Quantification of structural changes in the corpus callosumin children with profound hypoxic-ischaemic brain injury

Background Birth-related acute profound hypoxic–ischaemic brain injury has specific patterns of damage including the paracentral lobules. Objective To test the hypothesis that there is anatomically coherent regional volume loss of the corpus callosum as a result of this hemispheric abnormality. Materials and methods Study subjects included 13 children with proven acute profound hypoxic–ischaemic brain injury and 13 children with developmental delay but no brain abnormalities. A computerised system divided the corpus callosum into 100 segments, measuring each width. Principal component analysis grouped the widths into contiguous anatomical regions. We conducted analysis of variance of corpus callosum widths as well as support vector machine stratification into patient groups. Results There was statistically significant narrowing of the mid–posterior body and genu of the corpus callosum in children with hypoxic–ischaemic brain injury. Support vector machine analysis yielded over 95% accuracy in patient group stratification using the corpus callosum centile widths. Conclusion Focal volume loss is seen in the corpus callosum of children with hypoxic–ischaemic brain injury secondary to loss of commissural fibres arising in the paracentral lobules. Support vector machine stratification into the hypoxic–ischaemic brain injury group or the control group on the basis of corpus callosum width is highly accurate and points towards rapid clinical translation of this technique as a potential biomarker of hypoxic–ischaemic brain injur

Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies

Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC–MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC–MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC–MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and five quality control (QC) samples prepared from the study samples) were measured with GC × GC–MS and GC–MS to study the development and progression of insulin resistance, a primary characteristic of diabetes type 2. A total of 170 and 691 peaks were quantified in, respectively, the GC–MS and GC × GC–MS data for all study and QC samples. The quantitative results for the QC samples were compared to assess the quality of semi-automated GC × GC–MS processing compared to targeted GC–MS processing which involved time-consuming manual correction of all wrongly integrated metabolites and was considered as golden standard. The relative standard deviations (RSDs) obtained with GC × GC–MS were somewhat higher than with GC–MS, due to less accurate processing. Still, the biological information in the study samples was preserved and the added value of GC × GC–MS was demonstrated; many additional candidate biomarkers were found with GC × GC–MS compared to GC–MS

Genetic Polymorphisms in the Hypothalamic Pathway in Relation to Subsequent Weight Change – The DiOGenes Study

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes encoding the components involved in the hypothalamic pathway may influence weight gain and dietary factors may modify their effects. AIM: We conducted a case-cohort study to investigate the associations of SNPs in candidate genes with weight change during an average of 6.8 years of follow-up and to examine the potential effect modification by glycemic index (GI) and protein intake. METHODS AND FINDINGS: Participants, aged 20-60 years at baseline, came from five European countries. Cases ('weight gainers') were selected from the total eligible cohort (n = 50,293) as those with the greatest unexplained annual weight gain (n = 5,584). A random subcohort (n = 6,566) was drawn with the intention to obtain an equal number of cases and noncases (n = 5,507). We genotyped 134 SNPs that captured all common genetic variation across the 15 candidate genes; 123 met the quality control criteria. Each SNP was tested for association with the risk of being a 'weight gainer' (logistic regression models) in the case-noncase data and with weight gain (linear regression models) in the random subcohort data. After accounting for multiple testing, none of the SNPs was significantly associated with weight change. Furthermore, we observed no significant effect modification by dietary factors, except for SNP rs7180849 in the neuromedin β gene (NMB). Carriers of the minor allele had a more pronounced weight gain at a higher GI (P = 2 x 10⁻⁷). CONCLUSIONS: We found no evidence of association between SNPs in the studied hypothalamic genes with weight change. The interaction between GI and NMB SNP rs7180849 needs further confirmation

The role of leptin in the respiratory system: an overview

Since its cloning in 1994, leptin has emerged in the literature as a pleiotropic hormone whose actions extend from immune system homeostasis to reproduction and angiogenesis. Recent investigations have identified the lung as a leptin responsive and producing organ, while extensive research has been published concerning the role of leptin in the respiratory system. Animal studies have provided evidence indicating that leptin is a stimulant of ventilation, whereas researchers have proposed an important role for leptin in lung maturation and development. Studies further suggest a significant impact of leptin on specific respiratory diseases, including obstructive sleep apnoea-hypopnoea syndrome, asthma, COPD and lung cancer. However, as new investigations are under way, the picture is becoming more complex. The scope of this review is to decode the existing data concerning the actions of leptin in the lung and provide a detailed description of leptin's involvement in the most common disorders of the respiratory system

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS