Miracle-dz/UniFAR-FTUs huggingface dataset:
A Suspect Screening Method for Characterizing Multiple Chemical Exposures among a Demographically Diverse Population of Pregnant Women in San Francisco

Background: In utero exposure to environmental chemicals can adversely impact pregnancy outcomes and childhood health, but minimal biomonitoring data exist on the majority of chemicals used in commerce. Objectives: We aimed to profile exposure to multiple environmental organic acids (EOAs) and identify novel chemicals that have not been previously biomonitored in a diverse population of pregnant women. Methods: We used liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) to perform a suspect screen for 696 EOAs, (e.g., phenols and phthalate metabolites) on the maternal serum collected at delivery from 75 pregnant women delivering at two large San Francisco Hospitals. We examined demographic differences in peak areas and detection frequency (DF) of suspect EOAs using a Kruskal-Wallis Rank Sum test or Fisher’s exact test. We confirmed selected suspects by comparison with their respective reference standards. Results: We detected, on average, 56 [standard deviation (SD)]: 8) suspect EOAs in each sample (range: 32–73). Twelve suspect EOAs with DF≥ 60 were matched to 21 candidate compounds in our EOA database, two-thirds of which are novel chemicals. We found demographic differences in DF for 13 suspect EOAs and confirmed the presence of 6 priority novel chemicals: 2,4-Di-tert-butylphenol, Pyrocatechol, 2,4-Dinitrophenol, 3,5-Di-tert-butylsalicylic acid, 4-Hydroxycoumarin, and 2′-Hydroxyacetophenone (or 3′-Hydroxyacetophenone). The first two are high-production-volume chemicals in the United States. Conclusion: Suspect screening in human biomonitoring provides a viable method to characterize a broad spectrum of environmental chemicals to prioritize for targeted method development and quantification. https://doi.org/10.1289/EHP2920
Inductive Loop Axle Detector based on Resistance and Reactance Vehicle Magnetic Profiles

The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance magnetic profile to detect vehicle axles, including lifted axles. Accuracies of no less than 71.8% were achieved for vehicles travelling with a lifted axle, and no less than 98.8% for other vehicles. The axle detection accuracy was determined during a series of experiments carried out under normal traffic conditions, using profile analysis, video footage and reference signals from an axle load detector on a total of 4000 vehicles.
Imaging Cancer Metabolism: Underlying Biology and Emerging Strategies

Dysregulated cellular metabolism is a characteristic feature of malignancy that has been exploited for both imaging and targeted therapy. With regard to imaging, deranged glucose metabolism has been leveraged using 18F-FDG PET. Metabolic imaging with 18F-FDG, however, probes only the early steps of glycolysis; the complexities of metabolism beyond these early steps in this single pathway are not directly captured. New imaging technologies—both PET with novel radiotracers and MR-based methods—provide unique opportunities to investigate other aspects of cellular metabolism and expand the metabolic imaging armamentarium. This review will discuss the underlying biology of metabolic dysregulation in cancer, focusing on glucose, glutamine, and acetate metabolism. Novel imaging strategies will be discussed within this biologic framework, highlighting particular strengths and limitations of each technique. Emphasis is placed on the role that combining modalities will play in enabling multiparametric imaging to fully characterize tumor biology to better inform treatment.
Extubation of patients undergoing extracorporeal life support. A retrospective study

Introduction: The use of extracorporeal life support (ECLS) is increasing worldwide, in particular for the management of refractory cardiac arrest, cardiogenic shock and post cardiopulmonary bypass ventricular failure. Extubation of patients under extracorporeal membrane oxygenation (ECMO) for respiratory failure is a growing practice for adult and pediatric patients, especially for lung transplantation candidates. Because of potential complications and, specifically, accidental arterial decannulation, extubation of patients under ECLS is not standard practice. Our goal was to evaluate the interest in patient extubation under ECLS. Materials and methods: We performed a monocentric, retrospective study of all ECLS cases between January 2014 and January 2016. We excluded patients who died within the first 48 hours of ECLS. Results: We analyzed 57 of the initial 109 patients included in the study. The initial SOFA score was higher in the non-extubated group under ECLS, without significant difference (8.6 ± 2.8 vs 7.2 ± 2.1, p=0.065). Patients who were not extubated had a higher rate of acquired ventilator pneumonia (61.9% vs 26.7%, p=0.03). Moreover, patients who were extubated under ECLS had better 30-day survival rates (73.3% vs 40.5%, p=0.04). In multivariate analyses, the independent factors associated with mortality were age, duration of ECLS and the lack of extubation under ECLS. Conclusion: Extubation of patients under ECLS is safe and feasible. Furthermore, in extubated patients, we observed fewer cases of ventilator-associated pneumonia and better 30-day survival rates.
The importance and implications of preconception genetic testing for accurate fetal risk estimation in 21-hydroxylase congenital adrenal hyperplasia (CAH)

Abstract Preconception genetic testing should be offered to all patients with 21-hydroxylase congenital adrenal hyperplasia. We report how the preconception genetic testing of a lady and her partner dramatically changed the estimated risk to their offspring and the major implications the results had on pregnancy planning. The risk of conceiving a female fetus with congenital adrenal hyperplasia brings in considerations of prenatal dexamethasone therapy and prenatal diagnosis. We also highlight the differences between genetic testing on a research and clinical basis.
A Pareto-Based Sparse Subspace Learning Framework

High-dimensionality is a common characteristic of real-world data, which often results in high time and space complexity or poor performance of ensuing methods. Subspace learning, as one kind of dimension reduction method, provides a way to overcome the aforementioned problem. In this paper, we introduce multiobjective evolutionary optimization into subspace learning, and propose a Pareto-based sparse subspace learning algorithm for classification tasks. The proposed algorithm aims at minimizing two conflicting objective functions, the reconstruction error and the sparsity. A kernel trick derived from Gaussian kernel is implemented to the sparse subspace learning for the nonlinear phenomena of nature. In order to speed up the convergence, an entropy-driven initialization scheme and a gradient-descent mutation scheme are designed specifically. At last, a knee point is selected from the Pareto front to guarantee that we can obtain a solution with good classification performance, and yet as sparse as possible. The experiments and detailed analysis on real-life datasets and the hyperspectral images demonstrated that the proposed model achieves comparable results with the existing conventional subspace learning and evolutionary feature selection algorithms. Hence, this paper provides a more flexible and efficient approach for sparse subspace learning.
Decreased muscle strength is associated with proinflammatory cytokines but not testosterone levels in men with diabetes

The aim of this study was to compare muscle strength in male subjects with type 2 diabetes mellitus (DM2) with and without low plasma testosterone levels and assess the relationship between muscle strength, testosterone levels, and proinflammatory cytokines. Males (75) aged between 18 and 65 years were divided into 3 groups: control group that did not have diabetes and had a normal testosterone plasma level (>250 ng/dL), DnormalTT group that had DM2 with normal testosterone levels, and the DlowTT group that had DM2 and low plasma testosterone levels (<250 ng/dL). The age (means±SD) of the groups was 48.4±10, 52.6±7, and 54.6±7 years, respectively. Isokinetic concentric and isometric torque of knee flexors and extensors were analyzed by an isokinetic dynamometer. Plasma testosterone and proinflammatory cytokine levels were determined by chemiluminescence and ELISA, respectively. Glycemic control was analyzed by glycated hemoglobin (HbA1C). In general, concentric and isometric torques were lower and tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β plasma levels were higher in the groups with diabetes than in controls. There was no correlation between testosterone level and knee torques or proinflammatory cytokines. Concentric and isometric knee flexion and extension torque were negatively correlated with TNF-α, IL-6, and HbA1C. IL-6 and TNF-α were positively correlated with HbA1C. The results of this study demonstrated that muscle strength was not associated with testosterone levels in men with DM2. Low muscle strength was associated with inflammatory markers and poor glycemic control.
A Flexible Capacitive Pressure Sensor Based on Ionic Liquid

A flexible microfluidic super-capacitive pressure sensor is developed to measure the surface pressure of a complex structure. The innovative sensor contains a filter paper filled with ionic liquid, and coated with two indium tin oxide polyethylene terephthalate (ITO-PET) films on the top and bottom, respectively. When external pressure is applied on the top ITO-PET film of the sensor mounted on the surface of an aircraft, the capacitance between the two ITO-PET films will change because of the deformation of the top ITO-PET film. The external pressure will be determined based on the change of the capacitance. Compared to the traditional pressure sensor, the developed sensor provides a high sensitivity of up to 178.5 nF/KPa and rapid dynamic responses for pressure measurement. Meanwhile, experiments are also conducted to study the influence of the thickness of the sensing film, sensing area, temperature, and humidity.
Reduction of Redundant Rules in Association Rule Mining-Based Bug Assignment

Bug triaging is a process to decide what to do with newly coming bug reports. In this paper, we have mined association rules for the prediction of bug assignee of a newly reported bug using different bug attributes, namely, severity, priority, component and operating system. To deal with the problem of large data sets, we have taken subsets of data set by dividing the large data set using K-means clustering algorithm. We have used an Apriori algorithm in MATLAB to generate association rules. We have extracted the association rules for top 5 assignees in each cluster.The proposed method has been empirically validated on 14696 bug reports of Mozilla open source software project, namely, Seamonkey, Firefox and Bugzilla. The proposed method provides an improvement over the existing techniques for bug assignment problem.
Generalizability in Qualitative Research: A Tale of Two Traditions

Generalizability in qualitative research has been a controversial topic given that interpretivist scholars have resisted the dominant role and mandate of the positivist tradition within social sciences. Aiming to find universal laws, the positivist paradigm has made generalizability a crucial criterion for evaluating the rigor of quantitative research. This positivist echo has led generalizability to acquire a quantitative meaning, inappropriate for describing qualitative studies. The purpose of qualitative research has, thus, been directed toward providing in-depth explanations and meanings rather than generalizing findings. Through a critical review of empirical and theoretical studies, this commentary seeks to show that in qualitative domains, generalizability is possible provided that, first, generalizability is the main objective of the study; second, due precautions concerning the philosophy and terminology selected are taken. Hence, this commentary contributes to the literature on qualitative research by making suggestions for more consistent and unanimous procedures to adopt in qualitative inquiries.
Receptor-mediated dimerization of JAK2 FERM domains is required for JAK2 activation

Cytokines and interferons initiate intracellular signaling via receptor dimerization and activation of Janus kinases (JAKs). How JAKs structurally respond to changes in receptor conformation induced by ligand binding is not known. Here, we present two crystal structures of the human JAK2 FERM and SH2 domains bound to Leptin receptor (LEPR) and Erythropoietin receptor (EPOR), which identify a novel dimeric conformation for JAK2. This 2:2 JAK2/receptor dimer, observed in both structures, identifies a previously uncharacterized receptor interaction essential to dimer formation that is mediated by a membrane-proximal peptide motif called the ‘switch’ region. Mutation of the receptor switch region disrupts STAT phosphorylation but does not affect JAK2 binding, indicating that receptor-mediated formation of the JAK2 FERM dimer is required for kinase activation. These data uncover the structural and molecular basis for how a cytokine-bound active receptor dimer brings together two JAK2 molecules to stimulate JAK2 kinase activity.
Effects and Mechanism of Nano-Copper Exposure on Hepatic Cytochrome P450 Enzymes in Rats

Although nano-copper is currently used extensively, the adverse effects on liver cytochrome P450 (CYP450) enzymes after oral exposure are not clear. In this study, we determined the effects and mechanisms of action of nano- and micro-copper on the expression and activity of CYP450 enzymes in rat liver. Rats were orally exposed to micro-copper (400 mg/kg), Cu ion (100 mg/kg), or nano-copper (100, 200 and 400 mg/kg) daily for seven consecutive days. Histopathological, inflammatory and oxidative stress were measured in the livers of all rats. The mRNA levels and activity of CYP450 enzymes, as well as the mRNA levels of select nuclear receptors, were determined. Exposure to nano-copper (400 mg/kg) induced significant oxidative stress and inflammation relative to the controls, indicated by increased levels of interleukin (IL)-2, IL-6, interferon (IFN)-γ, macrophage inflammatory protein (MIP-1), total antioxidant capacity (T-AOC), malondialdehyde (MDA), inducible nitric oxide synthase (iNOS) and nitric oxide (NO) after exposure. The levels of mRNA expression of pregnane X receptor (PXR), constitutive androstane receptor (CAR) and aryl hydrocarbon receptor (AHR) were significantly decreased in 400 mg/kg nano-copper treated rats. Nano-copper activated the expression of the NF-kappa B (NF-κB), mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription (STAT)3 signaling pathways. Nano-copper decreased the mRNA expression and activity of CYP 1A2, 2C11, 2D6, 2E1 and 3A4 in a dose-dependent manner. The adverse effects of micro-copper are less severe than those of nano-copper on the CYP450 enzymes of rats after oral exposure. Ingestion of large amounts of nano-copper in animals severely affects the drug metabolism of the liver by inhibiting the expression of various CYP450 enzymes, which increases the risk of drug-drug interactions in animals.
A Comprehensive Study on Predicting Functional Role of Metagenomes Using Machine Learning Methods

“Metagenomics” is the study of genomic sequences obtained directly from environmental microbial communities with the aim to linking their structures with functional roles. The field has been aided in the unprecedented advancement through high-throughput omics data sequencing. The outcome of sequencing are biologically rich data sets. Metagenomic data consisting of microbial species which outnumber microbial samples, lead to the “curse of dimensionality” in datasets. Hence, the focus in metagenomics studies has moved towards developing efficient computational models using Machine Learning (ML), reducing the computational cost. In this paper, we comprehensively assessed various ML approaches to classifying high-dimensional human microbiota effectively into their functional phenotypes. We propose the application of embedded feature selection methods, namely, Extreme Gradient Boosting and Penalized Logistic Regression to determine important microbial species. The resultant feature set enhanced the performance of one of the most popular state-of-the-art methods, Random Forest (RF) over metagenomic studies. Experimental results indicate that the proposed method achieved best results in terms of accuracy, area under the Receiver Operating Characteristic curve (ROC-AUC), and major improvement in processing time. It outperformed other feature selection methods of filters or wrappers over RF and classifiers such as Support Vector Machine (SVM), Extreme Learning Machine (ELM), and k- Nearest Neighbors (k-NN).
Classification of injuries observed in functional classes of self‐injurious behaviour

BACKGROUND Limited research has examined how the functions of self-injurious behaviour (SIB) relate to the production of injuries and the location, type or severity of those injuries. METHODS Clinical and medical records were coded for 64 individuals hospitalised for SIB. When injuries were present, the physical properties of SIB and injuries were assessed across groups of individuals with automatically and socially maintained SIB. RESULTS Injuries were observed for 35 of the individuals who engaged in SIB. Individuals who engaged in a single form of SIB were more likely to have injuries (P < .05). Individuals with SIB maintained by automatic reinforcement had significantly more severe injuries to the head than those in the social group (q < .05, P = .0132, H = 12.54). CONCLUSION Although results are preliminary, the results provide evidence that the function of SIB may influence the severity and location of injuries produced.
A Prospective Cohort Study of Adolescents’ Memory Performance and Individual Brain Dose of Microwave Radiation from Wireless Communication

Background: The potential impact of microwave radiofrequency electromagnetic fields (RF-EMF) emitted by wireless communication devices on neurocognitive functions of adolescents is controversial. In a previous analysis, we found changes in figural memory scores associated with a higher cumulative RF-EMF brain dose in adolescents. Objective: We aimed to follow-up our previous results using a new study population, dose estimation, and approach to controlling for confounding from media usage itself. Methods: RF-EMF brain dose for each participant was modeled. Multivariable linear regression models were fitted on verbal and figural memory score changes over 1 y and on estimated cumulative brain dose and RF-EMF related and unrelated media usage (n=669–676). Because of the hemispheric lateralization of memory, we conducted a laterality analysis for phone call ear preference. To control for the confounding of media use behaviors, a stratified analysis for different media usage groups was also conducted. Results: We found decreased figural memory scores in association with an interquartile range (IQR) increase in estimated cumulative RF-EMF brain dose scores: −0.22 (95% CI: −0.47, 0.03; IQR: 953 mJ/kg per day) in the whole sample, −0.39 (95% CI: −0.67, −0.10; IQR: 953 mJ/kg per day) in right-side users (n=532), and −0.26 (95% CI: −0.42, −0.10; IQR: 341 mJ/kg per day) when recorded network operator data were used for RF-EMF dose estimation (n=274). Media usage unrelated to RF-EMF did not show significant associations or consistent patterns, with the exception of consistent (nonsignificant) positive associations between data traffic duration and verbal memory. Conclusions: Our findings for a cohort of Swiss adolescents require confirmation in other populations but suggest a potential adverse effect of RF-EMF brain dose on cognitive functions that involve brain regions mostly exposed during mobile phone use. https://doi.org/10.1289/EHP2427
Peptidylarginine deiminase 4 concentration, but not PADI4 polymorphisms, is associated with ICU mortality in septic shock patients

The objective of our study was to evaluate the association between peptidylarginine deiminase 4 (PAD4) concentration and its polymorphisms with mortality in patients with septic shock. We prospectively evaluated 175 patients aged over 18 years with septic shock upon intensive care unit (ICU) admission. However, 48 patients were excluded. Thus, 127 patients were enrolled in the study. At the time of the patients’ enrollment, demographic information was recorded. Blood samples were taken within the first 24 hours of the patient's admission to determine serum PAD4 concentrations and its polymorphism PADI4_89 [rs11203366], PADI4_94 [rs2240340] and PADI4_104 [rs1748033]. The mean age was 63.3 ± 15.2 years, 56.7% were male, PAD4 concentration was 4.62 (2.48‐6.20) ng/mL and the ICU mortality rate was 67.7%. The patients who died in the ICU had higher APACHE II and Sequential Organ Failure Assessment (SOFA) scores. In addition, PAD4 concentration was higher in patients who died during ICU stay. However, there were no differences regarding PADI4 polymorphisms and ICU mortality. In the logistic regression models, PAD4 concentrations were associated with ICU mortality when adjusted for APACHE II score and lactate (OR: 1.477; CI 95%: 1.186‐1.839; P < .001), and when adjusted for age, gender and APACHE II score (OR: 1.392; CI 95%: 1.145‐1.692; P < .001). In conclusion, PAD4 concentration, but not PADI4_89, PADI4_94 and PADI4_104 polymorphisms, is associated with ICU mortality in septic shock patients.
Predictors of Individual Resilience Characteristics Among Individuals Ages 65 and Older in Post-Disaster Settings

Abstract Objective Literature explores which factors most impact resilience and how these factors impact an individual and communities’ ability to cope with disaster. Less research has focused on how age impacts resilience. This research adapts several previous conceptual models used to investigate resilience. To investigate the unique vulnerabilities faced by older individuals in post-disaster settings, this analysis was undertaken to investigate predictors of individual resilience. Methods Data for the study were derived from the Centers for Disease Control and Prevention (CDC) Gulf States Population Survey (GSPS). The final sample included 5,713 adult residents from 4 gulf-coast states. Multiple linear regression was used for the analysis. Results All models (demographic, health, social, and combined) acted as significant predictors of individual resilience. Health and social resilience models accounted for more of the variance in resilience scores. In all models, age was negatively associated with resilience scores. Being female was protective across all models. The results of the model testing indicate inequitable disaster mitigation, with social and health indicators explaining the most variance in the resilience levels. Conclusion This research provides practitioners with the knowledge they need to focus their interventions on the areas where it is most needed to empower resilient individuals. (Disaster Med Public Health Preparedness. 2019;13:256–264)