Showing papers by "Cornell University published in 2015"

A global reference for human genetic variation.

Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

Combined Nivolumab and Ipilimumab or Monotherapy in Untreated Melanoma.

Abstract: The median progression-free survival was 11.5 months (95% confidence interval [CI], 8.9 to 16.7) with nivolumab plus ipilimumab, as compared with 2.9 months (95% CI, 2.8 to 3.4) with ipilimumab (hazard ratio for death or disease progression, 0.42; 99.5% CI, 0.31 to 0.57; P<0.001), and 6.9 months (95% CI, 4.3 to 9.5) with nivolumab (hazard ratio for the comparison with ipilimumab, 0.57; 99.5% CI, 0.43 to 0.76; P<0.001). In patients with tumors positive for the PD-1 ligand (PD-L1), the median progression-free survival was 14.0 months in the nivolumab-plus-ipilimumab group and in the nivolumab group, but in patients with PD-L1–negative tumors, progression-free survival was longer with the combination therapy than with nivolumab alone (11.2 months [95% CI, 8.0 to not reached] vs. 5.3 months [95% CI, 2.8 to 7.1]). Treatment-related adverse events of grade 3 or 4 occurred in 16.3% of the patients in the nivolumab group, 55.0% of those in the nivolumab-plus-ipilimumab group, and 27.3% of those in the ipilimumab group. CONCLUSIONS Among previously untreated patients with metastatic melanoma, nivolumab alone or combined with ipilimumab resulted in significantly longer progression-free survival than ipilimumab alone. In patients with PD-L1–negative tumors, the combination of PD-1 and CTLA-4 blockade was more effective than either agent alone. (Funded by Bristol-Myers Squibb; CheckMate 067 ClinicalTrials.gov number, NCT01844505.)

Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer

Abstract: Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non–small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti–PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.

Principles of nanoparticle design for overcoming biological barriers to drug delivery

Abstract: Biological barriers to drug transport prevent successful accumulation of nanotherapeutics specifically at diseased sites, limiting efficacious responses in disease processes ranging from cancer to inflammation. Although substantial research efforts have aimed to incorporate multiple functionalities and moieties within the overall nanoparticle design, many of these strategies fail to adequately address these barriers. Obstacles, such as nonspecific distribution and inadequate accumulation of therapeutics, remain formidable challenges to drug developers. A reimagining of conventional nanoparticles is needed to successfully negotiate these impediments to drug delivery. Site-specific delivery of therapeutics will remain a distant reality unless nanocarrier design takes into account the majority, if not all, of the biological barriers that a particle encounters upon intravenous administration. By successively addressing each of these barriers, innovative design features can be rationally incorporated that will create a new generation of nanotherapeutics, realizing a paradigmatic shift in nanoparticle-based drug delivery.

Tumour exosome integrins determine organotropic metastasis

Abstract: Ever since Stephen Paget's 1889 hypothesis, metastatic organotropism has remained one of cancer's greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.

Deep neural networks are easily fooled: High confidence predictions for unrecognizable images

Abstract: Deep neural networks (DNNs) have recently been achieving state-of-the-art performance on a variety of pattern-recognition tasks, most notably visual classification problems. Given that DNNs are now able to classify objects in images with near-human-level performance, questions naturally arise as to what differences remain between computer and human vision. A recent study [30] revealed that changing an image (e.g. of a lion) in a way imperceptible to humans can cause a DNN to label the image as something else entirely (e.g. mislabeling a lion a library). Here we show a related result: it is easy to produce images that are completely unrecognizable to humans, but that state-of-the-art DNNs believe to be recognizable objects with 99.99% confidence (e.g. labeling with certainty that white noise static is a lion). Specifically, we take convolutional neural networks trained to perform well on either the ImageNet or MNIST datasets and then find images with evolutionary algorithms or gradient ascent that DNNs label with high confidence as belonging to each dataset class. It is possible to produce images totally unrecognizable to human eyes that DNNs believe with near certainty are familiar objects, which we call “fooling images” (more generally, fooling examples). Our results shed light on interesting differences between human vision and current DNNs, and raise questions about the generality of DNN computer vision.

PD-1 Blockade with Nivolumab in Relapsed or Refractory Hodgkin's Lymphoma

Abstract: BACKGROUND Preclinical studies suggest that Reed–Sternberg cells exploit the programmed death 1 (PD-1) pathway to evade immune detection. In classic Hodgkin’s lymphoma, alterations in chromosome 9p24.1 increase the abundance of the PD-1 ligands, PD-L1 and PD-L2, and promote their induction through Janus kinase (JAK)–signal transducer and activator of transcription (STAT) signaling. We hypothesized that nivolumab, a PD-1–blocking antibody, could inhibit tumor immune evasion in patients with relapsed or refractory Hodgkin’s lymphoma. METHODS In this ongoing study, 23 patients with relapsed or refractory Hodgkin’s lymphoma that had already been heavily treated received nivolumab (at a dose of 3 mg per kilogram of body weight) every 2 weeks until they had a complete response, tumor progression, or excessive toxic effects. Study objectives were measurement of safety and efficacy and assessment of the PDL1 and PDL2 (also called CD274 and PDCD1LG2, respectively) loci and PD-L1 and PD-L2 protein expression. RESULTS Of the 23 study patients, 78% were enrolled in the study after a relapse following autologous stem-cell transplantation and 78% after a relapse following the receipt of brentuximab vedotin. Drug-related adverse events of any grade and of grade 3 occurred in 78% and 22% of patients, respectively. An objective response was reported in 20 patients (87%), including 17% with a complete response and 70% with a partial response; the remaining 3 patients (13%) had stable disease. The rate of progression-free survival at 24 weeks was 86%; 11 patients were continuing to participate in the study. Reasons for discontinuation included stem-cell transplantation (in 6 patients), disease progression (in 4 patients), and drug toxicity (in 2 patients). Analyses of pretreatment tumor specimens from 10 patients revealed copy-number gains in PDL1 and PDL2 and increased expression of these ligands. Reed–Sternberg cells showed nuclear positivity of phosphorylated STAT3, indicative of active JAK-STAT signaling. CONCLUSIONS Nivolumab had substantial therapeutic activity and an acceptable safety profile in patients with previously heavily treated relapsed or refractory Hodgkin’s lymphoma. (Funded by Bristol-Myers Squibb and others; ClinicalTrials.gov number, NCT01592370.)

Nivolumab and ipilimumab versus ipilimumab in untreated melanoma

Abstract: BackgroundIn a phase 1 dose-escalation study, combined inhibition of T-cell checkpoint pathways by nivolumab and ipilimumab was associated with a high rate of objective response, including complete responses, among patients with advanced melanoma. MethodsIn this double-blind study involving 142 patients with metastatic melanoma who had not previously received treatment, we randomly assigned patients in a 2:1 ratio to receive ipilimumab (3 mg per kilogram of body weight) combined with either nivolumab (1 mg per kilogram) or placebo once every 3 weeks for four doses, followed by nivolumab (3 mg per kilogram) or placebo every 2 weeks until the occurrence of disease progression or unacceptable toxic effects. The primary end point was the rate of investigator-assessed, confirmed objective response among patients with BRAF V600 wild-type tumors. ResultsAmong patients with BRAF wild-type tumors, the rate of confirmed objective response was 61% (44 of 72 patients) in the group that received both ipilimumab and ni...

The contentious nature of soil organic matter

Abstract: Instead of containing stable and chemically unique ‘humic substances’, as has been widely accepted, soil organic matter is a mixture of progressively decomposing organic compounds; this has broad implications for soil science and its applications. The exchange of nutrients, energy and carbon between soil organic matter, the soil environment, aquatic systems and the atmosphere is important for agricultural productivity, water quality and climate. Long-standing theory suggests that soil organic matter is composed of inherently stable and chemically unique compounds. Here we argue that the available evidence does not support the formation of large-molecular-size and persistent ‘humic substances’ in soils. Instead, soil organic matter is a continuum of progressively decomposing organic compounds. We discuss implications of this view of the nature of soil organic matter for aquatic health, soil carbon–climate interactions and land management. Soil organic matter contains a large portion of the world's carbon and plays an important role in maintaining productive soils and water quality. Nevertheless, a consensus on the nature of soil organic matter is lacking. Johannes Lehmann and Markus Kleber argue that soil organic matter should no longer be seen as large and persistent, chemically unique substances, but as a continuum of progressively decomposing organic compounds.

Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

Abstract: Machine-learning (ML) algorithms are increasingly utilized in privacy-sensitive applications such as predicting lifestyle choices, making medical diagnoses, and facial recognition. In a model inversion attack, recently introduced in a case study of linear classifiers in personalized medicine by Fredrikson et al., adversarial access to an ML model is abused to learn sensitive genomic information about individuals. Whether model inversion attacks apply to settings outside theirs, however, is unknown. We develop a new class of model inversion attack that exploits confidence values revealed along with predictions. Our new attacks are applicable in a variety of settings, and we explore two in depth: decision trees for lifestyle surveys as used on machine-learning-as-a-service systems and neural networks for facial recognition. In both cases confidence values are revealed to those with the ability to make prediction queries to models. We experimentally show attacks that are able to estimate whether a respondent in a lifestyle survey admitted to cheating on their significant other and, in the other context, show how to recover recognizable images of people's faces given only their name and access to the ML model. We also initiate experimental exploration of natural countermeasures, investigating a privacy-aware decision tree training algorithm that is a simple variant of CART learning, as well as revealing only rounded confidence values. The lesson that emerges is that one can avoid these kinds of MI attacks with negligible degradation to utility.

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Abstract: We consider learning representations of entities and relations in KBs using the neural-embedding approach. We show that most existing models, including NTN (Socher et al., 2013) and TransE (Bordes et al., 2013b), can be generalized under a unified learning framework, where entities are low-dimensional vectors learned from a neural network and relations are bilinear and/or linear mapping functions. Under this framework, we compare a variety of embedding models on the link prediction task. We show that a simple bilinear formulation achieves new state-of-the-art results for the task (achieving a top-10 accuracy of 73.2% vs. 54.7% by TransE on Freebase). Furthermore, we introduce a novel approach that utilizes the learned relation embeddings to mine logical rules such as "BornInCity(a,b) and CityInCountry(b,c) => Nationality(a,c)". We find that embeddings learned from the bilinear objective are particularly good at capturing relational semantics and that the composition of relations is characterized by matrix multiplication. More interestingly, we demonstrate that our embedding-based rule extraction approach successfully outperforms a state-of-the-art confidence-based rule mining approach in mining Horn rules that involve compositional reasoning.

Pancreatic cancer exosomes initiate pre-metastatic niche formation in the liver

Abstract: Lyden and colleagues report that pancreatic cancer-derived exosomes induce a pre-metastatic niche in the liver by promoting TGFβ secretion from Kupffer cells, leading to fibronectin production in hepatic stellate cells and macrophage recruitment.

An integrated map of structural variation in 2,504 human genomes

Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Privacy-Preserving Deep Learning

Abstract: Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text The unprecedented accuracy of deep learning methods has turned them into the foundation of new AI-based services on the Internet Commercial companies that collect user data on a large scale have been the main beneficiaries of this trend since the success of deep learning techniques is directly proportional to the amount of data available for training Massive data collection required for deep learning presents obvious privacy issues Users' personal, highly sensitive data such as photos and voice recordings is kept indefinitely by the companies that collect it Users can neither delete it, nor restrict the purposes for which it is used Furthermore, centrally kept data is subject to legal subpoenas and extra-judicial surveillance Many data owners--for example, medical institutions that may want to apply deep learning methods to clinical records--are prevented by privacy and confidentiality concerns from sharing the data and thus benefitting from large-scale deep learning In this paper, we design, implement, and evaluate a practical system that enables multiple parties to jointly learn an accurate neural-network model for a given objective without sharing their input datasets We exploit the fact that the optimization algorithms used in modern deep learning, namely, those based on stochastic gradient descent, can be parallelized and executed asynchronously Our system lets participants train independently on their own datasets and selectively share small subsets of their models' key parameters during training This offers an attractive point in the utility/privacy tradeoff space: participants preserve the privacy of their respective data while still benefitting from other participants' models and thus boosting their learning accuracy beyond what is achievable solely on their own inputs We demonstrate the accuracy of our privacy-preserving deep learning on benchmark datasets

DNA-Repair Defects and Olaparib in Metastatic Prostate Cancer.

Abstract: BackgroundProstate cancer is a heterogeneous disease, but current treatments are not based on molecular stratification. We hypothesized that metastatic, castration-resistant prostate cancers with DNA-repair defects would respond to poly(adenosine diphosphate [ADP]–ribose) polymerase (PARP) inhibition with olaparib. MethodsWe conducted a phase 2 trial in which patients with metastatic, castration-resistant prostate cancer were treated with olaparib tablets at a dose of 400 mg twice a day. The primary end point was the response rate, defined either as an objective response according to Response Evaluation Criteria in Solid Tumors, version 1.1, or as a reduction of at least 50% in the prostate-specific antigen level or a confirmed reduction in the circulating tumor-cell count from 5 or more cells per 7.5 ml of blood to less than 5 cells per 7.5 ml. Targeted next-generation sequencing, exome and transcriptome analysis, and digital polymerase-chain-reaction testing were performed on samples from mandated tumor...

T cell exclusion, immune privilege, and the tumor microenvironment

Abstract: Effective immunotherapy promotes the killing of cancer cells by cytotoxic T cells. This requires not only that cancer-specific T cells be generated, but also that these T cells physically contact cancer cells. The coexistence in some patients of cancer cells and T cells that recognize them indicates that tumors may exhibit the phenomenon of immune privilege, in which immunogenic tissue is protected from immune attack. Here, we review the evidence that stromal cells of the tumor microenvironment mediate this restriction by excluding T cells from the vicinity of cancer cells. Overcoming this T cell checkpoint may thus enable optimal immunotherapy.

Combined Measurement of the Higgs Boson Mass in pp Collisions at √s=7 and 8 TeV with the ATLAS and CMS Experiments

Abstract: A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4l decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis

Abstract: In this Review, we discuss the state-of-the-art understanding of non-precious transition metal oxides that catalyze the oxygen reduction and evolution reactions. Understanding and mastering the kinetics of oxygen electrocatalysis is instrumental to making use of photosynthesis, advancing solar fuels, fuel cells, electrolyzers, and metal–air batteries. We first present key insights, assumptions and limitations of well-known activity descriptors and reaction mechanisms in the past four decades. The turnover frequency of crystalline oxides as promising catalysts is also put into perspective with amorphous oxides and photosystem II. Particular attention is paid to electronic structure parameters that can potentially govern the adsorbate binding strength and thus provide simple rationales and design principles to predict new catalyst chemistries with enhanced activity. We share new perspective synthesizing mechanism and electronic descriptors developed from both molecular orbital and solid state band structure principles. We conclude with an outlook on the opportunities in future research within this rapidly developing field.

High-mobility three-atom-thick semiconducting films with wafer-scale homogeneity

Abstract: The large-scale growth of semiconducting thin films forms the basis of modern electronics and optoelectronics. A decrease in film thickness to the ultimate limit of the atomic, sub-nanometre length scale, a difficult limit for traditional semiconductors (such as Si and GaAs), would bring wide benefits for applications in ultrathin and flexible electronics, photovoltaics and display technology. For this, transition-metal dichalcogenides (TMDs), which can form stable three-atom-thick monolayers, provide ideal semiconducting materials with high electrical carrier mobility, and their large-scale growth on insulating substrates would enable the batch fabrication of atomically thin high-performance transistors and photodetectors on a technologically relevant scale without film transfer. In addition, their unique electronic band structures provide novel ways of enhancing the functionalities of such devices, including the large excitonic effect, bandgap modulation, indirect-to-direct bandgap transition, piezoelectricity and valleytronics. However, the large-scale growth of monolayer TMD films with spatial homogeneity and high electrical performance remains an unsolved challenge. Here we report the preparation of high-mobility 4-inch wafer-scale films of monolayer molybdenum disulphide (MoS2) and tungsten disulphide, grown directly on insulating SiO2 substrates, with excellent spatial homogeneity over the entire films. They are grown with a newly developed, metal-organic chemical vapour deposition technique, and show high electrical performance, including an electron mobility of 30 cm(2) V(-1) s(-1) at room temperature and 114 cm(2) V(-1) s(-1) at 90 K for MoS2, with little dependence on position or channel length. With the use of these films we successfully demonstrate the wafer-scale batch fabrication of high-performance monolayer MoS2 field-effect transistors with a 99% device yield and the multi-level fabrication of vertically stacked transistor devices for three-dimensional circuitry. Our work is a step towards the realization of atomically thin integrated circuitry.

Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance

Abstract: The role of epithelial-to-mesenchymal transition (EMT) in metastasis is a longstanding source of debate, largely owing to an inability to monitor transient and reversible EMT phenotypes in vivo. Here we establish an EMT lineage-tracing system to monitor this process in mice, using a mesenchymal-specific Cre-mediated fluorescent marker switch system in spontaneous breast-to-lung metastasis models. We show that within a predominantly epithelial primary tumour, a small proportion of tumour cells undergo EMT. Notably, lung metastases mainly consist of non-EMT tumour cells that maintain their epithelial phenotype. Inhibiting EMT by overexpressing the microRNA miR-200 does not affect lung metastasis development. However, EMT cells significantly contribute to recurrent lung metastasis formation after chemotherapy. These cells survived cyclophosphamide treatment owing to reduced proliferation, apoptotic tolerance and increased expression of chemoresistance-related genes. Overexpression of miR-200 abrogated this resistance. This study suggests the potential of an EMT-targeting strategy, in conjunction with conventional chemotherapies, for breast cancer treatment.

Biochar for environmental management : science, technology and implementation

Abstract: Proceedings of the 2013 International Conference on Material Science and Environmental Engineering-2013Environment, Climate, Plant and Vegetation GrowthBiochar for Environmental ManagementAgriculture Productivity in Tunisia Under Stressed EnvironmentHandbook of Ecological and Ecosystem EngineeringOrganic FarmingTropical Peatland Eco-managementBy-Products of Palm Trees and Their ApplicationsBiochar Applications in Agriculture and Environment ManagementSoil Health and Climate ChangeBiochar for Environmental ManagementBiochar for Environmental ManagementBiochar in European Soils and AgricultureBiomass to BiofuelsRecarbonizing global soils – A technical manual of recommended sustainable soil managementAdvances in Environmental Science and EngineeringEngineering Applications of BiocharPlant Ecophysiology and Adaptation under Climate Change: Mechanisms and Perspectives IIBiocharPlant Adaptation Strategies in Changing EnvironmentManaging Agricultural Greenhouse GasesManagement of Organic WasteBiomass Chars: Elaboration, Characterization and Applications ?Sustainability Science and TechnologyEnvironmental Information Systems: Concepts, Methodologies, Tools, and ApplicationsEncyclopedia of Environmental ChangeAdvanced Biofuels and BioproductsRenewable Energy and Environmental TechnologyBiochar for Environmental ManagementSoil Carbon Stabilization to Mitigate Climate ChangeRecarbonizing global soils – A technical manual of recommended management practicesStudyguide for Biochar for Environmental Management: Science and Technology by Johannes Lehmann (Editor), ISBN 9781844076581Bioenergy Research: Advances and ApplicationsSoil ErosionApplications of Biochar for Environmental SafetyBiocharAgricultural and Environmental Applications of BiocharEmerging Treatment Technologies for Waste ManagementGeotherapyGreen Grabbing: A New Appropriation of Nature

Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome

Abstract: The intestinal tract is inhabited by a large and diverse community of microbes collectively referred to as the gut microbiota. While the gut microbiota provides important benefits to its host, especially in metabolism and immune development, disturbance of the microbiota-host relationship is associated with numerous chronic inflammatory diseases, including inflammatory bowel disease and the group of obesity-associated diseases collectively referred to as metabolic syndrome. A primary means by which the intestine is protected from its microbiota is via multi-layered mucus structures that cover the intestinal surface, thereby allowing the vast majority of gut bacteria to be kept at a safe distance from epithelial cells that line the intestine. Thus, agents that disrupt mucus-bacterial interactions might have the potential to promote diseases associated with gut inflammation. Consequently, it has been hypothesized that emulsifiers, detergent-like molecules that are a ubiquitous component of processed foods and that can increase bacterial translocation across epithelia in vitro, might be promoting the increase in inflammatory bowel disease observed since the mid-twentieth century. Here we report that, in mice, relatively low concentrations of two commonly used emulsifiers, namely carboxymethylcellulose and polysorbate-80, induced low-grade inflammation and obesity/metabolic syndrome in wild-type hosts and promoted robust colitis in mice predisposed to this disorder. Emulsifier-induced metabolic syndrome was associated with microbiota encroachment, altered species composition and increased pro-inflammatory potential. Use of germ-free mice and faecal transplants indicated that such changes in microbiota were necessary and sufficient for both low-grade inflammation and metabolic syndrome. These results support the emerging concept that perturbed host-microbiota interactions resulting in low-grade inflammation can promote adiposity and its associated metabolic effects. Moreover, they suggest that the broad use of emulsifying agents might be contributing to an increased societal incidence of obesity/metabolic syndrome and other chronic inflammatory diseases.

TEER Measurement Techniques for In Vitro Barrier Model Systems

Abstract: Transepithelial/transendothelial electrical resistance (TEER) is a widely accepted quantitative technique to measure the integrity of tight junction dynamics in cell culture models of endothelial and epithelial monolayers. TEER values are strong indicators of the integrity of the cellular barriers before they are evaluated for transport of drugs or chemicals. TEER measurements can be performed in real time without cell damage and generally are based on measuring ohmic resistance or measuring impedance across a wide spectrum of frequencies. The measurements for various cell types have been reported with commercially available measurement systems and also with custom-built microfluidic implementations. Some of the barrier models that have been widely characterized using TEER include the blood–brain barrier (BBB), gastrointestinal (GI) tract, and pulmonary models. Variations in these values can arise due to factors such as temperature, medium formulation, and passage number of cells. The aim of this article ...

The biology of innate lymphoid cells

Abstract: The innate immune system is composed of a diverse array of evolutionarily ancient haematopoietic cell types, including dendritic cells, monocytes, macrophages and granulocytes. These cell populations collaborate with each other, with the adaptive immune system and with non-haematopoietic cells to promote immunity, inflammation and tissue repair. Innate lymphoid cells are the most recently identified constituents of the innate immune system and have been the focus of intense investigation over the past five years. We summarize the studies that formally identified innate lymphoid cells and highlight their emerging roles in controlling tissue homeostasis in the context of infection, chronic inflammation, metabolic disease and cancer.