Fatty Acid Metabolites Combine with Reduced β Oxidation to Activate Th17 Inflammation in Human Type 2 Diabetes

Mechanisms that regulate metabolites and downstream energy generation are key determinants of T cell cytokine production, but the processes underlying the Th17 profile that predicts the metabolic status of people with obesity are untested. Th17 function requires fatty acid uptake, and our new data show that blockade of CPT1A inhibits Th17-associated cytokine production by cells from people with type 2 diabetes (T2D). A low CACT:CPT1A ratio in immune cells from T2D subjects indicates altered mitochondrial function and coincides with the preference of these cells to generate ATP through glycolysis rather than fatty acid oxidation. However, glycolysis was not critical for Th17 cytokines. Instead, β oxidation blockade or CACT knockdown in T cells from lean subjects to mimic characteristics of T2D causes cells to utilize 16C-fatty acylcarnitine to support Th17 cytokines. These data show long-chain acylcarnitine combines with compromised β oxidation to promote disease-predictive inflammation in human T2D. Although glycolysis generally fuels inflammation, Nicholas, Proctor, and Agrawal et al. report that PBMCs from subjects with type 2 diabetes use a different mechanism to support chronic inflammation largely independent of fuel utilization. Loss- and gain-of-function experiments in cells from healthy subjects show mitochondrial alterations combine with increases in fatty acid metabolites to drive chronic T2D-like inflammation

An APRI+ALBI Based Multivariable Model as Preoperative Predictor for Posthepatectomy Liver Failure.

OBJECTIVE AND BACKGROUND Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an APRI+ALBI, aspartate aminotransferase to platelet ratio (APRI) combined with albumin-bilirubin grade (ALBI), based multivariable model (MVM) to predict PHLF and compare its performance to indocyanine green clearance (ICG-R15 or ICG-PDR) and albumin-ICG evaluation (ALICE). METHODS 12,056 patients from the National Surgical Quality Improvement Program (NSQIP) database were used to generate a MVM to predict PHLF B+C. The model was determined using stepwise backwards elimination. Performance of the model was tested using receiver operating characteristic curve analysis and validated in an international cohort of 2,525 patients. In 620 patients, the APRI+ALBI MVM, trained in the NSQIP cohort, was compared with MVM's based on other liver function tests (ICG clearance, ALICE) by comparing the areas under the curve (AUC). RESULTS A MVM including APRI+ALBI, age, sex, tumor type and extent of resection was found to predict PHLF B+C with an AUC of 0.77, with comparable performance in the validation cohort (AUC 0.74). In direct comparison with other MVM's based on more expensive and time-consuming liver function tests (ICG clearance, ALICE), the APRI+ALBI MVM demonstrated equal predictive potential for PHLF B+C. A smartphone application for calculation of the APRI+ALBI MVM was designed. CONCLUSION Risk assessment via the APRI+ALBI MVM for PHLF B+C increases preoperative predictive accuracy and represents an universally available and cost-effective risk assessment prior to hepatectomy, facilitated by a freely available smartphone app

Synergistic integration of optical and microwave satellite data for crop yield estimation

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or descriptor. Our second approach avoids summarizing statistics and uses machine learning to combine full time series of EVI and VOD. This study considers two statistical methods, a regularized linear regressionand its nonlinear extension called kernel ridge regression to directly estimate the county-level surveyed total production, as well as individual yields of the major crops grown in the region: corn, soybean and wheat. The study area includes the US Corn Belt, and we use agricultural survey data from the National Agricultural Statistics Service (USDA-NASS) for year 2015 for quantitative assessment. Results show that (1) the proposed EVI-VOD lag metric correlates well with crop yield and outperforms common single-sensor metrics for crop yield estimation; (2) the statistical (machine learning) models working directly with the time series largely improve results compared to previously reported estimations; (3) the combined exploitation of information from the optical and microwave data leads to improved predictions over the use of single sensor approaches with coefficient of determination R 2 ≥ 0.76; (4) when models are used for within-season forecasting with limited time information, crop yield prediction is feasible up to four months before harvest (models reach a plateau in accuracy); and (5) the robustness of the approach is confirmed in a multi-year setting, reaching similar performances than when using single-year data. In conclusion, results confirm the value of using both EVI and VOD at the same time, and the advantage of using automatic machine learning models for crop yield/production estimation

Resistance to pirimiphos-methyl in West African Anopheles is spreading via duplication and introgression of the Ace1 locus

Publisher Copyright: © 2021 Grau-Bové et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A. coluzzii. A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1, provides the key resistance diagnostic in an A. coluzzii population from Côte d’Ivoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 substitution and duplications occur on a unique resistance haplotype that evolved in A. gambiae and introgressed into A. coluzzii, and is now common in West Africa primarily due to selection imposed by other organophosphate or carbamate insecticides. Our findings highlight the predictive value of this complex resistance haplotype for phenotypic resistance and clarify its evolutionary history, providing tools to for molecular surveillance of the current and future effectiveness of pirimiphos-methyl based interventions.publishersversionpublishe

Vascular Cellular Adhesion Molecule-1 (VCAM-1) Expression in Mice Retinal Vessels Is Affected by Both Hyperglycemia and Hyperlipidemia

BACKGROUND: Inflammation has been proposed to be important in the pathogenesis of diabetic retinopathy. An early feature of inflammation is the release of cytokines leading to increased expression of endothelial activation markers such as vascular cellular adhesion molecule-1 (VCAM-1). Here we investigated the impact of diabetes and dyslipidemia on VCAM-1 expression in mouse retinal vessels, as well as the potential role of tumor necrosis factor-α (TNFα). METHODOLOGY/PRINCIPAL FINDINGS: Expression of VCAM-1 was examined by confocal immunofluorescence microscopy in vessels of wild type (wt), hyperlipidemic (ApoE(-/-)) and TNFα deficient (TNFα(-/-), ApoE(-/-)/TNFα(-/-)) mice. Eight weeks of streptozotocin-induced diabetes resulted in increased VCAM-1 in wt mice, predominantly in small vessels (<10 µm). Diabetic wt mice had higher total retinal TNFα, IL-6 and IL-1β mRNA than controls; as well as higher soluble VCAM-1 (sVCAM-1) in plasma. Lack of TNFα increased higher basal VCAM-1 protein and sVCAM-1, but failed to up-regulate IL-6 and IL-1β mRNA and VCAM-1 protein in response to diabetes. Basal VCAM-1 expression was higher in ApoE(-/-) than in wt mice and both VCAM-1 mRNA and protein levels were further increased by high fat diet. These changes correlated to plasma cholesterol, LDL- and HDL-cholesterol, but not to triglycerides levels. Diabetes, despite further increasing plasma cholesterol in ApoE(-/-) mice, had no effects on VCAM-1 protein expression or on sVCAM-1. However, it increased ICAM-1 mRNA expression in retinal vessels, which correlated to plasma triglycerides. CONCLUSIONS/SIGNIFICANCE: Hyperglycemia triggers an inflammatory response in the retina of normolipidemic mice and up-regulation of VCAM-1 in retinal vessels. Hypercholesterolemia effectively promotes VCAM-1 expression without evident stimulation of inflammation. Diabetes-induced endothelial activation in ApoE(-/-) mice seems driven by elevated plasma triglycerides but not by cholesterol. Results also suggest a complex role for TNFα in the regulation of VCAM-1 expression, being protective under basal conditions but pro-inflammatory in response to diabetes

Dysregulated Expression of Both the Costimulatory CD28 and Inhibitory CTLA-4 Molecules in PB T Cells of Advanced Cervical Cancer Patients Suggests Systemic Immunosuppression Related to Disease Progression

Cervical cancer (CC) occurs more frequently in women who are immunosuppressed, suggesting that both local and systemic immune abnormalities may be involved in the evolution of the disease. Costimulatory CD28 and inhibitory CTLA-4 molecules expressed in T cells play a key role in the balanced immune responses. There has been demonstrated a relation between CD28, CTLA-4, and IFN genes in susceptibility to CC, suggesting their importance in CC development. Therefore, we assessed the pattern of CD28 and CTLA-4 expression in T cells from PB of CC patients with advanced CC (stages III and IV according to FIGO) compared to controls. We also examined the ability of PBMCs to secrete IFN-gamma. We found lower frequencies of freshly isolated and ex vivo stimulated CD4 + CD28+ and CD8 + CD28+ T cells in CC patients than in controls. Loss of CD28 expression was more pronounced in the CD8+ T subset. Markedly increased proportions of CTLA-4+ T cells in CC patients before and after culture compared to controls were also observed. In addition, patients’ T cells exhibited abnormal kinetics of surface CTLA-4 expression, with the peak at 24 h of stimulation, which was in contrast to corresponding normal T cells, revealing maximum CTLA-4 expression at 72 h of stimulation. Of note, markedly higher IFN-gamma concentrations were shown in supernatants of stimulated PBMCs from CC patients. Conclusions: Our report shows the dysregulated CD28 and CTLA-4 expression in PB T cells of CC patients, which may lead to impaired function of these lymphocytes and systemic immunosuppression related to disease progression

Targeted metatranscriptomics of compost derived consortia reveals a GH11 exerting an unusual exo-1,4-β-xylanase activity

Background: Using globally abundant crop residues as a carbon source for energy generation and renewable chemicals production stands out as a promising solution to reduce current dependency on fossil fuels. In nature, such as in compost habitats, microbial communities efficiently degrade the available plant biomass using a diverse set of synergistic enzymes. However, deconstruction of lignocellulose remains a challenge for industry due to recalcitrant nature of the substrate and the inefficiency of the enzyme systems available, making the economic production of lignocellulosic biofuels difficult. Metatranscriptomic studies of microbial communities can unveil the metabolic functions employed by lignocellulolytic consortia and identify new biocatalysts that could improve industrial lignocellulose conversion. Results: In this study, a microbial community from compost was grown in minimal medium with sugarcane bagasse sugarcane bagasse as the sole carbon source. Solid-state nuclear magnetic resonance was used to monitor lignocellulose degradation; analysis of metatranscriptomic data led to the selection and functional characterization of several target genes, revealing the first glycoside hydrolase from Carbohydrate Active Enzyme family 11 with exo-1,4-β-xylanase activity. The xylanase crystal structure was resolved at 1.76 Å revealing the structural basis of exo-xylanase activity. Supplementation of a commercial cellulolytic enzyme cocktail with the xylanase showed improvement in Avicel hydrolysis in the presence of inhibitory xylooligomers. Conclusions: This study demonstrated that composting microbiomes continue to be an excellent source of biotechnologically important enzymes by unveiling the diversity of enzymes involved in in situ lignocellulose degradation

Genome variation and population structure among 1142 mosquitoes of the African malaria vector species Anopheles gambiae and Anopheles coluzzii

Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with a high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high-quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii. We analyzed whole genomes of 1142 individual mosquitoes sampled from the wild in 13 African countries, as well as a further 234 individuals comprising parents and progeny of 11 laboratory crosses. The data resource includes high-confidence single-nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We use these data to analyze genetic population structure and characterize genetic diversity within and between populations. We illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance and for accelerating research and development of new vector control tools. It also provides a unique resource for the study of population genomics and evolutionary biology in eukaryotic species with high levels of genetic diversity under strong anthropogenic evolutionary pressures

An investigation into aripiprazole's partial D(2) agonist effects within the dorsolateral prefrontal cortex during working memory in healthy volunteers

Rationale: Working memory impairments in schizophrenia have been attributed to dysfunction of the dorsolateral prefrontal cortex (DLPFC) which in turn may be due to low DLPFC dopamine innervation. Conventional antipsychotic drugs block DLPFC D2 receptors, and this may lead to further dysfunction and working memory impairments. Aripiprazole is a D2 receptor partial agonist hypothesised to enhance PFC dopamine functioning, possibly improving working memory. Objectives: We probed the implications of the partial D2 receptor agonist actions of aripiprazole within the DLPFC during working memory. Investigations were carried out in healthy volunteers to eliminate confounds of illness or medication status. Aripiprazole’s prefrontal actions were compared with the D2/5-HT2A blocker risperidone to separate aripiprazole’s unique prefrontal D2 agonist actions from its serotinergic and striatal D2 actions that it shares with risperidone. Method: A double-blind, placebo-controlled, parallel design was implemented. Participants received a single dose of either 5 mg aripiprazole, 1 mg risperidone or placebo before performing the n-back task whilst undergoing fMRI scanning. Results: Compared with placebo, the aripiprazole group demonstrated enhanced DLPFC activation associated with a trend for improved discriminability (d’) and speeded reaction times. In contrast to aripiprazole’s neural effects, the risperidone group demonstrated a trend for reduced DLPFC recruitment. Unexpectedly, the risperidone group demonstrated similar effects to aripiprazole on d’ and additionally had reduced errors of commission compared with placebo. Conclusion: Aripiprazole has unique DLPFC actions attributed to its prefrontal D2 agonist action. Risperidone’s serotinergic action that results in prefrontal dopamine release may have protected against any impairing effects of its prefrontal D2 blockade

Gender-specific association of body composition with inflammatory and adipose-related markers in healthy elderly Europeans from the NU-AGE study

Objectives: The aim of this work was to examine the cross-sectional relationship between body composition (BC) markers for adipose and lean tissue and bone mass, and a wide range of specific inflammatory and adipose-related markers in healthy elderly Europeans. Methods: A whole-body dual-energy X-ray absorptiometry (DXA) scan was made in 1121 healthy (65–79 years) women and men from five European countries of the “New dietary strategies addressing the specific needs of elderly population for a healthy aging in Europe” project (NCT01754012) cohort to measure markers of adipose and lean tissue and bone mass. Pro-inflammatory (IL-6, IL-6Rα, TNF-α, TNF-R1, TNF-R2, pentraxin 3, CRP, alpha-1-acid glycoprotein, albumin) and anti-inflammatory (IL-10, TGF-β1) molecules as well as adipose-related markers such as leptin, adiponectin, ghrelin, and resistin were measured by magnetic bead-based multiplex-specific immunoassays and biochemical assays. Results: BC characteristics were different in elderly women and men, and more favorable BC markers were associated with a better adipose-related inflammatory profile, with the exception of skeletal muscle mass index. No correlation was found with the body composition markers and circulating levels of some standard pro- and anti-inflammatory markers like IL-6, pentraxin 3, IL-10, TGF-β1, TNF-α, IL-6Rα, glycoprotein 130, TNF-α-R1, and TNF-α-R2. Conclusions: The association between BC and inflammatory and adipose-related biomarkers is crucial in decoding aging and pathophysiological processes, such as sarcopenia. DXA can help in understanding how the measurement of fat and muscle is important, making the way from research to clinical practice. Key Points: • Body composition markers concordantly associated positively or negatively with adipose-related and inflammatory markers, with the exception of skeletal muscle mass index. • No correlation was found with the body composition markers and circulating levels of some standard pro- and anti-inflammatory markers like IL-6, pentraxin 3, IL-10, TGF-β1, TNF-α, IL-6Rα, gp130, TNF-α-R1, and TNF-α-R2. • Skeletal muscle mass index (SMI) shows a good correlation with inflammatory profile in age-related sarcopenia