Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers

Background

Lung epithelial lining fluid (ELF)—sampled through sputum induction—is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

Objectives

To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

Methods

Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

Results

The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

Conclusions

We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

     

Uric acid levels are associated with endothelial dysfunction and severity of coronary atherosclerosis during a first episode of acute coronary syndrome

The role of serum uric acid in coronary artery disease has been extensively investigated. It was suggested that serum uric acid level (SUA) is an independent predictor of endothelial dysfunction and related to coronary artery lesions. However, the relationship between SUA and severity of coronary atherosclerosis evaluated via endothelial dysfunction using peripheral arterial tone (PAT) and the reactive hyperhemia index (RHI) has not been investigated during a first episode of acute coronary syndrome (ACS). The aim of our study was to address this point. We prospectively enrolled 80 patients with a first episode of ACS in a single-center observational study. All patients underwent coronary angiography, evaluation of endothelial function via the RHI, and SUA measurement. The severity of the coronary artery lesion was assessed angiographically, and patients were classified in three groups based on the extent of disease and Gensini and SYNTAX scores. Endothelial function was considered abnormal if RHI?<?1.67. We identified a linear correlation between SUA and RHI (R² =?0.66 P <?0.001). In multivariable analyses, SUA remained associated with RHI, even after adjustment for traditional cardiovascular risk factors and renal function. SUA was associated with severity of coronary artery disease. SUA is associated with severity of coronary atherosclerosis in patients with asymptomatic hyperuricemia. This inexpensive, readily measured biological parameter may be useful to monitor ACS patients.     

ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling

Species distribution modeling is a valuable tool with many applications across ecology and evolutionary biology. The selection of biologically meaningful environmental variables that determine relative habitat suitability is a crucial aspect of the modeling pipeline. The 19 bioclimatic variables from WorldClim are frequently employed, primarily because they are easily accessible and available globally for past, present and future climate scenarios. Yet, the availability of relatively few other comparable environmental datasets potentially limits our ability to select appropriate variables that will most successfully characterize a species’ distribution. We identified a set of 16 climatic and two topographic variables in the literature, which we call the ENVIREM dataset, many of which are likely to have direct relevance to ecological or physiological processes determining species distributions. We generated this set of variables at the same resolutions as WorldClim, for the present, mid‐Holocene, and Last Glacial Maximum (LGM). For 20 North American vertebrate species, we then assessed whether including the ENVIREM variables led to improved species distribution models compared to models using only the existing WorldClim variables. We found that including the ENVIREM dataset in the pool of variables to select from led to substantial improvements in niche modeling performance in 13 out of 20 species. We also show that, when comparing models constructed with different environmental variables, differences in projected distributions were often greater in the LGM than in the present. These variables are worth consideration in species distribution modeling applications, especially as many of the variables have direct links to processes important for species ecology. We provide these variables for download at multiple resolutions and for several time periods at envirem.github.io. Furthermore, we have written the ‘envirem’ R package to facilitate the generation of these variables from other input datasets.     

The Compensatory Immune-Regulatory Reflex System (CIRS) in Depression and Bipolar Disorder

Here, we review a novel concept namely the compensatory immune-regulatory reflex system (CIRS) as applied to the pathophysiology of major depressive disorder (MDD) and bipolar disorder (BD). There is evidence that a substantial subset of individuals with MDD and BD exhibit an activation of the immune-inflammatory response system (IRS), as indicated by an increased production of macrophagic M1 and T helper (Th)-1 pro-inflammatory cytokines, interleukin (IL)-6 trans-signaling, positive acute phase proteins (APPs), and complement factors. These immune aberrations appear to be evident during the course of major affective episodes of either depressive or (hypo) manic polarity. Here, we review (a) the current state of the art of CIRS functions in both mood disorders and (b) the possible role of CIRS-related biomarkers for the understanding of affective disorders within the framework of precision psychiatry that could also provide novel drug targets for both MDD and BD. CIRS-related abnormalities in mood disorders include elevated Th-2 and T regulatory (Treg) activities with increased IL-4 and IL-10 production, classical IL-6 signaling, increased levels of sIL-1R antagonist (sIL-1RA), soluble IL-2 (sIL-2R) and tumor necrosis factor–α- receptors, and positive APPs, including haptoglobin, hemopexin, α1-acid glycoprotein, α1-antitrypsin, and ceruloplasmin. It is concluded that CIRS is involved in MDD and BD by regulating the primary immune-inflammatory response, thereby contributing to spontaneous and antidepressant-promoted recovery from the acute phase of illness. Signs of activated IRS and CIRS pathways are observed in the remitted phases of both disorders indicating that there is no return to the original homeostasis after an acute episode, while later episodes of mood disorders are characterized by sensitized IRS and CIRS responses. New z-unit weighted composite biomarker scores are proposed, which reflect different aspects of IRS versus CIRS activation and may be used to estimate different IRS/CIRS activity ratios in mood and other neuroimmune disorders.     

Benzofuro[3,2-d]pyrimidines inspired from cercosporamide CaPkc1 inhibitor: Synthesis and evaluation of fluconazole susceptibility restoration

In a context of growing resistance to classical antifungal therapy, the design of new drugs targeting alternative pathways is highly expected. Benzofuro[3,2-d]pyrimidine derivatives, derived from (?)-cercosporamide, were synthesized and evaluated as potential Candida albicans PKC inhibitors in the aim of restoring susceptibility to azole treatment. Co-administration assay of benzofuropyrimidinedione 23 and fluconazole highlighted a synergistic effect on inhibition of cell growth of a Candida albicans resistant strain.     

Uncertainty analysis in LCA using precalculated aggregated datasets

Purpose

Some LCA software tools use precalculated aggregated datasets because they make LCA calculations much quicker. However, these datasets pose problems for uncertainty analysis. Even when aggregated dataset parameters are expressed as probability distributions, each dataset is sampled independently. This paper explores why independent sampling is incorrect and proposes two techniques to account for dependence in uncertainty analysis. The first is based on an analytical approach, while the other uses precalculated results sampled dependently.

Methods

The algorithm for generating arrays of dependently presampled aggregated inventories and their LCA scores is described. These arrays are used to calculate the correlation across all pairs of aggregated datasets in two ecoinvent LCI databases (2.2, 3.3 cutoff). The arrays are also used in the dependently presampled approach. The uncertainty of LCA results is calculated under different assumptions and using four different techniques and compared for two case studies: a simple water bottle LCA and an LCA of burger recipes.

Results and discussion

The meta-analysis of two LCI databases shows that there is no single correct approximation of correlation between aggregated datasets. The case studies show that the uncertainty of single-product LCA using aggregated datasets is usually underestimated when the correlation across datasets is ignored and that the magnitude of the underestimation is dependent on the system being analysed and the LCIA method chosen. Comparative LCA results show that independent sampling of aggregated datasets drastically overestimates the uncertainty of comparative metrics. The approach based on dependently presampled results yields results functionally identical to those obtained by Monte Carlo analysis using unit process datasets with a negligible computation time.

Conclusions

Independent sampling should not be used for comparative LCA. Moreover, the use of a one-size-fits-all correction factor to correct the calculated variability under independent sampling, as proposed elsewhere, is generally inadequate. The proposed approximate analytical approach is useful to estimate the importance of the covariance of aggregated datasets but not for comparative LCA. The approach based on dependently presampled results provides quick and correct results and has been implemented in EcodEX, a streamlined LCA software used by Nestlé. Dependently presampled results can be used for streamlined LCA software tools. Both presampling and analytical solutions require a preliminary one-time calculation of dependent samples for all aggregated datasets, which could be centrally done by database providers. The dependent presampling approach can be applied to other aspects of the LCA calculation chain.

     

Is non‐host pollen suitable for generalist bumblebees?

Current evidence suggests that pollen is both chemically and structurally protected. Despite increasing interest in studying bee–flower networks, the constraints for bee development related to pollen nutritional content, toxicity and digestibility as well as their role in the shaping of bee–flower interactions have been poorly studied. In this study we combined bioassays of the generalist bee Bombus terrestris on pollen of Cirsium, Trifolium, Salix, and Cistus genera with an assessment of nutritional content, toxicity, and digestibility of pollen. Microcolonies showed significant differences in their development, non‐host pollen of Cirsium being the most unfavorable. This pollen was characterized by the presence of quite rare δ7‐sterols and a low digestibility. Cirsium consumption seemed increase syrup collection, which is probably related to a detoxification mixing behavior. These results strongly suggest that pollen traits may act as drivers of plant selection by bees and partly explain why Asteraceae pollen is rare in bee generalist diet.