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Backgrounds: The development of several types of vaccines to avert COVID-19 has taken place. Despite several reports of undesirable reactions noted post-COVID-19 vaccine administration, later remains one of the best prevention and management tools in fighting the spread of the virus and its variants and reducing the harshness of this viral attack. The purpose of the current paper was to explore the side-effects experienced by the females in the Eastern Province of Saudi Arabia directly after receiving the booster dose of the Pfizer-BioNTech/BNT162b2 COVID-19 vaccine., Methods: A descriptive cross-sectional study among adults living in the East-ern Province, Saudi Arabia was applied. A survey link was, distributed through WhatsApp, SMS, or e-mail to community members. Respondent's demographic information was acquired, as well as information about any local and systemic side-effects reported following booster dose of BioNTech/BNT162b2 COVID-19 vaccine., Results: A total of 72.36% (432/597) of the respondents who participated in this study reported at least one side-effect. Pain and redness at the injection site (75.93%), myalgia (71.99%), headache (53.24%), fever (33.56%), and fatigue (43.78%) were the highest frequently stated side-effects. Furthermore, 9.25% of the respondents had to see a physician due to side effects, plus merely four participants were admitted to the hospital. The respondents working in the non-healthcare-related sector had a 1.677-fold more possibility of side effects in comparison with the other respondents (adjusted odds ratio = 1.677; 95% CI = 1.363, 2.064)., Conclusions: All reported side-effects were mild to moderate. These findings might persuade pessimists and refusers to get the COVID-19 vaccine. Myalgia and pain or redness at the site of injection were the most common reported side-effects in our study., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

DNA-protein interaction is a critical biological process that performs influential activities, including DNA transcription and recombination. DBPs (DNA-binding proteins) are closely associated with different kinds of human diseases (asthma, cancer, and AIDS), while some of the DBPs are used in the production of antibiotics, steroids, and anti-inflammatories. Several methods have been reported for the prediction of DBPs. However, a more intelligent method is still highly desirable for the accurate prediction of DBPs. This study presents an intelligent computational method, Target-DBPPred, to improve DBPs prediction. Important features from primary protein sequences are investigated via a novel feature descriptor, called EDF-PSSM-DWT (Evolutionary difference formula position-specific scoring matrix-discrete wavelet transform) and several other multi-evolutionary methods, including F-PSSM (Filtered position-specific scoring matrix), EDF-PSSM (Evolutionary difference formula position-specific scoring matrix), PSSM-DPC (Position-specific scoring matrix-dipeptide composition), and Lead-BiPSSM (Lead-bigram-position specific scoring matrix) to encapsulate diverse multivariate features. The best feature set from the features of each descriptor is selected using sequential forward selection (SFS). Further, four models are trained using Adaboost, XGB (eXtreme gradient boosting), ERT (extremely randomized trees), and LiXGB (Light eXtreme gradient boosting) classifiers. LiXGB, with the best feature set of EDF-PSSM-DWT, has attained 6.69% and 15.07% higher performance in terms of accuracies using training and testing datasets, respectively. The obtained results verify the improved performance of our proposed predictor over the existing predictors., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Sugarcane (Saccharum officinarum), a sugar crop commonly grown for sugar production all over the world, is susceptible to several insect pests attack in addition to bacterial, fungal and viral infections leading to substantial reductions in its yield. The complex genetic makeup and lack of resistant genes in genome of sugarcane have made the conventional breeding a difficult and challenging task for breeders. Using pesticides for control of the attacking insects can harm beneficial insects, human and other animals and the environment as well. As alternative and effective strategy for control of insect pests, genetic engineering has been applied for overexpression of cry proteins, vegetative insecticidal proteins (vip), lectins and proteinase inhibitors (PI). In addition, the latest biotechnological tools such as host-induced gene silencing (HIGS) and CRISPR/Cas9 can be employed for sustainable control of insect pests in sugarcane. In this review overexpression of the cry, vip, lectins and PI genes in transgenic sugarcane and their disease resistance potential is described.