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Nuclear receptors (NRs) are important biological targets of endocrine-disrupting chemicals (EDCs). Identifying chemicals that can act as EDCs and modulate the function of NRs is difficult because of the time and cost of in vitro and in vivo screening to determine the potential hazards of the 100 000s of chemicals that humans are exposed to. Hence, there is a need for computational approaches to prioritize chemicals for biological testing. Machine learning (ML) techniques are alternative methods that can quickly screen millions of chemicals and identify those that may be an EDC. Computational models of chemical binding to multiple NRs have begun to emerge. Recently, a Nuclear Receptor Activity (NuRA) dataset, describing experimentally derived small-molecule activity against various NRs has been created. We have used the NuRA dataset to develop an ensemble of ML-based models to predict the agonism, antagonism, binding and effector binding of small molecules to nine different human NRs. We defined the applicability domain of the ML models as a measure of Tanimoto similarity to the molecules in the training set, which enhanced the performance of the developed classifiers. We further developed a user-friendly web server named 'NR-ToxPred' to predict the binding of chemicals to the nine NRs using the best-performing models for each receptor. This web server is freely accessible at http://nr-toxpred.cchem.berkeley.edu. Users can upload individual chemicals using Simplified Molecular-Input Line-Entry System, CAS numbers or sketch the molecule in the provided space to predict the compound's activity against the different NRs and predict the binding mode for each.

Background and objectivesRas-mitogen-activated protein kinase (MAPK) signaling abnormalities occur in most brain arteriovenous malformations (bAVMs). No means exist to molecularly profile bAVMs without open surgery, limiting precision medicine approaches to treatment. Here, we report use of endoluminal biopsy of the vessel lumen of bAVMs to characterize gene expression and blood flow-mediated transcriptional changes in living patients.MethodsEndoluminal biopsy and computational fluid dynamic modeling (CFD) were performed in adults with unruptured AVMs with cerebral angiography. Each patient underwent surgical resection and cell sampling from a contiguous arterial segment. Fluorescence-assisted cell sorting enriched endothelial cells, which were sequenced on an Illumina HiSeq 4000 sequencer. Gene expression was quantified with RNA sequencing (RNAseq). Differential gene expression, ontology, and correlative analyses were performed. Results were validated with quantitative reverse transcription PCR (RT-qPCR).ResultsEndoluminal biopsy was successful in 4 patients without complication. Endoluminal biopsy yielded 269.0 ± 79.9 cells per biopsy (control 309.2 ± 86.6 cells, bAVM 228.8 ± 133.4 cells). RNAseq identified 106 differentially expressed genes (DEGs) in bAVMs (false discovery rate ≤0.05). DEGs were enriched for bAVM pathogenic cascades, including Ras-MAPK signaling (p < 0.05), and confirmed with RT-qPCR and a panel predictive of MAPK/extracellular signal-regulated kinase inhibitor response. Compared to patient-matched surgically excised tissues, endoluminal biopsy detected 83.3% of genes, and genome-wide expression strongly correlated (Pearson r = 0.77). Wall shear stress measured by CFD correlated with inflammatory pathway upregulation. Comparison of pre-embolization and postembolization samples confirmed flow-mediated gene expression changes.DiscussionEndoluminal biopsy allows molecular profiling of bAVMs in living patients. Gene expression profiles are similar to those of tissues acquired with open surgery and identify potentially targetable Ras-MAPK signaling abnormalities in bAVMs. Integration with CFD allows determination of flow-mediated transcriptomic alterations. Endoluminal biopsy may help facilitate trials of precision medicine approaches to bAVMs in humans.

BackgroundBreastfeeding is important for the health and development of the child, and for maternal health, in all country contexts. However, global sales of breast-milk substitutes (BMS), including infant, follow-up and toddler formulas, have 'boomed' in recent decades. This raises the importance of international food standards established by the Codex Alimentarius Commission (Codex) on the safety, composition and labelling of BMS. Such standards appear to be strongly contested by governments, industry and civil society groups, yet few studies have investigated the politics of Codex standard-setting processes. The aim of this paper is to understand who participates in decision-making, and how actors frame and contest proposals to revise the Codex Standard on Follow-up Formula (FUF).MethodsWe adopted a case study design involving two steps. First, we enumerated government, industry, civil society, and international organization stakeholders participating in standard-setting processes of the Codex Committee on Nutrition and Foods for Special Dietary Uses (CCNFSDU). Second, we conducted a framing analysis of stakeholder inputs during the FUF standard revision in CCNFSDU meetings. Publicly available online meeting reports (2015-2019) were retrieved, analyzed using a theoretical framework, and organized thematically.ResultsHigh-income country (HIC) delegates greatly outnumbered those from other country income categories. Industry representation was higher compared with other observer categories. Member state delegations included more industry representation than civil society representation, and were occasionally the only member state delegates. Industry stakeholders framed arguments in terms of trade implications, science, and flexible standards. Civil society groups used public health, science, and pro-breastfeeding frames.ConclusionCodex BMS standard-setting procedures are dominated by HICs and industry groups. Limited representation of civil society, and of low- and middle-income countries (LMICs), suggest actions are needed to substantially increase support for their involvement at Codex. Such representation may help to counteract power asymmetries and commercial influences on food standards for infants and young children.

BackgroundInternational food standards set by the Codex Alimentarius Commission (CAC), have become more prominent in international trade politics, since being referenced by various World Trade Organization (WTO) agreements. We examine how this impacts implementation of the World Health Organization (WHO) International Code of Marketing of Breast-milk Substitutes.MethodsUsing trade in commercial milk formulas (CMFs) as a case study, we collected detailed data on interventions across various WTO bodies between 1995 and 2019. We used language from these interventions to guide data collection on member state and observer positions during the CAC review of the Codex Standard for Follow-up Formula (CSFUF), and during CAC discussions on the relevance of WHO policies and guidelines.ResultsExporting member states made 245 interventions regarding CMFs at the WTO, many citing deviations from standards set by the CAC. These did not occur in formal disputes, but in WTO Committee and Accession processes, toward many countries. In Thailand, complaints are linked to weakened regulation. Exporters also sought to narrow the CSFUF at the CAC in a way that is at odds with recommendations in the International Code. Tensions are growing more broadly within the CAC regarding relevance of WHO recommendations. Countries coordinated during WTO committee processes to advocate for reapportioning core WHO funding to the CAC and in order to further influence standard-setting.ConclusionThe commercial interests of the baby food industry are magnifying inconsistencies between health guidelines set by the WHO, standard-setting at the CAC, and functions of the WTO. This poses serious concerns for countries' abilities to regulate in the interests of public health, in this case to protect breastfeeding and its benefits for the health of infants, children and mothers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.

BackgroundThe global milk formula market has 'boomed' in recent decades, raising serious concerns for breastfeeding, and child and maternal health. Despite these developments, few studies have investigated the global expansion of the baby food industry, nor the market and political practices corporations have used to grow and sustain their markets. In this paper, our aim is to understand the strategies used by the baby food industry to shape 'first-foods systems' across its diverse markets, and in doing so, drive milk formula consumption on a global scale. We used a theoretically guided synthesis review method, which integrated diverse qualitative and quantitative data sources.ResultsGlobal milk formula sales grew from ~US$1.5 billion in 1978 to US$55.6 billion in 2019. This remarkable expansion has occurred along two main historical axes. First, the widening geographical reach of the baby food industry and its marketing practices, both globally and within countries, as corporations have pursued new growth opportunities, especially in the Global South. Second, the broadening of product ranges beyond infant formula, to include an array of follow-up, toddler and specialized formulas for a wider range of age groups and conditions, thereby widening the scope of mother-child populations subject to commodification. Sophisticated marketing techniques have been used to grow and sustain milk formula consumption, including marketing through health systems, mass-media and digital advertising, and novel product innovations backed by corporate science. To enable and sustain this marketing, the industry has engaged in diverse political practices to foster favourable policy, regulatory and knowledge environments. This has included lobbying international and national policy-makers, generating and deploying favourable science, leveraging global trade rules and adopting corporate policies to counter regulatory action by governments.ConclusionThe baby food industry uses integrated market and political strategies to shape first-foods systems in ways that drive and sustain milk formula market expansion, on a global scale. Such practices are a major impediment to global implementation of the International Code of Marketing of Breastmilk Substitutes, and other policy actions to protect, promote and support breastfeeding. New modalities of public health action are needed to negate the political practices of the industry in particular, and ultimately to constrain corporate power over the mother-child breastfeeding dyad.

The ideal radiology report reduces diagnostic uncertainty, while avoiding ambiguity whenever possible. The purpose of this study was to characterize the use of uncertainty terms in radiology reports at a single institution and compare the use of these terms across imaging modalities, anatomic sections, patient characteristics, and radiologist characteristics. We hypothesized that there would be variability among radiologists and between subspecialities within radiology regarding the use of uncertainty terms and that the length of the impression of a report would be a predictor of use of uncertainty terms. Finally, we hypothesized that use of uncertainty terms would often be interpreted by human readers as hedging. To test these hypotheses, we applied a natural language processing (NLP) algorithm to assess and count the number of uncertainty terms within radiology reports. An algorithm was created to detect usage of a published set of uncertainty terms. All 642,569 radiology report impressions from 171 reporting radiologists were collected from 2011 through 2015. For validation, two radiologists without knowledge of the software algorithm reviewed report impressions and were asked to determine whether the report was uncertain or hedging. The relationship between the presence of 1 or more uncertainty terms and the human readers assessment was compared. There were significant differences in the proportion of reports containing uncertainty terms across patient admission status and across anatomic imaging subsections. Reports with uncertainty were significantly longer than those without, although report length was not significantly different between subspecialities or modalities. There were no significant differences in rates of uncertainty when comparing the experience of the attending radiologist. When compared with reader 1 as a gold standard, accuracy was 0.91, sensitivity was 0.92, specificity was 0.9, and precision was 0.88, with an F1-score of 0.9. When compared with reader 2, accuracy was 0.84, sensitivity was 0.88, specificity was 0.82, and precision was 0.68, with an F1-score of 0.77. Substantial variability exists among radiologists and subspecialities regarding the use of uncertainty terms, and this variability cannot be explained by years of radiologist experience or differences in proportions of specific modalities. Furthermore, detection of uncertainty terms demonstrates good test characteristics for predicting human readers assessment of uncertainty.

Background Though incidental pulmonary nodules are common, rates of guideline-recommended surveillance and associations between surveillance and mortality are unclear. In this study, we describe adherence (categorized as complete, partial, late and none) to guideline-recommended surveillance among patients with incidental 5-8 mm pulmonary nodules and assess associations between adherence and mortality. Methods This was a retrospective cohort study of 551 patients (≥35 years) with incidental pulmonary nodules conducted from September 1, 2008 to December 31, 2016, in an integrated safety-net health network. Results Of the 551 patients, 156 (28%) had complete, 87 (16%) had partial, 93 (17%) had late and 215 (39%) had no documented surveillance. Patients were followed for a median of 5.2 years [interquartile range (IQR), 3.6-6.7 years] and 82 (15%) died during follow-up. Adjusted all-cause mortality rates ranged from 2.24 [95% confidence interval (CI), 1.24-3.25] deaths per 100 person-years for complete follow-up to 3.30 (95% CI, 2.36-4.23) for no follow-up. In multivariable models, there were no statistically significant associations between the levels of surveillance and mortality (p > 0.16 for each comparison with complete surveillance). Compared with complete surveillance, adjusted mortality rates were non-significantly increased by 0.45 deaths per 100 person-years (95% CI, -1.10 to 2.01) for partial, 0.55 (95% CI, -1.08 to 2.17) for late and 1.05 (95% CI, -0.35 to 2.45) for no surveillance. Conclusions Although guideline-recommended surveillance of small incidental pulmonary nodules was incomplete or absent in most patients, gaps in surveillance were not associated with statistically significant increases in mortality in a safety-net population.

Objective: Tinnitus is a condition that causes distress and impairment across cognitive, functional, and psychiatric spectra. In the psychiatric realm, tinnitus has long been associated with depression. To better characterize the co-occurrence of depression and tinnitus, we performed a systematic review of the prevalence of depression among patients with tinnitus.Data sources: We comprehensively examined original studies reporting the prevalence of depression in adult populations with tinnitus, as indexed in the PubMed and Web of Science databases and published from January 2006 to August 2016.Review methods: All identified articles were reviewed independently by 2 researchers, with a third reviewer for adjudication. Included studies were evaluated for threats to validity across 3 domains-representativeness, response rate, and ascertainment of outcome-on a 4-point modified Newcastle-Ottawa Quality Assessment Scale.Results: Twenty-eight studies were included, representing 15 countries and 9979 patients with tinnitus. Among the included studies, the median prevalence of depression was 33%, with an interquartile range of 19% to 49% and an overall range of 6% to 84%. Studies were high quality overall, with a mean score of 3.3 (SD = 0.76), and 89% utilized a validated tool to ascertain depression.Conclusions: We conducted one of the largest contemporary comprehensive reviews, which suggests a 33% prevalence of depression among patients with tinnitus. Our review reaffirms that a substantial proportion of patients with tinnitus have depression, and we recommend that all who treat tinnitus should screen and treat their patients for depression, if present.

There is limited data describing endothelial cell (EC) gene expression between aneurysms and arteries partly because of risks associated with surgical tissue collection. Endovascular biopsy (EB) is a lower risk alternative to conventional surgical methods, though no such efforts have been attempted for aneurysms. We sought (1) to establish the feasibility of EB to isolate viable ECs by fluorescence-activated cell sorting (FACS), (2) to characterize the differences in gene expression by anatomic location and rupture status using single-cell qPCR, and (3) to demonstrate the utility of unsupervised clustering algorithms to identify cell subpopulations. EB was performed in 10 patients (5 ruptured, 5 non-ruptured). FACS was used to isolate the ECs and single-cell qPCR was used to quantify the expression of 48 genes. Linear mixed models and exploratory multilevel component analysis (MCA) and self-organizing maps (SOMs) were performed to identify possible subpopulations of cells. ECs were collected from all aneurysms and there were no adverse events. A total of 437 ECs was collected, 94 (22%) of which were aneurysmal cells and 319 (73%) demonstrated EC-specific gene expression. Ruptured aneurysm cells, relative controls, yielded a median p value of 0.40 with five genes (10%) with p values

Background and purposeShorter time-to-thrombolysis in acute ischemic stroke (AIS) is associated with improved functional outcome and reduced morbidity. We evaluate the effect of several interventions to reduce time-to-thrombolysis at an urban, public safety net hospital.MethodsAll patients treated with tissue plasminogen activator for AIS at our institution between 2008 and 2015 were included in a retrospective analysis of door-to-needle (DTN) time and associated factors. Between 2011 and 2014, we implemented 11 distinct interventions to reduce DTN time. Here, we assess the relative impact of each intervention on DTN time.ResultsThe median DTN time pre- and postintervention decreased from 87 (interquartile range: 68-109) minutes to 49 (interquartile range: 39-63) minutes. The reduction was comprised primarily of a decrease in median time from computed tomography scan order to interpretation. The goal DTN time of 60 minutes or less was achieved in 9% (95% confidence interval: 5%-22%) of cases preintervention, compared with 70% (58%-81%) postintervention. Interventions with the greatest impact on DTN time included the implementation of a stroke group paging system, dedicated emergency department stroke pharmacists, and the development of a stroke code supply box.ConclusionsMultidisciplinary, collaborative interventions are associated with a significant and substantial reduction in time-to-thrombolysis. Such targeted interventions are efficient and achievable in resource-limited settings, where they are most needed.