Dr Mohammed Mahmoud Youssif

The transition from Green to sustainable chemistry demands a paradigm shift in how analytical methodologies are evaluated, moving beyond isolated performance metrics toward holistic life-cycle assessment. In this study, we introduce a novel Sustainability Assessment Framework (Greenness, Applicability, Sustainability) to rigorously benchmark analytical strategies. As a proof-of-concept, the framework was applied to a complex pharmaceutical challenge: the impurity profiling of paracetamol (PAR) along with three official impurities: para-aminophenol (PAP), para-nitrophenol (PNP), and para-chloroacetanilide (PCA), and two co-formulated drugs ibuprofen (IBU) and chlorzoxazone (CHZ). Two chemometric models, partial least squares (PLS) and artificial neural networks (ANN), were utilized to achieve this purpose. Furthermore, both models were subjected to a variable selection process using genetic algorithm (GA) to identify the most significant wavelengths. The genetic algorithm-optimized neural network (GA-ANN) demonstrated superior predictive accuracy for the six-component mixture. The core innovation of this work lies in the comparative application of the Sustainability Assessment Framework, benchmarking the proposed chemometric method against a reference HPLC method using eight state-of-the-art metrics. Greenness was evaluated via Analytical Eco-Scale, GAPI, and AGREE; Applicability via BAGI, RGB12 algorithm, and EPPI; and Sustainability via the Carbon Footprint, NQS Index, and %Circularity. This study establishes the Framework as a robust prototype for modern quality control, validating chemometrics not merely as an alternative technique, but as a superior sustainable evolution aligned with the principles of the circular economy.

The COVID-19 pandemic has emphasized the critical need for novel therapeutic approaches. Favipiravir (FAV), an antiviral drug primarily used for influenza, has shown promising potential in treating COVID-19 and other RNA viral infections. A precise, reliable, and rapid fluorimetric method was established for the quantification of FAV in pharmaceutical formulations, even in the presence of its acid-induced degradation product. The acid-induced degradation product (ADP) of FAV was prepared through forced degradation, followed by characterization using IR and MS. The method leveraged the intrinsic fluorescence characteristics of FAV, exhibiting a linear response within the concentration range of 5–80 ng/mL at 416.5 nm using the first-order derivative processing. Key methodological parameters were optimized to enhance sensitivity, achieving detection and quantification limits of 1.6 ng/mL and 4.8 ng/mL, respectively. All calibration and fluorimetric measurement steps were performed in distilled water without the use of organic solvents or buffers, making the analytical determination phase entirely aqueous and environmentally benign. This method was effectively applied to FAV in both pure drug and pharmaceutical dosage forms. Compared with previously reported fluorimetric methods, it offers the unique combination of aqueous-based operation, stability-indicating capability, and superior analytical performance. Additionally, its environmental sustainability was evaluated using GAPI, AGREE, and RGB12 metrics, which confirmed its green and eco-friendly attributes.

Eukaryotic elongation factor 2 kinase (eEF2K) phosphorylates eukaryotic elongation factor 2 (eEF2) and slows translation elongation. In the nervous system, this pathway links neuronal activity, calcium signaling, energy status, and stress responses to selective protein synthesis programs that shape synaptic plasticity, circuit excitability, and cell survival. Dysregulated eEF2K/eEF2 signaling has been implicated in epilepsy, Alzheimer's disease, Parkinson's disease, major depressive disorder, Down syndrome, and other brain conditions. However, the literature remains fragmented, largely preclinical, and often interpreted in an overly therapeutic manner. This review synthesizes the field using a mechanistic framework. Across disorders, altered eEF2 phosphorylation converges on five major axes: synaptic plasticity and excitatory/inhibitory balance, oxidative and mitochondrial stress responses, neuroinflammation/neuroimmune regulation, and aging-related neurogenesis and cognitive resilience. In chronic neurodegenerative and neurodevelopmental settings, excessive eEF2K activity is frequently associated with impaired de novo protein synthesis, synaptic dysfunction, and cognitive decline, whereas genetic or pharmacological suppression can improve selected behavioral and electrophysiological outcomes. By contrast, in acute metabolic stress or certain immune-cell contexts, eEF2K activity may serve adaptive and anti-inflammatory functions. These findings indicate that eEF2K has context-dependent, rather than uniformly pathogenic, roles. We also highlight major translational barriers, including dependence on rodent models, limited causal human data, incomplete cell-type resolution, and the off-target liabilities of commonly used inhibitors such as NH125 and A-484954. Overall, the eEF2K/eEF2 axis represents a biologically important but therapeutically complex target that will require selective, cell-aware, and stage-specific modulation. Future progress depends on better biomarkers, human models, and more selective brain-penetrant inhibitors.

Multiple sclerosis (MS) is a chronic, immune-mediated demyelinating disorder of the central nervous system characterized by inflammation and progressive neurodegeneration. MS is a heterogeneous disease with varying presentations, disease courses, and prognosis. Although current disease-modifying therapies (DMTs) have been reported to reduce the frequency and severity of inflammatory demyelinating hallmarks of MS, improve relapse rate and long-term outcomes, they do not fully prevent disease progression, nor do they reverse existing neurological damage. This ongoing gap has driven growing interest in natural products as complementary or adjunctive strategies for MS management. Naturally occurring phytochemicals have been proposed as a potentially safe and effective therapeutic and complementary option for MS. Natural compounds have been reported to demonstrate anti-inflammatory, immunomodulatory, antioxidant, and neuroprotective activities in experimental models of MS. Together, these multifunctional properties target key mechanistic pathways implicated in disease pathogenesis, such as oxidative stress, mitochondrial dysfunction, and immune dysregulation. However, despite promising preclinical data, clinical translation remains limited by variability in dosing, bioavailability challenges, and insufficient large-scale trials. In this context, this review explores the scientific rationale for natural products in MS, provides an overview of disease mechanisms relevant to such interventions, and highlights future research needs to advance these compounds toward evidence-based integration.

The multi-label retinal disease classification is a difficult one since fundus images might comprise many co-occurring abnormalities, extreme in relation to the class, as well as significant lesion appearance variation. In order to deal with this issue, this paper suggests a combined deep learning architecture to diagnose retinal diseases automatically with the help of the MuReD dataset, which includes 2208 fundus images that were gathered at ARIA, STARE, and RFMiD and reformulated with 19 retinal disease labels, excluding the non-diagnostic category of OTHERS. The proposed model is based on a hybrid convolutional structure that integrates two complementary branches of feature extraction and implements a multi-stage preprocessing pipeline consisting of contrast enhancement, luminance correction, noise reduction, and retinal masking. Fusion and optimization of extracted feature representations are performed to perform multi-label prediction with binary supervision of label-wise predictions as sigmoid outputs. In order to assess the value of architecture and preprocessing design, ablation experiments were performed on a great scale by using single-backbone baselines, hybrid configurations, and preprocessing-specific configurations. According to the results, the highest F1-micro = 0.5484, PR-AUC micro = 0.5696, and ROC-AUC micro = 0.9349 were observed in the best variant of the hybrid, and the best PR-AUC micro = 0.5821 and ROC-AUC micro = 0.9369 were observed in another hybrid variant. Other tests on bootstrap confidence interval, calibration evaluation, Monte Carlo dropout, and repeated multi-seed experiments also indicated the strength of the proposed model. These results reveal that feature fusion with built-in deep learning is an effective solution to multi-label retinal disease diagnosis and has a potential real-world application to computer-aided screening and triage in ophthalmology.

Baicalin, a polyphenolic flavonoid, is the main bioactive flavone extracted from the roots of Scutellaria baicalensis. It has received increasing interest due to its broad spectrum of pharmacological activities and therapeutic benefits demonstrated in preclinical research. However, its molecular mechanisms and translational potential remain underdefined. This review systematically evaluates current evidence on baicalin, including its natural sources, chemical structure, biosynthesis, extraction techniques, pharmacokinetic features, molecular mechanisms, and therapeutic applications, as well as developments in drug delivery platforms designed to overcome its biopharmaceutical limitations. This structured literature review was conducted using data extracted from various databases, including the Egyptian Knowledge Bank, Scopus, Web of Science, PubMed, Google Scholar, and Elsevier. All possible keywords relevant to baicalin were utilized. Recent original articles, systematic reviews, meta-analysis, clinical studies, and high-quality reviews were prioritized. Baicalin exerts its therapeutic effects through modulation of various signaling pathways, primarily involving oxidative stress and inflammation. It exhibits anticancer, antimicrobial, antiviral, immunomodulatory, metabolic, and dermatological effects and alleviates various system disorders and drug-induced toxicity. Despite promising preclinical data, clinical translation is hindered by its poor solubility, limited bioavailability, and insufficient clinical validation. Emerging nano-delivery systems, such as liposomes, solid lipid nanoparticles, polymeric nanoparticles, and surface-modified nanoplatforms, have greatly improved the pharmacokinetic performance of baicalin. Nevertheless, the clinical translation of these approaches remains limited. While baicalin represents a promising multi-target therapeutic option, substantial research gaps remain. Future research should give priority to deeper mechanistic investigations, standardized formulation approaches, and well-designed clinical trials to bridge the gap between preclinical efficacy and clinical application, and to establish its optimal dosing, safety profile, and long-term efficacy.

Purinergic P2X receptor overactivation, impaired mitophagy, and NLRP3 inflammasome-driven neuroinflammation have been increasingly implicated in Parkinson's disease (PD) pathogenesis. Suramin, a purinergic receptor antagonist, has recently attracted attention for its neuroprotective effects in several neurological disorders. However, its potential to modulate the P2X/mitophagy/NLRP3 axis in PD remains unexplored. This study evaluated the neuroprotective effects of suramin in comparison with metformin, a reported mitophagy and inflammasome modulator, in a rotenone-induced PD rat model. Rotenone (1.5 mg/kg, s.c.) was administered on alternate days for three weeks. Suramin (100 mg/kg, I.V.) was administered on days 11 and 18, while metformin (200 mg/kg, p.o.) was given from days 11 to 21. Behavioral outcomes were evaluated using the open-field, footprint, grip strength, and rotarod tests. Expression levels of selected target signals were quantified using qPCR, ELISA, Western blot, and immunohistochemistry. Suramin and metformin significantly improved motor and behavioral performance, preserved dopaminergic integrity, improved tyrosine hydroxylase expression, and diminished α-synuclein accumulation, with suramin demonstrating greater efficacy. At the molecular level, suramin more effectively downregulated striatal P2X7R, P2X4R, and ROS levels and increased p-AMPK/t-AMPK ratio. Both treatments promoted mitophagy, as evidenced by increased PINK1, Parkin, and BNIP3 levels along with reduced LC3-II/I ratio. They also suppressed NLRP3 inflammasome activation and pyroptosis, with suramin showing more potent anti-inflammatory effects. Altogether, suramin's neuroprotective effects could be mediated via suppressing P2X7/P2X4 receptors, enhancing mitophagy and counteracting NLRP3-driven pyroptosis in the striatum, with its relatively stronger profile attributable to more robust P2X7/P2X4 signaling inhibition, underscoring its potential as a therapeutic candidate for PD.

OBJECTIVES: To evaluate the effect of a novel restorative approach using dimethyl sulfoxide (DMSO) as a cavity pretreatment on the material fracture and retention (primary outcome) of direct composite fillings placed on cervical carious lesions (CCLs).

METHODS: 45 patients presenting CCLs were screened and randomized into two groups containing 37 caries lesions/group: an untreated control (20 patients) and a DMSO-treated (25 patients) group. Following a parallel-study design, two calibrated operators placed 74 (n = 37) composite fillings (Filtek Z350XT, 3 M ESPE) using a 2-step etch-and-rinse adhesive (Single Bond 2, 3 M ESPE). After baseline assessments (7 days), fillings were evaluated at 12-, 24- and 36-month follow-ups according to the FDI criteria (fracture/retention, marginal staining, marginal adaptation, postoperative sensitivity and caries recurrence). For statistical analysis, Chi-Square and Cochran's Q tests were used (α = 0.05) following the Bonferroni correction.

RESULTS: DMSO had significant effects on the clinical performance of composite fillings placed on CCLs according to the FDI criteria (p < 0.05). Success rates after 36 months of untreated and DMSO-treated cavities were 65 % and 89 %, respectively, with a 70 % lower risk of failure when using DMSO. DMSO significantly reduced post-operative sensitivity and marginal staining and improved retention rates after 36 months (p < 0.05).

CONCLUSIONS: Long-term clinical performance of composite fillings using simplified etch-and-rinse adhesives can be optimized by employing DMSO as a cavity pretreatment.

CLINICAL SIGNIFICANCE: The use of DMSO can be a simple clinical approach to improve post-operative sensitivity of composite fillings, reduce risk of failures and extend service life by producing more stable composite-tooth interfaces.

OBJECTIVES: To evaluate the effect of a novel restorative approach using dimethyl sulfoxide (DMSO) as a cavity pretreatment on the material fracture and retention (primary outcome) of direct composite fillings placed on cervical carious lesions (CCLs).

METHODS: 45 patients presenting CCLs were screened and randomized into two groups containing 37 caries lesions/group: an untreated control (20 patients) and a DMSO-treated (25 patients) group. Following a parallel-study design, two calibrated operators placed 74 (n = 37) composite fillings (Filtek Z350XT, 3 M ESPE) using a 2-step etch-and-rinse adhesive (Single Bond 2, 3 M ESPE). After baseline assessments (7 days), fillings were evaluated at 12-, 24- and 36-month follow-ups according to the FDI criteria (fracture/retention, marginal staining, marginal adaptation, postoperative sensitivity and caries recurrence). For statistical analysis, Chi-Square and Cochran's Q tests were used (α = 0.05) following the Bonferroni correction.

RESULTS: DMSO had significant effects on the clinical performance of composite fillings placed on CCLs according to the FDI criteria (p < 0.05). Success rates after 36 months of untreated and DMSO-treated cavities were 65 % and 89 %, respectively, with a 70 % lower risk of failure when using DMSO. DMSO significantly reduced post-operative sensitivity and marginal staining and improved retention rates after 36 months (p < 0.05).

CONCLUSIONS: Long-term clinical performance of composite fillings using simplified etch-and-rinse adhesives can be optimized by employing DMSO as a cavity pretreatment.

CLINICAL SIGNIFICANCE: The use of DMSO can be a simple clinical approach to improve post-operative sensitivity of composite fillings, reduce risk of failures and extend service life by producing more stable composite-tooth interfaces.

This research focuses on creating a novel Brijaluronic-based terpesomal system capable of transporting quercetin (QER) efficiently to the brain. The vesicles were fabricated through an ethanol-injection method and then refined using a structured optimization approach in Design-Expert® software. The influence of three main formulation parameters: terpene-to-drug ratio, surfactant type, and hyaluronic acid amount were evaluated. The optimization process was designed to maximize EE%, minimize VS, and maintain ZP within an acceptable stability range. The optimal formula hit a desirability target of 0.957. It achieved an 88.66% EE%, featured nano-carriers sized at 72.09 nm, and had a stable charge of - 26.5 mV. Physicochemical characterization studies revealed a spherical morphology, an in-vitro release defined by a biphasic profile, and a secure structural integrity which was validated using FTIR analysis. Moreover, over the course of three months, the formulation did not degrade or change significantly, demonstrating its high degree of stability. Notably, terpesomes demonstrated a ~ 3.5-fold enhancement in antioxidant activity, reducing the IC₅₀ from 12.98 ± 0.82 µg/mL to 3.68 ± 0.20 µg/mL, representing a statistically and pharmacologically significant improvement. Radio-kinetic assessments further supported its potential for precise brain targeting. The brain/blood was highest for the optimized formulation at all-time points. Compared with the nasal QER solution, Technetium-99m ([Tc]Tc)-QER-loaded terpesomes exhibited superior brain-targeting efficiency, as evidenced by higher AUC, shorter T, and greater C values in the brain. Taken together, the Brijaluronic terpesomes represent a highly promising, innovative nano-platform. This engineered system appears poised to boost the effectiveness of QER in neurotherapeutic applications.

Imidacloprid (IMI) is a commonly used chloronicotinyl insecticide, although it has low specificity to humans, long-term exposure would induce neurotoxicity through cholinergic signaling disruption and ferroptosis activation. The current investigation aimed to explore the neuroprotective impact of deferiprone (DFP), an iron chelator, against IMI-induced neurotoxicity and whether co-administration with everolimus (EVR), an mTOR inhibitor known to induce autophagy and potentially enhance ferritinophagy, would alter this effect. Adult male Wistar rats were assigned randomly to four different experimental sets: control, IMI, IMI + DFP, and IMI + DFP + EVR groups. They were given IMI (90 mg/kg/day, p.o.), DFP (125 mg/kg/day, p.o.), and EVR (1 mg/kg/day, i.p.) for 30 days. Rats were subjected to neurobehavioral assessments including open-field, rotarod, Y-maze, and tail-immersion tests. Rats' cortices were examined histologically, and acetylcholinesterase (AChE) expression was evaluated immunohistochemically. Several biochemical markers were assessed including oxidative stress markers such as reduced and oxidized glutathione, superoxide dismutase and malondialdehyde, in addition to ferroptotic markers including acyl-CoA synthetase long-chain family member-4, lysophosphatidylcholine acyltransferase-3, iron responsive element binding protein-2, ferritin heavy chain-1, and transferrin receptor-1. IMI administration led to marked biochemical derangements, cortical damage, reduced AChE expression, altered spontaneous motor function, locomotor coordination, spatial memory, and pain threshold while increasing anxious behaviours. DFP ameliorated oxidative stress, reduced ferroptotic markers and alleviated the neurobehavioural defects. Meanwhile, co-administration of EVR abolished these protective effects, consistent with enhanced autophagy-associated iron release and ferroptosis activation. Overall, these findings support the therapeutic potential of DFP against IMI-induced neurotoxicity and highlight ferroptosis as a promising therapeutic target in pesticide-related neurodegeneration.

Vulvovaginal fungal infections remain a major therapeutic challenge due to poor drug penetration, recurrence, and limited efficacy of conventional formulations. Harnessing nanotechnology with a novel delivery platform offers a promising strategy to overcome these barriers. In this study, an innovative olaminogel was designed as an advanced nanocarrier for terconazole (TCZ) to enhance local antifungal therapy via the vaginal route. The formulation was prepared using the ethanol injection method and systematically optimized through a 2 factorial design considering limonene-to-surfactant ratio (factor A), oleylamine-to-drug ratio (factor B), and oleic acid-to-surfactant ratio (factor C). Optimization targeted maximal entrapment efficiency (EE%), minimal particle size (PS), and stable zeta potential (ZP). The optimized olaminogel achieved an EE% of 82.11, nano-metric PS of 217.25 nm, and a ZP of - 33.05 mV. TEM confirmed well-formed vesicles, while FTIR verified successful encapsulation. Further in vitro characterization revealed pseudo-plastic rheology, sustained biphasic drug release, and stability for 3 months. Mucoadhesion testing demonstrated strong adhesion of the olaminogel to vaginal mucosa. Ex vivo permeation across rabbit vaginal mucosa demonstrated significantly deeper penetration (180 µm vs. 55 µm) compared with plain TCZ gel, corroborated by in vivo CLSM imaging. Histopathological studies further confirmed biocompatibility and absence of irritation. Importantly, microbiological evaluation revealed markedly reduced MIC and MFC values, alongside an accelerated fungicidal effect, outperforming TCZ control. Collectively, these findings highlight olaminogel as a novel and potent intravaginal nanocarrier capable of improving drug retention, mucosal penetration, and antifungal efficacy, thereby presenting a next-generation platform for safe and effective management of vaginal fungal infections.

Brain tumors represent some of the most formidable challenges in neuro-oncology due to their aggressive clinical course, resistance to therapy, and profound molecular heterogeneity. Among the emerging regulatory elements reshaping our understanding of tumor biology are long non-coding RNAs (lncRNAs), a diverse class of RNA transcripts that modulate gene expression and cellular behavior without encoding proteins. This review provides an in-depth and integrative examination of the biogenesis, regulatory mechanisms, and functional roles of lncRNAs in brain tumor development and progression. We systematically explore both canonical and non-canonical pathways of lncRNA biogenesis, detailing how these influence structural specificity and molecular interactions. This review synthesized evidence retrieved from PubMed/MEDLINE, Scopus, and Web of Science, covering publications from January 2010 to June 2025. This analysis highlights key gaps, such as context-dependent therapeutic effects that limit translational applicability. A major focus is placed on the interplay between lncRNAs and core oncogenic signaling pathways, including Phosphoinositide 3-kinase (PI3K)/serine/threonine kinase (AKT), Signal Transducer and Activator of Transcription 3 (STAT3), Wingless/Int-1 (Wnt)/β-catenin, and Transforming Growth Factor-Beta (TGF-β), which drive malignant transformation, invasion, stemness, and therapeutic resistance in gliomas. Furthermore, we dissect the molecular functions of lncRNAs as epigenetic regulators, competitive endogenous RNAs (ceRNAs), and structural scaffolds, and discuss their contribution to the dynamic tumor microenvironment. By synthesizing the latest findings, this review underscores the academic and translational importance of targeting lncRNA-associated networks. It also highlights emerging therapeutic approaches, such as antisense oligonucleotides, RNA interference, CRISPR-Cas systems, and natural lncRNA-modulating compounds, which collectively represent a promising frontier in precision medicine for brain tumors. This work offers a critical framework for future research and therapeutic innovation in the lncRNA landscape of neuro-oncology.

Viniferin, a resveratrol-derived compound that belongs to a group of plant-produced stilbenoids, functions as a natural defense against microbial invasion, toxins, infections, and ultraviolet radiation. Alpha-(α-) viniferin (trimer), beta-(β-) viniferin (dimer), delta-(δ-) viniferin (oxidative dehydrodimer), epsilon-(ε-) viniferin (distinct dehydrodimer), gamma-(γ-) viniferin (isomeric oligomer), vitisin A (R-viniferin), and vitisin B (R2-viniferin) are structurally diverse forms with distinct pharmacological activities. Antioxidant studies showed that ε-viniferin exhibited a 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging half-maximal inhibitory concentration (IC₅₀) of about 80 µM. Also, suppression of nuclear factor kappa B, cyclooxygenase-2, and prostaglandin E₂ are anti-inflammatory mechanisms. R2-viniferin demonstrated an IC₅₀ of 9.7 µM against hepatocellular carcinoma HepG2 cells at 72 h, mediated through apoptosis and cell-cycle arrest, according to anticancer studies that demonstrated dose-dependent cytotoxicity. There have been reports of additional activity against models of glioblastoma and prostate cancer. In metabolic disorders, oral α-viniferin (20-40 mg/kg/day) improved lipid and glucose homeostasis in mice fed a high-fat diet, and it additionally improved liver and renal biomarkers such as blood urea nitrogen, creatinine, alanine aminotransferase, and aspartate aminotransaminase. Several bacterial strains have shown signs of preliminary antimicrobial action. By reducing excitotoxicity and oxidative stress, viniferins also have neuroprotective effects. They also have anti-melanogenic properties by blocking the tyrosinase and melanogenesis pathways. Collectively, viniferins demonstrate pleiotropic pharmacologic activities by defined molecular mechanisms and quantifiable dose-dependent effects. The properties classify viniferins as new multifunctional drug candidates for discovery and nutraceuticals, but they highlight the need for standardized pharmacologic assays, further preclinical validation, and pharmacokinetic optimization towards clinical use.

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder with limited effective pharmacological options. Endoplasmic reticulum (ER) stress and mitochondrial dysfunction have emerged as pivotal pathological mechanisms in PTSD pathophysiology, yet therapies targeting these pathways remain largely unexplored. Citicoline, recognized for its neuroprotective properties and capacity to modulate mitochondrial homeostasis, presents a promising candidate for intervention. This study investigated citicoline's therapeutic efficacy against behavioral and hippocampal molecular abnormalities induced by single prolonged stress (SPS) in male mice. Thirty-six mice were subdivided into control, citicoline (Citi) (100 mg/kg, p.o for 7 days), SPS (2-hour restraint, 20-minute forced swim, ether exposure), and SPS+Citi (SPS followed by citicoline for 7 days) groups. Citicoline administration effectively reversed stress-induced behavioral impairments in social novelty preference, marble burying, and cue-induced freezing. At the molecular level, citicoline restored ER homeostasis by attenuating the toxic unfolded protein response characterized by reductions in phosphorylated protein kinase RNA-like ER kinase, activating transcription factor (ATF) 4, and ATF6 while upregulating the protective X-box binding protein 1. Such improvements were accompanied by reactivation of impaired mitophagy through enhanced PTEN-induced kinase 1 and parkin expression, facilitating clearance of damaged mitochondria and reactive oxygen species. Furthermore, citicoline effectively countered oxidative stress, evidenced by suppressing malondialdehyde-mediated lipid peroxidation while restoring glutathione antioxidant reserves. Citicoline also normalized mitochondrial biogenesis by upregulating peroxisome proliferator-activated receptor gamma coactivator 1-alpha and prevented neuronal apoptosis by suppressing caspase-3. Collectively, these findings establish citicoline as a promising multi-targeted therapeutic candidate for behavioral and hippocampal molecular abnormalities after SPS in male mice.

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder with limited effective pharmacological options. Endoplasmic reticulum (ER) stress and mitochondrial dysfunction have emerged as pivotal pathological mechanisms in PTSD pathophysiology, yet therapies targeting these pathways remain largely unexplored. Citicoline, recognized for its neuroprotective properties and capacity to modulate mitochondrial homeostasis, presents a promising candidate for intervention. This study investigated citicoline's therapeutic efficacy against behavioral and hippocampal molecular abnormalities induced by single prolonged stress (SPS) in male mice. Thirty-six mice were subdivided into control, citicoline (Citi) (100 mg/kg, p.o for 7 days), SPS (2-hour restraint, 20-minute forced swim, ether exposure), and SPS+Citi (SPS followed by citicoline for 7 days) groups. Citicoline administration effectively reversed stress-induced behavioral impairments in social novelty preference, marble burying, and cue-induced freezing. At the molecular level, citicoline restored ER homeostasis by attenuating the toxic unfolded protein response characterized by reductions in phosphorylated protein kinase RNA-like ER kinase, activating transcription factor (ATF) 4, and ATF6 while upregulating the protective X-box binding protein 1. Such improvements were accompanied by reactivation of impaired mitophagy through enhanced PTEN-induced kinase 1 and parkin expression, facilitating clearance of damaged mitochondria and reactive oxygen species. Furthermore, citicoline effectively countered oxidative stress, evidenced by suppressing malondialdehyde-mediated lipid peroxidation while restoring glutathione antioxidant reserves. Citicoline also normalized mitochondrial biogenesis by upregulating peroxisome proliferator-activated receptor gamma coactivator 1-alpha and prevented neuronal apoptosis by suppressing caspase-3. Collectively, these findings establish citicoline as a promising multi-targeted therapeutic candidate for behavioral and hippocampal molecular abnormalities after SPS in male mice.

Rare neurological diseases are challenging to diagnose from brain MRI because of their low prevalence, heterogeneous imaging patterns, and limited annotated datasets. Deep learning may support image-level recognition, but results from curated datasets without complete patient-level identifiers require cautious interpretation. This study proposes RareNeuroXNet, a frequency-aware multi-branch attention framework for image-level classification of rare neurological diseases from brain MRI. The objective was to assess whether combining global anatomical, local fine-grained, and frequency-domain representations improves benchmark performance, calibration, and interpretability. RareNeuroXNet uses three complementary branches: a global branch for whole-image representation, a local branch for regional feature extraction, and an FFT magnitude-based frequency branch. Features are refined using CBAM attention, fused, and classified through a fully connected head. The model was evaluated on a balanced curated dataset with five rare neurological disease classes using five-fold cross-validation, ablation analysis, calibration metrics, internal baseline comparison, paired testing against DenseNet121 local-only, and Grad-CAM visualization. MCND was also used as a complementary cross-dataset neurological MRI benchmark, not as same-task external validation. RareNeuroXNet achieved strong image-level internal benchmark performance, with accuracy of 0.9924±0.0061, macro F1-score of 0.9924±0.0061, macro AUROC of 0.9998±0.0002, and macro AUPR of 0.9992±0.0007. Calibration was favorable, with ECE of 0.0052±0.0029 and NLL of 0.0276±0.0159. Ablation results showed that the local branch was the dominant contributor, while FFT and CBAM provided supportive refinement. Compared with DenseNet121 local-only, RareNeuroXNet showed modest classification gains and clearer calibration improvements. RareNeuroXNet demonstrated strong controlled image-level benchmark performance with high discrimination, stable cross-validation behavior, favorable calibration, and Grad-CAM interpretability. However, possible correlated slices, duplicate images, or subject overlap cannot be excluded. Future work should use patient-level, same-task, multi-center external validation and 3D multimodal MRI analysis.

Doxorubicin (DOX), a widely utilized chemotherapeutic agent, is associated with significant adverse effects, including cognitive dysfunction (chemobrain) and depression. Ketamine (KET), the anesthetic, was off-label used as antidepressant and got FDA approval in 2019 for treatment-resistant depression management. Hence, this study investigated the therapeutic efficacy of single [KET(S)] versus repeated [KET(R)] subanaesthetic ketamine in mitigating DOX-induced neurological alterations in rats. Forty-eight adult male Wistar rats were subdivided into four groups: control, DOX, KET(S) (DOX followed by a single KET dose, 15 mg/kg), and KET(R) (DOX followed by repeated KET doses, 15 mg/kg/day for 14 days). Results showed that DOX administration caused marked motor dysfunction, cognitive impairment and depression-like behavior, along with elevated neuroinflammation and disrupted neurotrophic signaling. Both KET regimens improved behavioral performance, suppressed systemic and local inflammation, evidenced by suppressing tumor necrosis factor-alpha and nicotinamide adenine dinucleotide phosphate oxidase activity. Also, KET(R) suppressed phosphorylation of key neurotransmitter transporters: phospho T53-dopamine transporter, phospho S563-glutamate transporter-1, and phospho T276-serotonin transporter, which led to enhanced hippocampal brain-derived neurotrophic factor/tropomyosin receptor kinase B signaling. Notably, KET(R) produced superior behavioral and biochemical improvements compared to KET(S). Histopathological examinations corroborated these findings. Collectively, these data suggest that KET, particularly when administered repeatedly at low doses, could be a promising adjunctive therapy to enhance quality of life for cancer patients undergoing DOX chemotherapy. However, because key intermediate nodes were not directly measured and KET-only control groups were not included, the proposed mechanistic cascade should be regarded as a hypothetical integrative model that warrants further validation.

BACKGROUND: To compare the adding effect of virtual reality exercises (VRE) versus high volume resistance training (HVRT) to low calorie diet (LCD) on blood biomarkers and body fat in obese adult females.

METHODS: Sixty sedentary obese females (aged 40-60 years; BMI 30-40 kg/m) were randomly assigned to three groups: VRE plus LCD, HVRT and LCD, or LCD only. Both exercise interventions were conducted three times weekly for 12 weeks. The outcome measures were lipid profile, glycated hemoglobin (Hb A1C), C-reactive protein (CRP), percentage of body fat (PBF), trunk fat (TF), waist hip ratio (WHR), skinfold thickness (SFT), quality of life (QOL), and fatigue severity (FS). All measurements were taken at baseline and after twelve weeks. Data were analyzed using mixed-model MANOVA with Bonferroni post-hoc tests (α < 0.05).

RESULTS: Significant multivariate effects were found for group, time, and group-time interaction (p < 0.001). Both VRE and HVRT groups demonstrated significant reductions in total cholesterol, triglycerides, LDL, HbA1c, CRP, PBF, TF, WHR, and skinfold thickness, with increased HDL and improved QOL and FS (p < 0.01). No significant differences were observed between VRE and HVRT groups (p > 0.05), whereas both were superior to LCD alone across all outcomes (p < 0.05).

CONCLUSION: Combining VRE or HVRT with a LCD resulted in comparable improvements on lipid profile, HbA1c, CRP, PBF, TF, WHR, SFT, QOL, and FS, exceeding the benefits of dietary intervention alone. Virtual reality exercise may offer an engaging alternative to traditional resistance training for obesity management in women.

Cyclin-dependent kinase 2 (CDK2) and vascular endothelial growth factor receptor 2 (VEGFR2) are essential for the development of tumor angiogenesis and the cell cycle, respectively. Inhibiting both kinases at the same time has therefore become a sensible anticancer tactic. A number of unique hybrid compounds containing isatin-triazole and isatin-imidazole scaffolds were created and thoroughly described in an effort to find dual CDK2/VEGFR2 inhibitors. Compounds 5d, 5k, and 10 showed the strongest antiproliferative activity against breast (MCF7) and prostate (PC3) cancer cell lines among the produced derivatives. Notably, compound 10 showed the most inhibitory potency, with IC values of 0.058 μM for VEGFR2 and 0.789 μM for CDK2, respectively. These values are on par with or higher than those of the reference standards, roscovitine and sunitinib. Additionally, a biological study showed that compounds 5d and 5 k had negligible off-target toxicity and were selectively lethal to cancer cells compared to normal HaCaT keratinocytes. Furthermore, cell cycle studies revealed that compound 5d produced S-phase arrest, whereas compounds 5 k and 10 mostly caused G-phase arrest, in line with their kinase inhibition profiles. Additionally, the potent analogues 5d and 10 substantially decreased colony formation and tumoral cell migration. Molecular docking and dynamics simulations helped to clarify the possible binding interactions inside the ATP-binding sites of CDK2 and VEGFR2, confirming the dual-binding mechanism that underlies their potent effects. According to all of these findings, compound 10 is a potential dual CDK2/VEGFR2 inhibitor that offers a helpful foundation for the development and optimization of future multitarget anticancer agents.

BACKGROUND & AIMS: Noninvasive tests (NITs) are widely used to risk-stratify patients with metabolic dysfunction-associated steatotic liver disease (MASLD); however, their performance may vary according to patient characteristics. We evaluated the accuracy of NITs in a large, multinational MASLD cohort across select subpopulations.

METHODS: We analyzed 18,759 adults with biopsy-confirmed MASLD from 41 countries. NITs included FIB-4, liver stiffness measurement (LSM), and Agile-3+. Diagnostic performance for advanced fibrosis (F3-F4) was measured using areas under the curve (AUCs) across subgroups defined by age, sex, type 2 diabetes (T2D), obesity, and alcohol use. Subgroup-specific cutoffs were derived.

RESULTS: Advanced fibrosis was present in 37% of patients. Pooled AUCs were 0.79 for FIB-4, 0.83 for LSM, and 0.86 for Agile-3+. FIB-4 accuracy declined with age (AUC 0.70 in ≥65 years vs 0.79 in <65 years, P<.0001) and in middle-aged patients with T2D. The LSM performance remained stable across T2D status but was moderately reduced in patients with obesity and, more profoundly, morbid obesity (body mass index [BMI] >35 kg/m). Sex and alcohol use had minimal impact on AUCs. Age- and T2D-specific FIB-4 cutoffs varied substantially to maintain predefined accuracy (sensitivity or specificity). The cutoffs for LSM also differed based on patients' BMI, with lower diagnostic cutoffs for advanced fibrosis required in nonobese MASLD (sensitivity 80%: 8.8 kPa in lean, 9.0 kPa overweight, 9.6 kPa in obesity, 11.0 kPa in morbid obesity).

CONCLUSIONS: Accuracy of NITs for advanced fibrosis in MASLD is influenced by age, T2D, and obesity. Age-adjusted FIB-4 thresholds may enhance risk stratification. Imaging-based and composite NITs (LSM and Agile-3+) provide more consistent performance across MASLD subpopulations.

Dental disorders, such as cavities, periodontal disease, and periapical infections, remain major global health issues, often resulting in pain, tooth loss, and systemic complications if not identified early. Traditional diagnostic methods rely heavily on visual inspection and manual interpretation of panoramic X-ray images by dental professionals, making them time-consuming, subjective, and less accessible in resource-limited settings. : Accurate and timely diagnosis is vital for effective treatment and prevention of disease progression, reducing healthcare costs and patient discomfort. Recent advances in deep learning (DL) have demonstrated remarkable potential to automate and improve the precision of dental diagnostics by objectively analyzing panoramic, periapical, and bitewing X-rays. In this research, a hybrid feature-fusion framework is proposed. It integrates handcrafted Histogram of Oriented Gradients (HOG) features with deep representations from DenseNet-201 and the Shifted Window (Swin) Transformer models. Sequential dependencies among the fused features were learned utilizing the Long Short-Term Memory (LSTM) classifier. The framework was evaluated on the Dental Radiography Analysis and Diagnosis (DRAD) dataset following preprocessing steps, including resizing, normalization, Contrast Limited Adaptive Histogram Equalization (CLAHE) enhancement, and image cropping. : The proposed LSTM-based hybrid model achieved 96.47% accuracy, 91.76% specificity, 94.92% precision, 91.76% recall, and 93.14% F1-score. : The proposed framework offers flexibility, interpretability, and strong empirical performance, making it suitable for various image-based recognition applications and serving as a reproducible framework for future research on hybrid feature fusion and sequence-based classification.

Isolation of beneficial probiotics from traditional foods is a priority in functional food research. We isolated and characterized a lactic acid bacteria (LAB) probiotic strain from Egyptian cuisine, with therapeutic applications for alleviating the manifestations of metabolic syndrome (MetS), including hyperglycemia, hypercholesterolemia and obesity. LAB (n = 10) were isolated from 12 food and juice samples, identified and assessed in vitro for glucose- and cholesterol-lowering capabilities. The most promising isolate underwent probiotic characterization, including gastrointestinal tolerance, surface hydrophobicity, auto-aggregation, and milk fermentation capacity. Other beneficial properties, such as exopolysaccharide production and antimicrobial activity, were also tested. The selected isolate was evaluated for a hypoglycemic and hypocholesterolemic effect using a high-fat diet/streptozotocin-induced hypercholesterolemia and diabetes model in Wistar rats. Lactiplantibacillus plantarum Y, isolated from Egyptian cottage cheese, reduced glucose and cholesterol levels in vitro by 53 ± 0.47% and 98 ± 0.18%. It showed good probiotic characteristics: minimal viability loss in simulated gastrointestinal conditions (0.07 and 0.08 log CFU/mL), good hydrophobicity (> 70%), high auto-aggregation (82.6 ± 0.86% after 24 h), positive exopolysaccharide production, milk fermentation capability with 21-day storage stability, and an antimicrobial activity against Staphylococcus aureus ATCC 25923, Salmonella enterica ATCC 14028, Klebsiella pneumoniae ATCC 10031, and Escherichia coli ATCC 25922. In vivo administration of L. plantarum Y in a MetS rat model resulted in significant hypoglycemic, hypocholesterolemic, and anti-obesity effects. In conclusion, L. plantarum Y is a promising probiotic for managing MetS manifestations. Further clinical investigations for use as a therapeutic intervention are highly recommended.

Accurate classification of cancer subtypes is crucial for personalised therapies and targeted interventions. In this study, we propose BioGAT-LGG, a deep learning framework that integrates multi-omics data, including mRNA, miRNA, and DNA methylation, using a correlation-based Graph Attention Network version 2 (GATv2) for biomarker discovery and Lower-Grade Glioma (LGG) subtype classification. Unlike existing methodologies that rely on external biological priors, such as protein-protein interaction networks or reference graphs, BioGAT-LGG constructs gene-driven correlation graphs, enabling the model to learn biologically meaningful molecular interactions. To improve feature interpretability and reduce dimensionality, LASSO regression is performed during model training. The model achieved 98.03% accuracy, with precision (98.12%), recall (97.74%), and F1-score (97.87%) in a stratified 10-fold cross-validation. Extensive analysis and enrichment of known cancer-related pathways, including PI3K-Akt signalling, Small Cell Lung Cancer, and Transcriptional Misregulation in Cancer, identified the biomarkers hsa-mir-3936, MTCO1P40, and CCND2, which were subsequently validated. These results indicate that BioGAT-LGG effectively captures biologically validated mechanisms and can enable clinically significant subtype classification and biomarker-guided decision-making. This framework thus lays a scalable foundation for multi-omics integration in oncology, which can be further adopted in other tumour types.

Lipopolysaccharide (LPS) in follicular fluid impairs steroid production and oocyte developmental competence in cows and mice. This study assessed LPS concentrations in equine follicular fluid and their association with steroid and some cytokine levels. Additionally, we evaluated whether LPS exposure during in vitro maturation (IVM) affects equine oocyte developmental competence. In experiment 1, follicular fluid from large follicles (>30 mm in diameter) was collected from 16 slaughterhouse mares, and concentrations of LPS, estradiol, progesterone, TNF-α, and IL-6 were measured. In experiment 2, cumulus-oocyte complexes (COCs) were held overnight, then matured in vitro with (1 ng LPS/1 mL; LPS group) or without LPS (control group), and mature oocytes (n = 47 and 45, respectively) were fertilized using ICSI. Follicular fluid concentrations of LPS ranged between 5.21 and 12.08 endotoxin unit (EU)/mL (10 EU = 1 ng) and were negatively correlated with progesterone, IL-6, and TNF-α levels. Compared to controls, LPS exposure during IVM did not significantly affect maturation (56 % vs. 61 %; P = 0.432), cleavage (71 % vs. 65 %; P = 0.873), or blastocyst rates (21 % vs. 19 %; P = 0.227). In conclusion, this is the first report detecting LPS in the follicular fluid of clinically healthy mares and showing its negative association with progesterone, IL-6, and TNF-α. Exposing equine COCs to 1 ng/mL LPS during in vitro maturation had no significant effect on blastocyst rates. However, further research is needed to determine whether blastocysts derived from oocytes matured under LPS exposure can establish pregnancy after transfer.

OBJECTIVES: To culturally adapt the Arabic version of the Exercise Adherence Rating Scale (EARS) and evaluate its psychometric properties in chronic low back pain patients (CLBP).

METHODS: This methodological study cross-culturally adapted EARS into Arabic (EARS-Ar) following recommended guidelines. Ninety-three CLBP outpatients were prescribed home-based exercises. Dimensionality of the EARS-Ar was assessed by Confirmatory Factor Analysis (CFA) and validity was assessed by comparing EARS-Ar with Fear-Avoidance Beliefs Questionnaire (FABQ), Numeric Pain Rating Scale (NPRS), and Roland Morris Disability Questionnaire (RMDQ). Internal consistency and test-retest reliability were evaluated. Responsiveness was examined using the receiver operating characteristic curve (AUC).

RESULTS: CFA confirmed dimensionality of the EARS-Ar. It had moderate negative correlations (rho= -0.42 to -0.62) with FABQ, NPRS, and RMDQ. EARS-Ar demonstrated excellent internal consistency ( = 0.97). Intraclass correlation coefficients were excellent (ICCs= 0.89-0.920) with acceptable corrected item correlations (rho= 0.56-0.77). Responsiveness of the EARs-Ar was good with significant moderate correlation (rho= 0.35) between the EARS-Ar change score and global rating of change (GRoC). A cutoff point of 12.5/24 was determined with moderate accuracy (AUC= 0.81, sensitivity= 81%, specificity= 41%).

CONCLUSIONS: EARS-Ar showed good reliability, validity, and responsiveness, which renders it a reliable tool for evaluating exercise adherence behavior of CLBP patients.

Progressive familial intrahepatic cholestasis (PFIC) syndromes are rare autosomal recessive disorders. We present the first detailed phenotype-genotype of PFIC children with normal gamma-glutamyltransferase (GGT) [normal GGT/PFIC] in an African population. Thirty-one pediatric patients belonging to 28 unrelated Egyptian families with normal GGT/PFIC were reported. Clinical, biochemical, histopathological, and genetic data were systematically analyzed. Patients were 15 males/16 females (55 ± 52 months at diagnosis). Apart from cholestasis, clinical features included severe pruritus (visual analogue scale 7.5 ± 3.4), hepatomegaly (80.6%), sleep deprivation (41.9%), and splenomegaly (19.4%). 13/28 families had ABCB11 variants (PFIC2), 6/28 families had ATP8B1 (PFIC1) and TJP2 (PFIC4) variants each, 2/28 had MYO5B variants (PFIC10), and one family had USP53 variants (PFIC7). Twenty-five disease-causing variants were reported, including 16 novel variants. PFIC1 patients were more severely affected compared to other PFIC syndromes, as the incidence of growth retardation, sibling deaths, skin changes, and progression to biliary diversion were all significantly higher (p value 0.006, 0.012, 0.037, and 0.012, respectively). In contrast, none of the 13 PFIC2 children progressed to biliary diversion, and all four PFIC10 children had normal liver transaminases. Our study expands the global phenotypic and genotypic knowledge of normal GGT/PFIC and will facilitate better care for the syndrome in Egypt.

Determination of postmortem interval (PMI) is a fundamental aspect of forensic medicine, aiding in the reconstruction of the time of death in medico-legal investigations. The present study aims to compare gender-based postmortem changes and investigates the role of collagen fibers as a potential indicator of PMI in albino rats. Eighteen male and nine female adult albino rats were examined. Three prostates, three uterine horns, and the quadriceps muscle of the hind limb of each animal were collected at six time points (0, 6, 24, 36, 48, and 144 h postmortem) after scarifying rats by neck dislocation. Morphological analysis revealed progressive softening of the organs with darker discoloration with increasing PMI. Histological examination using hematoxylin and eosin staining showed cellular degradation up to 48 h PM. Masson's trichrome staining highlighted the persistence of collagen fibers up to 144 h. Notably, male prostates exhibited greater resistance to postmortem degradation compared to female uteri, suggesting that potential sex identification by gonads is possible up to 48 h PM.