Explore the vast range of titles available.

Ageing-associated cancers are characterised by the dual hallmarks of persistent DNA damage and the ability of tumour cells to escape senescence checkpoints, which drive genomic instability and uncontrolled proliferation. In this study, we identified crucial proteins with PDB IDs—2YEX (Chk1 kinase), 4HG7 (MDM2 E3 ubiquitin ligase), 4JSX (mTOR kinase domain), and 5DS3 (PARP-1 DNA repair enzyme)—involved in ageing-related cancers and performed docking studies with Extra Precision (XP) followed by MM-GBSA-based pose processing against the FDA-approved DrugBank library (LigPrep: 10907 compounds). The extensive docking computations identified many good candidates; however, Mitoxantrone emerges as the topmost candidate with docking scores of −6.23 to −16.044 Kcal/mol and MM-GBSA score of −49.19 to −85.14 Kcal/mol, which currently is being used to treat advanced prostate cancer and acute nonlymphocytic leukaemia (ANLL) and would be easier to repurpose to other ageing-related cancers. Mitoxantrone also emerges as a better candidate compared to the control drug Doxorubicin. Further, the complex of all 4 proteins with Mitoxantrone was taken for interaction fingerprints and found that the most interacting residues with counts were 6GLY, 6VAL, 5GLU, 5LEU, 4ALA, 3ASP, and 3TYR, among others. The pharmacokinetics and Density Functional Theory computations further support Mitoxantrone as a potential candidate. We also performed a 5-nanoseconds (ns) WaterMap for hydration site identification and the role of water in stabilisation of the complex, followed by a 100 ns MD Simulation that resulted in stable deviation and fluctuations mostly under <2Å and a web of simulation interactions making the complex stable. Furthermore, the same trajectories were used for the Binding Free and Total Complex Energies computations, revealing that the complexes were stable. All the studies, from protein energies to docking to simulation and binding free energy, supported the stable complexes; however, experimental studies are necessary before their use.

Background: Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed genes (DEGs) for BC diagnosis and prognosis. Methods: A cohort of 701 samples from 11 GEO BC microarray datasets was used for the identification of significant DEGs. Seven ML methods, including RFECV-LR, RFECV-SVM, LR-L1, SVC-L1, RF, and Extra-Trees were applied for gene reduction and the construction of a diagnostic model for cancer classification. Kaplan–Meier survival analysis was performed for prognostic signature construction. The potential biomarkers were confirmed via qRT-PCR and validated by another set of ML methods including GBDT, XGBoost, AdaBoost, KNN, and MLP. Results: We identified 355 DEGs and predicted BC-associated pathways, including kinetochore metaphase signaling, PTEN, senescence, and phagosome-formation pathways. A hub of 28 DEGs and a novel diagnostic nine-gene signature (COL10A, S100P, ADAMTS5, WISP1, COMP, CXCL10, LYVE1, COL11A1, and INHBA) were identified using stringent filter conditions. Similarly, a novel prognostic model consisting of eight-gene signatures (CCNE2, NUSAP1, TPX2, S100P, ITM2A, LIFR, TNXA, and ZBTB16) was also identified using disease-free survival and overall survival analysis. Gene signatures were validated by another set of ML methods. Finally, qRT-PCR results confirmed the expression of the identified gene signatures in BC. Conclusion: The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively.

Introduction. Obesity is becoming the most common health problem of the 21st century, as it will contribute significantly to the high prevalence of cardiovascular disease in developing countries. The main objective of our study was to estimate the prevalence of obesity and overweight among adults attending primary health care settings, southwestern region of the Kingdom of Saudi Arabia. Methods. The studied population was composed of adults visiting primary health care centres in the southwestern region of Saudi Arabia. A cross-sectional study was carried out on a representative sample of 1681 adult patients. Obesity and overweight were defined according to the WHO standards. Statistical analysis was conducted using the statistical package SPSS 17.0. Logistic regression analysis was used to identify independent predictors of obesity and overweight in the studied population. Results. Data on body mass index (BMI) measurement was recorded for 1649 out of 1681 participants (98.1%). The overall mean weight was 74.1 ± 15.81 kg; and that for men was 77.69 ± 16.14 kg vs. 69.37 ± 14.02 kg for women with significant statistical difference of p < 0.001. The overall prevalence of overweight and obesity was, respectively, 38.3% and 27.6%. Smoking was not significantly associated with obesity, whereas hypertension was significantly associated with obesity. The risk of overweight or obesity significantly increased from the highest to the lowest monthly income; it passed from 1.67 CI 95% = [1.24-2.25] within the category 5000-7000 SAR to 2.23 CI 95% = [1.71-2.90] within the category less than 5000 SAR. Conclusion. Our study showed high prevalence of overweight and obesity which should be considered as a public health concern to be followed by specific interventions at the community level with multidisciplinary activities starting from childhood as a primordial prevention program.

BackgroundRecent advances in nanotechnology have offered new hope for cancer detection, prevention, and treatment. Nanomedicine, a term for the application of nanotechnology in medical and health fields, uses nanoparticles for several applications such as imaging, diagnostic, targeted cancer therapy, drug and gene delivery, tissue engineering, and theranostics. ResultsHere, we overview the current state-of-the-art of radiolabeled nanoparticles for molecular imaging and radionuclide therapy. Nanostructured radiopharmaceuticals of technetium-99m, copper-64, lutetium-177, and radium-223 are discussed within the scope of this review article.ConclusionNanoradiopharmaceuticals may lead to better development of theranostics inspired by ingenious delivery and imaging systems. Cancer nano-theranostics have the potential to lead the way to more specific and individualized cancer treatment.

Cardiovascular disease is the leading cause of morbidity/mortality worldwide. Metformin is the first therapy offering cardioprotection in type 2 diabetes and non-diabetic animals with unknown mechanism. We have shown that metformin improves angiogenesis via affecting expression of growth factors/angiogenic inhibitors in CD34+ cells under hyperglycemia-hypoxia. Now we studied the direct effect of physiological dose of metformin on human umbilical vein endothelial cells (HUVEC) under conditions mimicking hypoxia-hyperglycemia. HUVEC migration and apoptosis were studied after induction with euglycemia or hyperglycemia and/or CoCl2 induced hypoxia in the presence or absence of metformin. HUVEC mRNA was assayed by whole transcript microarrays. Genes were confirmed by qRT-PCR, proteins by western blot, ELISA or flow cytometry. Metformin promoted HUVEC migration and inhibited apoptosis via upregulation of vascular endothelial growth factor (VEGF) receptors (VEGFR1/R2), fatty acid binding protein 4 (FABP4), ERK/mitogen-activated protein kinase signaling, chemokine ligand 8, lymphocyte antigen 96, Rho kinase 1 (ROCK1), matrix metalloproteinase 16 (MMP16) and tissue factor inhibitor-2 under hyperglycemia-chemical hypoxia. Therefore, metformin’s dual effect in hyperglycemia-chemical hypoxia is mediated by direct effect on VEGFR1/R2 leading to activation of cell migration through MMP16 and ROCK1 upregulation, and inhibition of apoptosis by increase in phospho-ERK1/2 and FABP4, components of VEGF signaling cascades.

Background Breast cancer brain metastases (BCBM) develop in about 20–30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques. Methods We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p  < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM. Results The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3 , BNIP3 , BNIP3P1 , BRIP1 , CASP14 , CDC25A , DMBT1 , IDH2 , E2F1 , MYCN , RAD51 , RAD54L , and VDR . A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1 , SNORA2A , SNORA9 , SNORA10 , SNORA22 , SNORA24 , SNORA30 , SNORA37 , SNORA38 , SNORA52 , SNORA71A , SNORA71B , SNORA71C , SNORD13P2 , SNORD15A , SNORD34 , SNORD35A , SNORD41 , SNORD53 , and SCARNA22 . The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53 , BRCA1 , BRCA2 , ERBB2 , IDH1 , and IDH2 . WES detected numerous mutations, some of which affecting BC associated genes as CDH1 , HEPACAM , and LOXHD1 . Conclusions Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

Alpha therapy (TAT) relies on combining alpha-emitting radionuclides with specific cell-targeting vectors to deliver a high payload of cytotoxic radiation capable of destroying tumor tissues. TAT efficacy comes from the tissue selectivity of the targeting vector, the high linear energy transfer (LET) of the radionuclide, and the short range of alpha particles in tissues. Recent research studies have been directed to evaluate TAT on a preclinical and clinical scale, including evaluating damage to tumor tissues with minimal toxic radiation effects on surrounding healthy tissues. This review highlights the use of Actinium-225/Bismuth-213 radionuclides as promising candidates for TAT. Herein, we begin with a discussion on the production and supply of [225Ac]Ac/[213Bi]Bi followed by the formulation of [225Ac]Ac/[213Bi]Bi-radiopharmaceuticals using different radiolabeling techniques. Finally, we have summarized the preclinical and clinical evaluation of these potential radiotheranostic agents.

The widespread adoption and expansion of distance learning necessitates the consideration of issues related to learning passion, which is the strong desire of learners towards a specific activity of high value and meaning that enables the use of relevant cognitive and behavioral strategies to acquire, store, apply, share, use, absorb, and create knowledge. The current study aimed to measure learners’ practices of learning emotion processes, knowledge management, and organization in distance learning environments using tangible indicators. The study utilized a descriptive correlational approach to identify the effects of the study variables, including learning emotion (harmonious passion—emotional obsession), on knowledge management through the mediating role of self-regulation in distance learning environments. The results show that learners’ practices of learning emotion processes, knowledge management, and organization in distance learning environments were higher than average, and there was a significant correlation between emotion, self-regulation, and knowledge management. Additionally, learning emotion (harmonious passion and emotional obsession) had a statistically significant effect on self-organization processes and knowledge management. Structural equation modeling analysis confirmed the validity of the proposed path model, indicating that self-regulation plays a crucial role in mediating the relationship between emotion and knowledge management in distance learning environments.

Purpose Long COVID-19 is a growing public health concern, but its long-term burden and predictors remain underexplored, particularly in underrepresented populations. Methods This four-year prospective cohort study was conducted in Saudi Arabia, enrolling adults with confirmed acute COVID-19 from multiple affiliated healthcare centers between March 2020 and March 2024. Of 1,521 screened patients, 816 were enrolled and followed for up to four years (median: 24 months). Per WHO criteria, participants were classified as having long COVID-19 ( n  = 238) or resolved infection ( n  = 578). Demographics, comorbidities, vaccination, reinfection, and acute illness severity were recorded. Health-related quality of life (HRQoL) was assessed using SF-36 and EQ-5D-5 L. Logistic regression identified predictors of long COVID-19, and Cox proportional hazards models evaluated time to recovery. Results Fatigue (57.1%), post-exertional malaise (45.8%), cough (41.2%), and cognitive dysfunction (30.7%) were the most common persistent symptoms. Female sex (adjusted OR 11.11; 95% CI: 4.48–26.24) and diabetes mellitus (adjusted OR 14.3; 95% CI: 7.0–29.4) independently predicted long COVID-19. Delayed recovery was associated with female sex (aHR 3.36; 95% CI: 1.85–6.10), diabetes (aHR 1.57; 95% CI: 1.00–2.46), reinfection (aHR 1.86; 95% CI: 1.05–3.29), and hospitalization (aHR 1.08; 95% CI: 1.01–1.16). HRQoL scores remained significantly lower at 6 and 12 months. In the long COVID-19 group, 38.7% of patients normally resumed work within 12 months, compared to 82.3% in the resolved COVID-19 group. Conclusions Nearly 29% of post-acute COVID-19 patients developed long COVID-19 in this Middle Eastern cohort. Female sex, diabetes, reinfection, and hospitalization predicted delayed recovery. Persistent symptoms and impaired HRQoL highlight the need for early risk stratification and structured post-COVID care.

The S100A8 and epidermal growth factor receptor (EGFR) proteins are proto-oncogenes that are strongly expressed in a number of cancer types. EGFR promotes cellular proliferation, differentiation, migration and survival by activating molecular pathways. Involvement of proinflammatory S100A8 in tumor cell differentiation and progression is largely unclear and not studied in kidney cancer (KC). S100A8 and EGFR are potential therapeutic biomarkers and anticancer drug targets for KC. In this study, we explored molecular mechanisms of interaction profiles of both molecules with potential anticancer drugs. We undertook transcriptional profiling in Saudi KCs using Affymetrix HuGene 1.0 ST arrays. We identified 1478 significantly expressed genes, including S100A8 and EGFR overexpression, using cut-off p value <0.05 and fold change ≥2. Additionally, we compared and confirmed our findings with expression data available at NCBI's GEO database. A significant number of genes associated with cancer showed involvement in cell cycle progression, DNA repair, tumor morphology, tissue development, and cell survival. Atherosclerosis signaling, leukocyte extravasation signaling, notch signaling, and IL-12 signaling were the most significantly disrupted signaling pathways. The present study provides an initial transcriptional profiling of Saudi KC patients. Our analysis suggests distinct transcriptomic signatures and pathways underlying molecular mechanisms of KC progression. Molecular docking analysis revealed that the kinase inhibitor \"midostaurin\" has amongst the selected drug targets, the best ligand properties to S100A8 and EGFR, with the implication that its binding inhibits downstream signaling in KC. This is the first structure-based docking study for the selected protein targets and anticancer drug, and the results indicate S100A8 and EGFR as attractive anticancer targets and midostaurin with effective drug properties for therapeutic intervention in KC.