Effect of eco-physiological factors on biometric traits of green mussel Perna viridis cultured in the south-east coast of the Bay of Bengal, Bangladesh

Cyto and Genoprotective Potential of Tannic Acid Against Cadmium and Nickel Co-exposure Induced Hepato-Renal Toxicity in BALB/c Mice

Tannic acid (TA) is a metal chelating polyphenol that plays a crucial role in metal detoxification, but its modulatory role in co-exposure of these heavy metals' exposure needs to be explored. Cadmium (Cd) and nickel (Ni) are inorganic hazardous chemicals in the environment. Humans are prone to be exposed to the co-exposure of Cd and Ni, but the toxicological interactions of these metals are poorly defined. Present study was undertaken to study the preventive role of TA in Cd-Ni co-exposure-evoked hepato-renal toxicity in BALB/c mice. In the current investigation, increased oxidative stress in metal intoxicated groups was confirmed by elevated peroxidation of the lipids and significant lowering of endogenous antioxidant enzymes. Altered hepato-renal serum markers, DNA fragmentation, and histological alterations were also detected in the metal-treated groups. Present study revealed that Cd is a stronger toxicant than Ni and when co-exposure was administered, additive, sub-additive, and detrimental effects were observed. Prophylactic treatment with TA significantly reinstated the levels of lipid peroxidation (LPO), non-enzymatic, and enzymatic antioxidants. Moreover, it also restored the serum biomarker levels, DNA damage, and histoarchitecture of the given tissues. TA due to its metal chelating and anti-oxidative properties exhibited cyto- and genoprotective potential against Cd-Ni co-exposure-induced hepatic and renal injury.

Analytical study on users' awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

The study analyses user awareness of multimodal biometrics and its acceptability for online transactions in the current dynamic world. The study was performed on the five underlying perspectives: User Acceptability, Cognizant Factors towards Biometrics, Technological factors, Perceptional Factors (Fingerprints, Iris, Face Recognition and Voice) and Data Privacy Factors. A questionnaire was prepared and circulated to the 530 biometrics users; on that basis, the corresponding answer was obtained for analysis. SEM is first employed to gauge the research model and test the prominent hypothesized predictors, which are then used as inputs in the neural network to evaluate the relative significance of each predictor variable. By considering the standardized significance of the feed-for-back-propagation of ANN algorithms, the study found a significant effect of DPF_3 (93%), DPF_2 (50%) and DPF_4 (34%) on the adoption of MMB. In the Perceptional construct, PRF_2 (49%) and PRF_3 (33%) was relatively the most important predictor, whereas, in User Acceptability, UAC_2 (37%), UAC_3 & UAC_5 (41%) was vital to be considered. Only one item, TCF_2 (35%), from Technological Factors, followed by Cognizant factors, i.e., CFG_1 (33%), confirmed the best fit model to adopt MMB. The research is a novel effort when compared to past studies as it considered cognizant and perceptual factors in the proposed model, thereby expanding the analytical outlook of MMB literature. Thus, the study also explored several new and valuable practical implications for adopting multimodal instruments of biometrics along with certain limitations.