Miracle-dz/UniFAR-FTUs huggingface dataset:
Prophylactic Anticoagulation With Intermediate-Dose Certoparin in Vascular-Risk Pregnancies—The PACER-VARP Registry

The management of pregnant women at increased risk of thromboembolic/other vascular events is still a matter of debate. In a single-center, retrospective, observational trial, we analyzed the safety and efficacy of prophylactic anticoagulation with certoparin in pregnant women at intermediate- or high-risk by EThIG criteria of thromboembolic/other vascular events. Subcutaneous certoparin 8,000 IU once daily was administered immediately after pregnancy confirmation and continued for 6 weeks postpartum. We investigated 74 pregnancies (49 women; mean age 31.8 years; weight 77.3 kg). Most prevalent risk factors were factor V Leiden mutation (40.5%), thrombogenic factor II mutation (12.2%) and protein S deficiency (8.1%). In 76 control pregnancies prior to registry inclusion/without anticoagulation there were 14 cases [18.4%] of venous thromboembolism (between week 7 gestation and week 8 postpartum); 63.2% pregnancies resulted in abortion (median week 8.6 gestation). With certoparin anticoagulation, thromboembolism was 1.4%, exclusively non-major bleeding was 4.1% and abortion was 10.8%. One case of pre-eclampsia necessitating obstetric intervention occurred. Prophylactic anticoagulation with intermediate-dose certoparin throughout pregnancies at increased venous vascular risk was safe and effective.
Estimates of Intracellular Dopamine in Parkinson’s Disease: A Systematic Review and Meta-Analysis

Background: The hallmark of Parkinson’s disease is depletion of dopamine in the basal ganglia. Models of Parkinson’s disease include dopamine as a contributor to disease progression. However, intraneuronal levels of dopamine have not been reported. Objective: Meta-analytic methods were utilized to determine intracellular dopamine levels in Parkinson’s disease. Methods: A systematic review of the literature and frequentist meta-analyses were performed. Dopamine levels were scaled for cell and axon numbers as well as VMAT2 protein levels. Results: Reduced tissue dopamine, dopaminergic cell bodies and VMAT2 protein were confirmed. The ratio of Parkinson’s to normal brain intracellular dopamine scaled for either cell or axon number, each with VMAT2 level in the caudate ranged from 1.49 to 1.87 (p = 0.51 and p = 0.12, respectively) and in the putamen from 0.75 to 4.61 (p = 0.40 and 0.001, respectively). Conclusion: Free, intracellular dopamine levels are not reduced in Parkinson’s disease compared to normals to a similar degree as are total tissue concentrations, supporting the relevance of modulating VMAT2, neuromelanin and/or dopamine synthesis as rational neuroprotective strategies.
Effects of source water blending following treatment with sodium silicate as a corrosion inhibitor on metal release within a water distribution system

The effects of various sodium silicate corrosion inhibitor doses, ranging from 3 to 12 mg/L-SiO2, on iron release were investigated during a field study. The study was conducted within a preexisting drinking water distribution pilot system. The sources of iron release consisted of 1) lined cast iron, 2) un-lined cast iron, and 3) galvanized steel. Water quality changes occurred for each phase of operation (4 phases in total). Variations in water quality were implemented through blending differing proportions from 3 different source waters; groundwater, surface water, and desalinated water. The study analyzed both total and dissolved iron release. A nonlinear regression model was developed to describe total iron release in terms of water quality. A two-way ANOVA performed on the data set suggested that there was little validity for including silica dose in the empirical model. The empirical model suggested that alkalinity, chlorides, and pH had an effect on iron release (R = 0.36). Data included within the set for regressional analysis consisted of the experimental lines treated with sodium silicate and two control lines. One of the controls was designated as treatment with pH adjustment, while the other represented the equilibrium pH. Surface compositional analyses were performed on iron and galvanized steel coupons to offer incite into the possibility of protection by scale formation. Referring to silica deposits of the coupon surface, there was insufficient evidence that the coupons were different from those of the controls.
Extraction of Silver Ions from Aqueous Solutions by Emulsion Liquid Membrane

A comprehensive study pertaining to the emulsion liquid membrane (ELM) extraction process to enrich dilute aqueous solutions of silver salt is presented. The study has highlighted the importance and influence of membrane composition for maximizing the extraction of Ag+ ions. The liquid membrane was made up of Cyanex-302 as an extractant and the industrial solvent mainly consists of paraffinic and naphthenic hydrocarbons (C10-C14) as a diluent, Montane®-80 (sorbitan monooleate) as the surfactant and nitric acid solution as the stripping solution. The selection of the extractant (Cyanex-302) and the stripper (HNO3) was based on conventional liquid–liquid extraction studies. The role of pH as an important parameter in the LEM process for extraction of Ag+ was studied. Extraction of Ag+ increased with an increase in strip phase and carrier concentration. The fundamental parameters (emulsion stability, pH of the feed aqueous solution, agitation speed, surfactant concentration, strip phase concentration, carrier concentration, surfactant concentrations and treatment ratio) affecting the separation of Ag+ through the ELM were investigated to select the best combination of process parameters. The maximum extraction of Ag+ (about 99%) was achieved at a Montane®-80 concentration of 5% (v/v), strip phase concentration of 0.4M nitric acid and a phase ratio of 1:1.
Plasma volume status predicts prognosis in patients with acute heart failure syndromes

Background: The intravascular compartment is known as the plasma volume, and the extravascular compartment represents fluid within the interstitial space. Plasma volume expansion is a major symptom of heart failure. The aim of the current study was to investigate the impact of plasma volume status on the prognosis of acute heart failure syndromes. Methods and results: We analyzed 1115 patients with acute heart failure syndromes who were admitted to our hospital. These patients were divided into three groups based on their plasma volume status at admission: first tertile (plasma volume status <41.9%, n = 371), second tertile (41.9%⩽ plasma volume status <49.0%, n = 372), and third tertile (49.0%⩽ plasma volume status, n = 372). Plasma volume status was defined as follows: actual plasma volume = (1 − hematocrit) × [a + (b × body weight)] (a=1530 in males and a=864 in females, b=41.0 in males and b=47.9 in females); ideal plasma volume = c × body weight (c=39 in males and c=40 in females); and plasma volume status = [(actual plasma volume − ideal plasma volume)/ideal plasma volume] × 100 (%). In the Kaplan–Meier analysis, all-cause mortality, cardiac mortality and cardiac events increased progressively from the first to third tertile (p <0.001, respectively). In the Cox proportional hazard analysis, after adjusting for potential confounding factors, plasma volume status was an independent predictor of all-cause mortality (hazard ratio 1.429, p < 0.001), cardiac mortality (hazard ratio 1.416, p = 0.001) and cardiac events (hazard ratio 1.207, p = 0.004). Conclusion: Increased congestion is associated with increased morbidity and mortality in heart failure patients. Plasma volume status, which represents intravascular compartment and congestion, can identify poor prognosis in patients with acute heart failure syndromes.
Comparison between Adsorption in Pores of a Simple Geometry and Realistic Models of Porous Materials

We study, by means of Grand Canonical Monte Carlo simulations, the effect of disorder in pore morphology and topology on adsorption of simple fluids at 77 K. We consider the case of microporous carbons and mesoporous silicas. For both systems, we found that morphological and topological disorder affects the adsorption isotherm. Consequently, we show that complex porous networks cannot be modeled as a collection of unconnected pores of simple geometry. In the case of microporous carbons, the isosteric heat of adsorption for disordered systems differs significantly from that obtained for an assembly of unconnected slit pores. In contrast, the isosteric heat of adsorption for the disordered mesoporous silica sample compares reasonably well with that observed for a silica material having regular cylindrical pores.
Cr Incorporated MCM-41 Type Catalysts for Isobutane Dehydrogenation and Deactivation Mechanism

Cr incorporated MCM-41 type catalysts, which were prepared by direct hydrothermal synthesis and impregnation routes, were tested for dehydrogenation of isobutane. Among the surfactants (C17H38BrN, C19H42BrN, and C32H68BrN) used in the synthesis of MCM-41, C19H42BrN gave the best structure with ordered mesopores. Characterization results proved that chromium was very well dispersed within the MCM-41 lattice of the synthesized catalysts. In all of the synthesized catalysts, the presence of Cr6+ (2p3/2) in the form of chromates and Cr3+(2p1/2) in the form of CrOx or Cr2O3 was detected. All chromate types (mono, di, and poly) were observed in the catalyst synthesized hydrothermally according to the addition of metal solution simultaneously with silica source (CR_ALS). All characterization methods demonstrated that the highest amount of Cr6+ was present in this catalyst. Catalytic tests of the synthesized catalysts were carried out at 600 °C and at atmospheric pressure. The maximum conversion value (∼27%) was .
Impacts of Larval Diet on Pre-imaginal Development, Survival and Adult Size of Six Species of Coccinellidae (Coleoptera)

ABSTRACT: Laboratory reared predaceous lady beetles (Coccinellidae) have applications in many experiments, but can be challenging to rear optimally, especially since production of aphid prey can be time and space intensive. Alternatively, frozen Ephestia kuehniella Zeller (Lepidoptera: Pyralidae) eggs can be purchased and used to rear larvae. This study compared larval development, survival and adult size of six species of coccinellids on diets of Acyrthosiphon pisum Harris (Hemiptera: Aphididae) and E. kuehniella eggs. Larvae reared from field-collected adults were assigned to either A. pisum or E. kuehniella egg diets and fed ad libitum until pupation. Both diets were sufficient for development and did not impact survival for the six species. Coccinella Septempunctata L. developed faster and produced larger adults when fed A. pisum. Harmonia axyridis Pallas, Hippodamia Convergens Guerin and Coleomegilla maculata De Geer performed slightly better on E. kuehniella eggs. Based on these results, E. kuehniella eggs would be a suitable larval diet for all of the species tested, except for Coc. septempunctata.
Plant Size Distribution and Cross‐Country Income Differences

Cross‐country differences in income per worker are widely known to be enormous. Per capita income in the richest countries exceeds that in the poorest countries bymore than a factor of 50 (see KlenowandRodriguez‐ Clare 1997; Prescott 1998; Hall and Jones 1999; Caselli 2005). An important strand of the literature trying to understand cross‐country differences in per capita incomes has focused on the role of aggregate factor accumulation by abstracting from heterogeneity in the production units. But there is an emerging and growing body of research that takes a different approach, focusing instead on the misallocation of resources across plants (Restuccia and Rogerson 2007; Bartelsman, Haltiwanger, and Scarpetta 2008; Hsieh and Klenow 2009). Policies’ and institutions’ differential effects on the business climate broadly defined might significantly influence the allocation of resources across establishments. The working hypothesis in this literature is that not only the level of factor accumulation but also how these factors are allocated across heterogeneous production units matters in trying to understand income differences. Our paper contributes to this literature by performing a development accounting exercise using a new data set of more than 20 million establishments in 79 developing and industrialized countries. Specifically, we develop a simple model of heterogeneous production units that follows Melitz (2003). Plants’ dynamics and policy distortions are as in Restuccia and Rogerson (2007), but we assume that production units have constant returns to scale technologies and some degree of market power, as in Hsieh and Klenow (2009). We calibrate the model to match our data set. Our calibration exercise consists in finding the profile of output taxes and subsidies needed to match each country’s plant size distribution. These distortions should be interpreted as the different
Comment

There is now a fast growing literature extending real business cycle (RBC) models to include search and matching frictions. The aim of the literature is to explore the business cycle properties of the labor market as to what the basic mechanisms are and which shocks that matter. This is a very interesting area of research, and the literature has made considerable progress over the last fi ve to seven years. The paper of Justiniano and Michelacci makes a valuable contribution to this literature along several lines. First, it develops a more elaborate model than the existing ones, including novel shocks and mechanisms. Second, it uses a rather advanced estimation method, with a full information Bayesian method. Third, it includes a broader empirical application, analyzing the empirical performance of the United States and fi ve European countries (France, Germany, Norway, Sweden, and the United Kingdom). In this discussion, I will fi rst briefl y describe the key elements of the model, then consider some of them in more detail. Finally, I will discuss what we can learn from this paper, as well as from the literature to which it belongs. As will be clear, my overall view of the paper and the literature in general is favorable. Yet I also think that the analysis gives a somewhat exaggerated picture of how much of the variation in the data that the model is really able to explain. Future research should explore the validity of the key shocks and mechanisms, also by use of other methods and other type of data.
On the effect of velvet structures on trailing edge noise: experimental investigation and theoretical analysis

Abstract This study is inspired by the velvety structures on an owl's upper wing surface. Anechoic wind tunnel experiments were conducted to study the effect of the velvety structures on trailing edge noise as well as the boundary layer flow of a flat plate model. The tests were conducted in The Hong Kong University of Science and Technology low-speed wind tunnel, ultra-quiet noise injection test and evaluation device (UNITED). It was found that the trailing edge noise spectra are significantly modified by the velvety structures. In general, the velvety structures increase the low-frequency noise below a cross-over Strouhal number $St_c$ but reduce the spectral level at higher frequencies. The velvety surface also changes the boundary layer characteristics in terms of the boundary layer thickness, non-dimensional velocity distribution and turbulence distribution. Vortex shedding is suppressed by the velvety coating despite the blunt trailing edge. An analytic model is proposed for the trailing edge noise of a flat plate, including the effect of finite trailing edge thickness and velvety structures on the flat plate surface. The model uses the near wake distribution of the mean and fluctuating velocities in the streamwise direction as the input. The predictions, which require no empirical corrections, match well with the experiments for both the baseline and velvet-coated configurations. With a detailed non-dimensional analysis, this study proposes a potential aeroacoustic function of velvet structures, i.e. noise control through manipulation of boundary layer statistics.
The Triple Health Threat of Diabetes, Obesity, and Cancer—Epidemiology, Disparities, Mechanisms, and Interventions

Obesity and type 2 diabetes are both chronic, relapsing, progressive diseases that are recognized as risk factors for the development of multiple types of cancer. In a recent symposium titled “Hitting A Triple—Diabetes, Obesity, and the Emerging Links to Cancer Risk,” convened by The Obesity Society during ObesityWeek 2019, experts in the field presented the current science and highlighted existing research gaps. Topics included (1) the epidemiology of obesity and diabetes and their links to cancer risk; (2) racial and ethnic differences in obesity, diabetes, and cancer risk; (3) biological mechanisms common to obesity and diabetes that may increase cancer risk; and (4) innovative interventions that can be used to prevent the development of cancers related to obesity and diabetes. This report provides an overview of the symposium and describes key research gaps and pressing questions in need of answers to advance the field. The collective burden of obesity, diabetes, and cancer represents one of the largest public health challenges of the century. Although the symposium was titled “hitting a triple,” it was recognized that being able to disrupt the linkages among obesity, diabetes, and cancer would be a “grand slam” for public health and medicine.
Stromal HIF2 Regulates Immune Suppression in the Pancreatic Cancer Microenvironment

Background & Aims Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic, immunosuppressive stroma, which contributes to its resistance to immune checkpoint blockade therapies. The hypoxia-inducible factors (HIFs) mediate the cellular response to hypoxia, but their role within the PDAC tumor microenvironment remains unknown. Methods We used a dual recombinase mouse model to delete Hif1α or Hif2α in α-smooth muscle actin (αSMA)-expressing cancer-associated fibroblasts (CAFs) arising within spontaneous pancreatic tumors. The effects of CAF-Hif2α expression on tumor progression and composition of the tumor microenvironment were evaluated by Kaplan-Meier analysis, quantitative real-time polymerase chain reaction, histology, immunostaining, and by both bulk and single-cell RNA sequencing. CAF-macrophage crosstalk was modeled ex vivo using conditioned media from CAFs after treatment with hypoxia and PT2399, a HIF2 inhibitor currently in clinical trials. Syngeneic flank and orthotopic PDAC models were used to assess whether HIF2 inhibition improves response to immune checkpoint blockade. Results CAF-specific deletion of HIF2, but not HIF1, suppressed PDAC tumor progression and growth, and improved survival of mice by 50% (n = 21-23 mice/group, Log-rank P = 0.0009). Deletion of CAF-HIF2 modestly reduced tumor fibrosis and significantly decreased the intratumoral recruitment of immunosuppressive M2 macrophages and regulatory T cells. Treatment with the clinical HIF2 inhibitor PT2399 significantly reduced in vitro macrophage chemotaxis and M2 polarization, and improved tumor responses to immunotherapy in both syngeneic PDAC mouse models. Conclusions Together, these data suggest that stromal HIF2 is an essential component of PDAC pathobiology and is a druggable therapeutic target that could relieve tumor microenvironment immunosuppression and enhance immune responses in this disease.
PARROT: a flexible recurrent neural network framework for analysis of large protein datasets

The rise of high-throughput experiments has transformed how scientists approach biological questions. The ubiquity of large-scale assays that can test thousands of samples in a day has necessitated the development of new computational approaches to interpret this data. Among these tools, machine learning approaches are increasingly being utilized due to their ability to infer complex non-linear patterns from high-dimensional data. Despite their effectiveness, machine learning (and in particular deep learning) approaches are not always accessible or easy to implement for those with limited computational expertise. Here we present PARROT, a general framework for training and applying deep learning-based predictors on large protein datasets. Using an internal recurrent neural network architecture, PARROT is capable of tackling both classification and regression tasks while only requiring raw protein sequences as input. We showcase the potential uses of PARROT on three diverse machine learning tasks: predicting phosphorylation sites, predicting transcriptional activation function of peptides generated by high-throughput reporter assays, and predicting the fibrillization propensity of amyloid beta with data generated by deep mutational scanning. Through these examples, we demonstrate that PARROT is easy to use, performs comparably to state-of-the-art computational tools, and is applicable for a wide array of biological problems.
Istradefylline, an adenosine A2a receptor antagonist, ameliorates neutrophilic airway inflammation and psoriasis in mice

Objective Extracellular adenosine is produced from secreted ATP by cluster of differentiation (CD)39 and CD73. Both are critical nucleotide metabolizing enzymes of the adenosine generating pathway and are secreted by neuronal or immune cells. Adenosine plays a role in energy processes, neurotransmission, and endogenous regulation of inflammatory responses. Istradefylline is a selective adenosine A2a receptor (A2aR) antagonist used for the treatment of Parkinson’s disease. We have reported that adenosine primes hypersecretion of interleukin (IL)-17A via A2aR. Istradefylline, as well as an inhibitor of CD39 (ARL67156) and an inhibitor of CD73 (AMP-CP), suppressed IL-17A production, and the administration of istradefylline to mice with experimental autoimmune encephalomyelitis (EAE) led to the marked amelioration of the disease. These previous results suggest that adenosine is an endogenous modulator of neutrophilic inflammation. We investigated the effect of istradefylline, ARL67156 and AMP-CP on other mouse models of neutrophilic inflammation. Methods We tested the effect of istradefylline, ARL67156 and AMP-CP on OVA-induced neutrophilic airway inflammation or imiquimod (IMQ)-induced psoriasis in mice. These two model mice received these drugs orally or percutaneously, respectively. The production of IL-17A in the lung and ear thickness were used as an index of the effects. Results We show that istradefylline, ARL67156 and AMP-CP suppressed the OVA-induced IL-17A production in the lung and IMQ-induced psoriasis. Conclusion These results indicate that adenosine-mediated IL-17A production plays a role in neutrophilic inflammation models, and moreover, istradefylline, ARL67156, and AMP-CP are effective in animal models of neutrophilic inflammation. Some clinical relevancies in COVID-19 are discussed.