Type 2 diabetes mellitus (T2DM) is a common chronic disease that disproportionally affects disadvantaged groups. People with a low socioeconomic position (SEP) have increased risk of T2DM and people ...with a low SEP and T2DM have higher HbA
-levels compared to people with T2DM and high SEP. The aim of this study is to analyze longitudinal socioeconomic differences in health-related functioning in people with T2DM.
Longitudinal data from 1,537 participants of The Maastricht Study with T2DM were used (32.6% female, mean (SD) age 62.9 (7.7) years). SEP was determined by baseline measures of education, occupation and income. Health-related functioning (physical, mental and social) was measured with the Short-Form Health Survey and the Impact on Participation and Autonomy survey (all scored from 0 to 100). Associations of SEP and health-related functioning were studied annually over a 10-year period (median (IQR) 7.0 (5.0) years, baseline 2010-2018) using linear mixed methods adjusting for demographics, HbA
-levels and lifestyle factors.
Participants with a low SEP had significantly worse health-related functioning compared to those with a high SEP. For example, participants with low income had lower scores for physical (-4.49CI -5.77;-3.21), mental (-2.61-3.78,-1.44) and social functioning (-9.76-12.30;-7.23) compared to participants with high income on a scale from 0 to 100. In addition, participants with a low education significantly declined more over time in mental (score for interaction education with time - 0.23-0.37;-0.09) and social functioning (-0.44-0.77;-0.11) compared to participants with high education. Participants with low and intermediate incomes significantly declined more over time in physical functioning (-0.17 -0.34, -0.01 and - 0.18 -0.36, 0.00) compared to participants with high income.
Among people with T2DM, those with a lower SEP had worse health-related functioning in general than people with a higher SEP. Additionally, people with T2DM and low education developed poorer mental and social functioning over time compared to people with T2DM and high education. People with T2DM and low or intermediate income declined more in physical functioning over time than those with high incomes. In addition to HbA
-levels and lifestyle patterns, more attention is needed for socioeconomic differences in health-related functioning for people living with T2DM.
Objective:
We examined the association between low socioeconomic position (SEP) and Type 2 Diabetes Mellitus (T2DM), and the mediating role of psychosocial work environment by using counterfactual ...mediation analysis.
Methods:
Data from 8,090 participants of The Maastricht Study were analysed. SEP indicators (education, income, occupation), self-reported psychosocial work stressors, (pre)diabetes by oral glucose tolerance test were measured at baseline. Incident T2DM was self-reported per annum up to 9 years. Cox regression and causal mediation analyses were performed.
Results:
2.8% (
N
= 172) of the participants without T2DM at baseline reported incident T2DM. People with lower SEP more often had prevalent T2DM (e.g., education OR = 2.49, 95% CI: 2.16–2.87) and incident T2DM (e.g., education HR = 2.21, 95% CI: 1.53–3.20) than higher SEP. Low job control was associated with prevalent T2DM (OR = 1.44 95% CI: 1.25–1.67). Job control partially explained the association between income and prevalent T2DM (7.23%). Job demand suppressed the associations of education and occupation with prevalent T2DM. The mediation models with incident T2DM and social support were not significant.
Conclusion:
Socioeconomic inequalities in T2DM were present, but only a small part of it was explained by the psychosocial work environment.
This study examined the cross-sectional association between sleep duration, prediabetes, and type 2 diabetes, and its independence from the traditional lifestyle risk factors diet, physical activity, ...smoking behavior, and alcohol consumption.
Cross-sectional data from 5561 people aged 40-75 years recruited into The Maastricht Study between 2010 and 2018 were used (1:1 female:male and mean age: 60.1 years standard deviation: 8.6). Sleep duration was operationalized as in-bed time, algorithmically derived from activPAL3 accelerometer data (median 7 nights, IQR 1). Glucose metabolism status was determined with an oral glucose tolerance test. Multinomial logistic regression was used to assess the association of sleep duration as restricted cubic spline with prediabetes and type 2 diabetes. We adjusted for sex, age, educational level, the use of sleep medication or antidepressants, and the following lifestyle risk factors: diet quality, physical activity, smoking behavior, and alcohol consumption.
A U-shaped association between sleep duration and type 2 diabetes was found. Compared to those with a sleep duration of 8 hours, participants with a sleep duration of 5 and 12 hours had higher odds of type 2 diabetes (OR: 2.9 95% CI 1.9 to 4.4 and OR 3.2 2.0 to 5.2, respectively). This association remained after further adjustment for the lifestyle risk factors (OR: 2.6 1.7 to 4.1 and OR 1.8 1.1 to 3.1). No such association was observed between sleep duration and prediabetes.
Both short and long sleep durations are associated positively and independently of lifestyle and cardiovascular risk factors with type 2 diabetes, but not with prediabetes.
In this work the adsorption of tri-peptides on a mixed-mode resin was studied using isocratic pulse response experiments. Various salt concentration, temperature and pH combinations were used to ...measure retention times of several tri-peptides. The experiments were evaluated according to an extension of the stoichiometric displacement model and the steric mass action model of protein–ligand binding. The application of this model in the understanding of mixed mode adsorption process is discussed. A unique set of meaningful thermodynamic parameters was obtained for each resin-peptide-temperature and resin-peptide-pH combination. Finally it was shown that these thermodynamic parameters can be used in defining quantitative relationships within the framework of extra thermodynamic relationships.
Social interactions between individuals living in a group can have both positive and negative effects on welfare, productivity, and health of these individuals. Negative effects of social ...interactions in livestock are easier to observe than positive effects. For example, laying hens may develop feather pecking, which can cause mortality due to cannibalism, and pigs may develop tail biting or excessive aggression. Several studies have shown that social interactions affect the genetic variation in a trait. Genetic improvement of socially-affected traits, however, has proven to be difficult until relatively recently. The use of classical selection methods, like individual selection, may result in selection responses opposite to expected, because these methods neglect the effect of an individual on its group mates (social genetic effects). It has become clear that improvement of socially-affected traits requires selection methods that take into account not only the direct effect of an individual on its own phenotype but also the social genetic effects, also known as indirect genetic effects, of an individual on the phenotypes of its group mates. Here, we review the theoretical and empirical work on social genetic effects, with a focus on livestock. First, we present the theory of social genetic effects. Subsequently, we evaluate the evidence for social genetic effects in livestock and other species, by reviewing estimates of genetic parameters for direct and social genetic effects. Then we describe the results of different selection experiments. Finally, we discuss issues concerning the implementation of social genetic effects in livestock breeding programs. This review demonstrates that selection for socially-affected traits, using methods that target both the direct and social genetic effects, is a promising, but sometimes difficult to use in practice, tool to simultaneously improve production and welfare in livestock.
Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metrics, such as the ...Dice, are used as a metric to evaluate the performance of these models in order for results to be comparable.
However, there is a mismatch between the distributions of cases and the difficulty level of segmentation tasks in public data sets compared to clinical practice. Common metrics used to assess performance fail to capture the impact of this mismatch, particularly when dealing with datasets in clinical settings that involve challenging segmentation tasks, pathologies with low signal, and reference annotations that are uncertain, small, or empty. Limitations of common metrics may result in ineffective machine learning research in designing and optimizing models. To effectively evaluate the clinical value of such models, it is essential to consider factors such as the uncertainty associated with reference annotations, the ability to accurately measure performance regardless of the size of the reference annotation volume, and the classification of cases where reference annotations are empty.
We study how uncertain, small, and empty reference annotations influence the value of metrics on a stroke in-house data set regardless of the model. We examine metrics behavior on the predictions of a standard deep learning framework in order to identify suitable metrics in such a setting. We compare our results to the BRATS 2019 and Spinal Cord public data sets. We show how uncertain, small, or empty reference annotations require a rethinking of the evaluation. The evaluation code was released to encourage further analysis of this topic https://github.com/SophieOstmeier/UncertainSmallEmpty.git.
•Real-time angle-scanning surface plasmon resonance system with variable wavelength.•Choice of wavelength in accordance with the sensor and sample properties.•Offline protein immobilization on ...Aluminum oxide sensor surface.•Sensitive and robust antibody-protein interaction analysis.
A variable-wavelength Kretschmann configuration surface plasmon resonance (SPR) apparatus with angle scanning is presented. The setup provides the possibility of selecting the optimum wavelength with respect to the properties of the metal layer of the sensorchip, sample matrix, and biomolecular interaction of interest. Monitoring SPR curves over a wide angular range (39°) permits simultaneous determination of the total internal reflection angle (TIR), the resonance angle, and the intensity and width of the SPR dip, which are essential parameters for measuring binding events and achieving optimum sensitivity. The new apparatus was evaluated by recording full SPR curves at different wavelengths ranging from 600 to 890 nm using sensor surfaces of silver, gold and gold with deposited silicon oxide, aluminum oxide, titanium oxide and indium tin oxide which were exposed to air and an aqueous solution of sodium chloride. Clear wavelength dependencies of sensor-material resonance angles and SPR-dip widths were demonstrated. In order to investigate the capability of the system to probe molecular binding to different sensor surfaces, the layer-by-layer adsorption of charged polyelectrolytes was monitored in angular scanning mode at 600, 670, 785, and 890 nm. Although at longer wavelengths lower angular shifts were observed as result of layer deposition, the sharper dip, wider detection window and better signal-to-noise ratios at these wavelengths can be beneficial for binding studies. The applicability for biosensing was tested by immobilizing human serum albumin (HSA) on an aluminum-oxide-coated gold sensor using a new procedure and measuring the binding of anti-HSA antibodies at the optimal wavelength (890 nm) in angular-scanning and fixed-angle mode. The HSA biosensor showed negligible non-specific interaction and yielded almost ten times better sensitivity than obtained with a conventional gold-dextran-based sensor operated at 670/785 nm. Analysis of anti-HSA samples pre-incubated with different concentrations of HSA allowed measurement of the IC50 value. The reported data demonstrate the usefulness of the presented variable-wavelength angle-scanning SPR instrument, permitting continuous recording of full SPR curves in time at any selected wavelength in the 600–890 nm range using a sensor material of choice.
Every year three million people die as a result of bacterial infections, and this number may further increase due to resistance to current antibiotics. These antibiotics target almost all essential ...bacterial processes, leaving only a few new targets for manipulation. The host proteome has many more potential targets for manipulation in order to control bacterial infection, as exemplified by the observation that inhibiting the host kinase Akt supports the elimination of different intracellular bacteria including Salmonella and M. tuberculosis. If host kinases are involved in the control of bacterial infections, phosphatases could be as well. Here we present an integrated small interference RNA and small molecule screen to identify host phosphatase-inhibitor combinations that control bacterial infection. We define host phosphatases inhibiting intracellular growth of Salmonella and identify corresponding inhibitors for the dual specificity phosphatases DUSP11 and 27. Pathway analysis places many kinases and phosphatases controlling bacterial infection in an integrated pathway centered around Akt. This network controls host cell metabolism, survival, and growth and bacterial survival and reflect a natural host cell response to bacterial infection. Inhibiting two enzyme classes with opposite activities–kinases and phosphatases–may be a new strategy to overcome infections by antibiotic-resistant bacteria.
Filamentous fungi have been used as sources of metabolites and enzymes for centuries. For about two decades, molecular genetic tools have enabled us to use these organisms to express extra copies of ...both endogenous and exogenous genes. This review of current practice reveals that molecular tools have enabled several new developments. But it has been process development that has driven the final breakthrough to achieving commercially relevant quantities of protein. Recent research into gene expression in filamentous fungi has explored their wealth of genetic diversity with a view to exploiting them as expression hosts and as a source of new genes. Inevitably, the progress in the ‘genomics’ technology will further develop high-throughput technologies for these organisms.
Filamentous fungi have become preferred host organisms for protein production through a combination of molecular tools and process development.
Initial internet-based cognitive behavioral therapy (iCBT) programs for anxiety disorders in children and young people (CYP) have been developed and evaluated, however these have not yet been widely ...adopted in routine practice. The lack of guidance and formalized approaches to the development and dissemination of iCBT has arguably contributed to the difficulty in developing iCBT that is scalable and sustainable beyond academic evaluation and that can ultimately be adopted by healthcare providers. This paper presents a consensus statement and recommendations from a workshop of international experts in CYP anxiety and iCBT (#iCBTLorentz Workshop Group) on the development, evaluation, engagement and dissemination of iCBT for anxiety in CYP.
•This paper gives a consensus statement and recommendations for research on iCBT for anxiety in youth•We discuss considerations regarding the development, evaluation, engagement and dissemination of iCBT for anxiety in youth•ICBT for youth anxiety should be initially evaluated with a RCT, while further iterations could use other research designs•Consistent measures relating to youth anxiety and iCBT usage should be employed, as well as precise reporting of iCBT programs•Dissemination of iCBT for youth anxiety into routine clinical practice should be considered from the start of development
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