The impact of using combinatorial optimisation for static caching of posting lists

Abstract. Caching posting lists can reduce the amount of disk I/O required to evaluate a query. Current methods use optimisation proce-dures for maximising the cache hit ratio. A recent method selects posting lists for static caching in a greedy manner and obtains higher hit rates than standard cache eviction policies such as LRU and LFU. However, a greedy method does not formally guarantee an optimal solution. We investigate whether the use of methods guaranteed, in theory, to find an approximately optimal solution would yield higher hit rates. Thus, we cast the selection of posting lists for caching as an integer linear pro-gramming problem and perform a series of experiments using heuristics from combinatorial optimisation (CCO) to find optimal solutions. Using simulated query logs we find that CCO yields comparable results to a greedy baseline using cache sizes between 200 and 1000 MB, with modest improvements for queries of length two to three

Engineering periplasmic ligand binding proteins as glucose nanosensors

Diabetes affects over 100 million people worldwide. Better methods for monitoring blood glucose levels are needed for improving disease management. Several labs have previously made glucose nanosensors by modifying members of the periplasmic ligand binding protein superfamily. This minireview summarizes recent developments in constructing new versions of these proteins that are responsive within the physiological range of blood glucose levels, employ new reporter groups, and/or are more robust. These experiments are important steps in the development of novel proteins that have the characteristics needed for an implantable glucose nanosensor for diabetes management: specificity for glucose, rapid response, sensitivity within the physiological range of glucose concentrations, reproducibility, and robustness

Six-year follow-up of slaughterhouse surveillance (2008-2013): the Catalan Slaughterhouse Support Network (SESC)

Meat inspection has the ultimate objective of declaring the meat and offal obtained from carcasses of slaughtered animals fit or unfit for human consumption. This safeguards the health of consumers by ensuring that the food coming from these establishments poses no risk to public health. Concomitantly, it contributes to animal disease surveillance. The Catalan Public Health Protection Agency (Generalitat de Catalunya) identified the need to provide its meat inspectors with a support structure to improve diagnostic capacity: the Slaughterhouse Support Network (SESC). The main goal of the SESC was to offer continuing education to meat inspectors to improve the diagnostic capacity for lesions observed in slaughterhouses. With this aim, a web-based application was designed that allowed meat inspectors to submit their inquiries, images of the lesions, and samples for laboratory analysis. This commentary reviews the cases from the first 6 years of SESC operation (2008–2013). The program not only provides continuing education to inspectors but also contributes to the collection of useful information on animal health and welfare. Therefore, SESC complements animal disease surveillance programs, such as those for tuberculosis, bovine cysticercosis, and porcine trichinellosis, and is a powerful tool for early detection of emerging animal diseases and zoonoses

Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson's disease and schizophrenia

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided

Glucocorticoids in T cell apoptosis and function

Glucocorticoids (GCs) are a class of steroid hormones which regulate a variety of essential biological functions. The profound anti-inflammatory and immunosuppressive activity of synthetic GCs, combined with their power to induce lymphocyte apoptosis place them among the most commonly prescribed drugs worldwide. Endogenous GCs also exert a wide range of immunomodulatory activities, including the control of T cell homeostasis. Most, if not all of these effects are mediated through the glucocorticoid receptor, a member of the nuclear receptor superfamily. However, the signaling pathways and their cell type specificity remain poorly defined. In this review, we summarize our present knowledge on GC action, the mechanisms employed to induce apoptosis and the currently discussed models of how they may participate in thymocyte development. Although our knowledge in this field has substantially increased during recent years, we are still far from a comprehensive picture of the role that GCs play in T lymphocytes

Mitochondria function associated genes contribute to Parkinson's Disease risk and later age at onset

Mitochondrial dysfunction has been implicated in the etiology of monogenic Parkinson’s disease (PD). Yet the role that mitochondrial processes play in the most common form of the disease; sporadic PD, is yet to be fully established. Here, we comprehensively assessed the role of mitochondrial function-associated genes in sporadic PD by leveraging improvements in the scale and analysis of PD GWAS data with recent advances in our understanding of the genetics of mitochondrial disease. We calculated a mitochondrial-specific polygenic risk score (PRS) and showed that cumulative small effect variants within both our primary and secondary gene lists are significantly associated with increased PD risk. We further reported that the PRS of the secondary mitochondrial gene list was significantly associated with later age at onset. Finally, to identify possible functional genomic associations we implemented Mendelian randomization, which showed that 14 of these mitochondrial functionassociated genes showed functional consequence associated with PD risk. Further analysis suggested that the 14 identified genes are not only involved in mitophagy, but implicate new mitochondrial processes. Our data suggests that therapeutics targeting mitochondrial bioenergetics and proteostasis pathways distinct from mitophagy could be beneficial to treating the early stage of PD

Parkinson’s disease mouse models in translational research

Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson’s disease (PD), the higher is the predictive value for clinical trials. An ideal PD model should present behavioral signs and pathology that resemble the human disease. The increasing understanding of PD stratification and etiology, however, complicates the choice of adequate animal models for preclinical studies. An ultimate mouse model, relevant to address all PD-related questions, is yet to be developed. However, many of the existing models are useful in answering specific questions. An appropriate model should be chosen after considering both the context of the research and the model properties. This review addresses the validity, strengths, and limitations of current PD mouse models for translational research

Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. / Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. / Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. / Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. / Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. / Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Yersinia enterocolitica Targets Cells of the Innate and Adaptive Immune System by Injection of Yops in a Mouse Infection Model

Yersinia enterocolitica (Ye) evades the immune system of the host by injection of Yersinia outer proteins (Yops) via a type three secretion system into host cells. In this study, a reporter system comprising a YopE-β-lactamase hybrid protein and a fluorescent staining sensitive to β-lactamase cleavage was used to track Yop injection in cell culture and in an experimental Ye mouse infection model. Experiments with GD25, GD25-β1A, and HeLa cells demonstrated that β1-integrins and RhoGTPases play a role for Yop injection. As demonstrated by infection of splenocyte suspensions in vitro, injection of Yops appears to occur randomly into all types of leukocytes. In contrast, upon infection of mice, Yop injection was detected in 13% of F4/80+, 11% of CD11c+, 7% of CD49b+, 5% of Gr1+ cells, 2.3% of CD19+, and 2.6% of CD3+ cells. Taking the different abundance of these cell types in the spleen into account, the highest total number of Yop-injected cells represents B cells, particularly CD19+CD21+CD23+ follicular B cells, followed by neutrophils, dendritic cells, and macrophages, suggesting a distinct cellular tropism of Ye. Yop-injected B cells displayed a significantly increased expression of CD69 compared to non-Yop-injected B cells, indicating activation of these cells by Ye. Infection of IFN-γR (receptor)- and TNFRp55-deficient mice resulted in increased numbers of Yop-injected spleen cells for yet unknown reasons. The YopE-β-lactamase hybrid protein reporter system provides new insights into the modulation of host cell and immune responses by Ye Yops