bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing ExoMars Rover Remote Sensing Multispectral Science: Cross‐Rover Comparison Using Laboratory and Orbital Data
Authors: Grindrod P. M. , Stabbins R. B. , Motaghian S. , Allender E. J. , Cousins C. R. , Rice M. S. , Stephan K. 
Published: May 2022

AbstractMultispectral imaging instruments have been core payload components of Mars lander and rover missions for several decades. In order to place into context the future performance of the ExoMars Rosalind Franklin rover, we have carried out a detailed analysis of the spectral performance of three visible and near‐infrared (VNIR) multispectral instruments. We have determined the root mean square error (RMSE) between the expected multispectral sampling of the instruments and high‐resolution spectral reflectance data, using both laboratory spectral libraries and Mars orbital hyperspectral data. ExoMars Panoramic Camera (PanCam) and Mars2020 Perseverance Mastcam‐Z instruments have similar values of RMSE, and are consistently lower than for Mars Science Laboratory Mastcam, across both laboratory and orbital remote sensing data sets. The performance across mineral groups is similar across all instruments, with the lowest RMSE values for hematite, basalt, and basaltic soil. Minerals with broader, or absent, absorption features in these visible wavelengths, such as olivine, saponite, and vermiculite have overall larger RMSE values. Instrument RMSE as a function of filter wavelength and bandwidth suggests that spectral parameters that use shorter wavelengths are likely to perform better. Our simulations of the spectral performance of the PanCam instrument will allow the future use of targeted filter selection during ExoMars 2022 Rosalind Franklin operations on Mars.
Characterizing the Effect of Spatial Heterogeneity and the Deployment of Sampled Plots on the Uncertainty of Ground “Truth” on a Coarse Grid Scale: Case Study for Near‐Infrared (NIR) Surface Reflectance
Authors: Wen Jianguang , Wu Xiaodan , Wang Jingping , Tang Rongqi , Ma Dujuan , Zeng Qicheng , Gong Baochang , Xiao Qing 
Published: May 2022

AbstractThe quality of surface reflectance product is fundamentally important to ensure the information extracted from the downstream products can be trusted. However, ground validation of surface reflectance satellite products is challenging, because ground “truth” on a coarse grid scale based on sparse ground measurements is subject to uncertainty due to spatial heterogeneity. Based on a high‐resolution numerical simulation, this study quantifies the influence of spatial heterogeneity on the uncertainty of surface reflectance ground “truth” in different sampling cases (i.e., the number and positions of sampled plots). The effect of spatial heterogeneity is very small and even negligible when optimal locations are identified. By contrast, for the averaged condition without optimal sampling, spatial heterogeneity is almost the only source of uncertainty of ground “truth,” with determination coefficients of 0.94, 0.99, and 1 for 1, 2, and 3 sampled plots, respectively. The response coefficients between them are about 0.77, 0.55, and 0.47 for 1, 2, and 3 sampled plots, respectively. Optimal sampling plays a more important role in reducing the uncertainty of ground “truth” than increasing the number of sampled plots. Particularly, the latter is not helpful in reducing the uncertainty when the worst locations are adopted. Furthermore, the thresholds of spatial heterogeneity of surface reflectance to meet a predefined uncertainty of 0.01 (about 3.5% for surface reflectance over the study area) were given for different sampling cases over northern China. This study provides important guidance to aid in situ network design for the validation of 1 km satellite surface reflectance products.
Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach
Authors: Bej Saptarshi , Sarkar Jit , Biswas Saikat , Mitra Pabitra , Chakrabarti Partha , Wolkenhauer Olaf 
Published: May 2022

Abstract
Background
Studies on Type-2 Diabetes Mellitus (T2DM) have revealed heterogeneous sub-populations in terms of underlying pathologies. However, the identification of sub-populations in epidemiological datasets remains unexplored. We here focus on the detection of T2DM clusters in epidemiological data, specifically analysing the National Family Health Survey-4 (NFHS-4) dataset from India containing a wide spectrum of features, including medical history, dietary and addiction habits, socio-economic and lifestyle patterns of 10,125 T2DM patients.

Methods
Epidemiological data provide challenges for analysis due to the diverse types of features in it. In this case, applying the state-of-the-art dimension reduction tool UMAP conventionally was found to be ineffective for the NFHS-4 dataset, which contains diverse feature types. We implemented a distributed clustering workflow combining different similarity measure settings of UMAP, for clustering continuous, ordinal and nominal features separately. We integrated the reduced dimensions from each feature-type-distributed clustering to obtain interpretable and unbiased clustering of the data.

Results
Our analysis reveals four significant clusters, with two of them comprising mainly of non-obese T2DM patients. These non-obese clusters have lower mean age and majorly comprises of rural residents. Surprisingly, one of the obese clusters had 90% of the T2DM patients practising a non-vegetarian diet though they did not show an increased intake of plant-based protein-rich foods.

Conclusions
From a methodological perspective, we show that for diverse data types, frequent in epidemiological datasets, feature-type-distributed clustering using UMAP is effective as opposed to the conventional use of the UMAP algorithm. The application of UMAP-based clustering workflow for this type of dataset is novel in itself. Our findings demonstrate the presence of heterogeneity among Indian T2DM patients with regard to socio-demography and dietary patterns. From our analysis, we conclude that the existence of significant non-obese T2DM sub-populations characterized by younger age groups and economic disadvantage raises the need for different screening criteria for T2DM among rural Indian residents.
Response of blood glucose and GLP-1 to different food temperature in normal subject and patients with type 2 diabetes
Authors: Hu Yun , Zhang Peng , Ding Bo , Cao Xin , Zhong Yi , Lee Kok-Onn , Ma Jian-Hua 
Published: May 2022

Abstract
Background
Eating behavior is a major factor in type 2 diabetes. We investigated the different responses of glucose-regulating hormones to cold and hot glucose solutions in normal subjects and patients with type 2 diabetes.

Methods
In this crossover, self-controlled study, normal subjects (N = 19) and patients with type 2 diabetes (N = 22) were recruited and randomly assigned to a hot (50 °C) or a cold (8 °C) oral glucose-tolerance test (OGTT). The subsequent day, they were switched to the OGTT at the other temperature. Blood glucose, insulin, GIP, glucagon-like peptide-1 (GLP-1), and cortisol were measured at 0, 5, 10, 30, 60, and 120 min during each OGTT. After the hot OGTT, all subjects ingested hot (>42 °C) food and water for that day, and ingested food and water at room temperature (≤24 °C) for the day after cold OGTT. All participants had continuous glucose monitoring (CGM) throughout the study.

Results
Compared to cold OGTT, blood glucose was significantly higher with hot OGTT in both groups (both P < 0.05). However, insulin and GLP-1 levels were significantly higher in hot OGTT in normal subjects only (both P < 0.05). The GIP and cortisol responses did not differ with temperature in both groups. CGM showed that normal subjects had significantly higher 24-h mean glucose (MBG) (6.11 ± 0.13 vs. 5.84 ± 0.11 mmol/L, P = 0.021), and standard deviation of MBG with hot meals (0.59 ± 0.06 vs. 0.48 ± 0.05 mmol/L, P = 0.043), T2DM patients had higher MBG only (8.46 ± 0.38 vs. 8.88 ± 0.39 mmol/L, P = 0.022).

Conclusions
Food temperature is an important factor in glucose absorption and GLP-1 response. These food temperatures elicited differences are lost in type 2 diabetes.
Depression history modulates effects of subthalamic nucleus topography on neuropsychological outcomes of deep brain stimulation for Parkinson’s disease
Authors: Kratter Ian H. , Jorge Ahmed , Feyder Michael T. , Whiteman Ashley C. , Chang Yue-fang , Henry Luke C. , Karp Jordan F. , Richardson R. Mark 
Published: May 2022

AbstractPatients with psychiatric symptoms, such as depression, anxiety, and visual hallucinations, may be at increased risk for adverse effects following deep brain stimulation of the subthalamic nucleus for Parkinson’s disease, but there have been relatively few studies of associations between locations of chronic stimulation and neuropsychological outcomes. We sought to determine whether psychiatric history modulates associations between stimulation location within the subthalamic nucleus and postoperative affective and cognitive changes. We retrospectively identified 42 patients with Parkinson’s disease who received bilateral subthalamic nucleus deep brain stimulation and who completed both pre- and postoperative neuropsychological testing. Active stimulation contacts were localized in MNI space using Lead-DBS software. Linear discriminant analysis identified vectors maximizing variance in postoperative neuropsychological changes, and Pearson’s correlations were used to assess for linear relationships. Stimulation location was associated with postoperative change for only 3 of the 18 neuropsychological measures. Variation along the superioinferior (z) axis was most influential. Constraining the analysis to patients with a history of depression revealed 10 measures significantly associated with active contact location, primarily related to location along the anterioposterior (y) axis and with worse outcomes associated with more anterior stimulation. Analysis of patients with a history of anxiety revealed 5 measures with location-associated changes without a predominant axis. History of visual hallucinations was not associated with significant findings. Our results suggest that a history of depression may influence the relationship between active contact location and neuropsychological outcomes following subthalamic nucleus deep brain stimulation. These patients may be more sensitive to off-target (nonmotor) stimulation.
Dentists in action: a profession on-screen (1913-2013)
Authors: Gierok Samuel , Mirza Shahzeb A. , Karenberg Axel 
Published: May 2022

AbstractBackground Fictional portrayals of dentists in feature films have remained largely unexamined to date. The aim of this review is consequently to catalogue and analyse available films produced by US entertainment industry that present 'dentists in action'.Methods Relevant motion pictures were identified by means of keyword-based inquiries in search engines, online databases, websites and by handsearch.Results Between 1913-2013, almost 60 American films with dental treatment as a motif were released. Dentists on-screen appeared mainly in comedies and mostly as supporting actors. Surgical treatments dominated in earlier films and tooth-preserving therapy in later films; other fields of dentistry were marginalised. The time lag between a dental innovation and its screen debut varied between 50 years (x-rays) and 10 years (turbine). For a long time, filmmakers refused to allow female dentists to appear on screen. Although there is no consistent stereotype of a dentist, the figure of 'Dr Awkward' can be attributed to the silent film era, 'Dr Prosperous' to the 1960s/1970s and 'Dr Evil' to the 1980s/1990s.Discussion Popular media does not only reflect aspects of reality; they also create reality and establish a professional image. Thus, filmic representations of dentists have an immediate effect on an audience of millions of movie-goers and television viewers. Greater attention should be devoted to the interplay of cinematic and dental art by both dental professionals and film historians.
Management of acute traumatic dental injuries in the orthodontic patient
Authors: Patel Kishan , Mack Gavin , Djemal Serpil 
Published: May 2022

AbstractKnowledge of managing traumatic dental injuries (TDIs) is imperative for all dental practitioners. With the number of adults undertaking orthodontic treatment increasing, and children and adolescents alike continually being treated for orthodontics under the NHS in the UK, it is imperative that all clinicians - specialists and generalists - are aware of how to manage the orthodontic appliance in a patient presenting with a TDI in their active phase of orthodontics.This guidance will aid practitioners in implementing pragmatic approaches to manage the orthodontic appliance in a patient presenting with a TDI. Key focus will be given on fixed appliance therapy. Case examples and flow diagrams outlining best practice are given to manage the TDI and orthodontic appliance concurrently.
The streaming of plastic in the Mediterranean Sea
Authors: Baudena Alberto , Ser-Giacomi Enrico , Jalón-Rojas Isabel , Galgani François , Pedrotti Maria Luiza 
Published: May 2022

AbstractPlastic debris is a ubiquitous pollutant on the sea surface. To date, substantial research efforts focused on the detection of plastic accumulation zones. Here, a different paradigm is proposed: looking for crossroad regions through which large amounts of plastic debris flow. This approach is applied to the Mediterranean Sea, massively polluted but lacking in zones of high plastic concentration. The most extensive dataset of plastic measurements in this region to date is combined with an advanced numerical plastic-tracking model. Around 20% of Mediterranean plastic debris released every year passed through about 1% of the basin surface. The most important crossroads intercepted plastic debris from multiple sources, which had often traveled long distances. The detection of these spots could foster understanding of plastic transport and help mitigation strategies. Moreover, the general applicability and the soundness of the crossroad approach can promote its application to the study of other pollutants.
Gene-specific nonsense-mediated mRNA decay targeting for cystic fibrosis therapy
Authors: Kim Young Jin , Nomakuchi Tomoki , Papaleonidopoulou Foteini , Yang Lucia , Zhang Qian , Krainer Adrian R. 
Published: May 2022

AbstractLow CFTR mRNA expression due to nonsense-mediated mRNA decay (NMD) is a major hurdle in developing a therapy for cystic fibrosis (CF) caused by the W1282X mutation in the CFTR gene. CFTR-W1282X truncated protein retains partial function, so increasing its levels by inhibiting NMD of its mRNA will likely be beneficial. Because NMD regulates the normal expression of many genes, gene-specific stabilization of CFTR-W1282X mRNA expression is more desirable than general NMD inhibition. Synthetic antisense oligonucleotides (ASOs) designed to prevent binding of exon junction complexes (EJC) downstream of premature termination codons (PTCs) attenuate NMD in a gene-specific manner. We describe cocktails of three ASOs that specifically increase the expression of CFTR-W1282X mRNA and CFTR protein upon delivery into human bronchial epithelial cells. This treatment increases the CFTR-mediated chloride current. These results set the stage for clinical development of an allele-specific therapy for CF caused by the W1282X mutation.
Transmission of SARS-CoV-2 from humans to animals and potential host adaptation
Authors: Tan Cedric C. S. , Lam Su Datt , Richard Damien , Owen Christopher J. , Berchtold Dorothea , Orengo Christine , Nair Meera Surendran , Kuchipudi Suresh V. , Kapur Vivek , van Dorp Lucy , Balloux François 
Published: May 2022

AbstractSARS-CoV-2, the causative agent of the COVID-19 pandemic, can infect a wide range of mammals. Since its spread in humans, secondary host jumps of SARS-CoV-2 from humans to multiple domestic and wild populations of mammals have been documented. Understanding the extent of adaptation to these animal hosts is critical for assessing the threat that the spillback of animal-adapted SARS-CoV-2 into humans poses. We compare the genomic landscapes of SARS-CoV-2 isolated from animal species to that in humans, profiling the mutational biases indicative of potentially different selective pressures in animals. We focus on viral genomes isolated from mink (Neovison vison) and white-tailed deer (Odocoileus virginianus) for which multiple independent outbreaks driven by onward animal-to-animal transmission have been reported. We identify five candidate mutations for animal-specific adaptation in mink (NSP9_G37E, Spike_F486L, Spike_N501T, Spike_Y453F, ORF3a_L219V), and one in deer (NSP3a_L1035F), though they appear to confer a minimal advantage for human-to-human transmission. No considerable changes to the mutation rate or evolutionary trajectory of SARS-CoV-2 has resulted from circulation in mink and deer thus far. Our findings suggest that minimal adaptation was required for onward transmission in mink and deer following human-to-animal spillover, highlighting the ‘generalist’ nature of SARS-CoV-2 as a mammalian pathogen.
Visualizing discrete Fermi surfaces and possible nodal-line to Weyl state evolution in ZrSiTe
Authors: Bian Qi , Li Shaojian , Luo Aiyun , Zhang Zongyuan , Hu Jin , Zhu Yanglin , Shao Zhibin , Sun Haigen , Cheng Zhengwang , Mao Zhiqiang , Xu Gang , Pan Minghu 
Published: May 2022

AbstractTopological nodal line semimetals (TNLSMs) represent a quantum state of topological matter. When the crystal/time-reversal symmetry is broken, a nodal line state is expected to evolve into a Dirac semimetal, a Weyl semimetal, or other topological phases according to theoretical studies. Here, we report scanning tunneling microscopy (STM) based quasiparticle interference (QPI) measurements performed on the surface of TNLSM ZrSiTe single crystal. A discrete Fermi surface with multiple electron/hole pockets and the impurity-induced inter-/intra- pockets scatterings are directly visualized from QPI patterns. Moreover, the degenerated Dirac points at X point evolve into the pairs of Weyl nodes when Fe atoms are deposited, suggesting a possible phase transition from the nodal line to the Weyl state. The calculated band structures and the Weyl points by applying Zeeman splitting energies along x-direction, further confirm the existence of Weyl points in the Fe-doped ZrSiTe induced by the broken of time-reversal symmetry.
Immunosuppression broadens evolutionary pathways to drug resistance and treatment failure during Acinetobacter baumannii pneumonia in mice
Authors: Huo Wenwen , Busch Lindsay M. , Hernandez-Bird Juan , Hamami Efrat , Marshall Christopher W. , Geisinger Edward , Cooper Vaughn S. , van Opijnen Tim , Rosch Jason W. , Isberg Ralph R. 
Published: May 2022

AbstractAcinetobacter baumannii is increasingly refractory to antibiotic treatment in healthcare settings. As is true of most human pathogens, the genetic path to antimicrobial resistance (AMR) and the role that the immune system plays in modulating AMR during disease are poorly understood. Here we reproduced several routes to fluoroquinolone resistance, performing evolution experiments using sequential lung infections in mice that are replete with or depleted of neutrophils, providing two key insights into the evolution of drug resistance. First, neutropenic hosts acted as reservoirs for the accumulation of drug resistance during drug treatment. Selection for variants with altered drug sensitivity profiles arose readily in the absence of neutrophils, while immunocompetent animals restricted the appearance of these variants. Secondly, antibiotic treatment failure in the immunocompromised host was shown to occur without clinically defined resistance, an unexpected result that provides a model for how antibiotic failure occurs clinically in the absence of AMR. The genetic mechanism underlying both these results is initiated by mutations activating the drug egress pump regulator AdeL, which drives persistence in the presence of antibiotic. Therefore, antibiotic persistence mutations present a two-pronged risk during disease, causing drug treatment failure in the immunocompromised host while simultaneously increasing the emergence of high-level AMR.
Identification of metabolite extraction method for targeted exploration of antimicrobial resistance associated metabolites of Klebsiella pneumoniae
Authors: Kumar Ashok , Singh Sevaram , Gupta Sonu Kumar , Kumar Shailesh , Kumar Shrikant , Singh Rita , Thakur Lovnish , Kumar Manoj , Kapil Arti , Kumar Yashwant , Kumar Niraj 
Published: May 2022

AbstractAntimicrobial resistant Klebsiellapneumoniae (K. pneumoniae), as being a pathogen of critical clinical concern, urgently demands effective therapeutic options. However, the discovery of novel antibiotics over the last three decades has declined drastically and necessitates exploring novel strategies. Metabolomic modulation has been the promising approach for the development of effective therapeutics to deal with AMR; however, only limited efforts have been made to-date, possibly due to the unavailability of suitable metabolites extraction protocols. Therefore, in order to establish a detailed metabolome of K. pneumoniae and identify a method for targeted exploration of metabolites that are involved in the regulation of AMR associated processes, metabolites were extracted using multiple methods of metabolites extraction (freeze–thaw cycle (FTC) and sonication cycle (SC) method alone or in combination (FTC followed by SC; FTC + SC)) from K. pneumoniae cells and then identified using an orbitrap mass analyzer (ESI-LC–MS/MS). A total of 151 metabolites were identified by using FTC, 132 metabolites by using FTC+SC, 103 metabolites by using SC and 69 metabolites common among all the methods used which altogether enabled the identification of 199 unique metabolites. Of these 199, 70 metabolites were known to have an association with AMR phenotype and among these, the FTC + SC method yielded better (identified 55 metabolites), quantitatively and qualitatively compared to FTC and SC alone (identified 51 and 41 metabolites respectively). Each method of metabolite extraction showed a definite degree of biasness and specificity towards chemical classes of metabolites and jointly contributed to the development of a detailed metabolome of the pathogen. FTC method was observed to give higher metabolomic coverage as compared to SC alone and FTC + SC. However, FTC + SC resulted in the identification of a higher number of AMR associated metabolites of K. pneumoniae compared to FTC and SC alone.
Integration of thermal imaging and neural networks for mechanical strength analysis and fracture prediction in 3D-printed plastic parts
Authors: Boiko Daniil A. , Korabelnikova Victoria A. , Gordeev Evgeniy G. , Ananikov Valentine P. 
Published: May 2022

AbstractAdditive manufacturing demonstrates tremendous progress and is expected to play an important role in the creation of construction materials and final products. Contactless (remote) mechanical testing of the materials and 3D printed parts is a critical limitation since the amount of collected data and corresponding structure/strength correlations need to be acquired. In this work, an efficient approach for coupling mechanical tests with thermographic analysis is described. Experiments were performed to find relationships between mechanical and thermographic data. Mechanical tests of 3D-printed samples were carried out on a universal testing machine, and the fixation of thermal changes during testing was performed with a thermal imaging camera. As a proof of concept for the use of machine learning as a method for data analysis, a neural network for fracture prediction was constructed. Analysis of the measured data led to the development of thermographic markers to enhance the thermal properties of the materials. A combination of artificial intelligence with contactless nondestructive thermal analysis opens new opportunities for the remote supervision of materials and constructions.