Potential signaling pathways, biomarkers, natural drugs, and chronic myeloid leukemia therapeutics

The Philadelphia chromosome signals BCR-ABL1 migration in myeloid clonal proliferation disorders such as chronic myeloid leukemia (CML). The crucial function of the Musashi2-Numb axis in deciding cell fate and its connection to significant signaling pathways like Hedgehog and Notch, which are necessary for the self-renewal pathways of CML stem cells, will be the subject of future research in this work. For this review, we conducted a PubMed search using the terms Musashi2-Numb, signaling pathways, and leukemia. As a result, we assembled several studies. Tyrosine kinase inhibitors like imatinib can kill and eradicate BCR-ABL1 translocated cells, but they cannot directly target BCR-ABL1 leukemia stem cells. The primary issue is stem cells’ resistance to imatinib therapy. Since leukemia stem cells are thought to be treated by the Musashi2-Numb signaling pathway, a successful therapy approach may involve comprehending and controlling the downstream molecules and signaling pathway of BCR-ABL1 that are important in the survival and self-renewal of leukaemia stem cells. Here, we focused on the generalised perspectives of the drugs that target major signaling proteins and change elements or pathways downstream of BCR-ABL1 can effectively treat chronic leukemia stem cells. There are handful number of proteins such as Musashi2 which have substantial diagnostic use in leukemia treatment and strategy. After going through a number recent develeopments in CML and its therapeutics, I presented here an overview of the latest advancements in CML, natural drugs, biomarkers, potential signaling pathways, and treatment strategies

Enhancing dental practice: cutting-edge digital innovations

Digital technology offers many opportunities and challenges across various domains. Aim: This comprehensive review explores the transformative impact of digitalization on dental practices, encompassing digital Imaging, 3D printing, intraoral scanners, teledentistry, Artificial Intelligence, CAD-CAM technology, and virtual reality. Methods: A rigorous search was conducted across various electronic bases, including PubMed, Google Scholar, Scopus, and the National Center for Biotechnology Information (NCBI). The search employed keywords such as “Orthodontics,” “Dental Health,” “Dental Imaging,” “CAD-CAM,” “Digital Medicine,” “Teleconsultation,” “Intraoral Scanner,” “Artificial Intelligence (AI),” “Digital Health,” “Teledentistry,” and “3D Dentistry.” Papers published between 2017 and the present were considered, focusing on peer-reviewed journals and reviews providing comprehensive insights into digital dentistry. Results: The review highlights the diverse facts of digitalization in dentistry, emphasizing its potential benefits for patient practitioners and the dental industry. Digital impressions, 3D printing, and CAD-CAM are streamlining restorative dentistry. In orthodontics, digital models enable precise simulations. Artificial Intelligence promises more efficient diagnostics and treatment planning. Conclusion: Digital technology is poised to reshape dentistry, improving efficiency, patient outcomes, and practitioner experiences. However, challenges such as data security and ethical considerations must be addressed. The successful integration of digital dentistry into dental practice will require more research and innovation, even though this review offers a thorough overview of the field

Enhancing Trust –A Unified Meta-Model for Software Security Vulnerability Analysis

Over the last decade, a globalization of the software industry has taken place which has facilitated the sharing and reuse of code across existing project boundaries. At the same time, such global reuse also introduces new challenges to the Software Engineering community, with not only code implementation being shared across systems but also any vulnerabilities it is exposed to as well. Hence, vulnerabilities found in APIs no longer affect only individual projects but instead might spread across projects and even global software ecosystem borders. Tracing such vulnerabilities on a global scale becomes an inherently difficult task, with many of the resources required for the analysis not only growing at unprecedented rates but also being spread across heterogeneous resources. Software developers are struggling to identify and locate the required data to take full advantage of these resources. The Semantic Web and its supporting technology stack have been widely promoted to model, integrate, and support interoperability among heterogeneous data sources. This dissertation introduces four major contributions to address these challenges: (1) It provides a literature review of the use of software vulnerabilities databases (SVDBs) in the Software Engineering community. (2) Based on findings from this literature review, we present SEVONT, a Semantic Web based modeling approach to support a formal and semi-automated approach for unifying vulnerability information resources. SEVONT introduces a multi-layer knowledge model which not only provides a unified knowledge representation, but also captures software vulnerability information at different abstract levels to allow for seamless integration, analysis, and reuse of the modeled knowledge. The modeling approach takes advantage of Formal Concept Analysis (FCA) to guide knowledge engineers in identifying reusable knowledge concepts and modeling them. (3) A Security Vulnerability Analysis Framework (SV-AF) is introduced, which is an instantiation of the SEVONT knowledge model to support evidence-based vulnerability detection. The framework integrates vulnerability ontologies (and data) with existing Software Engineering ontologies allowing for the use of Semantic Web reasoning services to trace and assess the impact of security vulnerabilities across project boundaries. Several case studies are presented to illustrate the applicability and flexibility of our modelling approach, demonstrating that the presented knowledge modeling approach cannot only unify heterogeneous vulnerability data sources but also enables new types of vulnerability analysis

Gamma-Glutamylcysteine Ethyl Ester Protects against Cyclophosphamide-Induced Liver Injury and Hematologic Alterations via Upregulation of PPAR<i>γ</i>and Attenuation of Oxidative Stress, Inflammation, and Apoptosis

Gamma-glutamylcysteine ethyl ester (GCEE) is a precursor of glutathione (GSH) with promising hepatoprotective effects. This investigation aimed to evaluate the hepatoprotective effects of GCEE against cyclophosphamide- (CP-) induced toxicity, pointing to the possible role of peroxisome proliferator activated receptor gamma (PPARγ). Wistar rats were given GCEE two weeks prior to CP. Five days after CP administration, animals were sacrificed and samples were collected. Pretreatment with GCEE significantly alleviated CP-induced liver injury by reducing serum aminotransferases, increasing albumin, and preventing histopathological and hematological alterations. GCEE suppressed lipid peroxidation and nitric oxide production and restored GSH and enzymatic antioxidants in the liver, which were associated with downregulation of COX-2, iNOS, and NF-κB. In addition, CP administration significantly increased serum proinflammatory cytokines and the expression of liver caspase-3 and BAX, an effect that was reversed by GCEE. CP-induced rats showed significant downregulation of PPARγwhich was markedly upregulated by GCEE treatment. These data demonstrated that pretreatment with GCEE protected against CP-induced hepatotoxicity, possibly by activating PPARγ, preventing GSH depletion, and attenuating oxidative stress, inflammation, and apoptosis. Our findings point to the role of PPARγand suggest that GCEE might be a promising agent for the prevention of CP-induced liver injury.</jats:p

Attitudes and knowledge about contraceptive use of saudi married women: a cross-sectional study approach

The speedy change in the Saudi Arabian community\u27s socio-demographic pattern will significantly influence reproductive attitudes and practices with increasing preferences toward family planning because of the use of contraceptives. The current study was conducted to determine the attitudes and knowledge of married women in the Aseer region of Saudi Arabia regarding contraceptives use. Saudi married women from the Aseer region were the participants of this cross-sectional study. The study\u27s objectives were covered via a standardized questionnaire, and the study comprised of 412 married women. A 100 % participant’s response was demonstrated, while 31.8 % of the respondents were 31-40 years old. Most of the participants have a great awareness and knowledge about contraceptives, while (n=324; 78.6%) had previously used contraceptives. Additionally, 297 (72.1%) have intention to use contraceptive methods in the future. Majority of the participants (n=297; 91.6%) considered the economic and family planning as a reason for using the contraceptives, while natural family planning was mostly preferred (n=202; 49%). Logistic regression analysis exhibited significant correlation between the age, education, employment, monthly income and children number. The findings show that Saudi married women have high perceptions and knowledge of contraception. However, more effort is required to raise awareness regarding family planning and contraceptives, whereas the policy makers must exclude the obstacles to women from using contraceptives

Analysis of Autonomous Wheelchair Navigation Technologies in the Past Five Years: A Systematic Review

This study aims to analyze the latest developments in wheelchair navigation assistance systems. This analysis is obtained by conducting a systematic review of the significance of technologies for performance metrics and control strategies used. The autonomous category, input methods, tools used, technology used, test type, and accuracy were selected as reference metrics that set the comparison criteria, highlight innovative approaches, and discuss the development field of wheelchairs. In this work, to conduct the systematic review, four databases were identified. These include Science Direct, Taylor and Francis Online, Springer Journals, and IEEE Xplore. The pool of keywords set was selected to identify research articles published in the past five years. Inclusion and exclusion criteria were set to select the relevant studies that were consistent with the objectives of this study. Based on these criteria, 46 research papers were selected that met the inclusion requirements. The review study showed that wheelchair technology models such as autonomous control, 3D localization, and brain-computer interfaces (BCIs) were more precise in navigation and increased user independence. This systematic planning will help researchers, engineers, and practitioners make more realistic decisions to fill the gaps in available navigation aids and propose new and improved solutions for innovative assistant applications to ensure safety and accurate navigation. This study has many implications, especially the impact of reducing deaths and serious injuries among people with disabilities who use advanced technology wheelchairs

Sentiment Analysis of Semantically Interoperable Social Media Platforms Using Computational Intelligence Techniques

Competitive intelligence in social media analytics has significantly influenced behavioral finance worldwide in recent years; it is continuously emerging with a high growth rate of unpredicted variables per week. Several surveys in this large field have proved how social media involvement has made a trackless network using machine learning techniques through web applications and Android modes using interoperability. This article proposes an improved social media sentiment analytics technique to predict the individual state of mind of social media users and the ability of users to resist profound effects. The proposed estimation function tracks the counts of the aversion and satisfaction levels of each inter- and intra-linked expression. It tracks down more than one ontologically linked activity from different social media platforms with a high average success rate of 99.71%. The accuracy of the proposed solution is 97% satisfactory, which could be effectively considered in various industrial solutions such as emo-robot building, patient analysis and activity tracking, elderly care, and so on

Patient perception and attitudes toward magnetic resonance imaging safety

BackgroundMagnetic resonance imaging (MRI) scanners use strong, static and fast magnetic fields to form images. Due to rapid developments in MRI technology, several accidents have been recorded in hospitals worldwide as a result of insufficient knowledge about the dangers of MRI on the part of the patient or a failure to follow safety guidelines. This study evaluates patients’ perception and attitudes about MRI safety.AimsThis is a cross sectional study to evaluate the perception and attitudes of patients regarding MRI safety procedures.MethodsA 21 items questionnaire was collected from 119 patients in the MRI waiting area before the commencement of examination. Data were analysed using Statistical Package for the Social Sciences (SPSS) software (version 22.0, IBM Corp, Armonk, New York). The odds (OR) and 95 per cent confidence interval (CI) were used for analysis, the level of significance was set at p=0.05 using Chi-Square test to evaluate the relationship among the variables in the questionnaire.ResultsThe responses were collected from the patients and their relatives (46 male (38.6 per cent) and 73 female (61.4 per cent)). Approximately 71 per cent of the participants have already read or heard about MRI and the related safety aspects. 76 per cent of overall participants stated that they are aware of the need for preparation before an MRI exam with more awareness of MRI safety issues among younger patients (88 per cent). In this instance, females showed a higher level of knowledge (26 per cent) compared to males (11 per cent) with p=0.035.ConclusionPatients reported insufficient information about MRI safety which may increase the potential for accidents

Molecular docking supported investigation of antioxidant, analgesic and diuretic effects of Costus speciosus rhizome

ABSTRACT. The aim of the current study was to analyze the polyphenols and determines the antioxidant, analgesic and diuretic properties of the methanolic extract of&nbsp;C.speciosus&nbsp;rhizome. DPPH and ferric reducing antioxidant power (FRAP) assays were used to determine the antioxidant activity. Acetic acid-induced writhing and formalin-induced licking experiments were used to assess the analgesic effect. The total phenolic, flavonoid and flavonol contents were found 51.73± 0.25 mg GAE/g dry weight, 3.41± 0.07mg QE/g dry weights and 44.19± 2.24 mg QE/g dry weight, respectively. The plant extract exhibited weak antioxidant activity in the DPPH and FRAP assays, with an IC50 value of 1699±62 μg/mL and an EC50 value of 125±2 μg/mL, respectively. The extract significantly reduced the number of writhes at both doses (200 and 400 mg/kg body weight) as compared to the control. The extract (400 mg/kg) also significantly reduced the percent inhibition of licking by 31.96 and 62.69% compared to the control in the early and late phase, respectively. Compared to the standard drug furosemide, the plant extract also showed a weak diuretic effect. The docking study supported the analgesic activity of rhizome extract. The potent analgesic activity of the plant extract justifies the traditional and medicinal aspects. &nbsp; KEY WORDS: Costus speciosus, Analgesic activity, Diuretic effect, Molecular docking Bull. Chem. Soc. Ethiop. 2022, 36(3), 627-640.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; DOI: https://dx.doi.org/10.4314/bcse.v36i3.12 &nbsp