bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Complementary, Quantitative, and Confirmatory Method to UHPLC/ESI Q-Orbitrap Screening Based on UPHLC/ESI-MS/MS for Analysis of 416 Pesticides in Fruits and Vegetables
Authors: Chow Willis , Leung Daniel , Wang Jian 
Published: September 2021

Abstract

Background
Triple quadrupole (MS/MS) and high-resolution mass spectrometry (HRMS), coupled with ultra-high performance (UHP) liquid chromatography (LC) or gas chromatography (GC), are technologies used to analyze pesticide residues in fruits and vegetables. LC-MS/MS has been the gold standard for analysis of pesticides, offering reliable performance and sensitivity, while LC-HRMS is expanding in application to serve as another benchmark. Method development and testing scope expansion are constantly required with new generation mass spectrometers.

Objective
This article discusses the development and validation of a quantitative and confirmatory method that can analyze over 400 pesticide residues using a state-of-the-art UHPLC/electrospray ionization (ESI)-MS/MS system.

Methods
Homogenized fruit and vegetable samples were fortified with pesticides and were extracted using a modified quick, easy, cheap, effective, rugged, and safe method. Samples were injected onto a UHPLC/ESI-MS/MS system, and data were acquired in multiple reaction monitoring (MRM) mode. The method was validated using a nested experimental design, and was able to quantify and confirm 416 pesticides in fruits and vegetables. It was also complimentary to the UHPLC/ESI Q-Orbitrap quantitative and screening methods previously developed in the authors’ laboratory.

Results
The method demonstrated good performance. In all matrixes, 92% of pesticides yielded recoveries between 81–110%, more than 95% of pesticides yielded intermediate precision ≤20%, about 65% of pesticides yielded measurement uncertainties ≤20%, and 96% of pesticides yielded measurement uncertainties ≤50%.

Conclusion
This method shows great potential to be a standalone method or as part of a laboratory workflow for quantitative and confirmatory analysis of pesticide residues in fruits and vegetables.

Highlights
This method was developed using the same mobile phases, analytical columns, and extraction procedure, as UHPLC/ESI Q-Orbitrap methods. Extracts can be run on either system, streamlining monitoring programs and offering high sample throughput.
Micronization of Thebaine Extracted from Papaver bracteatum Lindl. Using Supercritical Fluid Technology
Authors: Salehi Hamze , Karimi Mehrnaz , Raofie Farhad 
Published: September 2021

Abstract

Background
Thebaine, as a main opiate alkaloid extracted from Papaveraceae plants, is widely used in the synthesis of many pharmaceutical ingredients such as buprenorphine, naltrexone, naloxone, and hydrocodone. Nevertheless, thebaine and related derivatives are often insoluble in aqueous media and have low bioavailability in digestive systems.

Objective
Reducing particle size and changing the morphology can mitigate the mentioned problem. In this study, extraction of thebaine from the capsule, stem, and root of Papaver bracteatum L. was optimized and micronization of extract components was developed to study solubility.

Methods
The extraction process was performed using supercritical carbon dioxide. Experimental central composite design was employed to determine the optimal conditions. Analysis of extract was done using a validated high performance liquid chromatography method and mass spectrometry. The micronization process was performed using an inhouse developed supercritical technique. The nanoparticles were characterized using field emission scanning electron microscopy (FESEM) and ImageJ software. The effect of micronization was explored on the solubility of extract components via ultraviolet spectroscopy.

Results
The percentage of thebaine in dried capsule, stem, and root powder was about 1.05, 0.31, and 0.83% respectively. The extraction results indicate that supercritical pressure has the greatest effect on the extraction yield. Analysis of FESEM images revealed that nanoparticles of extract components with particle size distribution of 5–100 nm were collected successfully.

Conclusion
The extraction results indicate that pressure has the greatest effect on the extraction yield. In vitro studies illustrated that the solubility of extract components increased up to 1.7 times during the micronization process.

Highlights
Expansion of supercritical methods as an effective method was performed for extracting and preparing alkaloid nanoparticles. This process led to improved oral bioavailability of alkaloids.
Comparisons of photosynthesis-related traits among understory lichens, mosses and vascular plant leaves in a high-elevation subalpine forest
Authors: Wang Zhe , Liu Xin , Zhu Zhangming , Ma Wenzhang , Bao Weikai 
Published: September 2021

AbstractMany mosses and lichens thrive in high-elevation subalpine forests and even become dominant species on the forest floor. Although they play an irreplaceable ecological role in the forest, less is known about their eco-physiological status, and how their photosynthesis-related functional traits differ from those of co-occurring vascular plants. We determined the carbon, nitrogen and phosphorus concentrations and stoichiometric ratios, tissue mass per area, chlorophyll concentrations and photosynthetic light–response curves of three lichens, three mosses and four vascular plants in a subalpine forest in the eastern Tibetan Plateau of China. Trait values were compared among and within each group. The lichens possessed a higher nitrogen concentration than that of mosses. In addition, the two poikilohydric groups exhibited lower concentrations of nitrogen, phosphorus and chlorophyll, light-saturated assimilation rates and photosynthetic nutrient use efficiencies, and higher light compensation points than those of vascular plant leaves. Furthermore, variations in photosynthesis-related traits for lichen species reflect their different adaptation strategies to their corresponding environments. In contrast, the differences were weak among the three forest-floor mosses and the three herb species. These results demonstrate that the high abundance of understory lichens and mosses in the high-elevation subalpine forest cannot be explained by the photosynthesis-related traits.
Creating Uncertainty in the Governance of Arrival and Return: Target-group Constructions in Bavarian AnkER Facilities
Authors: Münch Sybille 
Published: September 2021

AbstractGermany remains the number one destination for migrants in Europe. After 2015, following a backlash, burdens on municipalities and the inefficiency of the processing of asylum claims were widely problematized, as was the termination of residence and return of those deemed irregular migrants. Policymakers presented so-called AnkER centres, an acronym for central reception, decision-making, and repatriation facilities that translates as ‘anchor’ in German, as a solution that would accelerate procedures. Drawing from an interpretive case study of the AnkER pilots in Bavaria/Germany, we scrutinize meaning-making as reflected in contested constructions of target groups and identify the complex rationales of belonging shared by different ‘communities of meaning’ that pose a challenge to the promise of certainty declared in official documents.
The challenge of simultaneously matching the observed diversity of chemical abundance patterns in cosmological hydrodynamical simulations
Authors: Buck Tobias , Rybizki Jan , Buder Sven , Obreja Aura , Macciò Andrea V , Pfrommer Christoph , Steinmetz Matthias , Ness Melissa 
Published: September 2021

ABSTRACT
With the advent of large spectroscopic surveys the amount of high quality chemodynamical data in the Milky Way (MW) increased tremendously. Accurately and correctly capturing and explaining the detailed features in the high-quality observational data is notoriously difficult for state-of-the-art numerical models. In order to keep up with the quantity and quality of observational data sets, improved prescriptions for galactic chemical evolution need to be incorporated into the simulations. Here we present a new, flexible, time-resolved chemical enrichment model for cosmological simulations. Our model allows us to easily change a number of stellar physics parameters such as the shape of the initial mass function (IMF), stellar lifetimes, chemical yields, or SN Ia delay times. We implement our model into the Gasoline2 code and perform a series of cosmological simulations varying a number of key parameters, foremost evaluating different stellar yield sets for massive stars from the literature. We find that total metallicity, total iron abundance, and gas phase oxygen abundance are robust predictions from different yield sets and in agreement with observational relations. On the other hand, individual element abundances, especially alpha-elements show significant differences across different yield sets and none of our models can simultaneously match constraints on the dwarf and MW mass scale. This offers a unique way of observationally constraining model parameters. For MW mass galaxies we find for most yield tables tested in this work a bimodality in the [α/Fe] versus [Fe/H] plane of rather low intrinsic scatter potentially in tension with the observed abundance scatter.
Outflows from starburst galaxies with various driving mechanisms and their X-ray properties
Authors: Yu B P Brian , Owen Ellis R , Pan Kuo-Chuan , Wu Kinwah , Ferreras Ignacio 
Published: September 2021

ABSTRACT
Outflows in starburst galaxies driven by thermal-mechanical energy, cosmic rays, and their mix are investigated with 1D and 2D hydrodynamic simulations. We show that these outflows could reach a stationary state, after which their hydrodynamic profiles asymptotically approach previous results obtained semi-analytically for stationary outflow configurations. The X-rays from the simulated outflows are computed, and high-resolution synthetic spectra and broad-band light curves are constructed. The simulated outflows driven by thermal mechanical pressure and CRs have distinguishable spectral signatures, in particular, in the sequence of the keV K α lines of various ions and in the L-shell Fe emission complex. We demonstrate that broad-band colour analysis in X-rays is a possible alternative means to probe outflow driving mechanisms for distant galaxies, where observations may not be able to provide sufficient photons for high-resolution spectroscopic analyses.
An unbiased estimator of the full-sky CMB angular power spectrum at large scales using neural networks
Authors: Chanda Pallav , Saha Rajib 
Published: September 2021

ABSTRACTAccurate estimation of the cosmic microwave background (CMB) angular power spectrum is enticing due to the prospect for precision cosmology it presents. Galactic foreground emissions, however, contaminate the CMB signal and need to be subtracted reliably in order to lessen systematic errors on the CMB temperature estimates. Typically, bright foregrounds in a region lead to further uncertainty in temperature estimates in the area even after some foreground removal technique is performed and hence determining the underlying full-sky angular power spectrum poses a challenge. We explore the feasibility of utilizing artificial neural networks to predict the angular power spectrum of the full-sky CMB temperature maps from the observed angular power spectrum of the partial sky in which CMB temperatures in some bright foreground regions are masked. We present our analysis at large angular scales with two different masks. We produce unbiased predictions of the full-sky angular power spectrum and recover the underlying theoretical power spectrum using neural networks. Our predictions are also uncorrelated to a large extent. We further show that the multipole-space covariances of the predictions of full-sky spectra made by the artificial neural networks are much smaller than those of the estimates obtained using the pseudo-Cℓ method.
Haemophagocytic lymphohistiocytosis in a patient with familial Mediterranean fever and miliary tuberculosis: a case report
Authors: Cerme Emir , Oztas Mert , Balkan Ilker Inanc , Cetin Esin Aktas , Ugurlu Serdal 
Published: September 2021

ABSTRACT
Haemophagocytic lymphohistiocytosis (HLH) is a lethal complication of several infections, especially viral origin. Mycobacterium tuberculosis infection can also lead to HLH, yet it is an uncommon trigger. Considering the role of increased cytokines in HLH, autoinflammatory conditions, such as familial Mediterranean fever (FMF), might contribute to its development. Nevertheless, the possible relationship between FMF and HLH has been suggested only in some case reports. We present a case of FMF who admitted to the hospital with consitutional symptoms and chest pain regarding to recurrent pericarditis. On a blood test, pancytopenia and elevated acute phase reactants were seen. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography demonstrated positive FDG uptake sites on both the right and left surrenal glands, the visceral layer of pericard, and reactive lymphadenomegalies at multiple mediastinal regions. Bone marrow biopsy revealed haemophagocytosis. Methylprednisolone treatment was initiated. Despite immunosuppressive treatment, clinical and biochemical parameters deteriorated; thus, a thorax computed tomography was executed. Findings were consistent with miliary tuberculosis infection. M. tuberculosis was detected in blood culture and bronchoalveolar lavage culture material. Also, bone marrow and surrenal biopsy material revealed necrotising caseating granuloma.
Phase and amplitude electroencephalography correlations change with disease progression in people with idiopathic rapid eye-movement sleep behavior disorder
Authors: Roascio Monica , Canessa Andrea , Trò Rosella , Mattioli Pietro , Famà Francesco , Giorgetti Laura , Girtler Nicola , Orso Beatrice , Morbelli Silvia , Nobili Flavio , Arnaldi Dario , Arnulfo Gabriele 
Published: September 2021

Abstract

Study Objectives
Increased phase synchronization in electroencephalography (EEG) bands might reflect the activation of compensatory mechanisms of cognitive decline in people with neurodegenerative diseases. Here, we investigated whether altered large-scale couplings of brain oscillations could be linked to the balancing of cognitive decline in a longitudinal cohort of people with idiopathic rapid eye-movement sleep behavior disorder (iRBD).

Methods
We analyzed 18 patients (17 males, 69.7 ± 7.5 years) with iRBD undergoing high-density EEG (HD-EEG), presynaptic dopaminergic imaging, and clinical and neuropsychological (NPS) assessments at two time points (time interval 24.2 ± 5.9 months). We thus quantified the HD-EEG power distribution, orthogonalized amplitude correlation, and weighted phase-lag index at both time points and correlated them with clinical, NPS, and imaging data.

Results
Four patients phenoconverted at follow-up (three cases of parkinsonism and one of dementia). At the group level, NPS scores decreased over time, without reaching statistical significance. However, alpha phase synchronization increased and delta amplitude correlations decreased significantly at follow-up compared to baseline. Both large-scale network connectivity metrics were significantly correlated with NPS scores but not with sleep quality indices or presynaptic dopaminergic imaging data.

Conclusions
These results suggest that increased alpha phase synchronization and reduced delta amplitude correlation may be considered electrophysiological signs of an active compensatory mechanism of cognitive impairment in people with iRBD. Large-scale functional modifications may be helpful biomarkers in the characterization of prodromal stages of alpha-synucleinopathies.
The impact of global lineage dynamics, border restrictions, and emergence of the B.1.1.7 lineage on the SARS-CoV-2 epidemic in Norway
Authors: Osnes Magnus N , Alfsnes Kristian , Bråte Jon , Garcia Ignacio , Riis Rasmus K , Instefjord Kamilla H , Elshaug Hilde , Vollan Hilde S , Moen Line Victoria , Pedersen Benedikte Nevjen , Caugant Dominique A , Stene-Johansen Kathrine , Hungnes Olav , Bragstad Karoline , Brynildsrud Ola , Eldholm Vegard 
Published: September 2021

AbstractAs the COVID-19 pandemic swept through an immunologically naïve human population, academics and public health professionals scrambled to establish methods and platforms for genomic surveillance and data sharing. This offered a rare opportunity to study the ecology and evolution of SARS-CoV-2 over the course of the ongoing pandemic. Here, we use population genetic and phylogenetic methodology to characterize the population dynamics of SARS-CoV-2 and reconstruct patterns of virus introductions and local transmission in Norway against this backdrop. The analyses demonstrated that the epidemic in Norway was largely import driven and characterized by the repeated introduction, establishment, and suppression of new transmission lineages. This pattern changed with the arrival of the B.1.1.7 lineage, which was able to establish a stable presence concomitant with the imposition of severe border restrictions.
Age-specific effects of childhood Body Mass Index on multiple sclerosis risk
Authors: Hone Luke , Jacobs Benjamin M , Marshall Charles , Giovannoni Gavin , Noyce Alastair , Dobson Ruth 
Published: September 2021

AbstractObjectiveHigher Body Mass Index (BMI) during early life is thought to be a causal risk factor for Multiple Sclerosis (MS). We used longitudinal mendelian randomisation (MR) to determine whether there is a critical window during which BMI influences MS risk.MethodsSummary statistics for childhood BMI and for MS susceptibility were obtained from recent large GWAS. We generated exposure instruments for BMI during four non-overlapping epochs (< 3 months, 3 months-1.5 years, 2-5 years, and 7-8 years) and performed MR using the inverse-variance weighted method with standard sensitivity analyses. Multivariable MR was used to account for effects mediated via later-life BMI.ResultsFor all time epochs other than birth, genetically determined higher BMI was associated with an increased liability to MS: Birth (OR 0.81, 95% CI 0.50-1.31, NSNPs=7, p=0.39), Infancy (OR 1.18, 95%CI 1.04-1.33, NSNPs=18, p=0.01), Early childhood (OR 1.31, 95%CI 1.03-1.66, NSNPs=4, p=0.03), Later childhood (OR 1.34, 95% CI 1.08-1.66, NSNPs=4, p=0.01). Multivariable MR suggested that these effects may be mediated by effects on adult BMI.ConclusionWe provide evidence using MR that genetically-determined higher BMI during early life is associated with increased MS risk. This effect may be driven by shared genetic architecture with later-life BMI.
A method to reduce ELISA serial dilution assay workload applied to SARS-CoV-2 and seasonal HCoVs
Authors: Pattinson David , Jester Peter , Guan Lizheng , Yamayoshi Seiya , Chiba Shiho , Presler Robert , Rao Hongyu , Iwatsuki-Horimoto Kiyoko , Ikeda Nobuhiro , Hagihara Masao , Uchida Tomoyuki , Mitamura Keiko , Halfmann Peter , Neumann Gabriele , Kawaoka Yoshihiro 
Published: September 2021

AbstractObjectivesAssays using ELISA measurements on serially diluted serum samples have been heavily used to measure serum reactivity to SARS-CoV-2 antigens and are widely used in virology and elsewhere in biology. We test a method to reduce the workload of these assays, and measure reactivity of SARS-CoV-2 and HCoV antigens to human serum samples collected before and during the COVID-19 pandemic.MethodsWe apply Bayesian hierarchical modelling to ELISA measurements of human serum samples against SARS-CoV-2 and HCoV antigens.ResultsInflection titers for SARS-CoV-2 full-length spike protein (S1S2), spike protein receptor-binding domain (RBD), and nucleoprotein (N) inferred from three spread-out dilutions correlated with those inferred from eight consecutive dilutions with an R2 value of 0.97 or higher. We confirm existing findings showing a small proportion of pre-pandemic human serum samples contain cross-reactive antibodies to SARS-CoV-2 S1S2 and N, and that SARS-CoV-2 infection increases serum reactivity to the beta-HCoVs OC43 and HKU1 S1S2.ConclusionsIn serial dilution assays, large savings in resources and/or increases in throughput can be achieved by reducing the number of dilutions measured and using Bayesian hierarchical modelling to infer inflection or endpoint titers. We have released software for conducting these types of analysis.
A Deep Learning Method to Detect Opioid Prescription and Opioid Use Disorder from Electronic Health Records
Authors: Kashyap Aditya , Callison-Burch Chris , Boland Mary Regina 
Published: September 2021

ABSTRACTObjectiveAs the opioid epidemic continues across the United States, methods are needed to accurately and quickly identify patients at risk for opioid use disorder (OUD). The purpose of this study is to develop two predictive algorithms: one to predict opioid prescription and one to predict OUD.Materials and MethodsWe developed an informatics algorithm that trains two deep learning models over patient EHRs using the MIMIC-III database. We utilize both the structured and unstructured parts of the EHR and show that it is possible to predict both of these challenging outcomes.ResultsOur deep learning models incorporate both structured and unstructured data elements from the EHRs to predict opioid prescription with an F1-score of 0.88 ± 0.003 and an AUC-ROC of 0.93 ± 0.002. We also constructed a model to predict OUD diagnosis achieving an F1-score of 0.82 ± 0.05 and AUC-ROC of 0.94 ± 0.008.DiscussionOur model for OUD prediction outperformed prior algorithms for specificity, F1 score and AUC-ROC while achieving equivalent sensitivity. This demonstrates the importance of a.) deep learning approaches in predicting OUD and b.) incorporating both structured and unstructured data for this prediction task. No prediction models for opioid prescription as an outcome were found in the literature and therefore this represents an important contribution of our work as opioid prescriptions are more common than OUDs.ConclusionAlgorithms such as those described in this paper will become increasingly important to understand the drivers underlying this national epidemic.
A system biology approach identifies candidate drugs to reduce mortality in severely ill COVID-19 patients
Authors: Fava Vinicius M. , Bourgey Mathieu , Nawarathna Pubudu M. , Orlova Marianna , Cassart Pauline , Vinh Donald C. , Cheng Matthew Pellan , Bourque Guillaume , Schurr Erwin , Langlais David 
Published: September 2021

ABSTRACTDespite the availability of highly efficacious vaccines, Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) lacks effective drug treatment which results in a high rate of mortality. To address this therapeutic shortcoming, we applied a system biology approach to the study of patients hospitalized with severe COVID. We show that, at the time of hospital admission, patients who were equivalent on the clinical ordinal scale displayed significant differential monocyte epigenetic and transcriptomic attributes between those who would survive and those who would succumb to COVID-19. We identified mRNA metabolism, RNA splicing, and interferon signaling pathways as key host responses overactivated by patients who would not survive. Those pathways are prime drug targets to reduce mortality of critically ill COVID-19 patients leading us to identify Tacrolimus, Zotatifin, and Nintedanib as three strong candidates for treatment of severely ill patients at the time of hospital admission.TeaserEpigenetics distinguishes COVID-19 survivors already at hospital admission: lessons for drug repurposing.