Prediabetes and the risk of type 2 diabetes: investigating the roles of depressive and anxiety symptoms in the Lifelines Cohort Study

Background Depression and anxiety may increase the risk of progressing from prediabetes to type 2 diabetes. The present study examined the interactions between prediabetes status and elevated depressive and anxiety symptoms with the risk of type 2 diabetes. Methods Participants (N=72,428) were adults aged 40 years and above without diabetes at baseline from the Lifelines Cohort Study (58% female; mean age=51.4 years). The Mini-International Neuropsychiatric Interview screened for elevated symptoms of major depressive disorder and generalized anxiety disorder. Glycated hemoglobin A1c (HbA1c) levels determined prediabetes status at baseline (2007-2013), and HbA1c and self-reported diabetes diagnoses determined diabetes status at follow-up (2014-2017). Groups were formed for elevated depressive and anxiety symptoms, respectively, and prediabetes status at baseline (elevated depressive/anxiety symptoms with prediabetes, elevated depressive/anxiety symptoms alone, and prediabetes alone), and compared to a reference group (no prediabetes or anxiety/depression) on the likelihood of developing diabetes during the follow-up period. Findings N=1,300 (1.8%) participants developed diabetes. While prediabetes alone was associated with incident diabetes (OR=5.94; 95% CI=5.10-6.90, p<.001), the group with combined prediabetes and depressive symptoms had the highest likelihood of developing diabetes over follow-up (OR=8.29; 95% CI=5.58-12.32, p<.001). Similar results were found for prediabetes and anxiety symptoms (OR=6.57; 95% CI=4.62-9.33, p<.001), compared to prediabetes alone (OR=6.09; 95% CI=5.23-7.11, p<.001), though with a smaller effect. The interaction between depressive symptoms and prediabetes was synergistic in age-and-sex adjusted analyses. Conclusion Individuals with elevated depressive, and to some extent anxiety, symptoms in combination with prediabetes may represent a high-risk subgroup for type 2 diabetes

Mouse Stbd1 is N-myristoylated and affects ER-mitochondria association and mitochondrial morphology

Starch binding domain-containing protein 1 (Stbd1) is a carbohydrate-binding protein that has been proposed to be a selective autophagy receptor for glycogen. Here, we show that mouse Stbd1 is a transmembrane endoplasmic reticulum (ER)-resident protein with the capacity to induce the formation of organized ER structures in HeLa cells. In addition to bulk ER, Stbd1 was found to localize to mitochondria-associated membranes (MAMs), which represent regions of close apposition between the ER and mitochondria. We demonstrate that N-myristoylation and binding of Stbd1 to glycogen act as major determinants of its subcellular targeting. Moreover, overexpression of non-myristoylated Stbd1 enhanced the association between ER and mitochondria, and further induced prominent mitochondrial fragmentation and clustering. Conversely, shRNA-mediated Stbd1 silencing resulted in an increase in the spacing between ER and mitochondria, and an altered morphology of the mitochondrial network, suggesting elevated fusion and interconnectivity of mitochondria. Our data unravel the molecular mechanism underlying Stbd1 subcellular targeting, support and expand its proposed function as a selective autophagy receptor for glycogen and uncover a new role for the protein in the physical association between ER and mitochondria

Intrinsic flexibility of the EMT zeolite framework under pressure

The roles of organic additives in the assembly and crystallisation of zeolites are still not fully understood. This is important when attempting to prepare novel frameworks to produce new zeolites. We consider 18-crown-6 ether (18C6) as an additive, which has previously been shown to differentiate between the zeolite EMC-2 (EMT) and faujasite (FAU) frameworks. However, it is unclear whether this distinction is dictated by influences on the metastable free-energy landscape or geometric templating. Using high-pressure synchrotron X-ray diffraction, we have observed that the presence of 18C6 does not impact the EMT framework flexibility—agreeing with our previous geometric simulations and suggesting that 18C6 does not behave as a geometric template. This was further studied by computational modelling using solid-state density-functional theory and lattice dynamics calculations. It is shown that the lattice energy of FAU is lower than EMT, but is strongly impacted by the presence of solvent/guest molecules in the framework. Furthermore, the EMT topology possesses a greater vibrational entropy and is stabilised by free energy at a finite temperature. Overall, these findings demonstrate that the role of the 18C6 additive is to influence the free energy of crystallisation to assemble the EMT framework as opposed to FAU

Pressure-induced symmetry changes in body-centred cubic zeolites

Previous work has shown a strong correlation between zeolite framework flexibility and the nature of structural symmetry and phase transitions. However, there is little experimental data regarding this relationship, in addition to how flexibility can be connected to the synthesis of these open framework materials. This is of interest for the synthesis of novel zeolites, which require organic additives to permutate the resulting geometry and symmetry of the framework. Here, we have used high pressure powder X-ray diffraction to study the three zeolites: Na-X, RHO and ZK-5, which can all be prepared using 18-crown-6 ether as an organic additive. We observe significant differences in how the occluded 18-crown-6 ether influences the framework flexibility – this being dependant on the geometry of the framework. We use these differences as an indicator to define the role of 18-crown-6 ether during zeolite crystallisation. Furthermore, in conjunction with previous work we predict that pressure-induced symmetry transitions are intrinsic to body-centred cubic zeolites. The high symmetry yields fewer degrees of freedom, meaning it is energetically favourable to lower the symmetry to facilitate further compression.Dataset for the article "Pressure-induced symmetry changes in body-centred cubic zeolites"This repository contains the data included in the article "Pressure-induced symmetry changes in body-centred cubic zeolites". The data consists of high pressure powder X-ray diffraction data collected at the ID15B beamline at the European Synchrotron Radiation Facility (ESRF).Cubic High-Pressure Repository.zi

Hybrid Genetic Bees Algorithm applied to Single Machine Scheduling with Earliness and Tardiness Penalties

This paper presents a hybrid Genetic-Bees Algorithm based optimised solution for the single machine scheduling problem. The enhancement of the Bees Algorithm (BA) is conducted using the Genetic Algorithm's (GA's) operators during the global search stage. The proposed enhancement aims to increase the global search capability of the BA gradually with new additions. Although the BA has very successful implementations on various type of optimisation problems, it has found that the algorithm suffers from weak global search ability which increases the computational complexities on NP-hard type optimisation problems e.g. combinatorial/permutational type optimisation problems. This weakness occurs due to using a simple global random search operation during the search process. To reinforce the global search process in the BA, the proposed enhancement is utilised to increase exploration capability by expanding the number of fittest solutions through the genetical variations of promising solutions. The hybridisation process is realised by including two strategies into the basic BA, named as â\u80\u9creinforced global searchâ\u80\u9d and â\u80\u9cjumping functionâ\u80\u9d strategies. The reinforced global search strategy is the first stage of the hybridisation process and contains the mutation operator of the GA. The second strategy, jumping function strategy, consists of four GA operators as single point crossover, multipoint crossover, mutation and randomisation. To demonstrate the strength of the proposed solution, several experiments were carried out on 280 well-known single machine benchmark instances, and the results are presented by comparing to other well-known heuristic algorithms. According to the experiments, the proposed enhancements provides better capability to basic BA to jump from local minima, and GBA performed better compared to BA in terms of convergence and the quality of results. The convergence time reduced about 60% with about 30% better results for highly constrained jobs

A comparison of methods for studying the tumor microenvironment's spatial heterogeneity in digital pathology specimens

This study was supported by Lothian University Hospitals, Medical Research Scotland and Indica Labs, Inc. Indica Labs, Inc. also provided in-kind resource.Background: The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer. However, the significance of the intra-tumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intra-tumoral heterogeneity may aid the understanding of the TIME’s effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment. Methods: In this study we propose and apply two spatial statistical methodologies for the evaluation of the intra-tumor heterogeneity present in the distribution of CD3+ and CD8+ lymphocytes and tumor buds in 232 stage II colorectal cancer cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the inter-patient heterogeneity and the intra-tumor heterogeneity, was further developed. Results: Resultant data from each analysis, characterizing the spatial intra-tumor heterogeneity of lymphocytes and tumor buds, were used for the development of two new highly prognostic risk models. Conclusions: Our results highlight the value of applying spatial statistics for the assessment of the intra-tumor heterogeneity. Both Getis-Ord hotspot and our proposed Spatial Heatmap analysis are broadly applicable across other tissue types as well as other features of interest.Publisher PDFPeer reviewe