A Gas Sensor for the Selective Detection of Volatile Organic Compounds

Volatile Organic Compounds (VOCs) are an important class of air pollutant because many of them are harmful to human health. VOCs are typically present at very low concentrations – parts-per-billion (ppb) and lower – which makes their detection a significant challenge. Standard measurement techniques, such as Gas Chromatography (GC), are typically sensitive and selective, but are limited by their large size, high cost and complexity to operate. Such factors restrict deployment for practical applications, including measurement across air quality networks. In contrast, gas sensors are typically small, inexpensive and easily deployed, but are limited by poor selectivity. This work aims to establish the extent to which gas sensors can be used to achieve sensitive and selective detection of VOCs. Based on the processes of adsorption and desorption, it examines how temperature control of functionalised silica adsorbents can be used to produce discriminable signals of VOCs. In this context, the VOCs of interest were benzene, toluene, ethyl benzene, para-xylene (BTEX), due to their proven toxicity and prevalence in human environments. With the aim of producing a potentially deployable device, a novel sensing platform was designed and constructed. The main features of this Adsorption Device were an aluminium channel, a peltier module heating unit, flow path control and photoionisation detector (PID). In addition to unmodified silica, this thesis presents six modified silica adsorbents with amino, chloro, (n8) alkyl, fluoroalkyl, phenyl and chlorophenyl functionality. Analysis of BTEX vapours with the seven silica adsorbents indicated adsorption was physical (physisorption) and desorption was readily reversible between 25 and 100 °C. Adsorption was influenced by the strength of adsorbent-vapour interaction, which could be increased by introducing delocalised electron density (phenyl and chlorophenyl silica), but modification could not compensate for any significant loss of surface area and pore volume that occurred. PID responses during adsorption and desorption were found to be discriminable from each other. Vapour desorption was examined with different heating profiles, which were found to initiate distinct response patterns. Principle Component Analysis (PCA) of Adsorption Device data indicated that the responses were sufficiently discriminable that they could be offer a means of vapour selectivity. Tests of the Adsorption Device indicate that selective detection of individual and dual component BTEX vapours is achievable in the ppb concentration range and with a cycle time of 10 minutes. Classification algorithms based on the Adsorption Device output were found to be at least as accurate as previously published research. This work presents significant progress towards to the development of a selective and practical sensor for air quality applications

OptiJ: Open-source optical projection tomography of large organ samples

Abstract: The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples

OptiJ: Open-source optical projection tomography of large organ samples

The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples

Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Correction: genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

[This corrects the article on p. e13950 in vol. 5.]. Background: Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings: We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance: Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

A novel Alzheimer disease locus located near the gene encoding tau protein

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordAPOE ε4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ε4+ (10 352 cases and 9207 controls) and APOE ε4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ε4 status. Suggestive associations (P<1 × 10-4) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ε4+: 1250 cases and 536 controls; APOE ε4-: 718 cases and 1699 controls). Among APOE ε4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10-9). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ε4+ subjects (CR1 and CLU) or APOE ε4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10-7) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P≤1.3 × 10-8), frontal cortex (P≤1.3 × 10-9) and temporal cortex (P≤1.2 × 10-11). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10-6) and temporal cortex (P=2.6 × 10-6). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ε4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted

Skeletal muscle – A bystander or influencer of metabolic syndrome?

Background and aims: Metabolic syndrome is the concurrent presentation of multiple cardiovascular risk factors, including obesity, insulin resistance, hyperglycemia, dyslipidemia and hypertension. It has been suggested that some of these risk factors can have detrimental effects on the skeletal muscle while others can be a direct result of skeletal muscle abnormalities, showing a two-way directionality in the pathogenesis of the condition. This review aims to explore this bidirectional correlation by discussing the impact of metabolic syndrome on skeletal muscle tissue in general and will also discuss ways in which skeletal muscle alterations may contribute to the pathogenesis of metabolic syndrome. Methods: Literature searches were conducted with key words (e.g. metabolic syndrome, skeletal muscle, hyperglycemia) using PubMed, EBSCOhost, Science Direct and Google Scholar. All article types were included in the search. Results: The pathological mechanisms associated with metabolic syndrome, such as hyperglycemia and inflammation, have been associated with changes in skeletal muscle fiber composition, metabolism, insulin sensitivity, mitochondrial function, and strength. Additionally, some skeletal muscle alterations, particularly mitochondrial dysfunction and insulin resistance, are suggested to contribute to the development of metabolic syndrome. For example, the suggested underlying mechanisms of sarcopenia development are also contributors to metabolic syndrome pathogenesis. Conclusion: Whilst numerous studies have identified a relationship between metabolic syndrome and skeletal muscle abnormalities, further investigation into the underlying mechanisms is needed to elucidate the best prevention and management strategies for these conditions