Miracle-dz/UniFAR-FTUs huggingface dataset:
REG1A and RUNX3 Are Potential Biomarkers for Predicting the Risk of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Clinical features are traditionally used to predict DKD, yet with low diagnostic efficacy. Most of the recent biomarkers used to predict DKD are based on transcriptomics and metabolomics; however, they also should be used in combination with many other predictive indicators. The purpose of this study was thus to identify a simplified class of blood biomarkers capable of predicting the risk of developing DKD. The Gene Expression Omnibus database was screened for DKD biomarkers, and differentially expressed genes (DEGs) in human blood and kidney were identified via gene expression analysis and the Least Absolute Shrinkage and Selection Operator regression. A comparison of the area under the curve (AUC) profiles on multiple receiver operating characteristic curves of the DEGs in DKD and other renal diseases revealed that REG1A and RUNX3 had the highest specificity for DKD diagnosis. The AUCs of the combined expression of REG1A and RUNX3 in kidney (AUC = 0.929) and blood samples (AUC = 0.917) of DKD patients were similar to each other. The AUC of blood samples from DKD patients and healthy individuals obtained for external validation further demonstrated that REG1A combined with RUNX3 had significant diagnostic efficacy (AUC=0.948). REG1A and RUNX3 expression levels were found to be positively and negatively correlated with urinary albumin creatinine ratio and estimated glomerular filtration rate, respectively. Kaplan-Meier curves also revealed the potential of REG1A and RUNX3 for predicting the risk of DKD. In conclusion, REG1A and RUNX3 may serve as biomarkers for predicting the risk of developing DKD.
Low rank magnetic resonance fingerprinting

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.
Estimation of quantitative genetic parameters

This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximumlikelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill.
Associations of tumor necrosis factor-α polymorphisms with the risk of colorectal cancer: a meta-analysis

Background: Recently, the roles of tumor necrosis factor-α (TNF-α) polymorphisms in colorectal cancer (CRC) were analyzed by some pilot studies, with inconsistent results. Therefore, we performed the present study to better assess the relationship between TNF-α polymorphisms and the risk of CRC. Methods: Eligible studies were searched in PubMed, Medline, Embase and CNKI. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess correlations between TNF-α polymorphisms and CRC. Results: A total of 22 studies were included for analyses. A significant association with the risk of CRC was detected for TNF-α -308 G/A (recessive model: P = 0.004, OR = 1.42, 95%CI 1.12–1.79) polymorphism in overall analyses. Further subgroup analyses based on ethnicity of participants revealed that TNF-α -238 G/A was significantly correlated with the risk of CRC in Caucasians (dominant model: P = 0.01, OR = 0.47, 95%CI 0.26–0.86; overdominant model: P = 0.01, OR = 2.27, 95%CI 1.20–4.30; allele model: P = 0.02, OR = 0.51, 95%CI 0.29–0.90), while -308 G/A polymorphism was significantly correlated with the risk of CRC in Asians (recessive model: P = 0.001, OR = 2.23, 95%CI 1.38–3.63). Conclusions: Our findings indicated that TNF-α -238 G/A polymorphism may serve as a potential biological marker for CRC in Caucasians, and TNF-α -308 G/A polymorphism may serve as a potential biological marker for CRC in Asians.
Now or … later: Perceptual data are not immediately forgotten during language processing

Abstract Christiansen & Chater (C&C) propose that language comprehenders must immediately compress perceptual data by “chunking” them into higher-level categories. Effective language understanding, however, requires maintaining perceptual information long enough to integrate it with downstream cues. Indeed, recent results suggest comprehenders do this. Although cognitive systems are undoubtedly limited, frameworks that do not take into account the tasks that these systems evolved to solve risk missing important insights.
Short-Term Sleep Loss Alters Cytokine Gene Expression in Brain and Peripheral Tissues and Increases Plasma Corticosterone of Zebra Finch (Taeniopygia guttata)

Lack of sleep incurs physiological costs that include increased inflammation and alterations in the hypothalamic-pituitary-adrenal axis. Specifically, sleep restriction or deprivation leads to increased pro-inflammatory cytokine expression and elevated glucocorticoids in rodent models, but whether birds exact similar costs is unknown. In this study, we examined whether zebra finch (Taeniopygia guttata), an avian model species, exhibits physiological costs of sleep loss by using a novel automated sleep fragmentation/deprivation method, wherein a horizontal wire sweeps across a test cage to disrupt sleep every 120 s. We measured pro-inflammatory (IL-1β and IL-6) and anti-inflammatory (IL-10) cytokine gene expression in the periphery (fat, liver, spleen, and heart) and brain (hypothalamus, hippocampus, and apical hyperpallium) of captive finches after 12 h of exposure to a moving or stationary (control) bar during the night or the day. Plasma corticosterone, body mass, and behavioral profiles were also assessed. We predicted that birds undergoing sleep loss would exhibit elevated pro-inflammatory and reduced anti-inflammatory gene expression in brain and peripheral tissues compared with control birds. In addition, we predicted an increase in plasma corticosterone levels after sleep loss. As predicted, sleep loss increased pro-inflammatory gene expression, specifically in adipose tissue (IL-6), spleen (IL-1), and hippocampus (IL-6), but a decrease in anti-inflammatory expression (IL-10) was not detected. However, sleep loss elevated baseline concentrations of plasma corticosterone. Taken together, these results suggest that a diurnal songbird is sensitive to the costs of sleep loss.
Big data and biomedical informatics: Preparing for the modernization of clinical neuropsychology

Abstract Objective: Neuropsychology is poised for a fundamental shift as we modernize the ways in which behavior is measured. The amount and complexity of data generated by these new methods will be several orders of magnitude greater than what is currently created by analog measures and will quickly adopt characteristics of “Big Data. ” Adequate preparation for managing the influx of data will be critical for technology integration and modernization to be successful. Drawing from information technology, mathematics, statistics, computer science, and engineering, as well as, biology, genetics, and medicine, the field of biomedical informatics has rapidly evolved from its early days in computational biology to a burgeoning independent discipline that has much to offer neuropsychology. Method: Following a critical review of the relevant literature, the present article (1) provides an introductory overview of biomedical informatics and how these concepts are relevant to neuropsychology; (2) describes how biomedical informatics applications can be utilized to leverage existing data sources more effectively; and (3) discusses ideas for future developments designed to facilitate integration of new data derived from novel, technologically driven measurement tools. Within this context, applications intended for use by both the individual neuropsychologist to increase clinical efficiencies, as well as, larger field-wide initiatives intended to generate new information and derive new knowledge are discussed. Conclusions: By no means a comprehensive review of biomedical informatics, the present paper highlights that our approach to data needs to become a multidisciplinary endeavor in order to develop applications capable of effectively utilizing modern data sources.
Ultrasound Assessment of Gastric Content and Volume

Background:Aspiration of gastric contents can be a serious perioperative complication, attributing up to 9% of all anesthesia-related deaths. However, there is currently no practical, noninvasive bedside test to determine gastric content and volume in the perioperative period. Methods:The current study evaluates the feasibility of using bedside ultrasonography for assessing gastric content and volume. In the pilot phase, 18 healthy volunteers were examined to assess the gastric antrum, body, and fundus in cross-section in five prandial states: fasting and after ingestion of 250 mL of water, 500 mL of water, 500 mL of effervescent water, and a solid meal. In the phase II study, the authors concentrated on ultrasound examination of the gastric antrum in 36 volunteers for whom regression analysis was used to determine the correlation between gastric volume and antral cross-sectional area. Results:The gastric antrum provided the most reliable quantitative information for gastric volume. The antral cross-sectional area correlated with volumes of up to 300 mL in a close-to-linear fashion, particularly when subjects were in the right lateral decubitus position. Sonographic assessment of the gastric antrum and body provides qualitative information about gastric content (empty or not empty) and its nature (gas, fluid, or solid). The fundus was the gastric area least amenable to image and measure. Conclusions:Our preliminary results suggest that bedside two-dimensional ultrasonography can be a useful noninvasive tool to determine gastric content and volume.
Genome-wide identification of lncRNAs and mRNAs differentially expressed in non-functioning pituitary adenoma and construction of an lncRNA-mRNA co-expression network

ABSTRACT The involvement of long non-coding RNAs (lncRNAs) during tumorigenesis is a recent emerging theme. Yet no systematic evaluation of lncRNAs has been previously reported for non-functioning pituitary adenoma (NFPA), a fairly common type of intracranial tumor. Here, we report the first genome-wide expression profile for lncRNAs and mRNAs in NFPA, using formalin-fixed and paraffin-embedded tissue specimens. Using microarray analyses, we identified 113 lncRNAs and 80 mRNAs differentially expressed in NFPA; this list includes lncRNAs previously implicated in a variety of cancers. Using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) we further confirmed differential expression in NFPA for ten of the 113 lncRNAs. Using these ten doubly confirmed lncRNAs, we constructed an lncRNA-mRNA co-expression network comprising of 130 specific lncRNA-mRNA co-expression relationships. In addition, we conducted GO and KEGG analyses for the 80 mRNAs differentially expressed in NFPA. Our microarray and qRT-PCR analyses provided a working list of lncRNAs that may be functionally relevant to NFPA tumorigenesis. Our co-expression network in turn connected these largely uncharacterized lncRNAs to specific mRNAs, whose roles we further elucidated via GO and KEGG analyses, thus providing specific, testable hypotheses for the functions of these lncRNAs. Together, our study laid the foundation for future investigation of the specific function and mechanism by which lncRNAs are involved in NFPA tumorigenesis. Summary statement: We identified long non-coding RNAs and mRNAs differentially expressed in non-functioning pituitary adenomas via microarray analyses, and provided working hypotheses for how these RNAs may function via co-expression network analyses.
Does the Neurological Damage from a Traumatic Brain Injury Invalidate Measures of Psychopathology Such as the MMPI-2?

Objective The Gass correction model removes 14 items from the MMPI-2 which refer to neurological damage when assessing a person suffering a traumatic brain injury (TBI). Previous analysis supported ongoing inclusion of the five correction items from MMPI-2 Hs scale in individuals who suffered a TBI. This study investigates the remaining nine correction model items on the Hy and Sc scales. Participants A sample of patients with a TBI (n = 242), and the MMPI-2 normative sample (n = 2,600). Design Main Measures This is a cross-sectional study testing measurement invariance of two MMPI-2 scales (Hy and Sc) between the TBI and normative samples. Results Factor models for each scale were defined and assessed across multiple samples. The Hy scale generated a four-factor model (CFI range .913-.935, RMSEA range .025-.027). The Sc scale generated a five-factor model (CFI range .911-.962, RMSEA range .013-.018). Both models met the criteria of partial measurement invariance. Sensitivity and specificity analysis supported retaining all correction items when assessing persons with a TBI. Conclusions These results suggest continued inclusion of all 14 Gass correction model items when assessing a person with a TBI.
Distinct metabolic adjustments arise from acclimation to constant hypoxia and intermittent hypoxia in estuarine killifish (Fundulus heteroclitus)

ABSTRACT Many fish experience daily cycles of hypoxia in the wild, but the physiological strategies for coping with intermittent hypoxia are poorly understood. We examined how killifish adjust O2 supply and demand during acute hypoxia, and how these responses are altered after prolonged acclimation to constant or intermittent patterns of hypoxia exposure. We acclimated killifish to normoxia (∼20 kPa O2), constant hypoxia (2 kPa) or intermittent cycles of nocturnal hypoxia (12 h:12 h normoxia:hypoxia) for 28 days, and then compared whole-animal O2 consumption rates (ṀO2) and tissue metabolites during exposure to 12 h of hypoxia followed by reoxygenation in normoxia. Normoxia-acclimated fish experienced a pronounced 27% drop in ṀO2 during acute hypoxia, and modestly increased ṀO2 upon reoxygenation. They strongly recruited anaerobic metabolism during acute hypoxia, indicated by lactate accumulation in plasma, muscle, liver, brain, heart and digestive tract, as well as a transient drop in intracellular pH, and they increased hypoxia inducible factor (HIF)-1α protein abundance in muscle. Glycogen, glucose and glucose-6-phosphate levels suggested that glycogen supported brain metabolism in hypoxia, while the muscle used circulating glucose. Acclimation to constant hypoxia caused a stable ∼50% decrease in ṀO2 that persisted after reoxygenation, with minimal recruitment of anaerobic metabolism, suggestive of metabolic depression. By contrast, fish acclimated to intermittent hypoxia maintained sufficient O2 transport to support normoxic ṀO2, modestly recruited lactate metabolism and increased ṀO2 dramatically upon reoxygenation. Both groups of hypoxia-acclimated fish had similar glycogen, ATP, intracellular pH and HIF-1α levels as normoxic controls. We conclude that different patterns of hypoxia exposure favour distinct strategies for matching O2 supply and O2 demand. Summary: Fish acclimated to constant hypoxia induced metabolic depression, whereas fish acclimated to intermittent hypoxia maintained routine O2 demands, suggesting that distinct physiological mechanisms can be used to cope with different patterns of hypoxia exposure.
Analytical ART interruption does not irreversibly change pre-interruption levels of cellular HIV.

OBJECTIVE The impact of short-term analytical antiretroviral therapy (ART) interruptions on the levels of cellular HIV and of residual activation after subsequent ART-mediated plasma HIV viral load re-suppression remains under active investigation. DESIGN Peripheral blood mononuclear cells (PBMC) from 23 ART-suppressed, chronically HIV-1-infected subjects were evaluated at the initiation of an analytical treatment interruption (ATI), during ATI, and following plasma re-suppression of HIV with ART. METHODS T cell activation was measured by flow cytometry. Total cellular HIV DNA, and episomal 2-long terminal repeat (2-LTR) circles were measured by droplet digital PCR (ddPCR). Cellular HIV multiply spliced RNA (tat/rev), unspliced (gag), and poly(A) tailed transcripts [poly(A)] were measured by reverse transcriptase-ddPCR. Analyses were performed using R version 2.5. 1, or JMP Pro 11. RESULTS ATI (median ATI duration = 4 weeks) resulted in a rise of plasma HIV RNA (median = 72900 copies/ml), decrease in CD4 T cells/mm (median = 511.5 cells/mm; P = 0.0001), increase in T cell activation, and increase in cellular HIV DNA and RNA. Mean fluorescence intensity of CD38 on CD4HLA-DR T cells at baseline was positively associated with total HIV DNA levels during ATI (pol: P = 0.03, Rho = 0.44). Upon ART resumption, plasma HIV re-suppression occurred after a median of 13 weeks and resulted in restoration of pre-ATI CD4 T cells/mm, T cell activation, and levels of cellular HIV DNA and RNA. CONCLUSION Monitored viremia and immune activation during an ATI in ART-suppressed chronic HIV-infected subjects does not change the amount of persistent cellular HIV RNA or total HIV DNA after ART-mediated re-suppression.
ORTHOSCOPE: An Automatic Web Tool for Phylogenetically Inferring Bilaterian Orthogroups with User-Selected Taxa

Identification of orthologous or paralogous relationships of coding genes is fundamental to all aspects of comparative genomics. For accurate identification of orthologs among deeply diversified bilaterian lineages, precise estimation of gene trees is indispensable, given the complicated histories of genes over millions of years. By estimating gene trees, orthologs can be identified as members of an orthogroup, a set of genes descended from a single gene in the last common ancestor of all the species being considered. In addition to comparisons with a given species tree, purposeful taxonomic sampling increases the accuracy of gene tree estimation and orthogroup identification. Although some major phylogenetic relationships of bilaterians are gradually being unraveled, the scattering of published genomic data among separate web databases is becoming a significant hindrance to identification of orthogroups with appropriate taxonomic sampling. By integrating more than 250 metazoan gene models predicted in genome projects, we developed a web tool called ORTHOSCOPE to identify orthogroups of specific protein-coding genes within major bilaterian lineages. ORTHOSCOPE allows users to employ several sequences of a specific molecule and broadly accepted nodes included in a user-specified species tree as queries and to evaluate the reliability of estimated orthogroups based on topologies and node support values of estimated gene trees. A test analysis using data from 36 bilaterians was accomplished within 140 s. ORTHOSCOPE results can be used to evaluate orthologs identified by other stand-alone programs using genome-scale data. ORTHOSCOPE is freely available at https://www.orthoscope. jp or https://github.com/jun-inoue/orthoscope (last accessed December 28, 2018).
Importance of work environments on hospital outcomes in nine countries.

PURPOSE To determine the effect of hospital work environments on hospital outcomes across multiple countries. DESIGN Primary survey data using a common instrument were collected from separate cross sections of 98 116 bedside care nurses practising in 1406 hospitals in 9 countries between 1999 and 2009. MAIN OUTCOME MEASURES Nurse burnout and job dissatisfaction, patient readiness for hospital discharge and quality of patient care. RESULTS High nurse burnout was found in hospitals in all countries except Germany, and ranged from roughly a third of nurses to about 60% of nurses in South Korea and Japan. Job dissatisfaction among nurses was close to 20% in most countries and as high as 60% in Japan. Close to half or more of nurses in every country lacked confidence that patients could care for themselves following discharge. Quality-of-care rated as fair or poor varied from 11% in Canada to 68% in South Korea. Between one-quarter and one-third of hospitals in each country were judged to have poor work environments. Working in a hospital with a better work environment was associated with significantly lower odds of nurse burnout and job dissatisfaction and with better quality-of-care outcomes. CONCLUSIONS Poor hospital work environments are common and are associated with negative outcomes for nurses and quality of care. Improving work environments holds promise for nurse retention and better quality of patient care.
Budget impact analysis of niraparib and olaparib for maintenance treatment of platinum-sensitive, recurrent ovarian cancer in the US

Abstract Aims: This study aimed to evaluate the budget impact of niraparib and olaparib in patients with platinum-sensitive, recurrent ovarian cancer from a US third party payer perspective. Materials and methods: A budget impact model was constructed to assess the additional per member per month (PMPM) costs associated with the introduction of niraparib and olaparib, two poly ADP-ribose polymerase ribose polymerase (PARP) inhibitors recently approved to be used in platinum-sensitive, recurrent ovarian cancer patients with and without a gBRCA mutation. The model assessed both pharmacy costs and medical costs. Pharmacy costs included adjusted drug costs, coinsurance, and dispensing fees. Medical costs included costs associated with disease monitoring and management of adverse events from the treatment. Epidemiological data from the literature were used to estimate the target population size. The analysis used 1-year time frame, and patients were assumed on treatment until disease progression or death. All costs were computed in 2017 USD. One-way sensitivity analyses were conducted to evaluate the model robustness. Results: In a hypothetical plan of 1,000,000 members, 206 patients were estimated to be potential candidates for niraparib or olaparib maintenance treatment after applying all epidemiological parameters. At listed 30-day supply WAC prices of $14,750 for niraparib and $13,482 for olaparib, budget impacts of these two drugs were $0.169 PMPM and $0.156 PMPM, respectively, most of which were contributed by pharmacy costs. Sensitivity analyses suggested that assumptions around market share, platinum-sensitive rate after first treatment, and WAC prices affected results the most. Limitations: In this model, it was assumed that adopting niraparib and olaparib would not affect utilization of existing medications. Also, the estimated clinical parameters from clinical trials could differ from real-world data.