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The absence of CAC in asymptomatic individuals is associated with a very low incidence of cardiovascular events. Of symptomatic patients, 1-2% with zero CAC score have non-calcified coronary artery atherosclerosis, and at least one third of cardiovascular events occur in individuals with zero CAC. South Asians (SA) have proportionally higher case fatality rates for CVD, relatively younger age of presentation, and accelerated rate of atherosclerosis when compared with other ethnic groups. All consecutive patients who underwent a CTCA to evaluate angina or angina-equivalent symptoms during the study duration were enrolled retrospectively. Patients with prior myocardial infarction, history of revascularization, and congenital heart disease were excluded. MACE was defined as the total of cardiac death, non-fatal myocardial infarction, and/or non-elective revascularization. A total of 534 patients were enrolled after final exclusion. The mean age was 53 years ± 11. Males constituted 68.4% of the study population. Dyslipidemia was the most common co-morbid condition identified (50%), followed by diabetes (18.4%) and hypertension (3.6%). At least 28.8% of patients with zero CAC scores had the presence of coronary artery disease (soft plaque) of any degree. Obstructive CAD (>50%) was present in 5.8% of patients. Follow-up was available for 61.4% of patients. On a mean follow-up of 96.6 months ± 49.8 (range 21-194 months), all-cause MACE was observed in 8.8% of patients. The most common MACE was angina (3.96%) and all-cause mortality (3%). The baseline characteristics and MACE did not differ in patients with and without obstructive CAD. The baseline characteristics did not differ significantly between patients with and without MACE. The incidence of soft plaque in this SA cohort is higher than that reported in international studies. However, in symptomatic SA, a CAC score of zero carries a good long-term prognosis, irrespective of the degree of CAD.

The study's objectives are to identify the characteristics of customers and FinTech apps that resist using FinTech services in the era of technology. Consumer characteristics studied in this study were consumer-perceived digital self-efficacy and consumer-perceived digital knowledge. FinTech characteristics were perceived digital security concerns and perceived digital complexity.  Moreover, the research aimed to determine if consumers' techno-stress moderates the relationship between consumer characteristics and their resistance to FinTech. The model was supported by innovation resistance theory. Convenience sampling was used to gather data from 384 bank account holders from Rawalpindi and Islamabad. Adapted questionnaires with five-point Likert scales for each variable were used. Results indicated that all consumer characteristics have a negative and significant relationship with FinTech resistance. However, among FinTech characteristics, only perceived digital complexity positively influenced FinTech resistance, and the impact of perceived digital complexity was not found on FinTech resistance. The moderating role of techno-stress among all consumer characteristics and FinTech resistance was supported. The Moderating role of techno-stress was supported between FinTech characteristics i.e. perceived digital security and FinTech resistance but not supported between perceived digital concern and FinTech resistance. The findings suggest that educational initiatives, such as workshops, seminars, and online resources, can empower users with knowledge about FinTech solutions, thereby reducing perceived risk and resistance. Regular app reviews will help the organization adapt to evolving challenges and best practices in FinTech adoption.

Numerous systems are being employed in daily life where two entities authenticate each other over a range of distance. The distance involved is relatively small, but still attacks were documented. The distance bounding (DB) protocol was introduced to cater to security requirements. The schemes, however, are still prone to several threats; mainly the Relay Attack (Terrorist and Mafia Fraud). In Mafia Fraud, an attempts are made to get accepted as the prover either by replaying of messages or by the help a malicious key. In Terrorist fraud, an attempt is made to extract the secret from the verifying entity, either by extracting the key from the message captured or by physically tempering the verifying/proving entity. Therefore the mitigation of these attacks needs to be done; as to not put computational overhead on the scheme. The paper presents a comprehensive and comparative performance analysis of twelve DB protocols based on defined metrics. It also proposes a protocol which incorporates the design elements needed for added security, is computationally easy to implement and resistant to most of the threats mentioned. Analysis of the protocol is carried out against the security requirements.

Under elevated CO2, stomatai openings get reduced and hence can reduce the exposure of sensitive tissues to ozone (Morgan et al., 2003; Feng et al., 2008). [...]rising levels of CO2 are likely to have significant effects on plant growth, physiology, and chemistry (Ziska, 2008). Since plants convert carbon dioxide to oxygen by the process of photosynthesis while performing carbon sequestration, also called phytosequestration (Watson et al., 2000), current work is focused to explore CO2 uptake by different plant species and how environmental pollution affects that uptake. Teaching faculty also reported neuro-physiologic symptoms at CO2 levels exceeding 1000 ppm (Gaihre, Semple, Miller, Fielding, & Turner, 2014), (Muscatiello et al., 2015). [...]elevated levels of atmospheric CO2 may have detrimental effects on plant roots to soil interactions (De Deyn et al., 2008). The principal procedure in green biotechnology for soil working is to sequester and transform atmospheric CO2 in plant photosynthesis followed by its translocation below ground into plant roots (Hodge et al., 2009). Since plants play an important role in an environment as carbon sinks by sequestrating carbon, leaves from four different plant species were taken for carbon sequestration.

ABSTRACT Ovarian follicles develop through several distinct phases during fetal and postnatal periods and they release their matured ova upon puberty. A finite number of primordial follicles form in the fetal ovary from primordial germ cells (PG) during the first stage of fetal development. The primordial follicles consist of oocytes surrounded by a single layer of pregranulosa follicular cells and they remain dormant in the meiotic prophase I stage. Primordial pregranulosa follicular cells initiate activation of primordial follicle and govern the development of dormant oocytes. The primordial follicles take about 6 months to grow and develop to ovulatory graafian follicles in cattle and humans. Growth of preantral follicles is gonadotropin-independent whereas growth of antral follicles is gonadotropin-dependent. Changes occur during these stages in mammalian ovarian follicles to prepare the oocyte for successful maturation, fertilization and further embryonic development. The changes enable the zygotes to overcome maternal zygotic transition stage and follow their developmental competence to fetus. The changes were affected by in vivo and in vitro molecules and factors of the organisms and the surrounding conditions, respectively. Because of the importance of follicular changes during growth and development stages, which reflected in the developmental competence of oocytes, an attempt was made in this review to collect and combine the current knowledge on growth, development and maturation of ovarian follicles and resulting oocytes and their applications in assisted reproductive techniques.

In recent years, the consumption of social media content to keep up with global news and to verify its authenticity has become a considerable challenge. Social media enables us to easily access news anywhere, anytime, but it also gives rise to the spread of fake news, thereby delivering false information. This also has a negative impact on society. Therefore, it is necessary to determine whether or not news spreading over social media is real. This will allow for confusion among social media users to be avoided, and it is important in ensuring positive social development. This paper proposes a novel solution by detecting the authenticity of news through natural language processing techniques. Specifically, this paper proposes a novel scheme comprising three steps, namely, stance detection, author credibility verification, and machine learning-based classification, to verify the authenticity of news. In the last stage of the proposed pipeline, several machine learning techniques are applied, such as decision trees, random forest, logistic regression, and support vector machine (SVM) algorithms. For this study, the fake news dataset was taken from Kaggle. The experimental results show an accuracy of 93.15%, precision of 92.65%, recall of 95.71%, and F1-score of 94.15% for the support vector machine algorithm. The SVM is better than the second best classifier, i.e., logistic regression, by 6.82%.

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5′, 3′ UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Background Autologous hematopoietic stem-cell transplantation (HSCT) is the standard of care in many relapsed and refractory lymphoid malignancy, neuroblastoma, and multiple myeloma (MM). This study was conducted to describe the epidemiology of early infections that occurred within the first 100 days among patients who received HSCT for MM, Hodgkin (HL), and non-Hodgkin lymphoma (NHL) in Palestine. Methods This study was conducted in a retrospective cohort design in the only autologous HSCT in Palestine in the period between 2014 and 2021. The medical records of the patients were reviewed to identify and collect demographic, clinical, and microbiological data on bacterial, viral, fungal, and parasitic infections as diagnosed by cultures, polymerase chain reaction, and fluorescent antibody testing. Results A total of 145 patients were included in this study (median age = 44.0 [28.0, 53.5] years). Of those, 8 (5.5%) were younger than 18 years, 69 (47.6%) had MM, 53 (36.6%) had HL, and 23 (15.9%) had NHL. The source of fever had no focus in the majority of the cases 82 (56.6%), 12 (8.3%) had bloodstream infections, 8 (5.5%) had colitis, and 7.6 (5.0%) had pneumonia. Patients from whom gram-negative bacteria were isolated stayed in the hospital for longer duration compared to the other patients (median = 21.0 [19.0, 25.0] vs. 18.0 [15.0, 22.0] days, p-value = 0.043, respectively). The cumulative incidence of death in the first 100 days after infusion of stem cells was 3.4%. The cumulative incidence of death in the first 100 days post-transplantation was higher for patients with NHL compared to those with HL and MM (p-value = 0.017). Gram-negative and fungal infections were strong predictors of mortality. Conclusion Bacterial gram-positive and gram-negative infections were the most common early infections among patients who underwent autologous HSCT for hematological malignancies (HM) in the only center in Palestine. The findings of this study are informative to healthcare providers and planners of care for patients who are scheduled to receive autologous HSCT for HM.

Food plants play a crucial role in human survival, providing them essential nutrients. However, traditional breeding methods have not been able to keep up with the demands of the growing population. The improvement of food plants aims to increase yield, quality, and resistance to biotic and abiotic stresses. With CRISPR/Cas9, researchers can identify and edit key genes conferring desirable qualities in agricultural plants, including increased yield, enhanced product quality attributes, and increased tolerance to biotic and abiotic challenges. These modifications have enabled the creation of “smart crops” that exhibit rapid climatic adaptation, resistance to extreme weather conditions and high yield and quality. The use of CRISPR/Cas9 combined with viral vectors or growth regulators has made it possible to produce more efficient modified plants with certain conventional breeding methods. However, ethical and regulatory aspects of this technology must be carefully considered. Proper regulation and application of genome editing technology can bring immense benefits to agriculture and food security. This article provides an overview of genetically modified genes and conventional as well as emerging tools, including CRISPR/Cas9, that have been utilized to enhance the quality of plants/fruits and their products. The review also discusses the challenges and prospects associated with these techniques.

This study investigated the effects of activity-based and traditional analysis methods on students’ attitudes toward poetry, academic achievement, and cultural identity. A pre-test-post-test control group experimental design—a quantitative research method—was employed. The class using activity-based analysis methods for poetry analysis was designated as the experimental group, while the class following the traditional analysis method served as the control group. Participants were second-year students from the Kazakh Literature Department at a university in Almaty, Kazakhstan. The study spanned eight weeks and involved 18 female and 15 male students in the experimental group, with 17 female and 15 male students in the control group. All students provided informed consent to participate voluntarily. The Scale of Attitude toward Poetry, Poetry Analysis Skills Academic Achievement Test, and Cultural Identity Perception Scale were administered to measure the study variables. The findings revealed that activity-based analysis methods positively impacted students’ attitudes toward poetry, with the experimental group demonstrating a more favorable approach than the control group. Additionally, students in the experimental group achieved higher academic performance in poetry analysis skills than those in the control group. Although both groups showed a general improvement in their cultural identity perception, no significant difference was found between them. These results support the potential of activity-based approaches in poetry education to increase student achievement and attitudes. Consequently, integrating such methods should be actively encouraged in future educational practices.