Understanding local ethnic inequalities in childhood BMI through cross-sectional analysis of routinely collected local data

Background: Local-level analysis of ethnic inequalities in health is lacking, prohibiting a comprehensive understanding of the health needs of local populations and the design of effective health services. Knowledge of ethnic disparities in child weight status is particularly limited by overlooking both the heterogeneity within ethnic groupings; and the complex ecological contexts in which obesity arises. This study aimed to establish whether there was variation in childhood BMI across ethnic groups in Coventry, and the influence of individual, school and neighbourhood contexts, using routinely collected local data. Methods: National Child Measurement Programme data were compiled for the period 2007/8-2014/15 and combined with routinely collected local data reflecting school performance and demographics, and school and neighbourhood physical environments. Multi-level modelling using Monte Carlo Markov Chain methods was used to account for the clustering of children within schools and neighbourhoods. Ethnic group differences in BMI z-score (zBMI) were explored at 4-5 years and 10-11 years for girls and boys alongside individual, school and neighbourhood covariates. Results: At age 4-5 years (n = 28,407), ethnic group differences were similar for boys and girls, with children from South Asian, White other, Chinese and 'any other' ethnic groups having a significantly lower zBMI, and Black African children having a higher zBMI, versus White British (WB) children. Patterns differed considerably at age 10-11 years (n = 25,763) with marked sex differences. Boys from White other, Bangladeshi and Black African groups had a significantly higher zBMI than WB boys. For girls, only children from Black ethnic groups showed a significantly higher zBMI. Area-level deprivation was the only important school or neighbourhood covariate, but its inclusion did not explain ethnic group differences in child zBMI. Conclusion: This analysis contributes to the existing literature by identifying nuanced patterns of ethnic disparities in childhood adiposity in Coventry, supporting the targeting of early obesity prevention for children from Black African groups, as well as girls from Black Caribbean and Black other ethnic backgrounds; and boys from Bangladeshi and White other ethnic backgrounds. It also demonstrates the utility of exploring routinely collected local data sets in building a comprehensive understanding of local population needs.</p

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

Risk prediction tools for cancer in primary care.

Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an 'area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.This is the final version of the article. It was first available from NPG via http://dx.doi.org/10.1038/bjc.2015.40

Microcalorimetry and spectroscopic studies on the binding of dye janus green blue to deoxyribonucleic acid

The interaction of the phenazinium dye janus green blue (JGB) with deoxyribonucleic acid was investigated using isothermal titration calorimetry and thermal melting experiments. The calorimetric data were supplemented by spectroscopic studies. Calorimetry results suggested the binding affinity of the dye to DNA to be of the order of 105 M-1. The binding was predominantly entropy driven with a small negative favorable enthalpy contribution to the standard molar Gibbs energy change.The binding became weaker as the temperature and salt concentration was raised. The temperature dependence of the standard molar enthalpy changes yielded negative values of standard molar heat capacity change for the complexation revealing substantial hydrophobic contribution in the DNA binding. An enthalpy–entropy compensation behavior was also observed in the system. The salt dependence of the binding yielded the release of 0.69 number of cations on binding of each dye molecule. The non-polyelectrolytic contribution was found to be the predominant force in the binding interaction. Thermal melting studies revealed that the DNA helix was stabilized against denaturation by the dye. The binding was also characterized by absorbance, resonance light scattering and circular dichroism spectral measurements. The binding constants from the spectral results were close to those obtained from the calorimetric data. The energetic aspects of the interaction of the dye JGB to double stranded DNA are supported by strong binding revealed from the spectral data

Role of Dopamine D2 Receptors in Human Reinforcement Learning

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, while loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically-determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well.Neuropsychopharmacology accepted article peview online, 09 April 2014; doi:10.1038/npp.2014.84

A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry

This research investigates the impacts of the novel coronavirus disease, also referred to as COVID-19 pandemic, on the food and beverage industry. It examines both short-term and medium-to-long-term impacts of the pandemic and outlines strategies to reduce the potential consequences of those impacts. To this end, we use a qualitative, multiple-case-study methodology, collecting data from eight sample companies with fourteen respondents in the food and beverage industry in Bangladesh. The findings show that the short-term impacts of this pandemic, such as product expiry, shortage of working capital, and limited operations of distributors, are severe, while the medium-to-long-term impacts promise to be complex and uncertain. In the longer term, various performance metrics, such as return on investment by the firms, the contribution of the firms to the gross domestic product (GDP), and employee size, are all expected to decrease. Moreover, firms may need to restructure their supply chain and build relationships with new distributors and trade partners. The study proposes several strategies that managers in this sector can adopt to improve resiliency in the changing environment during and after the COVID-19 era. While this research is novel and contributes to both theory and practice, it does not consider small and medium-sized companies in the food and beverage industry. Therefore, the impacts and strategies we identify may not apply to smaller companies

Succinic semialdehyde dehydrogenase deficiency: Lessons from mice and men

Succinic semialdehyde dehydrogenase (SSADH) deficiency, a disorder of GABA degradation with subsequent elevations in brain GABA and GHB, is a neurometabolic disorder with intellectual disability, epilepsy, hypotonia, ataxia, sleep disorders, and psychiatric disturbances. Neuroimaging reveals increased T2-weighted MRI signal usually affecting the globus pallidus, cerebellar dentate nucleus, and subthalamic nucleus, and often cerebral and cerebellar atrophy. EEG abnormalities are usually generalized spike-wave, consistent with a predilection for generalized epilepsy. The murine phenotype is characterized by failure-to-thrive, progressive ataxia, and a transition from generalized absence to tonic-clonic to ultimately fatal convulsive status epilepticus. Binding and electrophysiological studies demonstrate use-dependent downregulation of GABA(A) and (B) receptors in the mutant mouse. Translational human studies similarly reveal downregulation of GABAergic activity in patients, utilizing flumazenil-PET and transcranial magnetic stimulation for GABA(A) and (B) activity, respectively. Sleep studies reveal decreased stage REM with prolonged REM latencies and diminished percentage of stage REM. An ad libitum ketogenic diet was reported as effective in the mouse model, with unclear applicability to the human condition. Acute application of SGS–742, a GABA(B) antagonist, leads to improvement in epileptiform activity on electrocorticography. Promising mouse data using compounds available for clinical use, including taurine and SGS–742, form the framework for human trials

Assessment of Food Safety Knowledge, Attitudes and Practices of Food Service Staff in Bangladeshi Hospitals: A Cross-Sectional Study.

Food safety knowledge, attitudes and practices among hospital food service staff are crucial in the prevention of foodborne disease outbreaks, as hospitalized patients are more vulnerable to potential hazards. This study, therefore, sought to assess the food safety knowledge, attitudes and practices of food service staff in Bangladeshi hospitals. A cross-sectional study was conducted among 191 food service staff from seven different hospitals in Dhaka and Chattogram from October 2021 to March 2022 using pretested questionnaires. Multiple linear regression was used to identify the factors associated with the food safety knowledge, attitudes and practices. The findings showed moderate knowledge but high levels of attitudes and practices of food safety among hospital food handlers. Food safety knowledge was significantly higher among males, participants from private hospitals and participants working in a hospital that had a food service supervisor and dietitian in charge of food service operations. Moreover, participants from private hospitals and participants working in a hospital that had a food service supervisor and dietitian in charge of food service operations had more positive attitudes and better practices regarding food safety. Hospital management should consider these factors for enhancing food handlers' knowledge and increase training and supervision on food safety practices to reduce foodborne diseases and outbreaks

Global, regional, and national burden of neurological disorders during 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Background Comparable data on the global and country-specific burden of neurological disorders and their trends are crucial for health-care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study provides such information but does not routinely aggregate results that are of interest to clinicians specialising in neurological conditions. In this systematic analysis, we quantified the global disease burden due to neurological disorders in 2015 and its relationship with country development level. Methods We estimated global and country-specific prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) for various neurological disorders that in the GBD classification have been previously spread across multiple disease groupings. The more inclusive grouping of neurological disorders included stroke, meningitis, encephalitis, tetanus, Alzheimer's disease and other dementias, Parkinson's disease, epilepsy, multiple sclerosis, motor neuron disease, migraine, tension-type headache, medication overuse headache, brain and nervous system cancers, and a residual category of other neurological disorders. We also analysed results based on the Socio-demographic Index (SDI), a compound measure of income per capita, education, and fertility, to identify patterns associated with development and how countries fare against expected outcomes relative to their level of development. Findings Neurological disorders ranked as the leading cause group of DALYs in 2015 (250·7 [95% uncertainty interval (UI) 229·1 to 274·7] million, comprising 10·2% of global DALYs) and the second-leading cause group of deaths (9·4 [9·1 to 9·7] million], comprising 16·8% of global deaths). The most prevalent neurological disorders were tension-type headache (1505·9 [UI 1337·3 to 1681·6 million cases]), migraine (958·8 [872·1 to 1055·6] million), medication overuse headache (58·5 [50·8 to 67·4 million]), and Alzheimer's disease and other dementias (46·0 [40·2 to 52·7 million]). Between 1990 and 2015, the number of deaths from neurological disorders increased by 36·7%, and the number of DALYs by 7·4%. These increases occurred despite decreases in age-standardised rates of death and DALYs of 26·1% and 29·7%, respectively; stroke and communicable neurological disorders were responsible for most of these decreases. Communicable neurological disorders were the largest cause of DALYs in countries with low SDI. Stroke rates were highest at middle levels of SDI and lowest at the highest SDI. Most of the changes in DALY rates of neurological disorders with development were driven by changes in YLLs. Interpretation Neurological disorders are an important cause of disability and death worldwide. Globally, the burden of neurological disorders has increased substantially over the past 25 years because of expanding population numbers and ageing, despite substantial decreases in mortality rates from stroke and communicable neurological disorders. The number of patients who will need care by clinicians with expertise in neurological conditions will continue to grow in coming decades. Policy makers and health-care providers should be aware of these trends to provide adequate services