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Background: Fish is considered an important food because it includes main nutrients (proteins, fats, and ash) and micronutrients (vitamins and minerals). The assessment of fish nutritional content data may offer crucial recommendations regarding freshwater fish consumption and preserving human well-being. Aim: Evaluate the safety and quality properties of Nasser Lake fish, Aswan, Egypt. Methods: A total of 250 samples, 50 of each Nile tilapia, Nile perch, Zander, Catfish, and Elephant-snout, from Nasser Lake, Aswan, Egypt; beheaded, eviscerated, filleted, and minced for determination of proximate analysis, amino acid, fatty acids, minerals and heavy metal, histamine content, cholesterol content, and sensory assessment. Results: The proximate analysis showed that all the samples examined were of good protein sources, with mean values ranging from 15.92% to 22.89%. Nile perch exhibits the highest levels of total fatty acids and amino acids. Heavy metal concentrations varied considerably among the analyzed samples, with a significant variance in the detection of metals among the examined fish. The findings show low histamine and cholesterol levels in the examined species, and were in accordance with those set by the National Food Safety Authority (NFSA) and the European Union Commission (EC). Accordingly, all samples are accepted based on their sensory properties. Conclusion: Nasser Lake fish are of high nutritional value and have an excellent supply of amino and fatty acids. [Open Vet J 2024; 14(6.000): 1403-1416]

BackgroundThe relationship between chronic hepatitis B (CHB) infection and natural killer (NK) cell dysfunction is well-established, but the specific role of HBV viral antigens in driving NK cell impairment in patients with CHB remains unclear. This study investigates the modulatory effects of hepatitis B virus subviral particles (HBVsvp, a representative model for HBsAg) on the phenotypic regulation (activating and inhibitory receptors), cytokine production and cytotoxic potential of peripheral blood mononuclear cell-derived natural killer cells (PBMCs-derived NK cell), which contributes to NK cell dysfunction in CHB infection, potentially serving as an effective HBV immune evasion strategy by the virus.MethodsNK cells were isolated from peripheral blood of patients with CHB (n=5) and healthy individuals (n=5), stimulated with HBVsvp. Subsequent flow cytometric characterization involved assessing changes in activating (NKp46 and NKG2D) and inhibitory (CD94) receptors expression, quantifying TNF-α and IFN- γ cytokine secretion, and evaluating the cytotoxic response against HepG2.2.15 cells with subsequent HBVsvp quantification.ResultsIn CHB patients, in vitro exposure of PBMCs-derived NK cell with HBVsvp (represent HBsAg model) significantly reduced NK cell-activating receptors expression (P = 0.022), increased expression of CD94 + NK cells (p = 0.029), accompanied with a reduced TNF-α - IFN-γ cytokine levels, and impaired cytotoxic capacity (evidenced by increased cell proliferation and elevated HBVsvp levels in co-cultures with HepG2.2.15 cells in a time-dependent), relative to healthy donors.ConclusionThese findings suggest that HBVsvp may induce dysfunctional NK cell responses characterized by phenotypic imbalance with subsequent reduction in cytokine and cytotoxic levels, indicating HBVsvp immunosuppressive effect that compromises antiviral defense in CHB patients. These data enhance our understanding of NK cell interactions with HBsAg and highlight the potential for targeting CD94 inhibitory receptors to restore NK cell function as an immunotherapeutic approach. Further clinical research is needed to validate these observations and establish their utility as reliable biomarkers.

Diabetes mellitus (DM) is the most prevalent cause of diabetic retinopathy (DRP). DRP has been recognized for a long time as a microvascular disease. Many drugs were used to treat DRP, including vildagliptin (VLD). In addition to its hypoglycemic effect, VLD minimizes ocular inflammation and improves retinal blood flow for individuals with type 2 diabetes mellitus. Nevertheless, VLD can cause upper respiratory tract infections, diarrhea, nausea, hypoglycemia, and poor tolerability when taken orally regularly due to its high water solubility and permeability. Effective ocular administration of VLD is achieved using solid lipid nanoparticles (SLNPs), which improve corneal absorption, prolonged retention, and extended drug release. Ocuserts (OCUs) are sterile, long-acting ocular dosage forms that diminish the need for frequent dosing while improving residence time and stability. Therefore, this study intends to develop VLD solid lipid nanoparticle OCUs (VLD-SLNPs-OCUs) to circumvent the issues commonly associated with VLD. SLNPs were prepared using the double-emulsion/melt dispersion technique. The optimal formula has been implemented in OCUs. Optimization and development of VLD-SLNPs-OCUs were performed using a Box-Behnken Design (BBD). VLD-SLNPs-OCUs loading efficiency was 95.28 ± 2.87%, and differential scanning calorimetry data (DSC) showed the full transformation of VLD to an amorphous state and the excellent distribution in the prepared OCUs matrices. The in vivo release of VLD from the optimized OCUs after 24 h was 35.12 ± 2.47%, consistent with in vitro drug release data of 36.89 ± 3.11. The optimized OCUs are safe to use in the eye, as shown by the ocular irritation test. VLD-SLNPs-OCUs provide extended VLD release, an advantageous alternative to conventional oral dose forms, resulting in fewer systemic adverse effects and less variation in plasma drug levels. VLD-SLNPs-OCUs might benefit retinal microvascular blood flow beyond blood glucose control and may be considered a promising approach to treating diabetic retinopathy.

Our attention concenters on deriving diverse forms of the soliton arising from the Myrzakulov-Lakshmanan XXXII (M-XXXII) that describes the generalized Heisenberg ferromagnetic equation. This model has been solved numerically only using the N-fold Darboux Transformation method, not solved analytically before. We will derive new types of the analytical soliton solutions that will be constructed for the first time in the framework of three impressive schemas that are prepared for this target. These three techniques are the Generalized Kudryashov scheme (GKS), the (G'/G)-expansion scheme and the extended direct algebraic scheme (EDAS). Moreover, we will establish the 2D, 3D graphical simulations that clear the new dynamic properties of our achieved solutions.

Given the cruciality of the thawing process to fish and their products as well as its impact on fish quality, this study aims to assess how different thawing techniques affect bacteriological changes, microstructure, and antioxidant activity enzymes in frozen fish fillets. As revealed, microwave thawing (MT) is a quick method, showing low microbial count and the least activity of antioxidant enzymes, while flowing water thawing (WT) preserves the fish microstructure.

Key Clinical Message Mycotic pseudoaneurysms can be a serious and life threatening complication of left sided infective endocarditis. They most commonly affect the major axial vessels. Profunda femoris artery (PFA) aneurysms are rare and present in only 0.5% of all peripheral aneurysms, regardless of the underlying etiology. We present a case of a patient who underwent mitral valve repair for severe mitral regurgitation secondary to culture negative IE which was complicated by multiple mycotic pseudoaneurysm. The PFA pseudoaneurysm which was affected and was complicated with a large hematoma compressing the femoral nerve. This was managed by a staged hybrid approach. Endovascular stenting was performed first to seal the pseudoaneurysm and facilitate open surgical repair using a reversed interposition saphenous vein graft. To the best of our knowledge, this is the first reported case of a PFA mycotic aneurysm (MA) being managed by a hybrid approach using endo‐vascular and open surgical repair. MAs and pseudoaneurysms are complex and life threatening conditions requiring meticulous planning for optimal management. Endovascular stenting can be considered as an alternative to surgical management in certain cases or as a bridge to definitive open surgical repair depending on anatomical location and associated complications.

Abstract Background Chronic hepatitis B virus (HBV) infection is a serious global health concern, with an increased incidence and risk of developing cirrhosis and hepatocellular carcinoma (HCC). Patients chronically infected with HBV are likely to experience chronic oxidative stress, leading to mitochondrial dysfunction. Photobiomodulation is induced by the absorption of low-level laser therapy (LLLT) with a red or infrared laser by cytochrome C oxidase enzyme, resulting in mitochondrial photoactivation. Although it is widely used in clinical practice, the use of LLL as adjuvant therapy for persistent HBV infection is uncommon. This study aimed to investigate the effect of LLLT dosage from 2 J/cm2 to 10 J/cm2 of red diode laser (650 nm) on both hepatoma cell lines (HepG2.2.15 [integrated HBV genome stable cell model] and non-integrated HepG2), with a subsequent impact on HBVsvp production. Methods The present study evaluated the effects of different fluences of low-level laser therapy (LLLT) irradiation on various aspects of hepatoma cell behavior, including morphology, viability, ultrastructure, and its impact on HBVsvp synthesis. Results In response to LLLT irradiation, we observed a considerable reduction in viability, proliferation, and HBVsvp production in both hepatoma cell lines HepG2.2.15 and HepG2. Ultrastructural modification of mitochondria and nuclear membranes: This effect was dose, cell type, and time-dependent. Conclusions The use of LLLT may be a promising therapy for HCC and HBV patients by reducing cell proliferation, HBVsvp production, and altering mitochondrial and nuclear structure involved in cellular death inducers. Further research is required to explore its clinical application.

Hepatocellular carcinoma (HCC) is a prevalent cancer worldwide. Late-stage detection, ineffective treatments, and tumor recurrence contribute to the low survival rate of the HCC. Conventional chemotherapeutic drugs, like doxorubicin (DOX), are associated with severe side effects, limited effectiveness, and tumor resistance. To improve therapeutic outcomes and minimize these drawbacks, combination therapy with natural drugs is being researched. Herein, we assessed the antitumor efficacy of Ceiba pentandra ethyl acetate extract alone and in combination with DOX against diethylnitrosamine (DENA)-induced HCC in rats. Our in vivo study significantly revealed improvement in the liver-function biochemical markers (ALT, AST, GGT, and ALP), the tumor marker (AFP-L3), and the histopathological features of the treated groups. A UHPLC-Q-TOF-MS/MS analysis of the Ceiba pentandra ethyl acetate extract enabled the identification of fifty phytomolecules. Among these are the dietary flavonoids known to have anticancer, anti-inflammatory, and antioxidant qualities: protocatechuic acid, procyanidin B2, epicatechin, rutin, quercitrin, quercetin, kaempferol, naringenin, and apigenin. Our findings highlight C. pentandra as an affordable source of phytochemicals with possible chemosensitizing effects, which could be an intriguing candidate for the development of liver cancer therapy, particularly in combination with chemotherapeutic drugs.

The microbial analysis of fish is critical for ensuring overall health. Uncooked fish can serve as a conduit for transmitting several types of microbes; the current investigation sought to assess the bacterial levels in various kinds of fish from Nasser Lake, Aswan, Egypt, considered the chief source of potable water in Egypt. Two hundred and fifty fish samples, including 50 of each Oreochromis niloticus, Sander lucioperca, Lates niloticus, Clarias gariepinus, and Mormyrus kannume, from Nasser Lake, Aswan, Egypt, were collected to detect the bacterial load, isolation, and identification of Aeromonas hydrophila, Pseudomonas aeruginosa, and Vibrio parahaemolyticus and their virulence genes. The findings revealed that Oreochromis niloticus and Clarias gariepinus exhibited higher bacterial loads than other fish species. Incidences of bacterial contamination among examined fishes were 28.8%, 20.4%, and 16% for Aeromonas hydrophila, Pseudomonas aeruginosa, and Vibrio parahaemolyticus, respectively. Additionally, PCR analysis detected the presence of aerA (60%) and Act (40%) genes in A. hydrophila, rpoB (70%) and LasB (30%) genes in P. aeruginosa, and ToxR (70%) and tdh (50%) genes in V. parahaemolyticus. The study suggested that the bacterial contamination levels in Oreochromis niloticus and Clarias gariepinus could be notably more significant than in other species that could potentially be harmful to the consumers, especially considering the identification of particular bacteria known to cause foodborne illnesses. Further recommendations emphasized that regular monitoring and assessments are required to preserve their quality.

Oral cancer is a severe health problem that accounts for an alarmingly high number of fatalities worldwide. Withania somnifera (L.) Dunal has been extensively studied against various tumor cell lines from different body organs, rarely from the oral cavity. We thus investigated the cytotoxicity of W. somnifera fruits (W-F) and roots (W-R) hydromethanolic extracts and their chromatographic fractions against oral squamous cell carcinoma (OSCC) cell lines [Ca9-22 (derived from gingiva), HSC-2, HSC-3, and HSC-4 (derived from tongue)] and three normal oral mesenchymal cells [human gingival fibroblast (HGF), human periodontal ligament fibroblast (HPLF), and human pulp cells (HPC)] in comparison to standard drugs. The root polar ethyl acetate (W-R EtOAc) and butanol (W-R BuOH) fractions exhibited the strongest cytotoxicity against the Ca9-22 cell line (CC50 = 51.8 and 40.1 μg/mL, respectively), which is relatively the same effect as 5-FU at CC50 = 69.4 μM and melphalan at CC50 = 36.3 μM on the same cancer cell line. Flow cytometric analysis revealed changes in morphology as well as in the cell cycle profile of the W-R EtOAc and W-R BuOH-treated oral cancer Ca9-22 cells compared to the untreated control. The W-R EtOAc (125 μg/mL) exerted morphological changes and induced subG1 accumulation, suggesting apoptotic cell death. A UHPLC MS/MS analysis of the extract enabled the identification of 26 compounds, mainly alkaloids, withanolides, withanosides, and flavonoids. Pharmacophore-based inverse virtual screening proposed that BRD3 and CDK2 are the cancer-relevant targets for the annotated withanolides D (18) and O (12), and the flavonoid kaempferol (11). Molecular modeling studies highlighted the BRD3 and CDK2 as the most probable oncogenic targets of anticancer activity of these molecules. These findings highlight W. somnifera’s potential as an affordable source of therapeutic agents for a range of oral malignancies.

Mycotoxins are fungal products often found in food, formed during growth, harvesting, drying or storage of fruits, seeds, or grains, leading to a variety of toxic effects in humans and animals. Aflatoxins are a family of polyketide secondary metabolite produced by the food-contaminating moulds Aspergillus parasiticus and Aspergillus flavus. Aflatoxin B1 (AFB1) is a carcinogenic, teratogenic, mutagenic and growth inhibitory mycotoxin. To explore the negative morphological effects of AFB1 on the developing mice embryo, 50 adult females albino mice (CD1) were divided into five groups (10 females for each group): Control, positive control and three groups treated with a daily oral dose of 5, 10 or 20 μg/kg bw of AFB1 extract. Fifteen days after treatments, females were caged with males. Pregnancy, mortality, embryos number rates and body weight of female mice and infants were recorded. At 21 days old, crown rump, head, ear, tail, fore and hind-limb lengths of mice infants were investigated. Current data showed a decrease in pregnancy and embryo number rate among females in the animals treated with 10 & 20 μg AFB1, while treatment with 5 μg showed an increase in pregnancy and embryo number rate compared to control one, while mortality rate among fetuses increased in the three experimental animals treated with AFB1. Some cases of abortion were observed in 10 & 20 μg groups, while ulcers were observed in 20 μg groups. Weight and all morphometric parameters showed significant decrease except tail length that showed insignificant increase in the treated groups compared to the control one, while ear length showed significant increase. Different congenital malformations were observed in infants such as tail loss, delayed hair and teeth development and poor ossification in treated groups. The present study demonstrated that AFB1 induced developmental anomalies and reduced quality and birth rate. Data clarified that minimum concentration of AFB1 required to induce teratogenicity is far beyond the minimum concentrations estimated in earlier literatures. It is suggested that AFB1 might change genetic elements and consequently interfere with bone mineralization and induce teratogenicity and anomalies during mice embryonic development. Further studies are required to explore the mechanism of action.

Background and Objectives: Urinary tract infections [UTIs] are considered the third most known risk of infection in human health around the world. There is increasing appreciation for the pathogenicity of Gram-positive and Gram-negative strains in UTIs, aside from fungal infection, as they have numerous virulence factors. Materials and Methods: In this study, fifty urine samples were collected from patients suffering from UTI. Among the isolates of UTI microbes, six isolates were described as MDR isolates after an antibiotic susceptibility test carried out using ten different antibiotics. An alternative treatment for microbial elimination involved the use of biosynthesized silver nanoparticles (AgNPs) derived from Solanum lycopersicum [S. cumin]. Results: The sizes and shapes of AgNPs were characterized through TEM imaging, which showed spherical particles in a size range of 35–80 nm, of which the average size was 53 nm. Additionally, the silver nanoparticles (AgNPs) demonstrated inhibitory activity against Staphylococcus aureus (OR648079), exhibiting a 31 mm zone of inhibition at a minimum inhibitory concentration (MIC) of 4 mg/mL and a minimum bactericidal concentration (MBC) of 8 mg/mL. This was followed by Aspergillus niger (OR648075), which showed a 30 mm inhibition zone at an MIC of 16 mg/mL and a minimum fungicidal concentration (MFC) of 32 mg/mL. Then, Enterococcus faecalis (OR648078), Klebsiella pneumoniae (OR648081), and Acinetobacter baumannii (OR648080) each displayed a 29 mm zone of inhibition at an MIC of 8 mg/mL and an MBC of 16 mg/mL. The least inhibition was observed against Candida auris (OR648076), with a 25 mm inhibition zone at an MIC of 16 mg/mL and an MFC of 32 mg/mL. Furthermore, AgNPs at different concentrations removed DPPH and H2O2 at an IC50 value of 13.54 μg/mL. Also, AgNPs at 3 mg/mL showed remarkable DNA fragmentation in all bacterial strains except Enterococcus faecalis. The phytochemical analysis showed the presence of different active organic components in the plant extract, which concluded that rutin was 88.3 mg/g, garlic acid was 70.4 mg/g, and tannic acid was 23.7 mg/g. Finally, AgNPs concentrations in the range of 3–6 mg/mL showed decreased expression of two of the fundamental genes necessary for biofilm formation within Staphylococcus aureus, fnbA (6 folds), and Cna (12.5 folds) when compared with the RecA gene, which decreased by one-fold when compared with the control sample. These two genes were submitted with NCBI accession numbers [OR682119] and [OR682118], respectively. Conclusions: The findings from this study indicate that biosynthesized AgNPs from Solanum lycopersicum exhibit promising antimicrobial and antioxidant properties against UTI pathogens, including strains resistant to multiple antibiotics. This suggests their potential as an effective alternative treatment for UTIs. Further research is warranted to fully understand the mechanisms of action and to explore the therapeutic applications of these nanoparticles in combating UTIs.

Shill attacks are a serious threat to the stability of filtering and recommendation systems. These attacks involve the injection of fake profiles into the system, which can compromise the reliability of system output. Several shilling attack detection techniques have been proposed, but they often have limitations in terms of accuracy. This works presents a enhanced method for detecting attacks in collaborative recommender systems. The proposed method is based on a combination of statistical and machine learning techniques. The statistical techniques are used to identify anomalous user behavior, while the machine learning techniques are used to classify users as either malicious or benign. The main contribution of the proposed method is the use of a hybrid approach that combines the strengths of statistical and machine learning techniques. The statistical techniques are able to identify anomalous user behavior that is not easily detected by machine learning techniques. The machine learning techniques are able to classify users as either malicious or benign with a high degree of accuracy. The proposed method was evaluated on a real-world dataset. The results showed that the proposed method was able to detect attacks with a high degree of accuracy. The proposed method uses a combination of ensemble learning and feature selection to achieve better accuracy than previous methods. The results of the experiments show that the proposed method can achieve an accuracy of up to 99%.

The stability and reliability of filtration and recommender systems are crucial for continuous operation. The presence of fake profiles, known as “shilling attacks,” can undermine the reliability of these systems. Therefore, it is important to detect and classify these attacks. Numerous techniques for detecting shilling attacks have been proposed, including supervised, semi-supervised, unsupervised, Deep Learning, and hyper deep learning methods. These techniques utilize well-known shilling attack models to target collaborative recommender systems. While previous research has focused on evaluating shilling attack strategies from a global perspective, considering factors such as attack size and attacker’s knowledge, there is a lack of comparative studies on the various existing and commonly used attack detection methods. This paper aims to fill this gap by providing a comprehensive survey of shilling attack models, detection attributes, and detection algorithms. Furthermore, we explore the traits of injected profiles that are exploited by detection algorithms, which has not been thoroughly investigated in prior works. We also conduct experimental studies on popular attack detection methods. Our experimental results reveal that hybrid deep learning algorithms exhibit the highest performance in shilling detection, followed by supervised learning algorithms and semi-supervised learning algorithms. In contrast, the unsupervised technique performs poorly. The deep learning-based Shilling Attack Detection demonstrates accuracy and quality in accurately identifying a variety of mixed attacks. This study provides valuable insights into shilling attack models, detection attributes, and detection algorithms. Our findings highlight the superior performance of hybrid deep learning algorithms in shilling detection, as well as the limitations of unsupervised techniques. Deep learning-based Shilling Attack Detection showcases its effectiveness and accuracy in identifying various types of attacks.

Background The threat of malpractice liability could alter anesthesiologists’ clinical attitudes and behavior leading them to practice defensive medicine (DM) which aims at protecting doctors from medicolegal claims.Purpose To explore the knowledge, attitude, and practice of Egyptian anesthesiologists towards DM and their attitude and previous experience regarding medical malpractice liability.Methods An online cross-sectional questionnaire was done on a convenience sample of anesthesiologists. The questionnaire involved physician data, knowledge, attitude, and practice regarding DM, their attitude and previous experience regarding medical malpractice liability, and justifications for practicing DM.Results The questionnaire was completed by 177 anesthesiologists. Only 10.7% of participants received training about malpractice liability. The concern of malpractice litigation was reported by 81.4% and 92.1% of participants thought that malpractice lawsuits will have a negative influence on their performance. Most of the anesthesiologists (70.6%) reported that at least one of their colleagues was named in malpractice lawsuits, while 32.7% of them reported being investigated for malpractices. Based on “Defensive Medicine Behavior Scale”, 61% of the participants had a very high score. The highest reported justification for DM was fatigue 27.7%.Conclusions Despite the fact that more than half of the participants’ knowledge of DM was insufficient, about 61% had a very high score for DM-related behaviors. This highlights the DM current situation among them which could endanger physicians’ proficiency, quality of care, patient rights, and cost. Efforts with medicolegal training should be made to keep physicians' risk perception and anxiety in balance to avoid DM.

This work predicts the dynamics of the COVID-19 under widespread vaccination to anticipate the virus's current and future waves. We focused on establishing two population-based models for predictions: the fractional-order model and the fractional-order stochastic model. Based on dose efficacy, which is one of the main imposed assumptions in our study, some vaccinated people will probably be exposed to infection by the same viral wave. We validated the generated models by applying them to the current viral wave in Egypt. We assumed that the Egyptian current wave began on 10th September 2021. Using current actual data and varying our models’ fractional orders, we generate different predicted wave scenarios. The numerical solution of our models is obtained using the fractional Euler method and the fractional Euler Maruyama method. At the end, we compared the current predicted wave under a high vaccination rate with the previous viral wave. Through this comparison, the vaccination control effect is quantified.

Abstract Slowing down age-related neurocognitive impairment has been a challenge. We evaluated the therapeutic effects of metformin in d-galactose-induced aging. Additionally, we studied the potential molecular mechanisms that could be responsible for metformin's anti-aging effects. Thirty male rats were equally divided into: 1—control group, which received saline solution, 2—d-galactose (D-gal) group, which received d-galactose (100 mg/kg/day) by gastric lavage for eight weeks, and 3—d-galactose + Metformin (D-gal + Met) treated group, which received d-galactose + metformin (200 mg/kg/day) by gastric lavage for eight weeks. Neurocognitive assessment was done. Measurement of inflammatory, oxidative stress, and BDNF biomarkers was performed. AMPK and PI3K genes expression were assessed. Hippocampal tissues were dissected for histopathological and immunohistochemical studies. D-gal resulted in neurocognitive impairments, elevation of inflammatory biomarkers, altered oxidative stress markers, decreased BDNF, decreased expression of synaptophysin and Bcl2 with increased expression of Caspase-3, and down-regulation of AMPK and PI3K genes. Neurodegenerative changes were present in the hippocampus. Metformin restored significantly D-gal induced neurodegenerative changes. We concluded that metformin could alleviate age-induced neurocognitive deficit via amelioration of neuroinflammation, attenuation of oxidative stress, reduction of apoptosis, as well as promotion of synaptic plasticity. These mechanisms could be mediated via the activation of the AMPK/BDNF/PI3K pathway.

Coleus forskohlii (Willd.) Briq. is a medicinal herb of the Lamiaceae family. It is native to India and widely present in the tropical and sub-tropical regions of Egypt, China, Ethiopia, and Pakistan. The roots of C. forskohlii are edible, rich with pharmaceutically bioactive compounds, and traditionally reported to treat a variety of diseases, including inflammation, respiratory disorders, obesity, and viral ailments. Notably, the emergence of viral diseases is expected to quickly spread; consequently, these data impose a need for various approaches to develop broad active therapeutics for utilization in the management of future viral infectious outbreaks. In this study, the naturally occurring labdane diterpenoid derivative, Forskolin, was obtained from Coleus forskohlii. Additionally, we evaluated the antiviral potential of Forskolin towards three viruses, namely the herpes simplex viruses 1 and 2 (HSV-1 and HSV-2), hepatitis A virus (HAV), and coxsackievirus B4 (COX-B4). We observed that Forskolin displayed antiviral activity against HAV, COX-B4, HSV-1, and HSV-2 with IC50 values of 62.9, 73.1, 99.0, and 106.0 μg/mL, respectively. Furthermore, we explored the Forskolin’s potential antiviral target using PharmMapper, a pharmacophore-based virtual screening platform. Forskolin’s modeled structure was analyzed to identify potential protein targets linked to its antiviral activity, with results ranked based on Fit scores. Cathepsin L (PDB ID: 3BC3) emerged as a top-scoring hit, prompting further exploration through molecular docking and MD simulations. Our analysis revealed that Forskolin’s binding mode within Cathepsin L’s active site, characterized by stable hydrogen bonding and hydrophobic interactions, mirrors that of a co-crystallized inhibitor. These findings, supported by consistent RMSD profiles and similar binding free energies, suggest Forskolin’s potential in inhibiting Cathepsin L, highlighting its promise as an antiviral agent.

Lignan phytomolecules demonstrate promising anti-Alzheimer activity by alleviating dementia and preserving nerve cells. The purpose of this work is to characterize the lignans of Anisacanthus virgularis and explore their potential anti-acetylcholinesterase and anti-ageing effects. Phytochemical investigation of A. virgularis aerial parts afforded a new furofuranoid-type lignan (1), four known structural analogues, namely pinoresinol (2), epipinoresinol (3), phillyrin (4), and pinoresinol 4-O-β-d-glucoside (5), in addition to p-methoxy-trans-methyl cinnamate (6) and 1H-indole-3-carboxaldehyde (7). The structures were established from thorough spectroscopic analyses and comparisons with the literature. Assessment of the anticholinesterase activity of the lignans 1–5 displayed noticeable enzyme inhibition of 1 (IC50 = 85.03 ± 4.26 nM) and 5 (64.47 ± 2.75 nM) but lower activity of compounds 2–4 as compared to the reference drug donepezil. These findings were further emphasized by molecular docking of 1 and 5 with acetylcholinesterase (AChE). Rapid overlay chemical similarity (ROCS) and structure–activity relationships (SAR) analysis highlighted and rationalized the anti-AD capability of these compounds. Telomerase activation testing of the same isolates revealed 1.64-, 1.66-, and 1.72-fold activations in cells treated with compounds 1, 5, and 4, respectively, compared to untreated cells. Our findings may pave the way for further investigations into the development of anti-Alzheimer and/or anti-ageing drugs from furofuranoid-type lignans.

Automated personality trait detection from text data has emerged and gained a great deal of attention in the subject area of affective computing and sentiment analysis. Most previous work has focused on features engineering such as linguistic styles and psycholinguistic databases which have correlations with personality. Recently, natural language processing has been affected significantly with transfer learning based on feature extraction and fine-tuning pre-trained language models. We propose a new deep learning-based model for personality prediction and classification using both data and classifier level fusion. The model gets benefit from, transfer learning in natural language processing through leading pre-trained language models namely Elmo, ULMFiT, and BERT. The proposed model demonstrates the powerfulness of the introduced method to be a promising personality prediction model. When evaluating the proposed method, results show a competitive and significant accuracy enhancement of about 1.25% and 3.12% in comparison to the most recent results for the two gold standard Essays and myPersonality datasets for personality detection.

This study aims to evaluate the effectiveness of the dietary addition of Spirulina platensis (SP) and/or garlic powder (GP) on heat-stressed broiler chickens. For this purpose, 600 Ross-308 broiler chicks were allocated at 22 days of age into five groups (G1–G5), each comprising six groups of 20 birds each. Chickens kept in G1 (negative control) were fed a basal diet and raised at 26 ± 1 °C. Chickens kept in G2 to G5 were exposed to periodic heat stress (35 ± 1 °C for 9 h/day) from 22 to 35 days old. Chickens in G2 (positive control) were provided a basal diet, while G3, G4, and G5 were fed a basal diet enriched with SP (1 g/kg diet), GP (200 mg/kg diet), or SP/GP (1 g SP/kg + 200 mg GP/kg diet), respectively. The assessment parameters included the chickens’ performance, malondialdehyde and total antioxidant capacity, blood biochemistry, intestinal morphology, and modulation of lactobacilli and total coliforms in the intestinal microbiota. Our findings demonstrated that supplementing heat-stressed chickens with SP and/or GP significantly mitigated the negative effects on the European production efficiency index (EPEF), survival rate, cholesterol profile, and oxidative stress markers. Chickens supplemented with GP and/or SP exhibited significantly better EPEF and survivability rates. Heat stress had a significant impact on both the gut structure and gut microbiota. However, SP and/or GP supplementation improved the gut morphology, significantly increased the intestinal lactobacilli, and reduced the coliform contents. It was also found that the simultaneous feeding of SP and GP led to even higher recovery levels with improved lipid metabolites, immunity, and oxidative status. Overall, supplementing chickens with SP and/or GP can alleviate the negative effects of heat stress.

Breast cancer (BC) is not only a mass of malignant cells but also a systemic inflammatory disease. BC pro-tumorigenic inflammation has been shown to promote immune evasion and provoke BC progression. The NOD-like receptor (NLR) family pyrin domain-containing protein 3 (NLRP3) inflammasome is activated when pattern recognition receptors (PRRs) sense danger signals such as calreticulin (CALR) from damaged/dying cells, leading to the secretion of interleukin-1β (IL-1β). CALR is a novel BC biological marker, and its high levels are associated with advanced tumors. NLRP3 expression is strongly correlated with an elevated proliferative index Ki67, BC progression, metastasis, and recurrence in patients with hormone receptor-positive (HR+) and triple-negative BC (TNBC). Tumor-associated macrophages (TAMs) secrete high levels of IL-1β promoting endocrine resistance in HR+ BC. Recently, an immunosuppressive soluble form of programmed death ligand 1 (sPD-L1) has been identified as a novel prognostic biomarker in triple-negative breast cancer (TNBC) patients. Interestingly, IL-1β induces sPD-L1 release. BC Patients with elevated IL-1β and sPD-L1 levels show significantly short progression-free survival. For the first time, this study aims to investigate the inhibitory impact of thymoquinone (TQ) on CALR, the NLRP3 pathway and sPD-L1 in HR+ and TNBC. Blood samples were collected from 45 patients with BC. The effect of differing TQ concentrations for different durations on the expression of CALR, NLRP3 complex components and IL-1β as well as the protein levels of sPD-L1 and IL-1β were investigated in the peripheral blood mononuclear cells (PBMCs) and TAMs of TNBC and HR+ BC patients, respectively. The findings showed that TQ significantly downregulated the expression of CALR, NLRP3 components and IL-1β together with the protein levels of secreted IL-1β and sPD-L1. The current findings demonstrated novel immunomodulatory effects of TQ, highlighting its potential role not only as an excellent adjuvant but also as a possible immunotherapeutic agent in HR+ and TNBC patients.

Strawberry anthocyanins often undergo chemical degradation during storage, which leads to color fading and bioactivity loss. These changes are increased by ascorbic acid, which accelerates anthocyanin degradation. The present study investigated the effect of citric acid as an alternative to ascorbic acid to adjust strawberry nectar pH. Several additions were also used as co-pigment sources to enhance color stability during a five-month dark storage period at ambient temperatures. The results showed that citric acid increased the stability of total and monomeric anthocyanin and reduced the formation of polymeric color. The fortification of the strawberry nectar with 0.2% green tea extract, 3% hot rosella extract, and 0.5% low-methoxyl pectin in the presence of citric acid led to enhance strawberry nectar color, high stability, and reduce anthocyanin degradation.

Personality Traits Detection is one of the important problems as a text analytics task in Natural Language Processing (NLP). Text analytics is the process of finding out insight knowledge over written text. Although most deep learning models give high performance, they often lack interpretability. Computer Vision (CV) has been affected significantly with inductive transfer learning, however training from scratch and task-specific modifications are still wanted in many NLP techniques.This paper addresses the problem of personality traits classification. We adopted the use of the Universal Language Model Fine-Tuning (ULMFiT) in personality traits detection. The model makes use of transfer learning rather than the classical shallow methods of word embedding and proved to be the most powerful model in many NLP problems.The basic advantage of using this model is that there is no need to do feature engineering before classification. When applied to benchmark dataset, the proposed method shows a statistical accuracy improvement of about 1% compared to the state-of-the-art results for the big five personality traits.

Breast cancer (BC) is one of the most common cancers, accounting for 2.3 million cases worldwide. BC can be molecularly subclassified into luminal A, luminal B HER2-, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These molecular subtypes differ in their prognosis and treatment strategies; thus, understanding the tumor microenvironment (TME) of BC could lead to new potential treatment strategies. The TME hosts a population of cells that act as antitumorigenic such as tumor-associated eosinophils or pro-tumorigenic such as cancer-associated fibroblasts (CAFs), tumor-associated neutrophils (TANs), monocytic-derived populations such as MDSCs, or most importantly “tumor-associated macrophages (TAMs),” which are derived from CD14+ monocytes. TAMs are reported to have the pro-inflammatory phenotype M1, which is found only in the very early stages of tumor and is not correlated with progression; however, the M2 phenotype is anti-inflammatory that is correlated with tumor progression and metastasis. The current study focused on controlling the anti-inflammatory activity in TAMs of hormonal, HER2+, and TNBC by epigenetic fine-tuning of two immunomodulatory proteins, namely, CD80 and mesothelin (MSLN), which are known to be overexpressed in BC with pro-tumorigenic activity. Long non-coding RNAs are crucial key players in tumor progression whether acting as oncogenic or tumor suppressors. We focused on the regulatory role of MALAT1 and HOTAIR lncRNAs and their role in controlling the tumorigenic activity of TAMs. This study observed the impact of manipulation of MALAT1 and HOTAIR on the expression of both CD80 and MSLN in TAMs of BC. Moreover, we analyzed the interlinkage between HOTAIR and MALAT1 as regulators to one another in TAMs of BC. The current study reported an upstream regulatory effect of HOTAIR on MALAT1. Moreover, our results showed a promising use of MALAT1 and HOTAIR in regulating oncogenic immune-modulatory proteins MSLN and CD80 in TAMs of HER2+ and TNBC. The downregulation of MALAT1 and HOTAIR resulted in the upregulation of CD80 and MSLN, which indicates that they might have a cell-specific activity in TAMs. These data shed light on novel key players affecting the anti-inflammatory activity of TAMs as a possible therapeutic target in HER2+ and TNBC.

Nowadays, human emotion recognition is a mandatory task for many human machine interaction fields. This paper proposes a novel multi-modal human emotion recognition framework. The proposed scheme utilizes first the 3D-Convolutional Neural Network (3D-CNN) deep learning architecture for extracting the spatio-temporal features from the electroencephalogram (EEG) signals, and the video data of human faces. Then, a combination of data augmentation, ensemble learning techniques is proposed to get the final fusion predictions. The fusion of the multi-modalities in the proposed scheme is carried out using data, and score fusion methods. Hence, three human recognition approaches are built to achieve the proposed goal. They are namely EEG-based emotion recognition approach, face-based emotion recognition approach, and fusion-based emotion recognition approach. For the EEG approach, the 3D-CNN is used to get the final predictions of the EEG signal. For the face approach, the Mask-RCNN object detection technique in combination with OpenCV libraries are first utilized to extract the exact face pixels with emotional content. Then, the Support Vector Machine (SVM) classifier is utilized to classify the 3D-CNN output features of the face chunks. For the fusion-based emotion recognition approach, two fusion techniques are experimented; bagging, and stacking. It is found that the stacking technique gives the best accuracy, and achieves recognition accuracies 96.13%, and 96.79% for valence, and arousal classes respectively using the grid search ensemble learning technique due to transferring the weights from the EEG, and the face approaches to the fusion-based emotion recognition approach. The proposed approach outperforms recent works in multi-modal emotion recognition field.

Humans are born storytellers as they use oral narratives as a vehicle to share their experiences. This study aimed to study how female Egyptian speakers formulate their personal experiences in oral narratives in the English Language. A need of this study was felt because not much is known how Arab EFL speakers build their oral narratives when its structure is talked about. The sample of this study comprised 24 female students from an Egyptian university pursuing a program in English language and literature, divided equally into two groups of intermediate and advanced levels. By using a non-experimental mixed model research design, the data was collected through semi structured interviews. The quantitative results were based on Mann-Whitney Test, which compared two unpaired groups to investigate the differences between the frequencies of the moves in the oral narratives as well as their use of structural tools; while the qualitative results were obtained from the participants' responses in the interview, which gave insight into how the participants formulated their narratives. Results show variations in the moves of narratives in both groups; however, there was no significant difference in the overall structure of each narrative. The study also attempted to compare the narrative structure of the female Egyptian EFL learners with that of their peers. It was found that there was no relationship between EFL proficiency and the structure of the narratives of female Egyptian at both advanced and intermediate levels. These findings will provide useful insights about the structural aspects of the oral narratives of Arab EFL learners.

The English reading ability of university students is crucial for their academic achievement, regardless of whether they are studying English or any other subject in English. Examining the affective factors that influence this ability is critical for understanding its development. Research has been conducted on the correlation between first language (L1) and English as a second language (ESL/EFL) reading attitudes, but there is limited research on the correlation between L2 and L1. This research seeks to investigate the similarities in reading perspectives between Arabic-speaking international students and English-speaking university students. The study employed surveys and semi-structured interviews to evaluate individuals' viewpoints on bilingual reading. The objective was to assess individuals' attitudes towards reading in two languages. Both quantitative and qualitative analyses were conducted. The study revealed that students' reading preferences remained consistent across different languages. However, the relationship between second-language reading attitudes and first-language reading attitudes was found to be minimal. The implications of the current study suggest that enhancing reading attitudes in both languages may enhance reading ability. The study utilised subjective data and targeted a specific demographic, limiting its generalizability to more diverse student populations.

Abstract Background Diffusion-tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that depicts the integrity of white matter (WM) tracts. This study was conducted to assess the utility of DTI tractography as an imaging technique in assessment of brain gliomas and planning of the surgical corridor. Results Twenty adult patients with brain gliomas were included. Neurological examination and conventional MRI and DTI scans were performed before and after surgery. Low-grade and high-grade tumors were found in 30% and 70% of patients, respectively. Preoperative DTI demonstrated five patterns of WM tract involvement: non-affected (10%), displaced (75%), edematous (55%), infiltrated (60%), and disrupted (20%). The obtained DTI scans were used for preoperative planning of the surgical corridor and extent of resection to achieve the maximum resection while preserving the WM tracts. Total resection was achieved in 40%, while 60% underwent subtotal resection. Postoperative neurological examination showed deterioration of cognitive function, motor power, and vision in 15%, 10%, and 5% of patients, respectively. Headache persisted in 15%, while motor power improved in 35% of patients. High-grade tumors were significantly associated with higher percentage of subtotal resection (p=0.018) and pattern IV (p=0.018). There was a significant association between the preoperative pattern of WM tract involvement and the postoperative DTI changes (p

Abstract Background In this study, we combined ultrasound and Doppler parameters to conclude the most accurate and applicable method for fetal lung maturity assessment. The purpose is to reduce risk of neonatal respiratory distress by assessment of fetal lung maturity through ultrasound and Doppler instead of amniocentesis. Results A total of 120 women were included. The ultrasound examination was performed at a gestational age ranging between 30 and 37 weeks and delivery occurred within 72 h from ultrasound. After birth, 19 fetuses were diagnosed with RDS. The ultrasound parameters assessed for fetal lung maturity showed varying sensitivity and specificity but presence of proximal tibial epiphyses showed the highest sensitivity (91%) and specificity (95%) followed by the presence of distal femoral epiphyses with 90% sensitivity and 84% specificity. The placental grade III maturity showed a sensitivity of 81% and 74% specificity followed by the presence of the amniotic fluid free-floating particles with an 83% sensitivity and 63% specificity, while echogenic fetal thalamus showed 77% and 79% for sensitivity and specificity, respectively, for prediction of fetal lung maturity. By using the fetal biometry, we could report that a BPD between 82.8 and 93.5 mm, AC between 295 and 322 mm, and FL (62.7-72.1 mm) correlated with mature fetal lungs. Regarding Doppler indices, increased resistive index of umbilical artery > 0.69 and of pulmonary artery > 0.78 correlated with neonatal RDS while fetuses with UtA RI values between 0.43 and 0.66 noticed in RDS vs (0.42-0.57) in the non-RDS. MCA RI values are also higher in RDS 0.77–0.88 vs 0.74–0.79 in non-RDS. On the other hand, analysis of colon grading and fetal lung echogenicity in relation to liver showed no significant value in the assessment of fetal lung maturity. Conclusion Ultrasound and Doppler showed good predictive value and accuracy and is considered a valuable non-invasive procedure in assessment of fetal lung maturity. However, no single parameter alone could show a definitive sign

Abstract Background Emergence of 2019-nCoV attracted global attention and WHO declared COVID-19 a public health emergency of international concern. Therefore we aimed to explore the severity and atypical manifestations of COVID-19 among children. Methods This is an observational cohort study conducted on 398 children with confirmed COVID-19 by using real-time reverse transcriptase polymerase chain reaction assay for detection of 2019-nCoV nucleic acid during the period from March to November 2020. Patients were subdivided regarding the severity of COVID-19 presentation into Group I (Non-severe COVID-19) was admitted into wards and Group II (Severe COVID-19) admitted into the PICU. Results Non- severe cases were 295cases (74.1%) and 103cases (25.9%) of severe cases. There was a significant difference between age groups of the affected children (P

Abstract Background One possible mechanism utilized by hepatitis C virus (HCV) to escape from the host’s innate immune surveillance is modification of its pathogen-associated molecular patterns (PAMPs) by altering or hiding its RNA which interfering with toll-like receptors (TLRs) signaling and ultimately hindering the production of proinflammatory cytokines, chemokines, and interferons (IFNs). This study aimed to examine the expression levels of TLR3, TLR7, and IFN-α to investigate the correlated expression pattern among them in chronic HCV patients. Patients included in this study were categorized into two different groups, non-treated chronic HCV patients and treated chronic HCV patients, in addition to healthy volunteers as a control group. The blood samples were assessed for HCVAb, HCVRNA, HCV genotypes, and different biochemical analyses. The mRNA levels of TLR3, TLR7, and IFN-α in peripheral blood of chronic HCV patients were quantitatively measured in comparison to healthy controls. Results The expression levels of TLR3, TLR7, and IFN-α were significantly downregulated in non-treated chronic HCV patients compared to both treated HCV patients and control subjects. On the other hand, treated HCV patients showed non-significant downregulation of the same three sensing receptors (TLR3, TLR7, and IFN-α) compared to control group. Obviously, the expression levels of IFN-α were positively correlated with the levels of both TLR3 and TLR7. Conclusion The exhausted innate immunity against HCV may correlate to HCV downregulation of TLR3 and TLR7 expression on innate immune cells with a subsequent decrease in INF-α production and the possibility of targeting these receptors to enhance the immune response and clear the infection needs further studies.

Change Detection (CD) is a hot remote sensing topic where the change zones are highlighted by analyzing bi-temporal or multi-temporal images. Recently, Deep learning (DL) paved the road to implement various reliable change detection approaches that overcome traditional CD methods limitation. However, high performance DL based approaches have explosion number of parameters that demanded extensive computation and memory usage in addition to large volumes of training data. To address this issue, we proposed a teacher-student setting for remote sensing imagery change detection. To distill the knowledge from the over-parameterized Siamese teacher network, we proposed tiny student network that was trained using the obtained categorical distribution of probability from the teacher paired Softmax output at high temperature. Practical Swarm Optimization (PSO) was applied in order to optimally configure student architecture. Finally, ample experiments were conducted on LEVIR-CD dataset. Also, we introduced EGSAR-CD dataset, which contains of a large set of bi-temporal SAR images with 460 image pairs ( $256 \times 256$ ). Experiment results indicate that we can reach up to $5.4\times $ reduction rate in number of parameters with loss of accuracy between 5% and 6% on the LEVIR-CD and EGSAR-CD datasets utilizing self-knowledge distillation.

Magnetic and ground penetrating radar (GPR) techniques are perhaps the most convenient and popular geophysical survey techniques for detecting the buried archaeological targets, because of their high speed and quality of information. The results of the two used techniques have been integrated in Dawwar Jabal, Fayoum Governorate, Egypt to detect the buried archaeological remains and their depths.The magnetic survey shows various high positive magnetic anomalies, some of these anomalies are related to the possible archaeological targets and the others are due to the mudstones which may include iron minerals. The results of the GPR survey after processing shows scattering and strong reflection of the subsurface oscillations along some profiles, which may reflect the existence of the possible buried objects. Meanwhile, no evidence of scattering or clear reflection for the signals are recorded along the other profiles which suggest that there is not any possibility of archaeological targets.The integration of the obtained results from the two used techniques indicates that there is some agreement in mapping the locations of the possible buried archaeological targets and their depths (1–7.5 m) for most of the detected targets. However, few targets are observed only on the data of one of the used techniques and disappeared along the other. This is related to the limitation of each technique. Therefore, such combination of the two mentioned techniques to detect the archaeological targets yields more information about the locations and depths of the buried targets than is obtain if each technique is used individually.

The human cognitive map formation is still an open question. Based on biological facts, the cognitive map origin goes back to the age of the fetus human. In this paper, our aim is to provide a possible answer to that question. Accordingly, we present a theoretical model of the development of the cognitive map of a fetus human using its sensorimotor data. We define positions of the cognitive map as associations between high-level perceptions created from different sensory sources. We use a proposed method referred to as Frequency-based-means clustering algorithm to develop the perceptions that form the association map. Our proposed theoretical model is tested on simulated data. Results show that our model is a possible candidate for demonstrating how the cognitive map is formed. In addition, comparison with k-means clustering is presented and results show that the frequency-based-means clustering has a better performance than k-means clustering and is more suitable for this application.

BackgroundPlant-parasitic nematodes are one of the major constraints to soybean production around the world. Plant-parasitic nematodes cause an estimated $78 billion in annual crop losses worldwide, with a 10–15% crop yield loss on average. Consequently, finding and applying sustainable methods to control diseases associated with soybean is currently in serious need.MethodsIn this study, we isolated, purified, characterized, and identified a novel cyanobacterial strain Oscillatoria sp. (blue-green alga). Based on its microscopic examination and 16S rRNA gene sequence, the aqueous and methanolic extracts of Oscillatoria were used to test their nematicidal activity against Meloidogyne incognita hatchability of eggs after 72 h of exposure time and juvenile mortality percentage in vitro after 24, 48, and 72 h of exposure time and reduction percentage of galls, eggmass, female number/root, and juveniles/250 soil. Also, the efficacy of the extract on improving the plant growth parameter and chlorophyll content under greenhouse conditions on soybean plant cv. Giza 111 was tested. Finally, the expression of PR-1, PR-2, PR-5, and PR15 (encoding enzymes) genes contributing to plant defense in the case of M. incognita invasion was studied and treated with Oscillatoria extract.ResultsThe aqueous and methanolic extracts of Oscillatoria sp. had nematicidal activity against M. incognita. The percentage of mortality and egg hatching of M. incognita were significantly increased with the increase of time exposure to Oscillatoria extract 96.7, 97, and 98 larvae mortality % with S concentration after 24, 48, and 72 h of exposure time. The aqueous extract significantly increased the percentage of Root-Knot nematodes (RKN) of egg hatching, compared with Oxamyl and methanol extract at 96.7 and 97% after 72 h and 1 week, respectively. With the same concentration in the laboratory experiment. Furthermore, water extracts significantly reduced the number of galls in soybean root, egg masses, and female/root by 84.1, 87.5, and 92.2%, respectively, as well as the percentage of J2s/250 g soil by 93.7%. Root, shoot lengths, dry weight, number of pods/plant, and chlorophyll content of soybean treated with Oscillatoria water extract were significantly higher than the control increasing by 70.3, 94.1, 95.5, and 2.02%, respectively. The plant defense system's gene expression was tracked using four important pathogenesis-related genes, PR-1, PR-2, PR-5, and PR15, which encode enzymes involved in plant defense.ConclusionsOscillatoria extract is a potential nematicide against root-knot nematode invasion in soybean.