Au Nanoparticle-Based Amplified DNA Detection on Poly-l-lysine Monolayer-Functionalized Electrodes

Affinity sensing of nucleic acids is among the most investigated areas in biosensing due to the growing importance of DNA diagnostics in healthcare research and clinical applications. Here, we report a simple electrochemical DNA detection layer, based on poly-l-lysine (PLL), in combination with gold nanoparticles (AuNPs) as a signal amplifier. The layer shows excellent reduction of non-specific binding and thereby high contrast between amplified and non-amplified signals with functionalized AuNPs; the relative change in current was 10-fold compared to the non-amplified signal. The present work may provide a general method for the detection of tumor markers based on electrochemical DNA sensing.

A Systems Approach to Achieve Equity in Healthcare Research

Healthcare in the United States is inequitable. The consequence of inequity is that the burden of serious chronic disease, such as diabetes, falls disproportionately on populations experiencing health disparities, predominantly Black, Indigenous, and people of color. [1] The reasons for the inequity include the negative impact of the social determinants of health of individuals and families from these communities, being underrepresented as participants in clinical research, having limited access to technologies that support self-care, and a lack of researchers and clinicians from these same populations. [2] To achieve equity and fairness, there is a need for a paradigm shift in healthcare research and innovation based on improving access, trust, and self-efficacy [3] to convert new knowledge into positive health outcomes.

Understanding challenges of using routinely collected health data to address clinical care gaps: a case study in Alberta, Canada

High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electronic medical record data are rich sources of information, they have significant limitations. Through four example projects from the Physician Learning Program in Edmonton, Alberta, Canada, we illustrate barriers to using routinely collected health data to conduct research and engage in clinical quality improvement. These include challenges with data availability for variables of clinical interest, data completeness within a clinical visit, missing and duplicate visits, and variability of data capture systems. We make four recommendations that highlight the need for increased clinical engagement to improve the collection and coding of routinely collected data. Advancing the quality and usability of health systems data will support the continuous quality improvement needed to achieve the quintuple aim.

Healthcare quality for Muslims: TCCM and TSR frameworks analyses

Purpose Transformative service research (TSR) has received considerable attention from researchers and marketers in recent years and becomes a research priority in health care. In response, this paper adapts the TSR entities and wellbeing framework to systematically review healthcare quality research on Muslim consumers. The purpose of this paper is to identify research gaps and provide directions for future research, aligning healthcare studies with the TSR framework. Design/methodology/approach The authors of this paper reviewed empirical papers in healthcare quality research on Muslim patients between the years 2000 and 2020. The recorded journal articles were synthesized using insights from the TSR framework. Several literature gaps were identified and future research directions were provided using the TCCM framework, in which T stands for theory, C for context, C for characteristics and M for methodology. Findings This paper finds studies that encompass several domains of the TSR framework including cultural and religious dimensions, service interaction and customer engagement dimensions and customer service wellbeing. Findings also reveal subject matters related to the TSR framework, which receive less attention in the healthcare literature. A number of potential avenues for theoretical extension in health care are also discussed. Social implications The implications of this paper are highly relevant to Muslim healthcare consumers, the healthcare system and society in general. The findings suggest inspiring changes in the healthcare ecosystem that yields a greater quality of life (health and wellbeing) for individuals and their respective communities. Originality/value This paper advances the current state of healthcare research by identifying and organizing components of TSR entities and wellbeing framework, using Muslim patients as the context. It enhances some pioneering approaches within the domain of TSR and quality dynamics and provides a holistic perspective as guidance and systematic thinking to further advancement in the field of services marketing and Islamic marketing.

Factors Influencing Self-Reported Medication Use in the Survey of Health Aging and Retirement in Europe (SHARE) Dataset

The validity of self-reported medication use in epidemiological studies is an important issue in healthcare research. Here we investigated factors influencing self-reported medication use for multiple diagnoses in the seventh wave of the Survey of Health Aging and Retirement in Europe (SHARE) dataset in n = 77,261 participants (ages: mean = 68.47, standard deviation = 10.03 years). The influence of mental, physical, and sociodemographic parameters on medication self-report was analyzed with logistic regressions and mediation models. Depression, memory function, and polypharmacy influenced the self-report of medication use in distinct disorders to varying degrees. In addition, sociodemographic factors, knowledge about diagnosis, the presence of several chronic illnesses, and restrictions of daily instrumental activities explained the largest proportion of variance. In the mediation model, polypharmacy had an indirect effect via depression and memory on self-reported medication use. Factors influencing medication self-report vary between different diagnoses, highlighting the complexity of medication knowledge. Therefore, it is essential to assess the individual parameters and their effect on medication behavior. Relying solely on medication self-reports is insufficient, as there is no way to gage their reliability. Thus, self-reported medication intake should be used with caution to indicate the actual medication knowledge and use.

Evaluation of Nootropic Activity of Leaf Extract of Anacardium occidentale L.

One of the plants that have been used for enthno medicinal purposes in traditional civilization is Anacardium occidentale L. of the family Anacardiaceae is native to Brazil also found in tropical countries such as Malaysia and India commonly known as cashew. The purpose of this study is to determine the in-vitro and in-vivo cognitive effects of an ethanolic leaf extract of the herb Anacardium occidentale on albino rats. Orally the ethanolic extract was administered in two doses (100 mg/kg and 400 mg/kg). The Elevated Plus maze and Y-maze showed statistically significant improvement in the memory process. The estimation of acetylcholinesterase enzyme in rats brain also shows improvement in the memory process by reducing acetylcholinesterase activity. Disorders related to cognition are one of the major health problems and increasing day by day especially affecting the elder individual. There is no proper medication for the impairment of memory. The study reveals that the ethanolic extract of the leaf of Anacardium occidentale has dose-dependent memory-enhancing performance. Synthetic drugs have a lot of side effects, whereas drugs belongs to natural substances have least side effect compared to synthetic one, which has gained a lots of importance. These studies need to be documented effectively. Research findings were contributed to meet the future needs in general healthcare, research, and conservation of endangered species and may give a lead to the discovery of newer drugs.

Enrolment in clinical research at UCLH and geographically distributed indices of deprivation

Healthcare should be judged by its equity as well as its quality. Both aspects depend not only on the characteristics of service delivery but also on the research and innovation that ultimately shape them. Conducting a fully-inclusive evaluation of the relationship between enrolment in primary research studies at University College London Hospitals NHS Trust and indices of deprivation, here we demonstrate a quantitative approach to evaluating equity in healthcare research and innovation. We surveyed the geographical locations, aggregated into Lower Layer Super Output Areas (LSOAs), of all England-resident UCLH patients registered as enrolled in primary clinical research studies. We compared the distributions of ten established indices of deprivation across enrolled and non-enrolled areas within Greater London and within a distance-matched subset across England. Bayesian Poisson regression models were used to examine the relation between deprivation and the volume of enrolment standardized by population density and local disease prevalence. A total of 54593 enrolments covered 4401 LSOAs in Greater London and 10150 in England, revealing wide geographical reach. The distributions of deprivation indices were similar between enrolled and non-enrolled areas, exhibiting median differences from 0.26% to 8.73%. Across Greater London, enrolled areas were significantly more deprived on most indices, including the Index of Multiple Deprivation; across England, a more balanced relationship to deprivation emerged. Regression analyses of enrolment volumes yielded weak biases, in favour of greater deprivation for most indices, with little modulation by local disease prevalence. Primary clinical research at UCLH has wide geographical reach. Areas with enrolled patients show similar distributions of established indices of deprivation to those without, both within Greater London, and across distance-matched areas of England. We illustrate a robust approach to quantifying an important aspect of equity in clinical research and provide a flexible set of tools for replicating it across other institutions.

Generalized Zero-Adjusted Models to Predict Medical Expenditures

In healthcare research, medical expenditure data for the elderly are typically semicontinuous and right-skewed, which involve a point mass at zero and may exhibit heteroscedasticity. The problem of a substantial proportion of zero values prevents traditional regression techniques based on the Gaussian, gamma, or inverse Gaussian distribution, which may lead to understanding the standard errors of the parameters and overestimating their significance. A common way to counter the problem is using zero-adjusted models. However, due to the right-skewness in the nonzeros’ response, conventional zero-adjusted models such as zero-adjusted gamma, zero-adjusted Inverse Gaussian, and classic Tobit may not perform well. Here, we firstly generalize those three types of the conventional zero-adjusted model to solve the problem of right-skewness in health care. The generalized zero-adjusted models are very flexible and include the zero-adjusted Weibull, zero-adjusted gamma, zero-adjusted inverse Gaussian, and classic Tobit models as their special cases. Using the Chinese Longitudinal Healthy Longevity Survey, we find that, according to the AIC, SBC, and deviance criteria, the zero-adjusted generalized gamma model is the best one of these generalized models to predict the odds of zero cost accurately. In order to depict the predictors affecting the amount expenditure, we further discuss the situations where the mean, dispersion of a nonzero amount expenditure and model the probability of a zero amount of ZAGG in terms of predictor variables using suitable link functions, respectively. Our analysis shows that age, health, chronic diseases, household income, and residence are the main factors influencing the medical expenditure for the elderly, but the insurance is not significant. To the best of our knowledge, little study focused on these situations, and this is the first time.