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Lung cancer is the most common cause of cancer death in the world. Effective early detection and appropriate medications can help treat this deadly cancer. Therefore, early detection of lung cancer is of utmost importance, especially in screening high-risk populations (such as smokers) with an urgent need to identify new biomarkers. The present study aimed to demonstrate the potential of using the panel of DNA methylation as a biomarker for the early diagnosis of lung cancer from sputum samples. The methylated promoter of p16INK4a, RASSF1A, and MGMT genes was estimated by the methylation-specific polymerase chain reaction in a sample of 84 lung cancer patients (65 smokers and 19 non-smokers). Based on the results, p16INK4a promoter methylation was significantly associated with smoking habit and lung cancer progression in terms of histological grading and patient staging. The sensitivity and specificity of the p16INK4a gene as a biomarker for lung cancer were 71% and 90%, respectively. The methylated promoter of RASSF1A was less sensitive (48%) as a biomarker for lung cancer with 83%. The results demonstrated a strong association between promoter methylation of RASSF1A and late stages of lung cancer (P=0.0007). The sensitivity of the MGMT gene as a biomarker for lung cancer was 61% with high specificity (92%), compared to other candidate genes in this study. The epigenetic alteration in the promoter region of p16INK4a, RASSF1A, and MGMT genes is highly associated with cancer cell development. It is suggested that the use of these candidate biomarkers can be used as an adjunct to computed tomography screening to diagnose patients at high risk for lung cancer after validation.

Membrane disruption refers to increasing cell membrane permeability. This state may be transient, allowing the cell to regain its function, or it can be lasting, resulting in the cell's demise. Disrupting the membrane can momentarily affect the blood-brain barrier, making drugs easier to penetrate. This research aimed to investigate issues related to the blood-brain barrier that resulted from irreversible membrane disruption, using computer simulations. This study investigated how changing electric fields affected things like the blood-brain barrier's cross-sectional area, gyration radius, mean square displacement, heat flux, electric current density, and how the electric field was distributed in the blood-brain barrier. The simulations were conducted to adjust and modify the final structure. During the initial phase of equilibration, simulations were conducted for 10–8 s, leading to the stabilization of the kinetic energy and potential energy of the initial atomic sample at specific values. As the electric field amplitude increased, the radius of gyration in the blood barrier also increased, reflecting enhanced molecular motion. Specifically, it increased from 32.79 to 33.30 Å when the amplitude increased from 0.1 to 0.6 eV This increased motion was due to larger oscillation ranges and intensified interatomic collisions, leading to a higher mean squared displacement of 27.37 nm² at 0.6 eV Additionally, the heat flux within the blood barrier increased to 0.0072 W/m², indicating that stronger electric fields induced more erratic molecular behavior.

Abstract Background Myrtus communis L. (MC) has been used in Mesopotamian medicine. Here, the cholinesterase (ChE) inhibitory potential of its methyl alcohol extracts has been investigated and computationally dissected. Method The ChE inhibition has been measured based on usual Ellman’s colorimetric method compared to a canonical ChE inhibitor, eserine. Through a deep text mining, the structures of phytocompounds (= ligands) of MC were curated from ChemSpider, PubChem, and ZINC databases and docked into protein targets, AChE (PDB 1EVE) and BChE (PDB 1P0I) after initial in silico preparedness and binding affinity (BA; kcal/mol) reported as an endpoint. The calculation of ADMET (absorption, distribution, metabolism, excretion, and toxicity) features of phytocompounds were retrieved from SwissADME ( http://www.swissadme.ch/ ) and admetSAR software to predict the drug-likeness or lead-likeness fitness. The Toxtree v2.5.1, software platforms ( http://toxtree.sourceforge.net/ ) have been used to predict the class of toxicity of phytocompounds. The STITCH platform ( http://stitch.embl.de ) has been employed to predict ChE-chemicals interactions. Results The possible inhibitory activities of AChE of extracts of leaves and berries were 37.33 and 70.00%, respectively as compared to that of eserine while inhibitory BChE activities of extracts of leaves and berries of MC were 19.00 and 50.67%, respectively as compared to that of eserine. Phytochemicals of MC had BA towards AChE ranging from -7.1 (carvacrol) to -9.9 (ellagic acid) kcal/mol. In this regard, alpha-bulnesene, (Z)-gamma-Bisabolene, and beta-bourbonene were top-listed low toxic binders of AChE, and (Z)-gamma-bisabolene was a more specific AChE binder. Alpha-cadinol, estragole, humulene epoxide II, (a)esculin, ellagic acid, patuletin, juniper camphor, linalyl anthranilate, and spathulenol were high class (Class III) toxic substances which among others, patuletin and alpha-cadinol were more specific AChE binders. Among intermediate class (Class II) toxic substances, beta-chamigrene was a more specific AChE binder while semimyrtucommulone and myrtucommulone A were more specific BChE binders. Conclusion In sum, the AChE binders derived from MC were categorized mostly as antiinsectants (e.g., patuletin and alpha-cardinal) due to their predicted toxic classes. It seems that structural amendment and stereoselective synthesis like adding sulphonate or sulphamate groups to these phytocompounds may make them more suitable candidates for considering in preclinical investigations of Alzheimer’s disease.

Lung cancer is the most common cause of cancer death in the world. Effective early detection and appropriate medications can help treat this deadly cancer. Therefore, early detection of lung cancer is of utmost importance, especially in screening high-risk populations (such as smokers) with an urgent need to identify new biomarkers. The present study aimed to demonstrate the potential of using the panel of DNA methylation as a biomarker for the early diagnosis of lung cancer from sputum samples. The methylated promoter of p16INK4a, RASSF1A, and MGMT genes was estimated by the methylation-specific polymerase chain reaction in a sample of 84 lung cancer patients (65 smokers and 19 non-smokers). Based on the results, p16INK4a promoter methylation was significantly associated with smoking habit and lung cancer progression in terms of histological grading and patient staging. The sensitivity and specificity of the p16INK4a gene as a biomarker for lung cancer were 71% and 90%, respectively. The methylated promoter of RASSF1A was less sensitive (48%) as a biomarker for lung cancer with 83%. The results demonstrated a strong association between promoter methylation of RASSF1A and late stages of lung cancer (P=0.0007). The sensitivity of the MGMT gene as a biomarker for lung cancer was 61% with high specificity (92%), compared to other candidate genes in this study. The epigenetic alteration in the promoter region of p16INK4a, RASSF1A, and MGMT genes is highly associated with cancer cell development. It is suggested that the use of these candidate biomarkers can be used as an adjunct to computed tomography screening to diagnose patients at high risk for lung cancer after validation. [ABSTRACT FROM AUTHOR]

Lung cancer is the most common cause of cancer death in the world. Effective early detection and appropriate medications can help treat this deadly cancer. Therefore, early detection of lung cancer is of utmost importance, especially in screening high-risk populations (such as smokers) with an urgent need to identify new biomarkers. The present study aimed to demonstrate the potential of using the panel of DNA methylation as a biomarker for the early diagnosis of lung cancer from sputum samples. The methylated promoter of p16 INK4a , RASSF1A , and MGMT genes was estimated by the methylation-specific polymerase chain reaction in a sample of 84 lung cancer patients (65 smokers and 19 non-smokers). Based on the results, p16 INK4a promoter methylation was significantly associated with smoking habit and lung cancer progression in terms of histological grading and patient staging. The sensitivity and specificity of the p16 INK4a gene as a biomarker for lung cancer were 71% and 90%, respectively. The methylated promoter of RASSF1A was less sensitive (48%) as a biomarker for lung cancer with 83%. The results demonstrated a strong association between promoter methylation of RASSF1A and late stages of lung cancer ( P =0.0007). The sensitivity of the MGMT gene as a biomarker for lung cancer was 61% with high specificity (92%), compared to other candidate genes in this study. The epigenetic alteration in the promoter region of p16 INK4a , RASSF1A , and MGMT genes is highly associated with cancer cell development. It is suggested that the use of these candidate biomarkers can be used as an adjunct to computed tomography screening to diagnose patients at high risk for lung cancer after validation.