Sajjad Ahmad

Bio: Sajjad Ahmad is an academic researcher from Abasyn University. The author has contributed to research in topics: Medicine & Epitope. The author has an hindex of 18, co-authored 164 publications receiving 1239 citations. Previous affiliations of Sajjad Ahmad include Quaid-i-Azam University.

Stilbene-based natural compounds as promising drug candidates against COVID-19.

Abstract: The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a great threat to public health. Currently, no potent medicine is availab...

Review of degradation and failure phenomena in photovoltaic modules

Abstract: The degradation of photovoltaic (PV) systems is one of the key factors to address in order to reduce the cost of the electricity produced by increasing the operational lifetime of PV systems. To reduce the degradation, it is imperative to know the degradation and failure phenomena. This review article has been prepared to present an overview of the state-of-the-art knowledge on the reliability of PV modules. Whilst the most common technology today is mono- and multi-crystalline silicon, this article aims to give a generic summary which is relevant for a wider range of photovoltaic technologies including cadmium telluride, copper indium gallium selenide and emerging low-cost high-efficiency technologies. The review consists of three parts: firstly, a brief contextual summary about reliability metrics and how reliability is measured. Secondly, a summary of the main stress factors and how they influence module degradation. Finally, a detailed review of degradation and failure modes, which has been partitioned by the individual component within a PV module. This section connects the degradation phenomena and failure modes to the module component, and its effects on the PV system. Building on this knowledge, strategies to improve the operational lifetime of PV systems and thus, to reduce the electricity cost can be devised. Through extensive testing and failure analysis, researchers now have a much better overview of stressors and their impact on long term stability. • Review of reliability metrics and test methodologies for photovoltaic modules • Indicative mapping of relationships between stressors, components, failures and effects in PV modules. • Assessment on the impact of degradation and failure on LCOE and EPBT. • Review of design considerations for all components in a PV module regarding reliability.

Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: a computational quest to identify potential natural antiviral for COVID-19 treatment.

Abstract: Nigella sativa or black seed is used as a medicinal plant around the globe. Oil and seeds have a long tradition of folklore use in various medicinal and food systems. The conventional therapeutic u...

Nanobio Silver: Its Interactions with Peptides and Bacteria, and Its Uses in Medicine

Abstract: Silver, known in metallic form since antiquity, has very early been recognized by mankind for its antimicrobial properties, a phenomenon observed, for example, in the context of drinking water (a silver coin in a well), food (silver cutlery, water storage recipients), and medicine (silver skull plates, teeth). Silver compounds were also shown to be useful. For example, dilute solutions of silver nitrate served long, and still do in some countries, as antimicrobial ointment to be instilled into Published in \" \" which should be cited to refer to this work.

Comparative Study on the Antibacterial Activity of Phytochemical Flavanones against Methicillin-resistant Staphylococcus aureus.

Abstract: Differently substituted flavanones were isolated from Leguminosae and their antibacterial activity was comparatively studied against methicillin-resistant Staphylococcus aureus (MRSA). The minimum inhibitory concentrations (MICs) of phytochemical flavanones to clinical isolates of MRSA were determined by a serial agar dilution method. The structure-activity relationship has indicated that 2',4'- or 2',6'-dihydroxylation of the B ring and 5,7-dihydroxylation of the A ring in the flavanone structure are important for significant anti-MRSA activity and that substitution with a certain aliphatic group at the 6- or 8-position also enhances the activity. Among the thirteen flavanones tested, tetrahydroxyflavanones with these structural characteristics isolated from Sophora exigua and Echinosophora koreensis showed intensive activity to inhibit the growth of all MRSA strains at 3.13-6.25 micrograms/ml. The present hydroxyflavanones would be useful in the phytotherapeutic strategy against MRSA infections.

Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies.

Abstract: Partial Least Squares-Discriminant Analysis (PLS-DA) is a PLS regression method with a special binary ‘dummy’ y-variable and it is commonly used for classification purposes and biomarker selection in metabolomics studies. Several statistical approaches are currently in use to validate outcomes of PLS-DA analyses e.g. double cross validation procedures or permutation testing. However, there is a great inconsistency in the optimization and the assessment of performance of PLS-DA models due to many different diagnostic statistics currently employed in metabolomics data analyses. In this paper, properties of four diagnostic statistics of PLS-DA, namely the number of misclassifications (NMC), the Area Under the Receiver Operating Characteristic (AUROC), Q 2 and Discriminant Q 2 (DQ 2) are discussed. All four diagnostic statistics are used in the optimization and the performance assessment of PLS-DA models of three different-size metabolomics data sets obtained with two different types of analytical platforms and with different levels of known differences between two groups: control and case groups. Statistical significance of obtained PLS-DA models was evaluated with permutation testing. PLS-DA models obtained with NMC and AUROC are more powerful in detecting very small differences between groups than models obtained with Q 2 and Discriminant Q 2 (DQ 2). Reproducibility of obtained PLS-DA models outcomes, models complexity and permutation test distributions are also investigated to explain this phenomenon. DQ 2 and Q 2 (in contrary to NMC and AUROC) prefer PLS-DA models with lower complexity and require higher number of permutation tests and submodels to accurately estimate statistical significance of the model performance. NMC and AUROC seem more efficient and more reliable diagnostic statistics and should be recommended in two group discrimination metabolomic studies.