Interaction of TiO2 nanoparticles with lung fluid proteins and the resulting macrophage inflammatory response.

Inhalation is a major exposure route to nanoparticles. Following inhalation, nanoparticles first interact with the lung lining fluid, a complex mixture of proteins, lipids, and mucins. We measure the concentration and composition of lung fluid proteins adsorbed on the surface of titanium dioxide (TiO2) nanoparticles. Using proteomics, we find that lung fluid results in a unique protein corona on the surface of the TiO2 nanoparticles. We then measure the expression of three cytokines (interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), and macrophage inflammatory protein 2 (MIP-2)) associated with lung inflammation. We find that the corona formed from lung fluid leads to elevated expression of these cytokines in comparison to bare TiO2 nanoparticles or coronas formed from serum or albumin. These experiments show that understanding the concentration and composition of the protein corona is essential for understanding the pulmonary response associated with human exposure to nanoparticles.

Evidence for compositionally distinct upper mantle plumelets since the early history of the Tristan-Gough hotspot.

Recent studies indicate that mantle plumes, which transfer material and heat from the earth's interior to its surface, represent multifaceted upwellings. The Tristan-Gough hotspot track (South Atlantic), which formed above a mantle plume, documents spatial geochemical zonation in two distinct sub-tracks since ~70 Ma. The origin and the sudden appearance of two distinct geochemical flavors is enigmatic, but could provide insights into the structural evolution of mantle plumes. Sr-Nd-Pb-Hf isotope data from the Late Cretaceous Rio Grande Rise and adjacent Jean Charcot Seamount Chain (South American Plate), which represent the counterpart of the older Tristan-Gough volcanic track (African Plate), extends the bilateral-zonation to ~100 Ma. Our results support recent numerical models, demonstrating that mantle plumes can split into distinct upper mantle conduits, and provide evidence that these plumelets formed at the plume head-to-plume tail transition. We attribute the plume zonation to sampling the geochemically-graded margin of the African Large Low-Shear-Velocity Province.

International development of a patient-centered core outcome set for assessing health-related quality of life in metastatic breast cancer patients.

PURPOSE: For patients living with metastatic breast cancer (MBC), achieving best possible health-related quality of life, along with maximizing survival, is vital. Yet, we have no systemic way to determine if we achieve these goals. A Core Outcome Set (COS) that allows standardized measurement of outcomes important to patients, but also promotes discussing these outcomes during clinical encounters, is long overdue. METHODS: An international expert group (EG) of patient advocates, researchers, medical specialists, nurse specialists, and pharmaceutical industry representatives (n = 17) reviewed a list of relevant outcomes retrieved from the literature. A broader group (n = 141: patients/patient advocates (n = 45), health care professionals/researchers (n = 64), pharmaceutical industry representatives (n = 28), and health authority representatives (n = 4)) participated in a modified Delphi procedure, scoring the relevance of outcomes in two survey rounds. The EG finalized the COS in a consensus meeting. RESULTS: The final MBC COS includes 101 variables about: (1) health-related quality of life (HRQoL, n = 26) and adverse events (n = 24); (2) baseline patient characteristics (n = 9); and (3) clinical variables (n = 42). Many outcome that cover aspects of HRQoL relevant to MBC patients are included, e.g. daily functioning (including ability to work), psychosocial/emotional functioning, sexual functioning, and relationship with the medical team. CONCLUSION: The COS developed in this study contains important administrative data, clinical records, and clinician-reported measures that captures the impact of cancer. The COS is important for standardization of clinical research and implementation in daily practice and has received accreditation by the International Consortium for Health Outcomes Measurement (ICHOM).

IL-2 availability regulates the tissue specific phenotype of murine intra-hepatic Tregs.

CD4+CD25+Foxp3+ Tregs are known to acquire tissue-specific features and exert cytoprotective and regenerative functions. The extent to which this applies to liver-resident Tregs is unknown. In this study, we aimed to explore the phenotypic and functional characteristics of adult murine liver resident Tregs during homeostasis. Additionally, we investigated their role in ameliorating liver inflammation and tissue damage. Quantification of Foxp3+CD4+CD25+ cells comparing different tissues showed that the liver contained significantly fewer resident Tregs. A combination of flow cytometry phenotyping and microarray analysis of intra-hepatic and splenic Tregs under homeostatic conditions revealed that, although intra-hepatic Tregs exhibited the core transcriptional Treg signature, they expressed a distinct transcriptional profile. This was characterized by reduced CD25 expression and increased levels of pro-inflammatory Th1 transcripts Il1b and Ifng. In vivo ablation of Tregs in the Foxp3-DTR mouse model showed that Tregs had a role in reducing the magnitude of systemic and intra-hepatic inflammatory responses following acute carbon tetrachloride (CCl4) injury, but their absence did not impact the development of hepatocyte necrosis. Conversely, the specific expansion of Tregs by administration of IL-2 complexes increased the number of intra-hepatic Tregs and significantly ameliorated tissue damage following CCl4 administration in C57BL/6 mice. The cytoprotective effect observed in response to IL-2c was associated with the increased expression of markers known to regulate Treg suppressive function. Our results offer insight into the transcriptome and complex immune network of intra-hepatic Tregs and suggest that strategies capable of selectively increasing the pool of intra-hepatic Tregs could constitute effective therapies in inflammatory liver diseases.

UAV Image-Based Crop Growth Analysis of 3D-Reconstructed Crop Canopies.

Plant growth rate is an essential phenotypic parameter for quantifying potential crop productivity. Under field conditions, manual measurement of plant growth rate is less accurate in most cases. Image-based high-throughput platforms offer great potential for rapid, non-destructive, and objective estimation of plant growth parameters. The aim of this study was to assess the potential for quantifying plant growth rate using UAV-based (unoccupied aerial vehicle) imagery collected multiple times throughout the growing season. In this study, six diverse lines of lentils were grown in three replicates of 1 m2 microplots with six biomass collection time-points throughout the growing season over five site-years. Aerial imagery was collected simultaneously with each manual measurement of the above-ground biomass time-point and was used to produce two-dimensional orthomosaics and three-dimensional point clouds. Non-linear logistic models were fit to multiple data collection points throughout the growing season. Overall, remotely detected vegetation area and crop volume were found to produce trends comparable to the accumulation of dry weight biomass throughout the growing season. The growth rate and G50 (days to 50% of maximum growth) parameters of the model effectively quantified lentil growth rate indicating significant potential for image-based tools to be used in plant breeding programs. Comparing image-based groundcover and vegetation volume estimates with manually measured above-ground biomass suggested strong correlations. Vegetation area measured from a UAV has utility in quantifying lentil biomass and is indicative of leaf area early in the growing season. For mid- to late-season biomass estimation, plot volume was determined to be a better estimator. Apart from traditional traits, the estimation and analysis of plant parameters not typically collected in traditional breeding programs are possible with image-based methods, and this can create new opportunities to improve breeding efficiency mainly by offering new phenotypes and affecting selection intensity.

A Therapeutic Antigen-Presenting Cell-Targeting DNA Vaccine VB10.16 in HPV16-Positive High-Grade Cervical Intraepithelial Neoplasia: Results from a Phase I/IIa Trial.

PURPOSE: To evaluate the safety, immunogenicity and efficacy of a therapeutic DNA vaccine VB10.16, using a unique modular vaccine technology that is based on linking antigens to CCL3L1 targeting module, in women with HPV16-positive high-grade cervical intraepithelial neoplasia (CIN). PATIENTS AND METHODS: We conducted a first-in-human, open-label, phase I/IIa clinical trial of VB10.16 in subjects with confirmed HPV16-positive CIN 2/3. The primary endpoint was the proportion of participants with adverse events, including dose-limiting toxicities. Secondary outcome measures included measuring the E6/E7-specific cellular immune response. In the Expansion cohort HPV16 clearance, regression of CIN lesion size and grading were assessed during a 12-month follow-up period. RESULTS: A total of 34 women were enrolled: 16 in two dose cohorts and 18 in the expansion cohort. No serious adverse events or dose-limiting toxicities were observed, and none of the subjects discontinued treatment with VB10.16 due to an adverse event. Mild to moderate injection site reactions were the most commonly reported adverse event (79%). HPV16-specific T-cell responses were observed after vaccination in the majority of the subjects. In the expansion cohort, HPV16 clearance was seen in 8 of 17 evaluable subjects (47%). Reductions in lesion size were seen in 16 subjects (94%) and 10 subjects (59%) had regression to CIN 0/1. Correlation between strong IFNγ T-cell responses and lesion size reduction was statistically significant (P < 0.001). CONCLUSIONS: The novel therapeutic DNA vaccine VB10.16 was well tolerated and showed promising evidence of efficacy and strong HPV16-specific T-cell responses in subjects with high-grade CIN.

Concentration and composition of the protein corona as a function of incubation time and serum concentration: an automated approach to the protein corona.

Nanoparticles in contact with proteins form a "corona" of proteins adsorbed on the nanoparticle surface. Subsequent biological responses are then mediated by the adsorbed proteins rather than the bare nanoparticles. The use of nanoparticles as nanomedicines and biosensors would be greatly improved if researchers were able to predict which specific proteins will adsorb on a nanoparticle surface. We use a recently developed automated workflow with a liquid handling robot and low-cost proteomics to determine the concentration and composition of the protein corona formed on carboxylate-modified iron oxide nanoparticles (200 nm) as a function of incubation time and serum concentration. We measure the concentration of the resulting protein corona with a colorimetric assay and the composition of the corona with proteomics, reporting both abundance and enrichment relative to the fetal bovine serum (FBS) proteins used to form the corona. Incubation time was found to be an important parameter for corona concentration and composition at high (100% FBS) incubation concentrations, with only a slight effect at low (10%) FBS concentrations. In addition to these findings, we describe two methodological advances to help reduce the cost associated with protein corona experiments. We have automated the digest step necessary for proteomics and measured the variability between triplicate samples at each stage of the proteomics experiments. Overall, these results demonstrate the importance of understanding the multiple parameters that influence corona formation, provide new tools for corona characterization, and advance bioanalytical research in nanomaterials.

Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients.

MOTIVATION: Sepsis is a leading cause of death and disability in children globally, accounting for ∼3 million childhood deaths per year. In pediatric sepsis patients, the multiple organ dysfunction syndrome (MODS) is considered a significant risk factor for adverse clinical outcomes characterized by high mortality and morbidity in the pediatric intensive care unit. The recent rapidly growing availability of electronic health records (EHRs) has allowed researchers to vastly develop data-driven approaches like machine learning in healthcare and achieved great successes. However, effective machine learning models which could make the accurate early prediction of the recovery in pediatric sepsis patients from MODS to a mild state and thus assist the clinicians in the decision-making process is still lacking. RESULTS: This study develops a machine learning-based approach to predict the recovery from MODS to zero or single organ dysfunction by 1 week in advance in the Swiss Pediatric Sepsis Study cohort of children with blood-culture confirmed bacteremia. Our model achieves internal validation performance on the SPSS cohort with an area under the receiver operating characteristic (AUROC) of 79.1% and area under the precision-recall curve (AUPRC) of 73.6%, and it was also externally validated on another pediatric sepsis patients cohort collected in the USA, yielding an AUROC of 76.4% and AUPRC of 72.4%. These results indicate that our model has the potential to be included into the EHRs system and contribute to patient assessment and triage in pediatric sepsis patient care. AVAILABILITY AND IMPLEMENTATION: Code available at https://github.com/BorgwardtLab/MODS-recovery. The data underlying this article is not publicly available for the privacy of individuals that participated in the study. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area.

Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90 per cent transmission reduction and 70-90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.

The role of PCOS in mental health and sexual function in women with obesity and a history of infertility.

STUDY QUESTION: Do mental health and sexual function differ between women with or without polycystic ovary syndrome (PCOS) with comparable BMI and fertility characteristics? SUMMARY ANSWER: Women with PCOS have a poorer mental quality of life than women without PCOS, but there were no differences in symptoms of depression, anxiety, physical quality of life or sexual function. WHAT IS KNOWN ALREADY: Various studies suggest that women with PCOS have poorer mental health, such as higher symptoms of anxiety and depression with a lower quality of life, and have an impaired sexual function compared to women without PCOS. However, in most studies, BMI and infertility status differ between women with and without PCOS, which may hamper comparability. STUDY DESIGN SIZE DURATION: This study is a cross-sectional analysis of a 5-year follow-up of a randomized controlled trial (RCT) among women with obesity and a history of infertility. PARTICIPANTS/MATERIALS SETTING METHODS: Participants in this follow-up study of an RCT were women with obesity and infertility randomized to a lifestyle intervention followed by infertility treatment or prompt infertility treatment (control), stratified by ovulatory status and trial centre. In total, 173 (30.0%) women of the 577 women randomized in the initial trial participated in this follow-up study, with a mean follow-up of 5.5 years (range 3.7-7.0 years); of these women 73 had been diagnosed with PCOS and 100 did not have PCOS. Participants completed questionnaires on symptoms of anxiety and depression (Hospital Anxiety and Depression scale (HADS)), quality of life (36-item Short Form Health Survey (SF-36)) and sexual function (McCoy Female Sexuality Questionnaire (MFSQ)). We also compared quality of life subscale scores in women with and without PCOS and compared them to an age-matched Dutch reference population with average BMI. Effect sizes were calculated to assess the differences. MAIN RESULTS AND THE ROLE OF CHANCE: Symptoms of anxiety and depression, physical quality of life and sexual function did not differ significantly between obese women with and without PCOS. However, women with PCOS had a worse mental quality of life summary component score (-3.60 [95% CI -6.72 to -0.56]), mainly due to a lower score on the subscale 'role limitations due to emotional problems' (-12.41 [95% CI -22.78 to -2.28]), compared to women without PCOS. However, compared to an age-matched Dutch reference population, the obese infertile women with and without PCOS both scored lower on almost all physical and mental quality of life subscales. LIMITATIONS REASONS FOR CAUTION: These are secondary analyses of the follow-up study of the RCT. No power analysis was performed for the outcomes included in this analysis and, as our study had a relatively small sample size, the null findings could be based on insufficient power to detect small differences between the groups. Our study population had a high mean BMI (average total group 34.5 [SD ± 5.1]); therefore, our results may only be generalizable to women with obesity. WIDER IMPLICATIONS OF THE FINDINGS: Our results indicate that PCOS status is associated with impaired mental quality of life. Anxiety and depression, physical quality of life and sexual function in obese infertile women with PCOS seem more related to the obesity than the PCOS status. STUDY FUNDING/COMPETING INTERESTS: The initial study and follow-up were supported by grants from: ZonMw (50-50110-96-518), the Dutch Heart Foundation (2013T085) and the European Commission (633595). The Department of Obstetrics and Gynaecology of the UMCG received an unrestricted educational grant from Ferring pharmaceuticals BV, The Netherlands, outside the submitted work. A.H. reports consultancy for Ferring pharmaceuticals. B.W.J.M. is supported by an NHMRC Practitioner Fellowship (GNT1082548). B.W.J.M. reports consultancy for ObsEva, Merck Merck KGaA, iGenomix and Guerbet. All other authors declare no competing interests. TRIAL REGISTRATION NUMBER: The initial trial was registered on 16 November 2008 in the Dutch trial register; clinical trial registry number NTR1530.

Risk Factors, Treatment and Prognosis of Patients with Lung Cancer after Heart Transplantation.

Long-term survival after heart transplantation (HTX) is impacted by adverse effects of immunosuppressive pharmacotherapy, and post-transplant lung cancer is a common occurrence. This study aimed to examine the risk factors, treatment, and prognosis of patients with post-transplant lung cancer. We included 625 adult patients who received HTX at Heidelberg Heart Center between 1989 and 2018. Patients were stratified by diagnosis and staging of lung cancer after HTX. Analysis comprised donor and recipient characteristics, medications including immunosuppressive drugs, and survival after diagnosis of lung cancer. A total of 41 patients (6.6%) were diagnosed with lung cancer after HTX, 13 patients received curative care and 28 patients had palliative care. Mean time from HTX until diagnosis of lung cancer was 8.6 ± 4.0 years and 1.8 ± 2.7 years from diagnosis of lung cancer until last follow-up. Twenty-four patients (58.5%) were switched to an mTOR-inhibitor after diagnosis of lung cancer. Multivariate analysis showed recipient age (HR: 1.05; CI: 1.01-1.10; p = 0.02), COPD (HR: 3.72; CI: 1.88-7.37; p < 0.01), and history of smoking (HR: 20.39; CI: 2.73-152.13; p < 0.01) as risk factors for post-transplant lung cancer. Patients in stages I and II had a significantly better 1-year (100.0% versus 3.6%), 2-year (69.2% versus 0.0%), and 5-year survival (53.8% versus 0.0%) than patients in stages III and IV (p < 0.01). Given the poor prognosis of late-stage post-transplant lung cancer, routine reassessment of current smoking status, providing smoking cessation support, and intensified lung cancer screening in high-risk HTX recipients are advisable.

Co-Stimulatory Bispecific Antibodies Induce Enhanced T Cell Activation and Tumor Cell Killing in Breast Cancer Models.

Although T cell-recruiting CD3-binding bispecific antibodies (BiMAb) have been proven to be clinically effective for hematologic malignancies, the success of BiMAb targeting solid tumor-associated antigens (TAA) in carcinomas so far remains poor. We reasoned that provision of co-stimulatory BiMAb in combination with αTAA-αCD3 BiMAb would boost T cell activation and proliferative capacity, and thereby facilitate the targeting of weakly or heterogeneously expressed tumor antigens. Various αTAA-αCD3 and αTAA-αCD28 BiMAb in a tetravalent IgG1-Fc based format have been analyzed, targeting multiple breast cancer antigens including HER2, EGFR, CEA, and EpCAM. Moreover, bifunctional fusion proteins of αTAA-tumor necrosis factor ligand (TNFL) superfamily members including 4-1BBL, OX40L, CD70 and TL1A have been tested. The functional activity of BiMAb was assessed using co-cultures of tumor cell lines and purified T cells in monolayer and tumor spheroid models. Only in the presence of tumor cells, αTAA-αCD3 BiMAb activated T cells and induced cytotoxicity in vitro, indicating a strict dependence on cross-linking. Combination treatment of αTAA-αCD3 BiMAb and co-stimulatory αTAA-αCD28 or αTAA-TNFL fusion proteins drastically enhanced T cell activation in terms of proliferation, activation marker expression, cytokine secretion and tumor cytotoxicity. Furthermore, BiMAb providing co-stimulation were shown to reduce the minimally required dose to achieve T cell activation by at least tenfold. Immuno-suppressive effects of TGF-ß and IL-10 on T cell activation and memory cell formation could be overcome by co-stimulation. BiMAb-mediated co-stimulation was further augmented by immune checkpoint-inhibiting antibodies. Effective co-stimulation could be achieved by targeting a second breast cancer antigen, or by targeting fibroblast activation protein (FAP) expressed on another target cell. In tumor spheroids derived from pleural effusions of breast cancer patients, co-stimulatory BiMAb were essential for the activation tumor-infiltrating lymphocytes and cytotoxic anti-tumor responses against breast cancer cells. Taken together we showed that co-stimulation significantly potentiated the tumoricidal activity of T cell-activating BiMAb while preserving the dependence on TAA recognition. This approach could provide for a more localized activation of the immune system with higher efficacy and reduced peripheral toxicities.

RNA atlas of human bacterial pathogens uncovers stress dynamics linked to infection.

Bacterial processes necessary for adaption to stressful host environments are potential targets for new antimicrobials. Here, we report large-scale transcriptomic analyses of 32 human bacterial pathogens grown under 11 stress conditions mimicking human host environments. The potential relevance of the in vitro stress conditions and responses is supported by comparisons with available in vivo transcriptomes of clinically important pathogens. Calculation of a probability score enables comparative cross-microbial analyses of the stress responses, revealing common and unique regulatory responses to different stresses, as well as overlapping processes participating in different stress responses. We identify conserved and species-specific 'universal stress responders', that is, genes showing altered expression in multiple stress conditions. Non-coding RNAs are involved in a substantial proportion of the responses. The data are collected in a freely available, interactive online resource (PATHOgenex).

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in a city

BackgroundTransmission chains within small urban areas (accommodating[~]30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a European urban area, Basel-City (Switzerland). Methodology. We combined detailed epidemiological, intra-city mobility, and socioeconomic data-sets with whole-genome-sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44% of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60% of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare-system burden (intensive-care-unit occupancy). Principal Findings. Transmissions were driven by socioeconomically weaker and highly mobile population groups with mostly cryptic transmissions, whereas amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90% transmission reduction, and 70-90% reduction of severe cases showed that prioritizing mobile, socioeconomically weaker populations for vaccination would effectively reduce case numbers. However, long-term intensive-care-unit occupation would also be effectively reduced if senior population groups were prioritized, provided there were no changes in testing and prevention strategies. Conclusions. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area. Author summaryWe examined SARS-CoV-2 transmission patterns within a European city (Basel, Switzerland) to infer drivers of the transmission during the first wave in spring 2020. The combination of diverse data (serological, genomic, transportation, socioeconomic) allowed us to combine phylogenetic analysis with mathematical modelling on related cases that were mapped to a residential address. As a result we could evaluate population groups driving SARS-CoV-2 transmission and quantify their effect on the transmission dynamics. We found traceable transmission chains in wealthier or more senior population groups and cryptic transmissions in the mobile, young or socioeconomic weaker population groups - these were identified as transmission drivers of the first wave. Based on this insight, we simulated vaccination scenarios for various vaccine efficacies to reflect different approaches undertaken to handle the epidemic. We conclude that vaccination of the mobile inherently younger population group would be most effective to handle following waves.

Automation and low-cost proteomics for characterization of the protein corona: experimental methods for big data.

Nanoparticles used in biological settings are exposed to proteins that adsorb on the surface forming a protein corona. These adsorbed proteins dictate the subsequent cellular response. A major challenge has been predicting what proteins will adsorb on a given nanoparticle surface. Instead, each new nanoparticle and nanoparticle modification must be tested experimentally to determine what proteins adsorb on the surface. We propose that any future predictive ability will depend on large datasets of protein-nanoparticle interactions. As a first step towards this goal, we have developed an automated workflow using a liquid handling robot to form and isolate protein coronas. As this workflow depends on magnetic separation steps, we test the ability to embed magnetic nanoparticles within a protein nanoparticle. These experiments demonstrate that magnetic separation could be used for any type of nanoparticle in which a magnetic core can be embedded. Higher-throughput corona characterization will also require lower-cost approaches to proteomics. We report a comparison of fast, low-cost, and standard, slower, higher-cost liquid chromatography coupled with mass spectrometry to identify the protein corona. These methods will provide a step forward in the acquisition of the large datasets necessary to predict nanoparticle-protein interactions.

Preconception lifestyle intervention reduces long term energy intake in women with obesity and infertility: a randomised controlled trial.

BACKGROUND: The preconceptional period may be an optimal window of opportunity to improve lifestyle. We previously showed that a 6 month preconception lifestyle intervention among women with obesity and infertility was successful in decreasing the intake of high caloric snacks and beverages, increasing physical activity and in reducing weight in the short term. We now report the effects of the preconception lifestyle intervention on diet, physical activity and body mass index (BMI) at 5.5 years (range = 3.7-7.0 years) after the intervention. METHODS: We followed women who participated in the LIFEstyle study, a multicentre RCT in which women with obesity and infertility were assigned to a six-month lifestyle intervention program or prompt infertility treatment (N = 577). Diet and physical activity 5.5 years later were assessed with an 173-item food frequency questionnaire (N = 175) and Actigraph triaxial accelerometers (N = 155), respectively. BMI was calculated from self-reported weight and previously measured height (N = 179). Dietary intake, physical activity, and BMI in the intervention and control group were compared using multivariate regression models. Additionally, dietary intake, physical activity and BMI of women allocated to the intervention arm with successful weight loss during the intervention (i.e. BMI < 29 kg/m2 or ≥ 5% weight loss), unsuccessful weight loss and the control group were compared with ANCOVA. RESULTS: Although BMI did not differ between the intervention and control group 5.5 years after the intervention (- 0.5 kg/m2 [- 2.0;1.1]; P = 0.56), the intervention group did report a lower energy intake (- 216 kcal/day [- 417;-16]; P = 0.04). Women in the intervention arm who successfully lost weight during the intervention had a significantly lower BMI at follow-up compared to women in the intervention arm who did not lose weight successfully (- 3.4 kg/m2 [- 6.3;-0.6]; P = 0.01), and they reported a significantly lower energy intake compared to the control group (- 301 kcal [- 589;-14]; P = 0.04). Macronutrient intake, diet quality, and physical activity did not differ between the intervention and control group, irrespective of successful weight loss during the intervention. CONCLUSIONS: In our study population, a preconception lifestyle intervention led to reduced energy intake 5.5 years later. Additionally, women allocated to the intervention group who were successful in losing weight during the intervention also had a lower BMI at follow-up. This shows the potential sustainable effect of a preconception lifestyle intervention. TRIAL REGISTRATION: This trial was registered on 16 November 2008 in the Dutch trial register; clinical trial registry number NTR1530 .

Diet and physical activity in pregnancy and offspring's cardiovascular health: a systematic review.

There is increasing evidence linking maternal diet and physical activity before and during pregnancy with offspring's cardiovascular health. Although many studies examined this association, the evidence has not been reviewed systematically. We therefore undertook a systematic review to synthesize evidence examining the association of maternal diet and physical activity before and during pregnancy with offspring's blood pressure and vascular health. We systematically searched the databases MEDLINE and EMBASE from inception to June 30, 2017. Eligibility screening, data extraction and quality assessment were performed by two independent reviewers. A total of 19 articles were included comprising three randomized controlled trials and 16 observational studies. Of the studies that examined the association of interest, 60% (three out of five studies) showed that high maternal carbohydrate intake was associated with higher offspring's blood pressure. Maternal protein intake during pregnancy was negatively associated with offspring carotid intima-media thickness in two out of two studies. No consistent findings for maternal fatty acid intake were found. There were too few studies to draw conclusions on energy intake, fibre intake, protein/carbohydrate ratio, specific foods, dietary patterns and maternal physical activity. Heterogeneity in exposure and outcome assessment hampered pooling. Also, owing to the observational nature of most studies, causality cannot be established. Harmonization of valid exposure and outcome measurements, and the development of core outcome sets are needed to enable more robust conclusions.

Methods and Tools in Genome-wide Association Studies.

Many traits, such as height, the response to a given drug, or the susceptibility to certain diseases are presumably co-determined by genetics. Especially in the field of medicine, it is of major interest to identify genetic aberrations that alter an individual's risk to develop a certain phenotypic trait. Addressing this question requires the availability of comprehensive, high-quality genetic datasets. The technological advancements and the decreasing cost of genotyping in the last decade led to an increase in such datasets. Parallel to and in line with this technological progress, an analysis framework under the name of genome-wide association studies was developed to properly collect and analyze these data. Genome-wide association studies aim at finding statistical dependencies-or associations-between a trait of interest and point-mutations in the DNA. The statistical models used to detect such associations are diverse, spanning the whole range from the frequentist to the Bayesian setting.Since genetic datasets are inherently high-dimensional, the search for associations poses not only a statistical but also a computational challenge. As a result, a variety of toolboxes and software packages have been developed, each implementing different statistical methods while using various optimizations and mathematical techniques to enhance the computations.This chapter is devoted to the discussion of widely used methods and tools in genome-wide association studies. We present the different statistical models and the assumptions on which they are based, explain peculiarities of the data that have to be accounted for and, most importantly, introduce commonly used tools and software packages for the different tasks in a genome-wide association study, complemented with examples for their application.

Accurate and adaptive imputation of summary statistics in mixed-ethnicity cohorts.

Motivation: Methods based on summary statistics obtained from genome-wide association studies have gained considerable interest in genetics due to the computational cost and privacy advantages they present. Imputing missing summary statistics has therefore become a key procedure in many bioinformatics pipelines, but available solutions may rely on additional knowledge about the populations used in the original study and, as a result, may not always ensure feasibility or high accuracy of the imputation procedure. Results: We present ARDISS, a method to impute missing summary statistics in mixed-ethnicity cohorts through Gaussian Process Regression and automatic relevance determination. ARDISS is trained on an external reference panel and does not require information about allele frequencies of genotypes from the original study. Our method approximates the original GWAS population by a combination of samples from a reference panel relying exclusively on the summary statistics and without any external information. ARDISS successfully reconstructs the original composition of mixed-ethnicity cohorts and outperforms alternative solutions in terms of speed and imputation accuracy both for heterogeneous and homogeneous datasets. Availability and implementation: The proposed method is available at https://github.com/BorgwardtLab/ARDISS. Supplementary information: Supplementary data are available at Bioinformatics online.