Metabolic syndrome (MetS) is associated with a plethora of different comorbidities. Exploring its key molecular mechanisms, such as advanced glycation end product and its receptor (AGE/RAGE) pathway, holds great potential. Numerous sources agree that targeting the AGE/RAGE pathway is a potential therapeutic strategy for MetS. However, the regulation of AGE/RAGE by microRNAs (miRNAs) in the context of MetS is still poorly understood. This review aimed to provide a systematic picture of the influence of miRNAs on AGE/RAGE in the context of MetS, with a particular focus on its ligands and receptors. This review achieves this in two ways: through an inductive “bottom-up” approach realized by a classical descriptive literature search, and through a deductive/synthetic “top-down” approach based on carefully selected miRNA profiling studies in MetS and its comorbidities. Although the initial inductive approach allowed the identification of some miRNAs of interest, almost all articles on this topic focus on the regulation of processes exclusively involved in atherogenesis. The new deductive approach has broadened the research horizon: It has enabled the discovery of new promising miRNAs and allowed for ranking different comorbid pathologies in MetS according to the degree of miRNA dysregulation of AGE/RAGE. Thus, in addition to atherosclerosis, significant miRNA dysregulation of AGE/RAGE was also described in MetS, particularly in immune cells, as well as in subcutaneous adipose tissue in obesity. This review, along with the novel approaches to systematizing the data contained therein may contribute to the understanding of MetS pathogenesis and the search for targets for the treatment of MetS.

Despite significant advances in Parkinson’s disease (PD) treatment, it remains incurable, with limited therapeutic options. Currently, repurposing already tested, safe drugs has emerged as an effective therapeutic strategy against various neurodegenerative diseases, including PD. Using a drug-repurposing approach, the current study investigated the neuroregenerative potential of polysialic acid mimicking compounds, 5-nonyloxytryptamine oxalate (5-NOT) and Epirubicin (Epi), an anti-cancer drug, in 1-methyl-4-phenylpyridinium (MPP+)-treated human neuroblastoma SH-SY5Y cells as a PD model.

The excitotoxic model was established by exposing SH-SY5Y cells to 500 µM of MPP+ and subsequently treating them with the test compounds. The effect of MPP+-induced toxicity on cellular and nuclear morphology, as well as on the expression of neuroplasticity and cell survival proteins, were studied by immunostaining, gelatin zymogram, and Western blot assays.

Treatment with 5-NOT and Epi significantly promoted the survival of MPP+-challenged SH-SY5Y cells and prevented changes in their cellular and nuclear morphology by regulating the expression of microtubule-associated protein (MAP-2) and polysialylated-neural cell adhesion molecule (PSA-NCAM) and NCAM synaptic plasticity proteins. Further, 5-NOT and Epi treatment also protected SH-SY5Y cells by restoring levels of nitric oxide, matrix metalloproteinase, and stress response proteins. Interstingly, 5-NOT attenuated MPP+-induced toxicity in SH-SY5Y cells by regulating the intrinsic protein kinase AKT/BAD apoptotic pathway and the P-38 MAP kinase synaptic plasticity pathway.

These preliminary findings suggest that 5-NOT, as a potential polysialic acid glycomimetic, may serve as a promising drug candidate for targeting neurodegeneration of dopaminergic neurons, a hallmark feature of PD.

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment. Conventional computer-aided detection systems have shown limitations, including high false-positive rates and low sensitivity. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have shown great potential in improving the accuracy and reliability of nodule detection and classification. This study aimed to develop and evaluate an automatic method for lung nodule detection and classification using a CNN-based architecture applied to computed tomography images from the publicly available LIDC-IDRI database.

This retrospective study was conducted on 82 patients (10,496 computed tomography slices) selected from the LIDC-IDRI database. The proposed method consists of five main steps: image preprocessing, lung parenchyma segmentation using Otsu’s thresholding and morphological operations, detection of nodule candidates, feature extraction, and classification using a CNN model. The CNN architecture includes two convolutional layers (20 and 30 filters, 3×3 kernel), ReLU activation, max-pooling layers, and a Softmax output layer. The network was trained with a mini-batch size of 32 for 50 epochs using the Stochastic Gradient Descent with Momentum optimizer (learning rate = 0.001, momentum = 0.9). Model performance was evaluated in terms of sensitivity, specificity, precision, and accuracy.

The proposed CNN model successfully detected pulmonary nodules and achieved accurate classification between benign and malignant nodules. On the LIDC-IDRI dataset, the model achieved a sensitivity of 98.7%, specificity of 97.5%, precision of 97.9%, and accuracy of 98.4%. Comparative analysis with recent studies, including hybrid CNN-long short-term memory and ResNet-based models, demonstrated that the proposed method provides competitive performance while maintaining lower computational complexity. The classification of nodule subtypes (solid, partially frosted, totally frosted) showed satisfactory discrimination results.

The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges limitations such as single-database validation and a relatively small training size. Future work will focus on validating the model across other datasets (e.g., ELCAP, NELSON) and optimizing multi-class classification performance to enhance generalizability and clinical applicability.

Hepatocellular carcinoma (HCC) represents the most prevalent malignancy in Egypt and globally. However, non-invasive diagnostic/prognostic biomarkers for early detection of HCC are still lacking. Circular RNAs (circRNAs) are one of the promising biomarkers. They are considered stable, long-stranded non-coding RNAs in a sealed circular form held together by covalent bonds. circRNAs have been observed in several genetic studies to play a vital role in the initiation and progression of malignancy. Our current cross-sectional study aimed to evaluate the potential role of serum-derived hsa_circ_101555 as a diagnostic biomarker for HCC, in addition to comparing its prognostic significance and predicting the response to therapy.

The serum expression level of hsa_circ_101555 was measured using real-time polymerase chain reaction in 62 clinically/radiologically diagnosed Egyptian HCC patients at baseline and three months after HCC treatment. These results were compared to those of 30 healthy subjects.

Our data showed that the mean circRNA value was highest in HCC cases (7.66 ± 3.74) compared to healthy controls (1.21 ± 0.96). Furthermore, the circRNA value showed excellent diagnostic accuracy in differentiating HCC patients from healthy controls at a cutoff point of 1.966, as indicated by an area under the curve of 0.984. In addition, it showed a prognostic role in differentiating between HCC progression and regression in these patients based on response evaluation criteria in solid tumors (RECIST)/ modified- RECIST (mRECIST) response categories at the cutoff point 5.1150, with an area under the curve of 0.891 and a standard error of 0.058. Interestingly, positive correlations between post-intervention circRNA levels and laboratory measurements were observed in our HCC patients, including the albumin-bilirubin score (r = 0.424, P = 0.001**), the neutrophil-to-lymphocyte ratio (r = 0.410, P = 0.001**), alpha-fetoprotein (r = 0.273, P = 0.032*), the aspartate aminotransferase/alanine aminotransferase ratio (r = 0.284, P = 0.025*), fibrosis-4 (r = 0.501, P = 0.000**), and the aspartate aminotransferase to platelet ratio score (r = 0.436, P = 0.000**), indicating an association with worsening liver inflammation, fibrosis, and disease progression. Lastly, post-intervention circRNA values were significantly correlated with clinical/pathological tumor key features, including larger tumors (>5 cm) (P = 0.019), multiplicity (tumor numbers > 3) (P = 0.031), vascular invasion (P = 0.030), Barcelona Clinic Liver Cancer stage C (P = 0.007), and advanced Tomur, Node, Metastasis stage (P = 0.012).

To our knowledge, this is the first study to highlight the expression levels of serum-derived hsa_circ_101555 in Egyptian HCC patients. Our data showed its upregulation in HCC cases compared to healthy subjects. Additionally, its increased levels were associated with tumor progression according to the RECIST/mRECIST categories. Furthermore, its significant correlation with markers/scores of liver inflammation, dysfunction, and tumor pathological features underscores its potential as a promising diagnostic/prognostic biomarker, aiding in better clinical decision-making for the management of hepatocellular carcinoma.

Infection control is essential for the success of prosthodontic and oral implant procedures, as microbial contamination can lead to serious complications such as denture stomatitis and peri-implantitis. While synthetic disinfectants like chlorhexidine are commonly used, they may cause side effects including irritation, toxicity, and the development of microbial resistance over time. Natural products derived from plants, animals, and minerals are currently being explored as safer alternatives. Compounds such as epigallocatechin gallate from green tea; eugenol from clove oil; quercetin, thymol, cinnamaldehyde, and flavonoids from propolis; and terpinen-4-ol from tea tree oil have shown strong antimicrobial and anti-biofilm properties. These natural agents are not only effective against harmful oral bacteria but also promote healing, are more biocompatible, environmentally friendly, and are often preferred by patients. However, challenges remain regarding their routine clinical use. The strength and composition of natural agents can vary, and there is a lack of consistent product standards, clinical trials, and comprehensive safety data. Currently, these products are not approved by the U.S. Food and Drug Administration for dental use and are only available as over-the-counter remedies. Production costs and scalability must also be evaluated in comparison with synthetic alternatives. Emerging technologies, such as nanocarriers and targeted delivery systems, are being developed to enhance the effectiveness of natural agents in dental applications. Further clinical research and the establishment of clear regulatory guidelines are necessary to support their integration into clinical practice. Natural disinfectants hold significant potential to become valuable, safe, and sustainable tools for maintaining hygiene in prosthodontics and oral implantology.

Leishmaniasis is a dangerous yet neglected tropical disease affecting a vast population of the world. Several medicinal plants and their constituents (natural products/phytochemicals) have been considered of prime importance for the management of leishmaniasis over the years. The present review sheds light on the molecular mechanisms of the constituents obtained from medicinal plants that are pre-clinically effective against leishmaniasis. Various mechanisms by which medicinal plant-derived natural products elicit their action against leishmaniasis are illustrated in the literature. The mechanisms identified include: disruption of cytoplasmic and mitochondrial membranes, induction of apoptosis and autophagy, modulation of gene expression and immunological pathways, pro-oxidant effects (disrupting redox balance) with mitochondrial dysfunction, cell cycle arrest, impaired cellular bioenergetics, i.e., adenosine triphosphate production and coagulation of cellular contents within Leishmania parasites. Future phytochemical and pharmacological (especially clinical) studies are necessary to further understand the mechanistic details of medicinal plant-derived natural compounds and to develop new phytotherapeutic entities from nature against leishmaniasis.

Mitochondrial respiratory complexes (Complexes I–V) and their assembly into respiratory supercomplexes (SCs) are fundamental to liver bioenergetics, redox homeostasis, and metabolic adaptability. Disruption of these systems contributes to major liver diseases, including non-alcoholic fatty liver disease, alcoholic liver disease, drug-induced liver injury, viral hepatitis, and hepatocellular carcinoma, by impairing adenosine triphosphate synthesis, increasing oxidative stress, and altering metabolic pathways. Recent advances have clarified the structural-functional interdependence of individual complexes within SCs, revealing their dynamic remodeling in response to physiological stress and pathological injury. These insights open opportunities for clinical translation, such as targeting SC stability with pharmacological agents, nutritional strategies, or gene therapy, and employing mitochondrial transplantation in cases of severe mitochondrial failure. Precision medicine approaches, incorporating multi-omics profiling and patient-derived models, may enable individualized interventions and early detection using SC integrity as a biomarker. By linking molecular mechanisms to therapeutic strategies, this review underscores the potential of mitochondrial-targeted interventions to improve outcomes in patients with liver disease.

Temporal lobe epilepsy (TLE) is the most common focal epilepsy, with many patients developing drug-resistant epilepsy. Surgical interventions, including stereoelectroencephalography (SEEG)-guided temporal lobe resection (TLR) and SEEG-guided responsive neurostimulation (RNS), are key treatment options. This systematic review compares the efficacy and safety of these interventions in drug-resistant TLE.

A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. A comprehensive search of multiple databases was performed (January 23–February 14, 2025). Eligible studies included adult patients with drug-resistant TLE undergoing SEEG-guided TLR or RNS (where SEEG was used pre-implant for localization). Primary outcomes assessed included seizure freedom, seizure reduction, adverse events, and quality of life (QoL) improvements. Quality assessments were performed using appropriate tools for randomized and observational studies.

Fifteen studies met the inclusion criteria, with sample sizes ranging from 10 to 440 participants. SEEG-guided TLR achieved an average seizure freedom rate of 58.5% (range: 32–85%) and a mean seizure reduction of 75% (range: 60–90%). SEEG-guided RNS resulted in an average seizure freedom rate of 12.85% and seizure reduction of 63.2%, with variability across studies. QoL improvements were reported in 80–82% of patients. Adverse events were infrequent but varied between interventions.

This review highlights the effectiveness of SEEG-guided TLR and RNS in managing drug-resistant TLE. While both interventions reduce seizure burden and improve QoL, seizure freedom rates are higher with resection. However, gaps remain in understanding long-term cognitive outcomes and demographic influences on treatment response. Future research should address these factors to refine patient selection and optimize epilepsy care.

Emergency department (ED) presentations are associated with higher cancer mortality. This study aimed to investigate the prevalence, frequency, and risk factors in Australian patients diagnosed with malignant skin cancers.

This data-linkage cohort study examined adult patients presenting to the ED at the Royal Melbourne and Western Health hospitals within 12 months of a malignant skin cancer diagnosis. Multivariable logistic and Poisson regressions were used to analyze factors influencing the prevalence and frequency of ED presentations.

A total of 3,873 patients were diagnosed with skin malignancies between 2010 and 2018, of which 631 were diagnosed with melanoma. The prevalence of ED presentation was 29%, representing 2,119 episodes of care (median: 0; range: 0–14). Risk factors for a higher prevalence and frequency included: age ≥75 years (odds ratio (OR) = 1.78 [95% confidence interval 1.47–2.15]; incidence risk ratio (IRR) = 1.52 [1.35–1.70]); male (OR = 1.17 [1.01–1.36]; IRR = 1.23 [1.12–1.35]); socioeconomic status levels of 0–30% (OR = 1.59 [1.24–2.03]; IRR = 1.69 [1.45–1.96]) and 71–100% (OR = 1.30 [1.07–1.58]; IRR = 1.27 [1.12–1.45]); preferred language other than English (OR = 1.47 [1.17–1.84]; IRR = 1.49 [1.32–1.69]); and experience with any systemic therapy or radiotherapy (OR = 3.77 [2.12–6.71]; IRR = 2.36 [1.82–3.05]). Age < 65 years was protective (OR = 0.72 [0.59–0.89]; IRR = 0.78 [0.68–0.90]). Other preferred languages and cancer treatment experience were also risk factors in the sub-cohort with melanoma.

This study reports the prevalence and frequency of ED presentations following a skin cancer diagnosis and their association with socioeconomic and linguistic factors in Australia. Increased awareness of these factors could help address health inequities and potentially reduce the need for ED presentations.