Miracle-dz/UniFAR-FTUs huggingface dataset:
The association between hospital case volume and in-hospital and one-year mortality after hip fracture surgery.

AIMS Hospital case volume is shown to be associated with postoperative outcomes in various types of surgery. However, conflicting results of volume-outcome relationship have been reported in hip fracture surgery. This retrospective cohort study aimed to evaluate the association between hospital case volume and postoperative outcomes in patients who had hip fracture surgery. We hypothesized that higher case volume would be associated with lower risk of in-hospital and one-year mortality after hip fracture surgery. METHODS Data for all patients who underwent surgery for hip fracture from January 2008 to December 2016 were extracted from the Korean National Healthcare Insurance Service database. According to mean annual case volume of surgery for hip fracture, hospitals were classified into very low (< 30 cases/year), low (30 to 50 cases/year), intermediate (50 to 100 cases/year), high (100 to 150 cases/year), or very high (> 150 cases/year) groups. The association between hospital case volume and in-hospital mortality or one-year mortality was assessed using the logistic regression model to adjust for age, sex, type of fracture, type of anaesthesia, transfusion, comorbidities, and year of surgery. RESULTS Between January 2008 and December 2016, 269,535 patients underwent hip fracture surgery in 1,567 hospitals in Korea. Compared to hospitals with very high volume, in-hospital mortality rates were significantly higher in those with high volume (odds ratio (OR) 1.10, 95% confidence interval ((CI) 1.02 to 1.17, p = 0.011), low volume (OR 1.22, 95% CI 1.14 to 1.32, p < 0.001), and very low volume (OR 1.25, 95% CI 1.16 to 1.34, p < 0.001). Similarly, hospitals with lower case volume showed higher one-year mortality rates compared to hospitals with very high case volume (low volume group, OR 1.15, 95% CI 1.11 to 1.19, p < 0.001; very low volume group, OR 1.10, 95% CI 1.07 to 1.14, p < 0.001). CONCLUSION Higher hospital case volume of hip fracture surgery was associated with lower in-hospital mortality and one-year mortality in a dose-response fashion. Cite this article: Bone Joint J 2020;102-B(10):1384-1391.
Identification and Reproducibility of Plasma Metabolomic Biomarkers of Habitual Food Intake in a US Diet Validation Study

Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet–metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46–0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies.
Design, Fabrication, and Validation of a Petri Dish-Compatible PDMS Bioreactor for the Tensile Stimulation and Characterization of Microtissues

In this paper, we report on a novel biocompatible micromechanical bioreactor (actuator and sensor) designed for the in situ manipulation and characterization of live microtissues. The purpose of this study was to develop and validate an application-targeted sterile bioreactor that is accessible, inexpensive, adjustable, and easily fabricated. Our method relies on a simple polydimethylsiloxane (PDMS) molding technique for fabrication and is compatible with commonly-used laboratory equipment and materials. Our unique design includes a flexible thin membrane that allows for the transfer of an external actuation into the PDMS beam-based actuator and sensor placed inside a conventional 35 mm cell culture Petri dish. Through computational analysis followed by experimental testing, we demonstrated its functionality, accuracy, sensitivity, and tunable operating range. Through time-course testing, the actuator delivered strains of over 20% to biodegradable electrospun poly (D, L-lactide-co-glycolide) (PLGA) 85:15 non-aligned nanofibers (~91 µm thick). At the same time, the sensor was able to characterize time-course changes in Young’s modulus (down to 10–150 kPa), induced by an application of isopropyl alcohol (IPA). Furthermore, the actuator delivered strains of up to 4% to PDMS monolayers (~30 µm thick), simultaneously characterizing their elastic modulus up to ~2.2 MPa. The platform repeatedly applied dynamic (0.23 Hz) tensile stimuli to live Human Dermal Fibroblast (HDF) cells for 12 hours (h) and recorded the cellular reorientation towards two angle regimes, with averages of −58.85° and +56.02°. The device biocompatibility with live cells was demonstrated for one week, with no signs of cytotoxicity. We can conclude that our PDMS bioreactor is advantageous for low-cost tissue/cell culture micromanipulation studies involving mechanical actuation and characterization. Our device eliminates the need for an expensive experimental setup for cell micromanipulation, increasing the ease of live-cell manipulation studies by providing an affordable way of conducting high-throughput experiments without the need to open the Petri dish, reducing manual handling, cross-contamination, supplies, and costs. The device design, material, and methods allow the user to define the operational range based on their targeted samples/application.
An Isolated Population of the Virginia Varying Hare

ment Station. The catch per hour per angler for 1946-1948 was 0.166, and for 1949-1951 it was 0.149; the difference (0.017) is not statistically significant (Table 4). The probable reason that the angling quality exhibited little change lies in the fact that the stream temperature increase after replacement of the dam, although of statistically significant proportions, was well within the limits of physiological tolerance by brook trout. If, for example, midsummer water temperatures had averaged 68-70' F. before the dam was constructed, and if the same increases in water temperature had resulted from the impoundment, the stream very likely would have been reduced to the status of a marginal trout water or would have been lost as trout water entirely. Accepted for publication October 15, 1953.
A Stearoyl–Coenzyme A Desaturase Inhibitor Prevents Multiple Parkinson Disease Phenotypes in α‐Synuclein Mice

Parkinson disease (PD) has useful symptomatic treatments that do not slow the neurodegenerative process, and no significant disease‐modifying treatments are approved. A key therapeutic target in PD is α‐synuclein (αS), which is both genetically implicated and accumulates in Lewy bodies rich in vesicles and other lipid membranes. Reestablishing αS homeostasis is a central goal in PD. Based on previous lipidomic analyses, we conducted a mouse trial of a stearoyl–coenzyme A desaturase (SCD) inhibitor (“5b”) that prevented αS‐positive vesicular inclusions and cytotoxicity in cultured human neurons.
Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach

Background Deep learning models have attracted significant interest from health care researchers during the last few decades. There have been many studies that apply deep learning to medical applications and achieve promising results. However, there are three limitations to the existing models: (1) most clinicians are unable to interpret the results from the existing models, (2) existing models cannot incorporate complicated medical domain knowledge (eg, a disease causes another disease), and (3) most existing models lack visual exploration and interaction. Both the electronic health record (EHR) data set and the deep model results are complex and abstract, which impedes clinicians from exploring and communicating with the model directly. Objective The objective of this study is to develop an interpretable and accurate risk prediction model as well as an interactive clinical prediction system to support EHR data exploration, knowledge graph demonstration, and model interpretation. Methods A domain-knowledge–guided recurrent neural network (DG-RNN) model is proposed to predict clinical risks. The model takes medical event sequences as input and incorporates medical domain knowledge by attending to a subgraph of the whole medical knowledge graph. A global pooling operation and a fully connected layer are used to output the clinical outcomes. The middle results and the parameters of the fully connected layer are helpful in identifying which medical events cause clinical risks. DG-Viz is also designed to support EHR data exploration, knowledge graph demonstration, and model interpretation. Results We conducted both risk prediction experiments and a case study on a real-world data set. A total of 554 patients with heart failure and 1662 control patients without heart failure were selected from the data set. The experimental results show that the proposed DG-RNN outperforms the state-of-the-art approaches by approximately 1.5%. The case study demonstrates how our medical physician collaborator can effectively explore the data and interpret the prediction results using DG-Viz. Conclusions In this study, we present DG-Viz, an interactive clinical prediction system, which brings together the power of deep learning (ie, a DG-RNN–based model) and visual analytics to predict clinical risks and visually interpret the EHR prediction results. Experimental results and a case study on heart failure risk prediction tasks demonstrate the effectiveness and usefulness of the DG-Viz system. This study will pave the way for interactive, interpretable, and accurate clinical risk predictions.
Intrapersonal Factors Impact Advance Care Planning Among Cancer Patients

Background: Cancer patients infrequently engage in advance care planning processes. Establishing preferences for future medical treatment without advance care planning may not be patient-centered, as it fails to consider important factors that influence these important decisions. Objective: The purpose of this study was to assess the influence of patient intrapersonal factors including race, religion, level of depression, and cancer stage on overall preferences for future medical treatment, including the presence of a (DNR), power of attorney, and advance directive. Design: A retrospective chart review design was used. Patients were included who were diagnosed with cancer at The Ohio State University James Comprehensive Cancer Center from 01/2015 to 08/2019. Results: A total of 3,463 patients were included. Median age was 59 years (IQR: 49, 67) and the majority of the patients was female (88.7%). Compared with no religious preference, patients who identified as religious had 61% higher odds (95%CI: 1.08-2.40) of having a DNR and approximately 30% higher odds of having a power of attorney (95%CI: 1.08-1.62) or advance directive (95%CI: 1.02-1.64). Patients with clinically relevant depression had more than twice the odds of having a DNR versus patients with no/lower levels of clinical depression (OR: 2.08; 95%CI: 1.40-3.10). White patients had higher odds of having a power of attorney (OR: 1.57; 95%CI: 1.16-2.13) and an advance directive (OR: 3.10; 95% CI: 1.95-4.93) than African-American/Black patients. Conclusions: Understanding the factors that affect preferences for future medical treatment is necessary for medical professionals to provide proper care and support to patients diagnosed with cancer and their families.
FMO1 Is Involved in Excess Light Stress-Induced Signal Transduction and Cell Death Signaling

Because of their sessile nature, plants evolved integrated defense and acclimation mechanisms to simultaneously cope with adverse biotic and abiotic conditions. Among these are systemic acquired resistance (SAR) and systemic acquired acclimation (SAA). Growing evidence suggests that SAR and SAA activate similar cellular mechanisms and employ common signaling pathways for the induction of acclimatory and defense responses. It is therefore possible to consider these processes together, rather than separately, as a common systemic acquired acclimation and resistance (SAAR) mechanism. Arabidopsis thaliana flavin-dependent monooxygenase 1 (FMO1) was previously described as a regulator of plant resistance in response to pathogens as an important component of SAR. In the current study, we investigated its role in SAA, induced by a partial exposure of Arabidopsis rosette to local excess light stress. We demonstrate here that FMO1 expression is induced in leaves directly exposed to excess light stress as well as in systemic leaves remaining in low light. We also show that FMO1 is required for the systemic induction of ASCORBATE PEROXIDASE 2 (APX2) and ZINC-FINGER OF ARABIDOPSIS 10 (ZAT10) expression and spread of the reactive oxygen species (ROS) systemic signal in response to a local application of excess light treatment. Additionally, our results demonstrate that FMO1 is involved in the regulation of excess light-triggered systemic cell death, which is under control of LESION SIMULATING DISEASE 1 (LSD1). Our study indicates therefore that FMO1 plays an important role in triggering SAA response, supporting the hypothesis that SAA and SAR are tightly connected and use the same signaling pathways.
The Impact of Controlled Ovarian Stimulation Hormones on the Metabolic State and Endocannabinoid System of Human Cumulus Cells

Different Follicle Stimulating Hormone (FSH) formulation and Luteinizing Hormone (LH) are used in Assisted Reproductive Technology (ART) to induce follicles development and oocytes maturation, but it is still under debate which protocol is to be preferred. In the present study, the different effects on cumulus cells (CCs) of three controlled ovarian stimulation (COS) protocols, based on urinary FSH, recombinant FSH, or human Menopausal Gonadotropin (hMG) administration, were assessed. CCs were obtained from 42 normal-responders women undergoing COS, randomly divided into three groups according to the used gonadotropin formulation. Differences were found in the expression of genes belonging to the endocannabinoid system (the receptors CNR1, CNR2 and TRPV1, and the enzymes involved in the metabolisms of anandamide, NAPE-PLD and FAAH, and 2-acylglycerol, DAGL and MAGL); consistently, changes in lipid (PPARα, and FASN) and carbohydrate (GLUT1 and GLUT9) metabolisms, in CCs’ macromolecules composition (highlighted by Fourier Transform Infrared Microspectroscopy, FTIRM), and in the number of retrieved oocytes were found. For the first time, statistically significant evidence on the differences related to each COS protocol on the endocannabinoid system, metabolism and macromolecular composition of CCs was found, representing a proof of concept to be further confirmed in a larger cohort of patients.
THE OPTIMUM FLIGHT SPEEDS OF FLYING ANIMALS

Conventional models of bird flight combine metabolic, mechanical, and aerodynamic components to calculate the rate of fuel consumption and power required for flight, from which we may derive the optimal speeds flying animals should use in different situations. These models contain the implicit assumption that the metabolic and mechanical components of power output are constant and show no systematic variation with speed. This assumption underlies the optimum flight speeds, optimum climb protocol, maximum endurance and maximum flight range predicted by these models. Here we consider alternatives to the assumption that power is independent of speed and show that if the aerodynamic power output from a constant rate of fuel consumption varies with flight speed, then the optima derived from current models of animal flight need to be revised. In some cases (e.g. optimum flight speeds) the current models give answers that are only quantitatively wrong, but in some cases (e.g. optimal cruising altitude) current models give answers that are qualitatively wrong.
Effect of a brief scenario-tailored educational program on parents' risk knowledge, perceptions and decisions to administer prescribed opioids: a randomized controlled trial.

This randomized, controlled trial evaluated whether a brief educational program (i.e., Scenario-Tailored Opioid Messaging Program [STOMP]) would improve parental opioid risk knowledge, perceptions, and analgesic efficacy; ensure safe opioid use decisions, and impact prescription opioid use after surgery. Parent-child dyads (n=604) who were prescribed an opioid for short-term use were randomized to routine instruction (Control) or routine plus STOMP administered preoperatively. Baseline and follow-up surveys assessed parents' awareness and perceived seriousness of adverse opioid effects, and their analgesic efficacy. Parents' decisions to give an opioid in hypothetical scenarios and total opioid doses they gave to children at home were assessed at follow-up. STOMP parents gained enhanced perceptions of opioid-related risks over time while Controls did not; however, risk perceptions did not differ between groups except for addiction risk. STOMP parents exhibited marginally greater self-efficacy compared to Controls (mean difference vs. controls=0.58 [95% CI 0.08, 1.09], p=.023). STOMP parents had a 53% lower odds of giving an opioid in an excessive sedation scenario (odds ratio 0.47 [95% CI 0.28, 0.78], p=.003), but otherwise made similar scenario-based opioid decisions. STOMP was not associated with total opioid doses administered at home. Instead, parents' analgesic efficacy and pain-relief preferences explained 7%, while child and surgical factors explained 22% of the variance in opioid doses. Scenario-tailored education enhanced parents' opioid risk knowledge, perceptions and scenario-based decision-making. While this may inform later situation-specific decision-making, our research did not demonstrate an impact on total opioid dosing which was primarily driven by surgical and child-related factors.
Intraprocedurally EOB-MRI/US fusion imaging focusing on hepatobiliary phase findings can help to reduce the recurrence of hepatocellular carcinoma after radiofrequency ablation

Abstract Background & aims To explore the ability of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI)/ultrasound (US) fusion imaging (FI) to improve the prognosis of radiofrequency ablation (RFA) by ablating the characteristic findings of hepatocellular carcinoma (HCC) in hepatobiliary phase (HBP) imaging. Methods We retrospectively recruited 115 solitary HCC lesions with size of (15.9 ± 4.6) mm. They were all treated by RFA and preoperative EOB-MRI. According to the modalities guiding RFA performance, the lesions were grouped into contrast enhanced US (CEUS)/US guidance group and EOB-MRI/US FI guidance group. For the latter group, the ablation scope was set to cover the HBP findings (peritumoral hypointensity and irregular protruding margin). The presence of HBP findings, the modalities guided RFA, the recurrence rate were observed. Results After an average follow-up of 377 days, local tumor progression (LTP) and intrahepatic distant recurrence (IDR) were 14.8% and 38.4%, respectively. The lesions having HBP findings exhibited a higher recurrence rate (73.7%) than the lesions without HBP findings (42.9%) (p = 0.002) and a low overall recurrence-free curve using the Kaplan-Meier method (p = 0.038). Using EOB-MRI/US FI as guidance, there was no difference in the recurrence rate between the groups with and without HBP findings (p = 0.799). In lesions with HBP findings, RFA guided by EOB-MRI/US FI (53.8%) produced a lower recurrence rate than CEUS/US (84.0%) (p = 0.045). Conclusions The intraprocedurally application of EOB-MRI/US FI to determine ablation scope according to HBP findings is feasible and beneficial for prognosis of RFA.
First Report on the Finding of Listeria mnocytogenes ST121 Strain in a Dolphin Brain

Listeria monocytogenes (Lm) is a ubiquitous bacterium that causes the foodborne illness, listeriosis. Clonal complexes (CC), such as CC121, are overrepresented in the food production industry, and are rarely reported in animals and the environment. Working within a European-wide project, we investigated the routes by which strains are transmitted from environments and animals to food and the food production environment (FPE). In this context, we report, for the first time, the occurrence of a ST121 (CC121) strain isolated from a dolphin brain. The genome was compared with the genomes of 376 CC121 strains. Genomic comparisons showed that 16 strains isolated from food were the closest to the dolphin strain. Like most of the food strains analyzed here, the dolphin strain included genomic features (transposon Tn6188, plasmid pLM6179), both described as being associated with the strain’s adaptation to the FPE. Like all 376 strains, the dolphin strain contained a truncated actA gene and inlA gene, both described as being associated with attenuated virulence. Despite this fact, the strain was able to cross blood-brain barrier in immunosuppressed dolphin exposed polychlorinated biphenyl and invaded by parasites. Our data suggest that the dolphin was infected by a food-related strain released into the Mediterranean Sea.
Projecting the continental accumulation of alien species through to 2050

Biological invasions have steadily increased over recent centuries. However, we still lack a clear expectation about future trends in alien species numbers. In particular, we do not know whether alien species will continue to accumulate in regional floras and faunas, or whether the pace of accumulation will decrease due to the depletion of native source pools. Here, we apply a new model to simulate future numbers of alien species based on estimated sizes of source pools and dynamics of historical invasions, assuming a continuation of processes in the future as observed in the past (a business‐as‐usual scenario). We first validated performance of different model versions by conducting a back‐casting approach, therefore fitting the model to alien species numbers until 1950 and validating predictions on trends from 1950 to 2005. In a second step, we selected the best performing model that provided the most robust predictions to project trajectories of alien species numbers until 2050. Altogether, this resulted in 3,790 stochastic simulation runs for 38 taxon–continent combinations. We provide the first quantitative projections of future trajectories of alien species numbers for seven major taxonomic groups in eight continents, accounting for variation in sampling intensity and uncertainty in projections. Overall, established alien species numbers per continent were predicted to increase from 2005 to 2050 by 36%. Particularly, strong increases were projected for Europe in absolute (+2,543 ± 237 alien species) and relative terms, followed by Temperate Asia (+1,597 ± 197), Northern America (1,484 ± 74) and Southern America (1,391 ± 258). Among individual taxonomic groups, especially strong increases were projected for invertebrates globally. Declining (but still positive) rates were projected only for Australasia. Our projections provide a first baseline for the assessment of future developments of biological invasions, which will help to inform policies to contain the spread of alien species.