extracellular protons is higher than that of intracellular protons. This predicts an inward quantum current of protons through the closed sodium channels. Additionally, the values of quantum conductance are influential and can depolarize the membrane potential according to the quantum version of the GHK equation. The quantum mechanism of depolarization is distinct from other mechanisms because the quantum model suggests that protons can directly depolarize the membrane potential, and not only through indirect effects as proposed by other mechanisms in the literature. Understanding the pathophysiology of arrhythmias mediated by depolarization during acidosis is crucial to treat and control them and to improve the overall clinical outcomes of patients.

Answering a query through a peer-to-peer database presents one of the greatest challenges due to the high cost and time required to obtain a comprehensive response. Consequently, these systems were primarily designed to handle approximation queries. In our research, the primary objective was to develop an intelligent system capable of responding to approximate set-value inquiries. This paper explores the use of particle optimization to enhance the system’s intelligence. In contrast to previous studies, our proposed method avoids the use of sampling. Despite the utilization of the best sampling methods, there remains a possibility of error, making it difficult to guarantee accuracy. Nonetheless, achieving a certain degree of accuracy is crucial in handling approximate queries. Various factors influence the accuracy of sampling procedures. The results of our studies indicate that the suggested method has demonstrated improvements in terms of the number of queries issued, the number of peers examined, and its execution time, which is significantly faster than the flood approach. Answering queries poses one of the most arduous challenges in peer-to-peer databases, as obtaining a complete answer is both costly and time-consuming. Consequently, approximation queries have been adopted as a solution in these systems. Our research evaluated several methods, including flood algorithms, parallel diffusion algorithms, and ISM algorithms. When it comes to query transmission, the proposed method exhibits superior cost-effectiveness and execution times.

Modern irrigation practices and industrial pollution can contribute to the simultaneous occurrence of salinity and heavy metal contamination in large areas of the world, resulting in significant negative effects on crop productivity and sustainability. This study aimed to investigate the growth-promoting potentials of an important endophytic fungal strain SL3 and to compare its potential with exogenous IAA (indole-3-acetic acid) in the context of salt and heavy metal stress. The strain was assessed for plant growth-promoting traits such as the production of indole-3-acetic acid, gibberellins (GA), and siderophore. We selected two important crops, mung bean and maize, and examined various physiological and biochemical characteristics under 300 mM NaCl and 2.5 mM Pb stress conditions, with and without the application of IAA and SL3. This study’s results demonstrated that both IAA and SL3 positively impacted the growth and development of plants under normal and stressed conditions. In NaCl and Pb-induced stress conditions, the growth of mung bean and maize plants was significantly reduced. However, the application of IAA and SL3 helped to alleviate stress, leading to a significant increase in shoot/root length and weight compared to IAA and SL3 non-treated plants. The results revealed that photosynthetic pigments, accumulation of catalase (CAT), phenolic contents, polyphenol oxidase, and flavanols are higher in the IAA and SL3-treated plants than in the non-inoculated plants. This study’s findings revealed that applying the SL3 fungal strain positively influenced various physiological and biochemical processes in tested plant species under normal and stress conditions of NaCl and Pb. These findings also suggested that SL3 could be a potential replacement for widely used IAA to promote plant growth by improving photosynthetic efficiency, reducing oxidative stress, and enhancing metabolic activities in plants, including mung and maize. Moreover, this study highlights that SL3 has synergistic effects with IAA in enhancing resilience to salt and heavy stress and offers a promising avenue for future agricultural applications in salt and heavy metal-affected regions.

The goal of an antiviral agent research is to find an antiviral drug that reduces viral growth without harming healthy cells. Transformations of the virus, new viral strain developments, the resistance of viral pathogens, and side effects are the current challenges in terms of discovering antiviral drugs. The time has come and it is now essential to discover a natural antiviral agent that has the potential to destroy viruses without causing resistance or other unintended side effects. The pharmacological potency of thymoquinone (TQ) against different communicable and non-communicable diseases has been proven by various studies, and TQ is considered to be a safe antiviral substitute. Adjunctive immunomodulatory effects in addition to the antiviral potency of TQ makes it a major compound against viral infection through modulating the production of nitric oxide and reactive oxygen species, decreasing the cytokine storm, and inhibiting endothelial dysfunction. Nevertheless, TQ’s low oral bioavailability, short half-life, poor water solubility, and conventional formulation are barriers to achieving its optimal pharmacologic benefits. Nano-formulation proposes numerous ways to overcome these obstacles through a small particle size, a big surface area, and a variety of surface modifications. Nano-based pharmaceutical innovations to combat viral infections using TQ are a promising approach to treating surmounting viral infections.

Metallic nanoparticles have received a significant amount of reflection over a period of time, attributed to their electronic, specific surface area, and surface atom properties. The biogenic synthesis of iron oxide nanoparticles (FeONPs) is demonstrated in this study. The green synthesis of metallic nanoparticles (NPs) is acquiring considerable attention due to its environmental and economic superiorities over other methods. Leptolyngbya sp. L-2 extract was employed as a reducing agent, and iron chloride hexahydrate (FeCl3·6H2O) was used as a substrate for the biogenic synthesis of FeONPs. Different spectral methods were used for the characterization of the biosynthesized FeONPs, ultraviolet-visible (UV-Vis) spectroscopy gave a surface plasmon resonance (SPR) peak of FeONPs at 300 nm; Fourier transform infrared (FTIR) spectral analysis was conducted to identify the functional groups responsible for both the stability and synthesis of FeONPs. The morphology of the FeONPs was investigated using scanning electron microscopy (SEM), which shows a nearly spherical shape, and an X-ray diffraction (XRD) study demonstrated their crystalline nature with a calculated crystallinity size of 23 nm. The zeta potential (ZP) and dynamic light scattering (DLS) measurements of FeONPs revealed values of −8.50 mV, suggesting appropriate physical stability. Comprehensive in-vitro pharmacogenetic properties revealed that FeONPs have significant therapeutic potential. FeONPs have been reported to have potential antibacterial and antifungal properties. Dose-dependent cytotoxic activity was shown against Leishmania tropica promastigotes (IC50: 10.73 µg/mL) and amastigotes (IC50: 16.98 µg/mL) using various concentrations of FeONPs. The cytotoxic potential was also investigated using brine shrimps, and their IC50 value was determined to be 34.19 µg/mL. FeONPs showed significant antioxidant results (DPPH: 54.7%, TRP: 49.2%, TAC: 44.5%), protein kinase (IC50: 96.23 µg/mL), and alpha amylase (IC50: 3745 µg/mL). The biosafety of FeONPs was validated by biocompatibility tests using macrophages (IC50: 918.1 µg/mL) and red blood cells (IC50: 2921 µg/mL). In conclusion, biogenic FeONPs have shown potential biomedical properties and should be the focus of more studies to increase their nano-pharmacological significance for biological applications.

Oral cancer (OC) is one of the most common forms of head and neck cancer and continues to have the lowest survival rates worldwide, even with advancements in research and therapy. The prognosis of OC has not significantly improved in recent years, presenting a persistent challenge in the biomedical field. In the field of oncology, artificial intelligence (AI) has seen rapid development, with notable successes being reported in recent times. This systematic review aimed to critically appraise the available evidence regarding the utilization of AI in the diagnosis, classification, and prediction of oral cancer (OC) using histopathological images. An electronic search of several databases, including PubMed, Scopus, Embase, the Cochrane Library, Web of Science, Google Scholar, and the Saudi Digital Library, was conducted for articles published between January 2000 and January 2023. Nineteen articles that met the inclusion criteria were then subjected to critical analysis utilizing QUADAS-2, and the certainty of the evidence was assessed using the GRADE approach. AI models have been widely applied in diagnosing oral cancer, differentiating normal and malignant regions, predicting the survival of OC patients, and grading OC. The AI models used in these studies displayed an accuracy in a range from 89.47% to 100%, sensitivity from 97.76% to 99.26%, and specificity ranging from 92% to 99.42%. The models’ abilities to diagnose, classify, and predict the occurrence of OC outperform existing clinical approaches. This demonstrates the potential for AI to deliver a superior level of precision and accuracy, helping pathologists significantly improve their diagnostic outcomes and reduce the probability of errors. Considering these advantages, regulatory bodies and policymakers should expedite the process of approval and marketing of these products for application in clinical scenarios.

Voltage-gated channels are crucial in action potential initiation and propagation and there are many diseases and disorders related to them. Additionally, the classical mechanics are the main mechanics used to describe the function of the voltage-gated channels and their related abnormalities. However, the quantum mechanics should be considered to unravel new aspects in the voltage-gated channels and resolve the problems and challenges that classical mechanics cannot solve. In the present study, the aim is to mathematically show that quantum mechanics can exhibit a powerful tendency to unveil novel electrical features in voltage-gated channels and be used as a promising tool to solve the problems and challenges in the pathophysiology of excitability-related diseases. The model of quantum tunneling of ions through the intracellular hydrophobic gate is used to evaluate the influence of membrane potential and gating free energy on the tunneling probability, single channel conductance, and quantum membrane conductance. This evaluation is mainly based on graphing the mathematical relationships between these variables. The obtained mathematical graphs showed that ions can achieve significant quantum membrane conductance, which can affect the resting membrane potential and the excitability of cells. In the present work, quantum mechanics reveals original electrical properties associated with voltage-gated channels and introduces new insights and implications into the pathophysiology of excitability- related disorders. In addition, the present work sets a mathematical and theoretical framework that can be utilized to conduct experimental studies in order to explore the quantum aspects of voltage-gated channels and the quantum bioelectrical property of biological membranes.

Respiratory viral infections are a leading global cause of disease with multiple viruses detected in 20–30% of cases, and several viruses simultaneously circulating. Some infections with unique viral copathogens result in reduced pathogenicity, while other viral pairings can worsen disease. The mechanisms driving these dichotomous outcomes are likely variable and have only begun to be examined in the laboratory and clinic. To better understand viral–viral coinfections and predict potential mechanisms that result in distinct disease outcomes, we first systematically fit mathematical models to viral load data from ferrets infected with respiratory syncytial virus (RSV), followed by influenza A virus (IAV) after 3 days. The results suggest that IAV reduced the rate of RSV production, while RSV reduced the rate of IAV infected cell clearance. We then explored the realm of possible dynamics for scenarios that had not been examined experimentally, including a different infection order, coinfection timing, interaction mechanisms, and viral pairings. IAV coinfection with rhinovirus (RV) or SARS-CoV-2 (CoV2) was examined by using human viral load data from single infections together with murine weight-loss data from IAV-RV, RV-IAV, and IAV-CoV2 coinfections to guide the interpretation of the model results. Similar to the results with RSV-IAV coinfection, this analysis shows that the increased disease severity observed during murine IAV-RV or IAV-CoV2 coinfection was likely due to the slower clearance of IAV-infected cells by the other viruses. The improved outcome when IAV followed RV, on the other hand, could be replicated when the rate of RV infected cell clearance was reduced by IAV. Simulating viral–viral coinfections in this way provides new insights about how viral–viral interactions can regulate disease severity during coinfection and yields testable hypotheses ripe for experimental evaluation.

Neuroanatomy is always a challenging topic for veterinary students. It is widely accepted that understanding the anatomy of the central nervous system (CNS) is essential to explain many of the pathological processes that affect the brain. Although its study has varied over time to achieve this goal, in human and veterinary medicine it is difficult to find a teaching method that associates normal anatomy with pathological alterations of the brain. For the first time, we have created an educational tool that combines neuroanatomy and neuropathology, using different magnetic resonance (MR) images as a basis and EspINA software as analyzer, to obtain segmented structures and 3D reconstructions of the dog brain. We demonstrate that this combination is an optimal tool to help anatomists to understand the encephalon, and additionally to help clinicians to recognize illness including a multitude of neurological problems. In addition, we have tried to see whether photogrammetry, which is a common technique in other sciences, for example geology, could be useful to teach veterinary neuroanatomy. Although we still need further investigations, we have been able to generate 3D reconstructions of the whole brain, with very promising results to date.

Naringenin (NRG) is one of the most important naturally occurring flavonoids, predominantly found in some edible fruits, such as citrus species and tomatoes. It has several biological activities, such as antioxidant, antitumor, antiviral, antibacterial, anti-inflammatory, antiadipogenic, and cardioprotective effects. The heavy metal lead is toxic and triggers oxidative stress, which causes toxicity in many organs, including the liver and brain. This study explored the potential protective role of NRG in hepato- and neurotoxicity caused by lead acetate in rats. Four groups of ten male albino rats were included: group 1 was a control, group 2 was orally treated with lead acetate (LA) at a dose of 500 mg/kg BW, group 3 was treated with naringenin (NRG) at a dose of 50 mg/kg BW, and group 4 was treated with 500 mg/kg LA and 50 mg/kg NRG for 4 weeks. Then, blood was taken, the rats were euthanized, and liver and brain tissues were collected. The findings revealed that LA exposure induced hepatotoxicity with a significant increase in liver function markers (p < 0.05). In addition, albumin and total protein (TP) and the albumin/globulin ratio (A/G ratio) (p < 0.05) were markedly lowered, whereas the serum globulin level (p > 0.05) was unaltered. LA also induced oxidative damage, demonstrated by a significant increase in malonaldehyde (MDA) (p < 0.05), together with a pronounced antioxidant system reduction (SOD, CAT, and GSH) (p < 0.05) in both liver and brain tissues. Inflammation of the liver and brain caused by LA was indicated by increased levels of nuclear factor kappa beta (NF-κβ) and caspase-3, (p < 0.05), and the levels of B-cell lymphocyte-2 (BCL-2) and interleukin-10 (IL-10) (p < 0.05) were decreased. Brain tissue damage induced by LA toxicity was demonstrated by the downregulation of the neurotransmitters norepinephrine (NE), dopamine (DA), serotonin (5-HT), and creatine kinase (CK-BB) (p < 0.05). Additionally, the liver and brain of LA-treated rats displayed notable histopathological damage. In conclusion, NRG has potential hepato- and neuroprotective effects against lead acetate toxicity. However, additional research is needed in order to propose naringenin as a potential protective agent against renal and cardiac toxicity mediated by lead acetate.

Cadmium (Cd) and lead (Pb) are global environmental pollutants. In this study, Nostoc sp. MK-11 was used as an environmentally safe, economical, and efficient biosorbent for the removal of Cd and Pb ions from synthetic aqueous solutions. Nostoc sp. MK-11 was identified on a morphological and molecular basis using light microscopic, 16S rRNA sequences and phylogenetic analysis. Batch experiments were performed to determine the most significant factors for the removal of Cd and Pb ions from the synthetic aqueous solutions using dry Nostoc sp. MK1 biomass. The results indicated that the maximum biosorption of Pb and Cd ions was found under the conditions of 1 g of dry Nostoc sp. MK-11 biomass, 100 mg/L of initial metal concentrations, and 60 min contact time at pH 4 and 5 for Pb and Cd, respectively. Dry Nostoc sp. MK-11 biomass samples before and after biosorption were characterized using FTIR and SEM. A kinetic study showed that a pseudo second order kinetic model was well fitted rather than the pseudo first order. Three isotherm models Freundlich, Langmuir, and Temkin were used to explain the biosorption isotherms of metal ions by Nostoc sp. MK-11 dry biomass. Langmuir isotherm, which explains the existence of monolayer adsorption, fitted well to the biosorption process. Considering the Langmuir isotherm model, the maximum biosorption capacity (qmax) of Nostoc sp. MK-11 dry biomass was calculated as 75.757 and 83.963 mg g−1 for Cd and Pb, respectively, which showed agreement with the obtained experimental values. Desorption investigations were carried out to evaluate the reusability of the biomass and the recovery of the metal ions. It was found that the desorption of Cd and Pb was above 90%. The dry biomass of Nostoc sp. MK-11 was proven to be efficient and cost-effective for removing Cd and especially Pb metal ions from the aqueous solutions, and the process is eco-friendly, feasible, and reliable.

Staphylococcus aureus is a prominent cause of food-borne diseases worldwide. Enterotoxigenic strains of this bacteria are frequently found in raw milk, and some of these strains are resistant to antimicrobials, posing a risk to consumers. The main objectives of this study were to determine the antimicrobial resistance pattern of S. aureus in raw milk and to detect the presence of mecA and tetK genes in it. A total of 150 milk samples were obtained aseptically from lactating cattle, including Holstein Friesian, Achai, and Jersey breeds, maintained at different dairy farms. The milk samples were checked for the presence of S. aureus, and it was detected in 55 (37%) of them. The presence of S. aureus was verified by culturing on selective media, gram staining, and performing coagulase and catalase tests. Further confirmation was performed through PCR with a species-specific thermonuclease (nuc) gene. Antimicrobial susceptibility testing of the confirmed S. aureus was then determined by using the Kirby–Bauer disc diffusion technique. Out of the 55 confirmed S. aureus isolates, 11 were determined to be multidrug-resistant (MDR). The highest resistance was found to penicillin (100%) and oxacillin (100%), followed by tetracycline (72.72%), amikacin (27.27%), sulfamethoxazole/trimethoprim (18.18%), tobramycin (18.18%), and gentamycin (9.09%). Amoxicillin and ciprofloxacin were found to be susceptible (100%). Out of 11 MDR S. aureus isolates, the methicillin resistance gene (mecA) was detected in 9 isolates, while the tetracycline resistance gene (tetK) was found in 7 isolates. The presence of these methicillin- and tetracycline-resistant strains in raw milk poses a major risk to public health, as they can cause food poisoning outbreaks that can spread rapidly through populations. Our study concludes that out of nine empirically used antibiotics, amoxicillin, ciprofloxacin, and gentamicin were highly effective against S. aureus compared to penicillin, oxacillin, and tetracycline.

Recognition of lying is a more complex cognitive process than truth-telling because of the presence of involuntary cognitive cues that are useful to lie recognition. Researchers have proposed different approaches in the literature to solve the problem of lie recognition from either handcrafted and/or automatic lie features during court trials and police interrogations. Unfortunately, due to the cognitive complexity and the lack of involuntary cues related to lying features, the performances of these approaches suffer and their generalization ability is limited. To improve performance, this study proposed state transition patterns based on hands, body motions, and eye blinking features from real-life court trial videos. Each video frame is represented according to a computed threshold value among neighboring pixels to extract spatial–temporal state transition patterns (STSTP) of the hand and face poses as involuntary cues using fully connected convolution neural network layers optimized with the weights of ResNet-152 learning. In addition, this study computed an eye aspect ratio model to obtain eye blinking features. These features were fused together as a single multi-modal STSTP feature model. The model was built using the enhanced calculated weight of bidirectional long short-term memory. The proposed approach was evaluated by comparing its performance with current state-of-the-art methods. It was found that the proposed approach improves the performance of detecting lies.

Natural antioxidant polyphenolic compounds obtained from different plants are considered antioxidants for curing various chronic pathological diseases such as cardiovascular disorders and cancer. Quercetin (a polyphenolic flavonol) has attracted much attention from dietitians and medicinal chemists due to its wide variety of pharmacological activities, including anti-diabetic, anti-hypertensive, anti-carcinogenic, anti-asthmatic, anti-viral, and antioxidant activities. Furthermore, structurally, it is well suited to stabilize emulsions. The present review depicts the important role of the quercetin nanoemulsion technique, used to enhance the solubility of target materials both in vivo and in vitro as well as to decrease the risk of degradation and metabolism of drugs. Researchers have used cryo-TEM to study the morphology of quercetin nanoemulsions. The effects of various parameters such as pH, salts, and solvent concentration on quercetin nanoemulsion have been investigated for quercetin nanoemulsion. Many studies have used UV–Vis spectroscopy and HPLC for the characterization of these particles such as solubility, stability, and encapsulating efficiency.

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Chronic kidney disease (CKD) refers to the gradual decline of kidney function over months or years. Early detection of CKD is crucial and significantly affects a patient’s decreasing health progression through several methods, including pharmacological intervention in mild cases or hemodialysis and kidney transportation in severe cases. In the recent past, machine learning (ML) and deep learning (DL) models have become important in the medical diagnosis domain due to their high prediction accuracy. The performance of the developed model mainly depends on choosing the appropriate features and suitable algorithms. Accordingly, the paper aims to introduce a novel ensemble DL approach to detect CKD; multiple methods of feature selection were used to select the optimal selected features. Moreover, we study the effect of the optimal features chosen on CKD from the medical side. The proposed ensemble model integrates pretrained DL models with the support vector machine (SVM) as the metalearner model. Extensive experiments were conducted by using 400 patients from the UCI machine learning repository. The results demonstrate the efficiency of the proposed model in CKD prediction compared to other models. The proposed model with selected features using mutual_info_classi obtained the highest performance.

Diabetes mellitus is linked to both short-term and long-term health problems. Therefore, its detection at a very basic stage is of utmost importance. Research institutes and medical organizations are increasingly using cost-effective biosensors to monitor human biological processes and provide precise health diagnoses. Biosensors aid in accurate diabetes diagnosis and monitoring for efficient treatment and management. Recent attention to nanotechnology in the fast-evolving area of biosensing has facilitated the advancement of new sensors and sensing processes and improved the performance and sensitivity of current biosensors. Nanotechnology biosensors detect disease and track therapy response. Clinically efficient biosensors are user-friendly, efficient, cheap, and scalable in nanomaterial-based production processes and thus can transform diabetes outcomes. This article is more focused on biosensors and their substantial medical applications. The highlights of the article consist of the different types of biosensing units, the role of biosensors in diabetes, the evolution of glucose sensors, and printed biosensors and biosensing systems. Later on, we were engrossed in the glucose sensors based on biofluids, employing minimally invasive, invasive, and noninvasive technologies to find out the impact of nanotechnology on the biosensors to produce a novel device as a nano-biosensor. In this approach, this article documents major advances in nanotechnology-based biosensors for medical applications, as well as the hurdles they must overcome in clinical practice.

Diabetes and its complications, such as delayed wound healing, are increasing at an alarming rate in India, putting an enormous strain on the country’s limited healthcare resources. Hence, the present study proposes to screen/identify the possible mechanisms and to study the effect of the flavonoid-enriched fraction of Selaginella bryopteris extract against human keratinocyte cell lines (HaCaT) and streptozocin (STZ)-induced diabetic wounds in a male Wistar rat model. Chemical profiling was performed by an MTT assay. The obtained GC–MS analysis results showed the presence of amentoflavone, gallic acid, imidazole, palmitic acid, catechine, L-fucitol, lupeol, and myo-inositol as the major bioactive phytoconstituents. S. bryopteris induces the generation of ROS, the condensation of chromatin in the nucleus, and changes in the membrane potential of mitochondria in HaCaT cell lines. An S. bryopteris-dependent induction of apoptosis-mediated cell death in HaCaT cell lines was confirmed by an AO/PI analysis. Mitochondrial depolarization was reflected in JC-1 staining of cells. The wound size was reduced and epithelialization was enhanced. Keratinocyte migration decreased interleukins, TNF-α, IL-2, and IL-6 and the expression of pro-apoptotic (p53, caspase-3, caspase-9, and Bax) and anti-apoptotic (Bcl-2) genes in a dose-dependent manner. Keratinocyte migration increased antioxidant enzyme levels (CAT, SOD, MDA, and GSH). Wound healing is facilitated through the mitochondria-mediated apoptosis pathway, revealing a new area of diabetic wound therapy.

There are many studies that focus on extracting harmonics from both DC and AC sides of grid-interfaced photovoltaic (PV) systems. Based on these studies, the paper introduces an efficient method depending on hybrid DC voltage, and an active and reactive power (DC-V PQ) control scheme in a single-stage three-phase grid-interfaced PV system. The proposed scheme is designed to regulate DC voltage to minimize power loss and energy share between the network reconfiguration and the utility grid. Moreover, the technique is more effective at dealing with uncertainty and has higher reliability under various operating scenarios. These operations are the insertion of linear load 1, nonlinear load, and linear load 2. Moreover, a novel objective function (OF) is developed to improve the dynamic response of the system. OF is coupled with a particle swarm optimization (PSO) algorithm and a gradient optimization (GBO) algorithm. The analysis and the comparative study prove the superiority of GBO with counterfeits algorithm.

Nonalcoholic fatty liver disease (NAFLD) is common among Saudi patients with type 2 diabetes (T2DM). However, recommended clinical procedures to detect it are unavailable in many locations. Therefore, better and more available diagnostic biomarkers for NAFLD are needed. Various serum parameters were suggested, and algorithms that employ routine measurements in clinical practice have been developed for the prediction of fat stores in the liver in different populations. However, no such studies have been conducted on Saudis. We aimed to compare selected biochemical markers and calculated indices in T2DM patients diagnosed with NAFLD and patients without NAFLD to find the best markers associated with NAFLD. A cross-sectional study was employed to recruit 67 people with T2DM from endocrine outpatient clinics at King Abdul-Aziz University Hospital. NAFLD was detected by ultrasonography in 28 patients. Demographic information, anthropometric, and blood pressure (BP) measurements were taken. Fasting blood samples were obtained to measure glucose, glycated haemoglobin, lipid profile, liver function tests, and highly sensitive C-reactive protein. Fatty liver index, hepatic steatosis index, NAFLD-liver fat score, and triglyceride and glucose index were calculated. Following stepwise forward likelihood ratio regression with independent variables included in one model using binary logistic regression with age and waist circumference (WC) entered as covariates, elevated diastolic BP and low high-density lipoprotein- cholesterol remained significantly associated with NAFLD (p = 0.002 and 0.03, respectively). However, none of the investigated indices could be used to diagnose the disease adequately due to low specificity, even after calculating new cut-off values. Investigating novel markers and adjusting existing equations used to calculate indices to improve sensitivity and specificity in our population is needed.

Clarithromycin (CLR), categorized as a Biopharmaceutical Classification System class II drug, has several gastrointestinal tract side effects and an extremely unpalatable bitter taste. The current study aimed to design transdermal patch-embedded CLR niosomes to overcome the aforementioned CLR-related challenges. Various niosomal formulations were successfully fabricated and characterized for their morphology, size, in vitro release, and antimicrobial efficacy. Subsequently, the CLR niosomes were loaded into transdermal patches using the solvent casting method. The polydispersity index of the niosomes ranged from 0.005 to 0.360, indicating the uniformity of the niosomes. The encapsulating efficiency (EE)% varied from 12 to 86%. The optimal Chol: surfactant ratio for drug release was found to be 0.5:1. In addition, the encapsulation of CLR into niosomal nanovesicles did not reduce the antibacterial activity of the CLR. The niosomal patch had a significantly higher permeability coefficient of CLR than the conventional patch. In addition to that, a shear-thinning behavior was observed in the niosomal gels before loading them into a niosomal patch. The flux (Jss) of the niosomal patch was significantly higher than the conventional patch by more than 200 times. In conclusion, niosome-based transdermal patches could be a promising method for the transdermal drug delivery of class II drugs and drugs experiencing GIT side effects.

The present study investigated the interaction effects (additive, synergistic, and antagonistic) of different groups of spices, their constituent phenolic compounds, and synthetic antioxidants on the total phenol (TP) content and antioxidant activity, as measured by the ferric-reducing antioxidant power (FRAP) of the mixtures. The results showed that there was an additive effect in all the groups studied, except for the group containing turmeric or curcumin. The groups containing turmeric or curcumin showed a moderate synergistic effect. Among the groups of spices, the highest summated TP (50.6 mg GAE/mL) and FRAP (106.2 mg Trolox/mL) values were observed in the group containing clove, cinnamon, pimento, rosemary, oregano, and cardamom. In the case of the groups of pure phenolics, the highest summated TP (364.96 mg GAE/mL) and FRAP (1124.25 mg Trolox/mL) values were observed in the group containing eugenol, acetyl eugenol, caffeic acid, and protocatechuic acid. The summated and combined TP and FRAP values of the samples correlated highly with the correlation coefficients (r2) of 0.976 and 0.988, respectively, inferring an additive nature of the interaction effect in most of the groups studied. The interactions of phenolics in mixtures are very complex, being affected by a number of factors, and requires more investigations. The current study will add considerable knowledge to the existing literature to understand the diversity and mechanisms of interactions.

We detected a new target quantitative trait locus (QTL) for lodging resistance in rice by analyzing lodging resistance to typhoons (Maysak and Haishen) using a scale from 0 (no prostrating) to 1 (little prostrating or prostrating) to record the resistance score in a Cheongcheong/Nagdong double haploid rice population. Five quantitative trait loci for lodging resistance to typhoons were detected. Among them, qTyM6 and qTyH6 exhibited crucial effects of locus RM3343–RM20318 on chromosome 6, which overlaps with our previous rice lodging studies for the loci qPSLSA6-2, qPSLSB6-5, and qLTI6-2. Within the target locus RM3343–RM20318, 12 related genes belonging to the cytochrome P450 protein family were screened through annotation. Os06g0599200 (OsTyM/Hq6) was selected for further analysis. We observed that the culm and panicle lengths were positively correlated with lodging resistance to typhoons. However, the yield was negatively correlated with lodging resistance to typhoons. The findings of this study improve an understanding of rice breeding, particularly the culm length, early maturing, and heavy panicle varieties, and the mechanisms by which the plant’s architecture can resist natural disasters such as typhoons to ensure food safety. These results also provide the insight that lodging resistance in rice may be associated with major traits such as panicle length, culm length, tiller number, and heading date, and thereby improvements in these traits can increase lodging resistance to typhoons. Moreover, rice breeding should focus on maintaining suitable varieties that can withstand the adverse effects of climate change in the future and provide better food security.

Industry 5.0 is projected to be an exemplary improvement in digital transformation allowing for mass customization and production efficiencies using emerging technologies such as universal machines, autonomous and self-driving robots, self-healing networks, cloud data analytics, etc., to supersede the limitations of Industry 4.0. To successfully pave the way for acceptance of these technologies, we must be bound and adhere to ethical and regulatory standards. Presently, with ethical standards still under development, and each region following a different set of standards and policies, the complexity of being compliant increases. Having vague and inconsistent ethical guidelines leaves potential gray areas leading to privacy, ethical, and data breaches that must be resolved. This paper examines the ethical dimensions and dilemmas associated with emerging technologies and provides potential methods to mitigate their legal/regulatory issues.

Oat is an essential Rabi crop commonly used as green fodder. The nutritional requirements of oats are higher than those of other Rabi fodder crops. Higher doses of inorganic fertilizers are required to meet this demand, which is not economical for fodder production. This study evaluates the best economical dose of integrated nutrient management for attaining higher yield and better nutritional quality of oat. The experiment was conducted on the Agronomy Research Farm, University of Agriculture, Faisalabad, Punjab, Pakistan. The seed varieties used in this experiment were Oat-2011 Sargodha and Oat-F-411 (2021) Faisalabad. The experimental treatments were organized in factorial Randomized Complete Block Design (RCBD) arrangements, with each treatment replicated three times. The results revealed that treatment (T4) 50% RDF + 5 t/ha. Farmyard Manure + seed inoculation azotobacter was found to be the most appropriate than all other treatments.

Promising Land and Water Conservation Practices (LWCPs) play a vital role in restraining floods and keeping the land productive. Floods are usually destructive and increase the risk of drowning, waterborne diseases, malnutrition, and multiple long-term knock-on effects. Similarly, the 2022 monsoon season has prompted the most severe flood in Pakistan. The main objective of this review is to highlight the importance of LWCPs as an adaptation strategy for flood mitigation. Moreover, different LWCPs are discussed concerning studies carried out in different regions and published in scientific journals, technical reports, and notes from experts. It was observed that both the in situ and ex situ LWCPs have a significant effect on reducing land degradation and flood control. Additionally, most of the reviewed studies showed a positive impact of LWCPs on agricultural productivity, primarily due to the retention of nutrients and moisture. Hence, land conservation practices including biological and agronomic measures (i.e., contour farming, conservation tillage, strip cropping, vegetation, etc.), and mechanical or engineering methods (i.e., check dams, bunding, ponds/reservoirs, etc.) are aimed at reducing the run-off velocity and mitigating the floods. The results of this study will encourage the stakeholders to adopt LWCPs to lessen flood hazards and uplift agricultural production by limiting the land degradation processes.

The application of water-retention polymers with improved fertilizers is a better crop-growing technique, especially in soils where the water-retention capacity is low. In Pakistan, different types of fertilizers, such as urea, DAP, MOP or SOP, are used from sowing to harvesting of crops. The use of water-retention polymers in low water-retaining soils is very important to increase its retention time. The experiment was conducted on half an acre of land in FFC Research Center located in Dyyalgarh, Millat Rd., near Deputy Wala interchange M4, Faisalabad, Punjab, Pakistan. The seed variety used in this experiment is zincole and the seed rate is 50 kg/acre. This experiment contains four different treatments, and each treatment contains three replicates. In T1, no water-retention polymers were used, while T2 was treated with standard and neem-coated urea under no water-retention polymer application. While in T3 and T4 recommended doses of polymers were used with standard and neem-coated urea. Irrigation scheduling was determined using tensiometers.. The research is aimed to keep moisture available in the root zone for better growth. For proper moisture monitoring tensiometers were installed.