Awad Alzebair

Graphene oxide (GO) membranes present a compelling alternative to the permeability-selectivity trade-off inherent in conventional polymer membranes. However, the incomplete mechanistic understanding and the absence of scalable, defect-controlled fabrication processes continue to hinder their practical deployment. This review synthesizes and integrates transport mechanisms, computational modeling, fabrication, and translational constraints across graphene-based membrane architectures into a comprehensive design-oriented framework. Five key aspects of this synthesis are highlighted. Firstly, the available evidence supports a three-regime transport model, which unifies viscous near-frictionless flow, activated molecular hopping, and solution–diffusion. This reframes selectivity as a tunable function of the C/O ratio and interlayer chemistry. Secondly, a quantitative parity analysis of literature data reveals that classical molecular dynamics tends to overestimate GO laminate water permeance by a representative factor of approximately 3–8× across the matched comparisons examined. This discrepancy can be corrected using a tortuosity–porosity factor derived from wet-state XRD. Machine-learning force fields (GAP, MACE), while still in an early stage of development with limited reported applications, narrow the residual discrepancy to within 1.5–2× in the studies reviewed. Thirdly, a tiered computational roadmap identifies nuclear quantum effects as critical for proton-transport applications but unresolved for water permeance in GO laminate geometry. Fourthly, performance across water nanofiltration, gas separation, ion recovery, and osmotic energy harvesting is benchmarked against commercial references, with explicit caveats regarding the heterogeneity of testing conditions across cited studies, alongside a technology readiness assessment. Lastly, a standardized 500-h hydraulic stability protocol is proposed to facilitate cross-laboratory comparison. Collectively, this synthesis provides a structured, albeit not exhaustively validated, basis for the discussion of next-generation membrane design.

The lichens Tephromela atra and Tephromela grumosa were studied in detail using various techniques, including morphological identification, biochemical taxonomy (chemotaxonomy), anatomical, and molecular characterization. The molecular characterization of Tephromela atra and Tephromela grumosa (Pers.) Hafelner & Cl. Roux was analyzed using internal transcribed spacer rDNA (ITS1) genes and the sequences obtained were compared with the ITS sequences of the other Tephromela species in GenBank (NCBI). The sequences were analyzed against reference sequences from the GenBank databases using the programs; BLAST, ClustalW, and MEGA11. The phylogenetic relationship was evaluated. The results show that some samples of Tephromela atra obtained in this study are closer to the same species isolated from Greece, while other samples are closer to other samples isolated from Italy and Austria. Moreover, the Tephromela grumosa isolated from Eskisehir Bozdag Mountain form a separate branch closer to the Tephromela grumosa samples isolated from Italy. Our study shows that lichens are an important source of biodiversity in Türkiye, which has a high species richness in Anatolia.

Monoclonal antibody (mAb) therapy has revolutionized the treatment of various diseases, including cancer and autoimmune disorders. However, the emergence of SARS-CoV-2 variants, as well as other pathogenic variants, poses challenges in maintaining the therapeutic efficacy of mAbs. In this mini review article, we aim to explore the strategies to overcome variants resistance in mAb therapy against viral infections. Firstly, we discuss the mechanisms through which variants can evade the neutralizing effects of mAbs. Understanding these mechanisms is crucial in developing targeted approaches to combat resistance. Next, we delve into the strategies being pursued to address variants resistance. These include developing new mAbs or antibody cocktails that target multiple epitopes, engineering mAbs with improved binding affinities or enhanced neutralizing capabilities, and exploring alternative therapeutic modalities such as bispecific antibodies or antibody-drug conjugates. Furthermore, we highlight the role of computational modeling and artificial intelligence in predicting variant escape mutations and aiding in the design of more effective mAbs. Additionally, we examine the importance of continuous surveillance and monitoring of emerging variants to inform treatment strategies. This article emphasizes the urgent need for proactive approaches to tackle variants resistance in mAb therapy. By combining innovative design strategies, computational modeling, and vigilant surveillance, we can maintain the therapeutic effectiveness of mAbs and stay ahead in the battle against evolving pathogens and viral infections.

Lichens and their secondary metabolites are of particular interest as they can be used as an alternative to synthetic drugs in the treatment of various diseases. The present study was carried out to investigate in vitro antioxidant and antimicrobial activities of acetone, dichloromethane, petroleum ether, and methanol extracts of the lichen Tephromela atra and its major metabolites. α-alectoronic acid and α-collatolic acid were identified as bioactive substances in the lichen Tephromela atra . The antibacterial activity was investigated using the disk diffusion method and the minimum inhibitory concentrations were determined against eleven bacterial species, nine fungal species, and four yeast species using broth microdilution method. The antioxidant activity of the methanol extracts of Tephromela atra was measured by the free radical scavenging ability using the DPPH method. The extracts of α-alectoronic acid and α-collatolic acid showed significant inhibitory activity against most of the tested bacteria, especially the lowest MIC values of the two acids for Bacillus subtilis . Furthermore, the antioxidant activity was determined in vitro by measuring the radical scavenging capacity of the extracts on DPPH. The methanol extracts showed significant antioxidant activity and high DPPH scavenging activity at all concentrations. The results indicate that the extracts of Tephromela atra and the natural products obtained can be used as a source of antimicrobial and antioxidant agents in the pharmaceutical industry. HIGHLIGHTS: The present study determines the antibacterial and antifungal activities of the Tephromela atra , lichen extracts, and its isolated major constituents (α-alectoronic acid and α-collatolic acid), as well as evaluates the antioxidant capacity. Although there are some studies on α-alectoronic acid and α-collatolic acid, isolated in different lichens, there is no study on the biological activity and antioxidant capacity of lichen Tephromela atra . The MIC values of isolates were evaluated against a broad range of microorganisms including eleven species of bacteria, nine species of fungi, and four species of yeasts. α-Alectoronic and α-collatolic acid extracts showed significant inhibitory activity against most of the tested bacteria, especially the lowest MIC values of both acids for Bacillus subtilis. Our results provide a future perspective that Tephromela atra extracts and the isolated metabolites might be used as effective antimicrobial and antioxidant agents in pharmaceutical areas. Graphical

The integration of bioinformatics in drug discovery has revolutionized the field of pharmaceutical research. The use of computational tools and techniques has enabled researchers to analyze vast amounts of data, identify potential drug targets, and design new drugs with greater precision and efficiency. The integration of bioinformatics has also facilitated the development of personalized medicine, where drugs can be tailored to individual patients based on their genetic makeup. However, there are still challenges that need to be addressed, such as the need for more accurate predictive models and the ethical considerations surrounding the use of patient data. Overall, the integration of bioinformatics in drug discovery holds great promise for improving human health and advancing our understanding of disease mechanisms. In this mini-review, we discuss how Bioinformatics plays a crucial role in each step of drug discovery by providing tools and techniques to analyze large amounts of data generated from various sources, as well as the challenges and the opportunities offered by bioinformatics.