Miracle-dz/UniFAR-FTUs huggingface dataset:
Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative).

BACKGROUND The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data. CONTENT This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices. SUMMARY Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.
Hepatitis A, B, and A/B vaccination series completion among US adults: A claims-based analysis

ABSTRACT Hepatitis A and B disease burden persists in the US. We assessed hepatitis A and hepatitis B vaccination series completion rates among 350,240 commercial/Medicare and 12,599 Medicaid enrollees aged ≥19 years. A vaccination series was considered as completed provided that the minimum interval between doses, as defined by the CDC, and the minimum number of doses were reached. We stratified completion rates by vaccine type (i.e. monovalent or bivalent) at initial vaccination for each cohort. In the commercial/Medicare cohort, the series completion rate was 32.0% for hepatitis A and 39.6% for hepatitis B among those who initiated with a monovalent vaccine, and it was 36.2% for hepatitis A and 48.9% for hepatitis B among those who initiated with a bivalent vaccine. In the Medicaid cohort, the series completion rate was 21.0% for hepatitis A and 24.0% for hepatitis B among those who initiated with a monovalent vaccine, and it was 19.0% for hepatitis A and 24.6% for hepatitis B among those who initiated with a bivalent vaccine. In conclusion, hepatitis A and B vaccination series completion rates were low, and appeared to be lower among Medicaid than among commercial/Medicare enrollees. Commercial/Medicare enrollees who initiated with a bivalent vaccine had higher series completion rates than those who initiated with monovalent vaccines – an observation that was not made among Medicaid enrollees.
Twenty-gene-based prognostic model predicts lung adenocarcinoma survival

Introduction Lung adenocarcinoma (LAC) accounts for more than a half of non-small cell lung cancer with high morbidity and mortality. Progression of treatment has not accelerated the improvement of its prognosis. Hence, it is an urgent need to develop novel biomarkers for its early diagnosis and treatment. Materials and methods In this study, we proposed to identify LAC survival-related genes through comprehensive analysis of large-scale gene expression profiles. LAC gene expression data sets were obtained from The Cancer Genome Atlas (TCGA). Identification of differentially expressed genes (DEGs) in LAC compared with adjacent normal lung tissues was first performed followed by univariate Cox regression analysis to obtain genes that are significantly associated with LAC survival (SurGenes). Then, we conducted sure independence screening (SIS) for SurGenes to identify more reliable genes and the prognostic signature for LAC survival prediction. Another two lung cancer data sets from TCGA and Gene Expression Omnibus (GEO) were used for the validation of prognostic signature. Results A total of 20 genes were obtained, which were significantly associated with the overall survival (OS) of LAC patients. The prognostic signature, a weighted linear combination of the 20 genes, could successfully separate LAC samples with high OS from those with low OS and had robust predictive performance for survival (training set: p-value <2.2×10−16; testing set: p-value =2.04×10−5, area under the curve (AUC) =0.615). Combined with GEO data set, we obtained four genes, that is, FUT4, SLC25A42, IGFBP1, and KLHDC8B that are found in both the prognostic signature and DEGs of LAC in GEO data set. Discussion The prognostic signature combined with multi-gene expression profiles provides a moderate OS prediction for LAC and should be helpful for appropriate treatment method selection.
Implicit Quantile Networks for Distributional Reinforcement Learning

In this work, we build on recent advances in distributional reinforcement learning to give a generally applicable, flexible, and state-of-the-art distributional variant of DQN. We achieve this by using quantile regression to approximate the full quantile function for the state-action return distribution. By reparameterizing a distribution over the sample space, this yields an implicitly defined return distribution and gives rise to a large class of risk-sensitive policies. We demonstrate improved performance on the 57 Atari 2600 games in the ALE, and use our algorithm's implicitly defined distributions to study the effects of risk-sensitive policies in Atari games.
Effects of low, subchronic exposure of 2,4‐Dichlorophenoxyacetic acid (2,4‐D) and commercial 2,4‐D formulations on early life stages of fathead minnows (Pimephales promelas)

Aquatic herbicides are commonly used to control a wide variety of algae and plants, but they also have the potential to contaminate and affect nontarget organisms. However, the impacts of low‐level 2,4‐dichlorophenoxyacetic acid (2,4‐D) herbicide exposure on larval fish are not well understood. We conducted a series of experiments to determine the effects of low concentrations (0.05, 0.50, and 2.00 ppm) of 2 commercial 2,4‐D amine salt herbicide formulations (Weedestroy® AM40 [WAM40] and DMA® 4 IVM [DMA4]) and pure 2,4‐D on the development and survival of fathead minnows (Pimephales promelas) at various life cycle stages. Larval survival (30 d post hatch [dph]) was decreased following exposure of eggs and larvae to pure 2,4‐D (0.50 ppm; p ≤ 0.001), as well as to WAM40 (0.50 and 2.00 ppm; p ≤ 0.001, p ≤ 0.001) and DMA4 (0.50 and 2.00 ppm; p ≤ 0.001, p ≤ 0.001). The results also narrowed the critical window of exposure for effects on survival to the period between fertilization and 14 dph. Development was not negatively altered by any of the compounds tested, although the commercial formulations increased larval total length and mass at 2.00 ppm. Altogether, the results indicate that the use of 2,4‐D herbicides for weed control in aquatic ecosystems at current recommended concentrations (<2 ppm whole lake; <4 ppm spot treatment) could present risks to fathead minnow larval survival. Environ Toxicol Chem 2018;37:2550–2559. © 2018 SETAC
Prenatal and Neonatal Factors Predicting Sleep Problems in Children Born Extremely Preterm or With Extremely Low Birthweight

Objective: Prematurely born children have been reported to have more sleep problems throughout childhood than children born at term. The aim of this study was to explore if prenatal or neonatal factors can predict sleep problems at age 11 years in children born extremely preterm (EPT). Method: A prospective observational study of all infants who were born EPT in Norway in 1999 and 2000. Prenatal and neonatal data were collected by all Norwegian obstetric and pediatric departments. Parental questionnaire mapped sleep problems and sleep habits at the age of 11 years. Results: Of the 372 eligible children, 221 participated. Of those, 28.1% snored, 27.5% had difficulty falling asleep or frequent awakenings and 17.2% suffered from daytime sleepiness. The mean sleep duration was 9.4 h (range 4.3–11.0 h). Smoking in pregnancy predicted snoring (odds ratio 4.3). Neonatal cerebral hemorrhage and being born small for gestational age predicted difficulty falling asleep or frequent awakenings (odds ratio 2.2 and 2.3). Other morbidities during pregnancy or the newborn period, gestational age or the burden of treatment in the neonatal intensive care unit did not predict sleep problems. None of the studied prenatal or neonatal factors predicted daytime sleepiness or sleep duration <9 h. Conclusion: Of numerous prenatal and neonatal factors, only smoking during pregnancy, being born small for gestational age and cerebral hemorrhage predicted sleep problems at 11 years of age among these children born EPT.
Gut microbiota dysbiosis and diarrhea in kidney transplant recipients

Posttransplant diarrhea is associated with kidney allograft failure and death, but its etiology remains unknown in the majority of cases. Because altered gut microbial ecology is a potential basis for diarrhea, we investigated whether posttransplant diarrhea is associated with gut dysbiosis. We enrolled 71 kidney allograft recipients for serial fecal specimen collections in the first 3 months of transplantation and profiled the gut microbiota using 16S ribosomal RNA (rRNA) gene V4‐V5 deep sequencing. The Shannon diversity index was significantly lower in 28 diarrheal fecal specimens from 25 recipients with posttransplant diarrhea than in 112 fecal specimens from 46 recipients without posttransplant diarrhea. We found a lower relative abundance of 13 commensal genera (Benjamini‐Hochberg adjusted P ≤ .15) in the diarrheal fecal specimens including the same 4 genera identified in our prior study. The 28 diarrheal fecal specimens were also evaluated by a multiplexed polymerase chain reaction (PCR) assay for 22 bacterial, viral, and protozoan gastrointestinal pathogens, and 26 specimens were negative for infectious etiologies. Using PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) to predict metagenomic functions, we found that diarrheal fecal specimens had a lower abundance of metabolic genes. Our findings suggest that posttransplant diarrhea is not associated with common infectious diarrheal pathogens but with a gut dysbiosis.
Hypertonic Lactate to Improve Cerebral Perfusion and Glucose Availability After Acute Brain Injury*

Objectives: Lactate promotes cerebral blood flow and is an efficient substrate for the brain, particularly at times of glucose shortage. Hypertonic lactate is neuroprotective after experimental brain injury; however, human data are limited. Design: Prospective study (clinicaltrials.gov NCT01573507). Setting: Academic ICU. Patients: Twenty-three brain-injured subjects (13 traumatic brain injury/10 subarachnoid hemorrhage; median age, 59 yr [41–65 yr]; median Glasgow Coma Scale, 6 [3–7]). Interventions: Three-hour IV infusion of hypertonic lactate (sodium lactate, 1,000 mmol/L; concentration, 30 µmol/kg/min) administered 39 hours (26–49 hr) from injury. Measurements and Main Results: We examined the effect of hypertonic lactate on cerebral perfusion (using transcranial Doppler) and brain energy metabolism (using cerebral microdialysis). The majority of subjects (13/23 = 57%) had reduced brain glucose availability (baseline pretreatment cerebral microdialysis glucose, < 1 mmol/L) despite normal baseline intracranial pressure (10 [7–15] mm Hg). Hypertonic lactate was associated with increased cerebral microdialysis lactate (+55% [31–80%]) that was paralleled by an increase in middle cerebral artery mean cerebral blood flow velocities (+36% [21–66%]) and a decrease in pulsatility index (–21% [13–26%]; all p < 0.001). Cerebral microdialysis glucose increased above normal range during hypertonic lactate (+42% [30–78%]; p < 0.05); reduced brain glucose availability correlated with a greater improvement of cerebral microdialysis glucose (Spearman r = –0.53; p = 0.009). No significant changes in cerebral perfusion pressure, mean arterial pressure, systemic carbon dioxide, and blood glucose were observed during hypertonic lactate (all p > 0.1). Conclusions: This is the first clinical demonstration that hypertonic lactate resuscitation improves both cerebral perfusion and brain glucose availability after brain injury. These cerebral vascular and metabolic effects appeared related to brain lactate supplementation rather than to systemic effects.
Seasonal Body Composition Variation Amongst Elite European Professional Soccer Players: An Approach of Talent Identification

Abstract The primary aim of the investigation was to study the seasonal changes in body composition in elite European soccer players and identify key playing positional differences. Twenty-two players (age = 24 ± 3.7 years, body height = 180.45 ± 5.12 cm, body mass = 76.66 ± 5.34 kg) were tested. Players’ mass (kg), lean body mass (LBM), fat free mass (FFM), fat mass (FM), muscle girths (MG) and sum of 8 skinfolds (mm) were measured across 5 time points (T0 = Start of pre-season training; T1 = End of pre-season training; T2 = Mid-season; T3 = End of mid-season break; T4 = End of season). Players were divided into their tactical positional roles for analysis. The specific positions they were divided into included defenders (n = 8), midfielders (n = 8) and forwards (n = 6). Assessment of training and matchplay exposure were also recorded. Sites-4, Sites-7, Sites-8 and Fat Mass decreased dramatically from T0 to T1 and T2 in all playing positions (p < 0.01), while no remarkable differences were found between T2, T3 and T4. Except for defenders, calf girth and lean mass were higher in T2, T3 and T4 compared to T0 and T1 (p < 0.01). Midfielders were found to be leaner than forwards and defenders in all data collection time point sessions. Defenders showed higher values in calf girth and lean body mass than midfielders and forwards. It can be concluded from this investigation that there are large variances n positional body composition profiles amongst professional European soccer players. Furthermore, significant changes are prevalent and occur across the season from LBM, FFM, MG and skinfold assessment amongst European elite level soccer players.
Search for source rocks of the crude oils of the Drmno depression (southern part of the Pannonian Basin, Serbia)

In a search for source rocks of the crude oils of the Drmno depression (southern part of the Pannonian Basin, Serbia), based on bulk and specific organic geochemical pa- rameters, six out of eight Sirakovo, Bubu{inac and Bradarac sedimentary core samples were found to possess typical source rock characteristics. By comparing the results observed for these sedimentary samples with the corresponding properties of the crude oils from the Sirakovo and Bradarac oil-gas fields, a positive organic geochemical oil-source rock correla- tion was experienced for the first time within this basin. This finding may be considered as an important step towards the ultimate organic geochemical/geological interpretation of the Drmno depression.
FrankenGAN

Coarse building mass models are now routinely generated at scales ranging from individual buildings to whole cities. Such models can be abstracted from raw measurements, generated procedurally, or created manually. However, these models typically lack any meaningful geometric or texture details, making them unsuitable for direct display. We introduce the problem of automatically and realistically decorating such models by adding semantically consistent geometric details and textures. Building on the recent success of generative adversarial networks (GANs), we propose FrankenGAN, a cascade of GANs that creates plausible details across multiple scales over large neighborhoods. The various GANs are synchronized to produce consistent style distributions over buildings and neighborhoods. We provide the user with direct control over the variability of the output. We allow him/her to interactively specify the style via images and manipulate style-adapted sliders to control style variability. We test our system on several large-scale examples. The generated outputs are qualitatively evaluated via a set of perceptual studies and are found to be realistic, semantically plausible, and consistent in style.
Technical complications following implant‐supported restorative therapy performed in Sweden

OBJECTIVE The aim of this study was to evaluate the occurrence and consequences of technical complications in implant-supported restorative therapy. MATERIAL & METHODS The occurrence and consequences of technical complications in implant-supported restorative therapy over a mean follow-up period of 5.3 years were assessed based on documentation in files from 2,666 patients. Risk indicators were identified by the use of survival models, considering repeated events. Results were expressed as hazard ratios (HR) including 95% confidence intervals. RESULTS Technical complications occurred in 24.8% of the patients. Chipping and loss of retention were the most common, affecting 11.0% and 7.9% of supraconstructions, respectively, while implant-related complications (e.g., implant fracture) were rare. More than 50% of the affected patients experienced technical complications more than once and almost all reported complications led to interventions by a dental professional. The extent of the supraconstruction was the strongest risk indicator for both chipping (HR < 0.2) and loss of retention (HR > 3). CONCLUSION Over a 5-year period, technical complications in implant-supported restorative therapy occurred frequently and their management required professional intervention.
Comparison of microdosimetry-based absorbed doses to control tumours and clinically obtained tumour absorbed doses in treatments with 223Ra

We performed Monte Carlo simulations in order to determine by means of microdosimetry calculations the average number of hits to the cell nucleus required to reach a tumour control probability (TCP) of 0.9, , for the source geometry of a nucleus embedded in a homogeneous distribution of 223Ra atoms. From the results obtained and following the MIRD methodology, we determined the values of lesion absorbed doses needed to reach a TCP of 0.9, , for different values of mass density, cell radiosensitivity, nucleus radius and lesion volume. The greatest variation of those absorbed doses occurred with cell radiosensitivity and no dependence was found on mass density. The source geometry used was chosen because we aimed to compare the values of with the lesion absorbed doses obtained from image-based macrodosimetry in treatments of metastatic castration-resistant prostate cancer with 223Ra which were obtained assuming a homogeneous distribution of 223Ra atoms within the lesion. In a comparison with a study including 29 lesions, results showed that even for the case of the most radiosensitive cells simulated, 45% of the lesions treated following a schedule of two cycles of 110 kBq kg−1 body mass would receive absorbed doses below the values of determined in this study.
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) is a widely deployed method to sample from high-dimensional distributions in Statistics and Machine learning. HMC is known to run very efficiently in practice and its popular second-order ``leapfrog" implementation has long been conjectured to run in $d^{1/4}$ gradient evaluations. Here we show that this conjecture is true when sampling from strongly log-concave target distributions that satisfy a weak third-order regularity property associated with the input data. Our regularity condition is weaker than the Lipschitz Hessian property and allows us to show faster convergence bounds for a much larger class of distributions than would be possible with the usual Lipschitz Hessian constant alone. Important distributions that satisfy our regularity condition include posterior distributions used in Bayesian logistic regression for which the data satisfies an ``incoherence" property. Our result compares favorably with the best available bounds for the class of strongly log-concave distributions, which grow like $d^{{1}/{2}}$ gradient evaluations with the dimension. Moreover, our simulations on synthetic data suggest that, when our regularity condition is satisfied, leapfrog HMC performs better than its competitors -- both in terms of accuracy and in terms of the number of gradient evaluations it requires.
Mental versus physical fatigue after subarachnoid hemorrhage: differential associations with outcome

Fatigue is a major consequence of subarachnoid hemorrhage (SAH), but the specific characteristics are unclear. Our objective was to investigate the nature of post‐SAH fatigue (mental or physical) and to determine the relationship with functional outcome in the chronic stage. Also, the possible influence of mood disorders and acute SAH‐related factors [SAH type and external cerebrospinal fluid (CSF) drainage] on the presence of fatigue was investigated.
Itaconic acid mediates crosstalk between macrophage metabolism and peritoneal tumors

Control of cellular metabolism is critical for efficient cell function, although little is known about the interplay between cell subset–specific metabolites in situ, especially in the tumor setting. Here, we determined how a macrophage-specific (Mϕ-specific) metabolite, itaconic acid, can regulate tumor progression in the peritoneum. We show that peritoneal tumors (B16 melanoma or ID8 ovarian carcinoma) elicited a fatty acid oxidation–mediated increase in oxidative phosphorylation (OXPHOS) and glycolysis in peritoneal tissue–resident macrophages (pResMϕ). Unbiased metabolomics identified itaconic acid, the product of immune-responsive gene 1–mediated (Irg1-mediated) catabolism of mitochondrial cis-aconitate, among the most highly upregulated metabolites in pResMϕ of tumor-bearing mice. Administration of lentivirally encoded Irg1 shRNA significantly reduced peritoneal tumors. This resulted in reductions in OXPHOS and OXPHOS-driven production of ROS in pResMϕ and ROS-mediated MAPK activation in tumor cells. Our findings demonstrate that tumors profoundly alter pResMϕ metabolism, leading to the production of itaconic acid, which potentiates tumor growth. Monocytes isolated from ovarian carcinoma patients’ ascites fluid expressed significantly elevated levels of IRG1. Therefore, IRG1 in pResMϕ represents a potential therapeutic target for peritoneal tumors.
How to Maintain Maximal Straight Path Running Speed on a Curved Path in Sprint Events

Abstract This study aims to clarify the ideal technique for running on a curved path during sprinting events. Participants were twelve male track and field athletes including long jumpers and sprinters. The participants performed a 60-m sprint with maximal effort on straight and curved paths. Participants were divided into “good curve runners” and “poor curve runners” according to the curved path running speed relative to that of the straight path. Kinematic variables and ground reaction forces (GRFs) were registered and compared between the groups and paths. The running speed, step length, and flight distance of the outside leg on the curved path were lower than on the straight path only in poor curve runners. The medial-lateral GRF and impulse showed an increase during curved path running for both groups. However, the maximum posterior GRF and impulse decreased only in poor curve runners. The ideal technique for running on a curved path is to maintain the same kinematics and kinetics in the sagittal plane as on a straight path.