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1 – 10 of 56Rucha Wadapurkar, Sanket Bapat, Rupali Mahajan and Renu Vyas
Ovarian cancer (OC) is the most common type of gynecologic cancer in the world with a high rate of mortality. Due to manifestation of generic symptoms and absence of specific…
Abstract
Purpose
Ovarian cancer (OC) is the most common type of gynecologic cancer in the world with a high rate of mortality. Due to manifestation of generic symptoms and absence of specific biomarkers, OC is usually diagnosed at a late stage. Machine learning models can be employed to predict driver genes implicated in causative mutations.
Design/methodology/approach
In the present study, a comprehensive next generation sequencing (NGS) analysis of whole exome sequences of 47 OC patients was carried out to identify clinically significant mutations. Nine functional features of 708 mutations identified were input into a machine learning classification model by employing the eXtreme Gradient Boosting (XGBoost) classifier method for prediction of OC driver genes.
Findings
The XGBoost classifier model yielded a classification accuracy of 0.946, which was superior to that obtained by other classifiers such as decision tree, Naive Bayes, random forest and support vector machine. Further, an interaction network was generated to identify and establish correlations with cancer-associated pathways and gene ontology data.
Originality/value
The final results revealed 12 putative candidate cancer driver genes, namely LAMA3, LAMC3, COL6A1, COL5A1, COL2A1, UGT1A1, BDNF, ANK1, WNT10A, FZD4, PLEKHG5 and CYP2C9, that may have implications in clinical diagnosis.
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Rana I. Mahmood, Harraa S. Mohammed-Salih, Ata’a Ghazi, Hikmat J. Abdulbaqi and Jameel R. Al-Obaidi
In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their…
Abstract
Purpose
In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.
Design/methodology/approach
Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.
Findings
The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.
Originality/value
This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.
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Rajat Chandel, Vikas Kumar, Ramandeep Kaur, Satish Kumar, Ankit Kumar, Dharminder Kumar and Swati Kapoor
Pyrus Pyrifolia (Sand Pear) is one of the most underused pear variety despite its nutraceutical potential. Therefore, this paper aims to explore the Pyrus Pyrifolia in term of…
Abstract
Purpose
Pyrus Pyrifolia (Sand Pear) is one of the most underused pear variety despite its nutraceutical potential. Therefore, this paper aims to explore the Pyrus Pyrifolia in term of origin, distribution and classification, nutritional and bioactive potential, therapeutic potential and valorization along with future prospectus.
Design/methodology/approach
A wide variety of publications (88) were identified through electronic databases (Science direct, PubMed, SciELO, Google scholar, Link springer and Research gate) under the umbrella of different keywords such as bioactive compounds, health benefits, nutrition, sand pear, Pyrus and Pyrus pyrifolia.
Findings
Pyrus Pyrifolia (Sand Pear) is abundant in nutritional and bioactive compounds such as phenolic acids, flavonoids, terpenoids, vitamins and minerals. It exhibits therapeutic potential as being an antioxidant, anti-obesity, anti-diabetic, anti-inflammatory and anti-cancer agent. However, P. pyrifolia is not much explored by food researchers and industrialists, hence remaining underused. A few attempts have been made toward the use of P. pyrifolia for jam, jelly, candy and wine preparation. However, more research is required for the commercial processing of P. pyrifolia and to enhance its availability outside its growing area.
Originality/value
In this paper, nutritional and bioactive compounds of P. pyrifolia are discussed that provide knowledge to the researchers for its use as a functional ingredient.
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Majid Monajjemi and Fatemeh Mollaamin
Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated…
Abstract
Purpose
Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.
Design/methodology/approach
The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.
Findings
The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.
Originality/value
The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.
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Oswald A. J. Mascarenhas, Munish Thakur and Payal Kumar
We revisit the problem of redesigning the Master in Business Administration (MBA) program, curriculum, and pedagogy, focusing on understanding and seeking to tame its “wicked…
Abstract
Executive Summary
We revisit the problem of redesigning the Master in Business Administration (MBA) program, curriculum, and pedagogy, focusing on understanding and seeking to tame its “wicked problems,” as an intrinsic part and challenge of the MBA program venture, and to render it more realistic and relevant to address major problems and their consequences. We briefly review the theory of wicked problems and methods of dealing with their consequences from multiple perspectives. Most characterization of problems classifies them as simple (problems that have known formulations and solutions), complex (where formulations are known but not their resolutions), unstructured problems (where formulations are unknown, but solutions are estimated), and “wicked” (where both problem formulations and their resolutions are unknown but eventually partially tamable). Uncertainty, unpredictability, randomness, and ambiguity increase from simple to complex to unstructured to wicked problems. A redesigned MBA program should therefore address them effectively through the four semesters in two years. Most of these problems are real and affect life and economies, and hence, business schools cannot but incorporate them into their critical, ethical, and moral thinking.
Amin Reihani, Fatemeh Shaki and Ala Azari
Acrylamide (AA) is predominantly used as a synthetic substance within various industries. However, AA is also recognized as a carcinogen. Zinc oxide nanoparticles (ZnO-NPs) are…
Abstract
Purpose
Acrylamide (AA) is predominantly used as a synthetic substance within various industries. However, AA is also recognized as a carcinogen. Zinc oxide nanoparticles (ZnO-NPs) are becoming increasingly attractive as medical agents. However, to the knowledge, the effects of ZnO-NPs on preventing cytotoxicity with AA have not been reported. Therefore, this study aims to determine the protective effects of ZnO-NPs against the cytotoxicity caused by AA.
Design/methodology/approach
MTT assay was used to determine the cytotoxicity. Reactive oxygen species (ROS) formation, carbonyl protein, malondialdehyde (MDA) and glutathione (GSH) were measured and analyzed statistically.
Findings
The findings observed that the presence of 200 µM AA led to a substantial reduction in cell viability (p < 0.001). However, ZnO-NPs restored cell viability at 50 and 100 µM concentrations (p = 0.0121 and p = 0.0011, respectively). The levels of ROS were significantly reduced (p = 0.001 and p = < 0.001) to 518 ± 47.57 and 364 ± 47.79, respectively, compared to the AA group. The levels of GSH were significantly increased (p = 0.004 and p = 0.002) to 16.9 ± 1.3 and 17.6 ± 0.5, respectively, compared to the AA group. The levels of MDA were significantly decreased (p = 0.005, p < 0.001 and p < 0.001) when compared to the AA group, as were the levels of carbonyl protein (p = 0.009 and p < 0.002) in comparison to the AA group.
Originality/value
In summary, the outcomes of this research indicate that ZnO-NPs played a role in inhibiting AA-induced oxidative stress and cytotoxicity.
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Clair Reynolds Kueny, Alex Price and Casey Canfield
Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower…
Abstract
Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.
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Muhammad Adnan Hasnain, Hassaan Malik, Muhammad Mujtaba Asad and Fahad Sherwani
The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a…
Abstract
Purpose
The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a very common dental health problem for all people. The detection of dental issues and the selection of the most suitable method of treatment are both determined by the results of a radiological examination. Dental x-rays provide important information about the insides of teeth and their surrounding cells, which helps dentists detect dental issues that are not immediately visible. The analysis of dental x-rays, which is typically done by dentists, is a time-consuming process that can become an error-prone technique due to the wide variations in the structure of teeth and the dentist's lack of expertise. The workload of a dental professional and the chance of misinterpretation can be decreased by the availability of such a system, which can interpret the result of an x-ray automatically.
Design/methodology/approach
This study uses deep learning (DL) models to identify dental diseases in order to tackle this issue. Four different DL models, such as ResNet-101, Xception, DenseNet-201 and EfficientNet-B0, were evaluated in order to determine which one would be the most useful for the detection of dental diseases (such as fillings, cavity and implant).
Findings
Loss and accuracy curves have been used to analyze the model. However, the EfficientNet-B0 model performed better compared to Xception, DenseNet-201 and ResNet-101. The accuracy, recall, F1-score and AUC values for this model were 98.91, 98.91, 98.74 and 99.98%, respectively. The accuracy rates for the Xception, ResNet-101 and DenseNet-201 are 96.74, 93.48 and 95.65%, respectively.
Practical implications
The present study can benefit dentists from using the DL model to more accurately diagnose dental problems.
Originality/value
This study is conducted to evaluate dental diseases using Convolutional neural network (CNN) techniques to assist dentists in selecting the most effective technique for a particular clinical condition.
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Suchismita Swain, Kamalakanta Muduli, Anil Kumar and Sunil Luthra
The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships…
Abstract
Purpose
The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.
Design/methodology/approach
Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.
Findings
The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.
Practical implications
Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.
Originality/value
At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.
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