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Breast cancer, a complex global health concern, has predominantly been studied for nuclear DNA variations. However, the role of mitochondrial DNA (mtDNA) haplogroups in breast cancer susceptibility, especially in Pakistan, remains underexplored. This case-control study investigates the association between mtDNA haplogroups and breast cancer in Pakistan. The study reveals a significant abundance of haplogroup M in breast cancer cases by analyzing breast cancer patients and healthy controls through mitochondrial control region genome sequencing (p < 0.001). Increased frequencies of haplogroups M, H, and R in patients compared to controls suggest their potential role in breast cancer susceptibility. Triple-Negative Breast Cancer (TNBC) cases are also linked to haplogroup M, showing a statistically significant association with a p-value of 0.002. This suggests a potential meaningful association between haplogroup M and the occurrence of TNBC in the studied population. These findings emphasize the importance of mitochondrial genetics in breast cancer risk among the Pakistani population, offering insights for biomarker discovery and targeted interventions. Recognizing mitochondrial genetics in breast cancer risk assessment holds promise for tailored medicine strategies and may impact global breast cancer research and prevention efforts. [ABSTRACT FROM AUTHOR]

Dengue is an arboviral infection predominant in tropical and subtropical areas. It has inhabited the earth for the last few decades affecting almost 50% of the population in developing nations. Dengue infection covers a high range of symptoms for instance mild to acute hemorrhage fever, dengue shock syndrome, and liver dysfunction. Early diagnosis of the disease is crucial for prompt treatment strategies. One of the detection strategies of the infection can be made through viral structural peptides that act as markers for discernment, including Capsid (C) protein. In the proposed research, the structural gene obtained from local isolates was targeted for detection. For this purpose, a bacterial expression system was used to amplify, clone, and express the structural protein C. The expression of structural protein C was examined by SDS PAGE and verified by western blot and dot blot. The acquired antigen was purified which carries the potential for the development of a vaccine against dengue as well as for an in-house diagnostic assay. In this study, an in-house diagnostic ELISA has been compared to a commercially available kit to determine the specificity and sensitivity of the designed diagnostic ELISA. The aim underlying this study was to develop an accurate, error-free, unambiguous, and cost-friendly in-house ELISA, for the detection of antibodies in Pakistan's most prevalent dengue virus serotype 2 (DENV-2). The progress of this research would likewise foreshadow advancements of novel vaccines for future counteraction of dengue infection as C protein is highly immunogenic. [ABSTRACT FROM AUTHOR]

AbstractSocial robots, driven by cutting-edge technologies are designed to cater to various societal needs, facilitating complex human interactions involving multiple users and stakeholders. Their integration into daily life is anticipated to increase significantly. Within this context, the domain of shopping robots, which play a crucial role in enhancing and diversifying shopping experiences where human interaction is paramount, holds immense potential for development. This article aims to provide an overview of the current landscape of shopping robots and explore future research directions in this evolving field. Through this systematic review, key trends and insights in the field of shopping robots are identified, while also offering a categorization in the form of a 3D conceptual scheme, called the Public Space Robot (PSR) framework. The outcomes reveal significant developments over the past two decades (2002–2024), with the main concentration on developing and deploying mobile robots that offer functional or autonomous interaction for navigation assistance and customer service in shopping malls and retail stores. [ABSTRACT FROM AUTHOR]

Fire detection and extinguishing systems are critical for safeguarding lives and minimizing property damage. These systems are especially vital in combating forest fires. In recent years, several forest fires have set records for their size, duration, and level of destruction. Traditional fire detection methods, such as smoke and heat sensors, have limitations, prompting the development of innovative approaches using advanced technologies. Utilizing image processing, computer vision, and deep learning algorithms, we can now detect fires with exceptional accuracy and respond promptly to mitigate their impact. In this article, we conduct a comprehensive review of articles from 2013 to 2023, exploring how these technologies are applied in fire detection and extinguishing. We delve into modern techniques enabling real-time analysis of the visual data captured by cameras or satellites, facilitating the detection of smoke, flames, and other fire-related cues. Furthermore, we explore the utilization of deep learning and machine learning in training intelligent algorithms to recognize fire patterns and features. Through a comprehensive examination of current research and development, this review aims to provide insights into the potential and future directions of fire detection and extinguishing using image processing, computer vision, and deep learning. [ABSTRACT FROM AUTHOR]

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Objective: To identify the genetic variants in the CYP1B1 gene associated with Primary Congenital Glaucoma (PCG) and to predict its pathological effect. Method: A descriptive study was conducted in the time period of nine months (September 2021-May 2022) after the ethical approval was taken from The Children Hospital and Institute of Child Health (CH & ICH). Two milliliters of the blood sample from PCG-affected individuals were collected in EDTA vacutainers and genomic DNA was extracted by a phenol-chloroform method. The semi-quantification of extracted DNA was done by agarose gel electrophoresis. PCR amplification was performed by specific primers of CYP1B1 gene then termination sequencing (di-deoxy) was done to detect the genetic variants. Different bioinformatics tools such as BLAST, Ensembl, Clustal Omega, Polyphen and SIFT were used for the further analysis of mutation causing the disease. Results: A total of 85% of patients were bilaterally affected, while 15% were unilaterally affected. Mutation analysis identified five non related known variants. Two missense mutations (c.355 G/T p.A119S and c.685G/A p.E229K) occurred in 94% patients and intragenic SNP occurred in 29% patients along with the 1% somatic (c.693C/A p.F231L) and stop gained mutation (c.840C/A p.C280*). Conclusion: Genetic analysis in the current study showed that 85% of PCG affected patients were due to the CYP1B1 mutation, and disease heterogeneity might be reduced through genetic counseling. [ABSTRACT FROM AUTHOR]