14 research outputs found
In situ strain & cure monitoring in liquid composite moulding by fibre Bragg grating sensors
No full textStructural Integrity & CompositesAerospace Engineerin
Impact drugs targeting cardiometabolic risk on the gut microbiota
No full textPURPOSE OF REVIEW: Alterations in the gut microbiome composition or function are associated with risk factors for cardiometabolic diseases, including hypertension, hyperlipidemia and hyperglycemia. Based on recent evidence that also oral medications used to treat these conditions could alter the gut microbiome composition and function and, vice versa, that the gut microbiome could affect the efficacy of these treatments, we reviewed the literature on these observed interactions. RECENT FINDINGS: While the interaction of metformin with the gut microbiome has been studied most, other drugs that target cardiometabolic risk are gaining attention and often showed associations with alterations in microbiome-related features, including alterations in specific microbial taxa or pathways, microbiome composition or microbiome-derived metabolites, while the gut microbiome was also involved in drug metabolism and drug efficacy. As for metformin, for some of them even a potential therapeutic effect via the gut microbiome is postulated. However, exact mechanisms remain to be elucidated. SUMMARY: There is growing interest in clarifying the interactions between the gut microbiome and drugs to treat hypertension, hyperlipidemia and hyperglycemia as well as the first pass effect of microbiome on drug efficacy. While mostly analysed in animal models, also human studies are gaining more and more traction. Improving the understanding of the gut microbiome drug interaction can provide clinical directions for therapy by optimizing drug efficacy or providing new targets for drug development
Analyzing Type 2 Diabetes Associations with the Gut Microbiome in Individuals from Two Ethnic Backgrounds Living in the Same Geographic Area
No full textInternational audienceIt is currently unknown whether associations between gut microbiota composition and type 2 diabetes (T2D) differ according to the ethnic background of individuals. Thus, we studied these associations in participants from two ethnicities characterized by a high T2D prevalence and living in the same geographical area, using the Healthy Life In Urban Settings (HELIUS) study. We included 111 and 128 T2D participants on metformin (Met-T2D), 78 and 49 treatment-naïve T2D (TN-T2D) participants, as well as a 1:1 matched group of healthy controls from, respectively, African Surinamese and South-Asian Surinamese descent. Fecal microbiome profiles were obtained through 16S rRNA gene sequencing. Univariate and machine learning analyses were used to explore the associations between T2D and the composition and function of the gut microbiome in both ethnicities, comparing Met-T2D and TN-T2D participants to their respective healthy control. We found a lower α-diversity for South-Asian Surinamese TN-T2D participants but no significant associations between TN-T2D status and the abundance of bacterial taxa or functional pathways. In African Surinamese participants, we did not find any association between TN-T2D status and the gut microbiome. With respect to Met-T2D participants, we identified several bacterial taxa and functional pathways with a significantly altered abundance in both ethnicities. More alterations were observed in South-Asian Surinamese. Some altered taxa and pathways observed in both ethnicities were previously related to metformin use. This included a strong negative association between the abundance of Romboutsia and Met-T2D status. Other bacterial taxa were consistent with previous observations in T2D, including reduced butyrate producers such as Anaerostipes hadrus. Hence, our results highlighted both shared and unique gut microbial biomarkers of Met-T2D in individuals from different ethnicities but living in the same geographical area. Future research using higher-resolution shotgun sequencing is needed to clarify the role of ethnicity in the association between T2D and gut microbiota composition
Momentum Effects and Mean Reversion in Real Estate Securities
No full textThis article is the winner of the International Real Estate Investment/ Portfolio Management manuscript prize (sponsored by LaSalle Investment Management) presented at the American Real Estate Society Annual Meeting. This article tests for the presence of both price continuation and price reversals in international real estate securities. The results reveal evidence of performance persistence in international markets over short and medium term horizons, however the evidence on price reversals is less compelling. The empirical analysis tests for mean reversion using Variance Ratio and Augmented Dickey-Fuller tests. In neither case is there consistent evidence of mean reversion in international real estate securities. The portfolio switching tests do reveal some evidence of performance reversals. However, while under-performing markets do outperform over longer horizons, they do not do so at statistically significant levels.
Proteome2virus: Shotgun mass spectrometry data analysis pipeline for virus identification
No full textObjectives: Shotgun proteomics is a generic method enabling detection of multiple viral species in one assay. The reliable and accurate identification of these viral species by analyzing peptides from MS-spectra is a challenging task. The aim of this study was to develop an easy accessible proteome analysis approach for the identification of viruses that cause respiratory and gastrointestinal infections. Methods: For this purpose, a shotgun proteomics based method and a web application, ‘proteome2virus’, were developed. Identified peptides were searched in a database comprising proteomic data of 46 viruses known to be infectious to humans. Results: The method was successfully tested for cultured viruses and eight fecal samples consisting of ten different viral species from seven different virus families, including SARS-CoV-2. The samples were prepared with two different sample preparation methods and were measured with two different mass spectrometers. Conclusions: The results demonstrate that the developed web application is applicable to different MS data sets, generated from two different instruments, and that with this approach a high variety of clinically relevant viral species can be identified. This emphasizes the potential and feasibility for the diagnosis of a wide range of viruses in clinical samples with a single shotgun proteomics analysis
Additional file 1 of Ethnic variations in metabolic syndrome components and their associations with the gut microbiota: the HELIUS study
No full textAdditional file 1: Fig S1-S8. PDF file with all supplementary figures S1-S8 and corresponding figure legends
Proteome2virus: Shotgun mass spectrometry data analysis pipeline for virus identification
No full textObjectives: Shotgun proteomics is a generic method enabling detection of multiple viral species in one assay. The reliable and accurate identification of these viral species by analyzing peptides from MS-spectra is a challenging task. The aim of this study was to develop an easy accessible proteome analysis approach for the identification of viruses that cause respiratory and gastrointestinal infections. Methods: For this purpose, a shotgun proteomics based method and a web application, ‘proteome2virus’, were developed. Identified peptides were searched in a database comprising proteomic data of 46 viruses known to be infectious to humans. Results: The method was successfully tested for cultured viruses and eight fecal samples consisting of ten different viral species from seven different virus families, including SARS-CoV-2. The samples were prepared with two different sample preparation methods and were measured with two different mass spectrometers. Conclusions: The results demonstrate that the developed web application is applicable to different MS data sets, generated from two different instruments, and that with this approach a high variety of clinically relevant viral species can be identified. This emphasizes the potential and feasibility for the diagnosis of a wide range of viruses in clinical samples with a single shotgun proteomics analysis
Stock return, risk and asset pricing
No full textThis thesis attempts to address a number of issues that have been identified in the asset pricing literature as essential for shaping stock returns. These issues include the need to uncover the link between the macroeconomic variables and stock returns. In addition to this, is the need to decide, in light of the findings of the literature, whether to advise investors to include idiosyncratic risk and downside risk as risk factors in their asset pricing models. The results presented here suggest, consistent with other previous studies, that stock returns are a function of a number of previously identified risk factors along with the wider set of macroeconomic variables. These macroeconomic variables could be represented by a number of estimated macro factors. However, only one of these estimated factors emerged as significant in explaining the cross-section of stock returns. Nevertheless, it is important to note that the size (SMB) and value (HML) factors remain important factors in explaining the cross sectional returns on UK stocks, even with the existence of the other risk factors. This finding of inability of the examined macroeconomic variables to capture the pricing power of the SMB and the HML may cast doubt on the possibility of finding more macroeconomic factors that are able to account for these two factors in the cross section of returns in the UK. Interestingly, this conclusion seems to contradict previous authors' findings of potential links in the UK market. The results also support past studies that find that downside risk is an important risk factor and by allowing the downside risk premium to vary with business cycle conditions, downside risk might be a better measure of risk than market risk. Nevertheless, this thesis shows that although this finding is applicable in times of economic expansion, during recession, there is no conclusive relationship between . downside risk and stock returns. Furthermore, this thesis supports the studies which find that idiosyncratic risk is not significant in pricing stocks. However in contrast to other studies, it reveals this by showing that time-varying risk could be the reason behind the potentially illusive findings of idiosyncratic risk effect. This thesis confirms that, for London Stock Exchange investors, macroeconomic variables should never be overlooked when estimating stock returns and downside risk could be an influential risk factor
Intronic variant screening with targeted next-generation sequencing reveals first pseudoexon in LDLR in familial hypercholesterolemia
No full textBackground and aims: Familial hypercholesterolemia (FH) is caused by pathogenic variants in LDLR, APOB, or PCSK9 genes (designated FH+). However, a significant number of clinical FH patients do not carry these variants (designated FH-). Here, we investigated whether variants in intronic regions of LDLR attribute to FH by affecting pre-mRNA splicing. Methods: LDLR introns are partly covered in routine sequencing of clinical FH patients using next-generation sequencing. Deep intronic variants, >20 bp from intron-exon boundary, were considered of interest once (a) present in FH- patients (n = 909) with LDL-C >7 mmol/L (severe FH-) or after in silico analysis in patients with LDL-C >5 mmol/L (moderate FH-) and b) absent in FH + patients (control group). cDNA analysis and co-segregation analysis were performed to assess pathogenicity of the identified variants. Results: Three unique variants were present in the severe FH- group. One of these was the previously described likely pathogenic variant c.2140+103G>T. Three additional variants were selected based on in silico analyses in the moderate FH- group. One of these variants, c.2141-218G>A, was found to result in a pseudo-exon inclusion, producing a premature stop codon. This variant co-segregated with the hypercholesterolemic phenotype. Conclusions: Through a screening approach, we identified a deep intronic variant causal for FH. This finding indicates that filtering intronic variants in FH- patients for the absence in FH + patients might enrich for true FH-causing variants and suggests that intronic regions of LDLR need to be considered for sequencing in FH- patients
