Land sparing versus land sharing:Moving forward

To address the challenges of biodiversity conservation and commodity production, a framework has been proposed that distinguishes between the integration (land sharing) and separation (land sparing) of conservation and production. Controversy has arisen around this framework partly because many scholars have focused specifically on food production rather than more encompassing notions such as land scarcity or food security. Controversy further surrounds the practical value of partial trade-off analyses, the ways in which biodiversity should be quantified, and a series of scale effects that are not readily accounted for. We see key priorities for the future in (1) addressing these issues when using the existing framework, and (2) developing alternative, holistic ways to conceptualise challenges related to food, biodiversity, and land scarcity

ApoCIII-Enriched LDL in Type 2 Diabetes Displays Altered Lipid Composition, Increased Susceptibility for Sphingomyelinase, and Increased Binding to Biglycan

Objective- Apolipoprotein CIII (apoCIII) is an independent risk factor for cardiovascular disease, but the molecular mechanisms involved are poorly understood. Here, we investigated potential proatherogenic properties of apoCIII-containing LDL from hypertriglyceridemic patients with type 2 diabetes. Research design and methods - LDL was isolated from controls and subjects with type 2 diabetes, and from apoB transgenic mice. LDL-biglycan binding was analyzed with a solid-phase assay using immunoplates coated with biglycan. Lipid composition was analyzed with mass spectrometry. Hydrolysis of LDL by sphingomyelinase was analyzed after labeling plasma LDL with [(3)H]sphingomyelin. ApoCIII isoforms were quantified after isoelectric focusing. Human aortic endothelial cells were incubated with desialylated apoCIII or with LDL enriched with specific apoCIII isoforms. Results- We showed that enriching LDL with apoCIII only induced a small increase in LDL-proteoglycan binding, and this effect was dependent on a functional Site A in apoB100. Our findings indicated that intrinsic characteristics of the diabetic LDL other than apoCIII per se are responsible for further increased proteoglycan binding of diabetic LDL with high endogenous apoCIII, and we showed alterations in the lipid composition of diabetic LDL with high apoCIII. We also demonstrated that high apoCIII increased susceptibility of LDL to hydrolysis and aggregation by SMase. In addition, we demonstrated that sialylation of apoCIII increased with increasing apoCIII content, and that sialylation of apoCIII was essential for its proinflammatory properties. Conclusions- We have demonstrated a number of features of apoCIII-containing LDL from hypertriglyceridemic patients with type 2 diabetes that could explain the proatherogenic role of apoCIII

hiPSC-derived hepatocytes closely mimic the lipid profile of primary hepatocytes: A future personalised cell model for studying the lipid metabolism of the liver

Peer reviewe

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Smoking is a predictor of complications in all types of surgery : a machine learning-based big data study

Background: Machine learning algorithms are promising tools for smoking status classification in big patient data sets. Smoking is a risk factor for postoperative complications in major surgery. Whether this applies to all surgery is unknown. The aims of this retrospective cohort study were to develop a machine learning algorithm for clinical record-based smoking status classification and to determine whether smoking and former smoking predict complications in all surgery types. Methods: All surgeries performed in a Finnish hospital district from 1 January 2015 to 31 December 2019 were analysed. Exclusion criteria were age below 16 years, unknown smoking status, and unknown ASA class. A machine learning algorithm was developed for smoking status classification. The primary outcome was 90-day overall postoperative complications in all surgeries. Secondary outcomes were 90-day overall complications in specialties with over 10 000 surgeries and critical complications in all surgeries. Results: The machine learning algorithm had precisions of 0.958 for current smokers, 0.974 for ex-smokers, and 0.95 for never-smokers. The sample included 158 638 surgeries. In adjusted logistic regression analyses, smokers had increased odds of overall complications (odds ratio 1.17; 95 per cent c.i. 1.14 to 1.20) and critical complications (odds ratio 1.21; 95 per cent c.i. 1.14 to 1.29). Corresponding odds ratios of ex-smokers were 1.09 (95 per cent c.i. 1.06 to 1.13) and 1.09 (95 per cent c.i. 1.02 to 1.17). Smokers had increased odds of overall complications in all specialties with over 10 000 surgeries. ASA class was the most important complication predictor. Conclusion: Machine learning algorithms are feasible for smoking status classification in big surgical data sets. Current and former smoking predict complications in all surgery types.Peer reviewe

Liver-specific deletion of the Plpp3 gene alters plasma lipid composition and worsens atherosclerosis in apoE(-/-) mice

The PLPP3 gene encodes for a ubiquitous enzyme that dephosphorylates several lipid substrates. Genome-wide association studies identified PLPP3 as a gene that plays a role in coronary artery disease susceptibility. The aim of the study was to investigate the effect of Plpp3 deletion on atherosclerosis development in mice. Because the constitutive deletion of Plpp3 in mice is lethal, conditional Plpp3 hepatocyte-specific null mice were generated by crossing floxed Plpp3 mice with animals expressing Cre recombinase under control of the albumin promoter. The mice were crossed onto the athero-prone apoE(-/-) background to obtain Plpp3(f/f)apoE(-/-) Alb-Cre(+) and Plpp3(f/f)apoE(-/-) Alb-Cre(-) offspring, the latter of which were used as controls. The mice were fed chow or a Western diet for 32 or 12 weeks, respectively. On the Western diet, Alb-Cre+ mice developed more atherosclerosis than Alb-Cre- mice, both at the aortic sinus and aorta. Lipidomic analysis showed that hepatic Plpp3 deletion significantly modified the levels of several plasma lipids involved in atherosclerosis, including lactosylceramides, lysophosphatidic acids, and lysophosphatidylinositols. In conclusion, Plpp3 ablation in mice worsened atherosclerosis development. Lipidomic analysis suggested that the hepatic Plpp3 deletion may promote atherosclerosis by increasing plasma levels of several low-abundant pro-atherogenic lipids, thus providing a molecular basis for the observed results

Liver-specific deletion of the Plpp3 gene alters plasma lipid composition and worsens atherosclerosis in apoE -/- mice

The PLPP3 gene encodes for a ubiquitous enzyme that dephosphorylates several lipid substrates. Genome-wide association studies identified PLPP3 as a gene that plays a role in coronary artery disease susceptibility. The aim of the study was to investigate the effect of Plpp3 deletion on atherosclerosis development in mice. Because the constitutive deletion of Plpp3 in mice is lethal, conditional Plpp3 hepatocyte-specific null mice were generated by crossing floxed Plpp3 mice with animals expressing Cre recombinase under control of the albumin promoter. The mice were crossed onto the athero-prone apoE -/- background to obtain Plpp3 f/f apoE -/- Alb-Cre + and Plpp3 f/f apoE -/- Alb-Cre - offspring, the latter of which were used as controls. The mice were fed chow or a Western diet for 32 or 12 weeks, respectively. On the Western diet, Alb-Cre + mice developed more atherosclerosis than Alb-Cre - mice, both at the aortic sinus and aorta. Lipidomic analysis showed that hepatic Plpp3 deletion significantly modified the levels of several plasma lipids involved in atherosclerosis, including lactosylceramides, lysophosphatidic acids, and lysophosphatidylinositols. In conclusion, Plpp3 ablation in mice worsened atherosclerosis development. Lipidomic analysis suggested that the hepatic Plpp3 deletion may promote atherosclerosis by increasing plasma levels of several low-abundant pro-atherogenic lipids, thus providing a molecular basis for the observed results

LipidXplorer: A Software for Consensual Cross-Platform Lipidomics

LipidXplorer is the open source software that supports the quantitative characterization of complex lipidomes by interpreting large datasets of shotgun mass spectra. LipidXplorer processes spectra acquired on any type of tandem mass spectrometers; it identifies and quantifies molecular species of any ionizable lipid class by considering any known or assumed molecular fragmentation pathway independently of any resource of reference mass spectra. It also supports any shotgun profiling routine, from high throughput top-down screening for molecular diagnostic and biomarker discovery to the targeted absolute quantification of low abundant lipid species. Full documentation on installation and operation of LipidXplorer, including tutorial, collection of spectra interpretation scripts, FAQ and user forum are available through the wiki site at: https://wiki.mpi-cbg.de/wiki/lipidx/index.php/Main_Page

Organic Farming Improves Pollination Success in Strawberries

Pollination of insect pollinated crops has been found to be correlated to pollinator abundance and diversity. Since organic farming has the potential to mitigate negative effects of agricultural intensification on biodiversity, it may also benefit crop pollination, but direct evidence of this is scant. We evaluated the effect of organic farming on pollination of strawberry plants focusing on (1) if pollination success was higher on organic farms compared to conventional farms, and (2) if there was a time lag from conversion to organic farming until an effect was manifested. We found that pollination success and the proportion of fully pollinated berries were higher on organic compared to conventional farms and this difference was already evident 2–4 years after conversion to organic farming. Our results suggest that conversion to organic farming may rapidly increase pollination success and hence benefit the ecosystem service of crop pollination regarding both yield quantity and quality