bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of time-dependent effects of ambient temperatures on health by vulnerable groups in Korea in 1999–2018
Authors: Park Jongchul , Chae Yeora 
Published: January 2023

AbstractThis study compared the relative risks of heat days on mortalities by vulnerable groups (elderly, single-person households, less-educated) in the past decade (1999–2008) and the recent decade (2009–2018) in four cities, Seoul, Incheon, Daegu, and Gwangju, in Korea. It has been known that the health impacts of heatwaves have gradually decreased over time due to socio-economic development, climate adaptation, and acclimatization. Contrary to general perception, we found that the recent relative risk of mortality caused by heat days has increased among vulnerable groups. It may associate with recent increasing trends of severe heat days due to climate change. The increasing relative risk was more significant in single-person households and less-educated groups than in the elderly. It implies that the impacts of climate change-induced severe heat days have been and will be concentrated on vulnerable groups. It suggests that social polarization and social isolation should be addressed to reduce heatwave impacts. Furthermore, this study shows the necessity of customized heatwave policies, which consider the characteristics of vulnerable groups.
Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach
Authors: Devasia James , Goswami Hridayanand , Lakshminarayanan Subitha , Rajaram Manju , Adithan Subathra 
Published: January 2023

AbstractChest X-rays are the most economically viable diagnostic imaging test for active pulmonary tuberculosis screening despite the high sensitivity and low specificity when interpreted by clinicians or radiologists. Computer aided detection (CAD) algorithms, especially convolution based deep learning architecture, have been proposed to facilitate the automation of radiography imaging modalities. Deep learning algorithms have found success in classifying various abnormalities in lung using chest X-ray. We fine-tuned, validated and tested EfficientNetB4 architecture and utilized the transfer learning methodology for multilabel approach to detect lung zone wise and image wise manifestations of active pulmonary tuberculosis using chest X-ray. We used Area Under Receiver Operating Characteristic (AUC), sensitivity and specificity along with 95% confidence interval as model evaluation metrics. We also utilized the visualisation capabilities of convolutional neural networks (CNN), Gradient-weighted Class Activation Mapping (Grad-CAM) as post-hoc attention method to investigate the model and visualisation of Tuberculosis abnormalities and discuss them from radiological perspectives. EfficientNetB4 trained network achieved remarkable AUC, sensitivity and specificity of various pulmonary tuberculosis manifestations in intramural test set and external test set from different geographical region. The grad-CAM visualisations and their ability to localize the abnormalities can aid the clinicians at primary care settings for screening and triaging of tuberculosis where resources are constrained or overburdened.
Efficient gene–environment interaction testing through bootstrap aggregating
Authors: Lau Michael , Kress Sara , Schikowski Tamara , Schwender Holger 
Published: January 2023

AbstractGene–environment (GxE) interactions are an important and sophisticated component in the manifestation of complex phenotypes. Simple univariate tests lack statistical power due to the need for multiple testing adjustment and not incorporating potential interplay between several genetic loci. Approaches based on internally constructed genetic risk scores (GRS) require the partitioning of the available sample into training and testing data sets, thus, lowering the effective sample size for testing the GxE interaction itself. To overcome these issues, we propose a statistical test that employs bagging (bootstrap aggregating) in the GRS construction step and utilizes its out-of-bag prediction mechanism. This approach has the key advantage that the full available data set can be used for both constructing the GRS and testing the GxE interaction. To also incorporate interactions between genetic loci, we, furthermore, investigate if using random forests as the GRS construction method in GxE interaction testing further increases the statistical power. In a simulation study, we show that both novel procedures lead to a higher statistical power for detecting GxE interactions, while still controlling the type I error. The random-forests-based test outperforms a bagging-based test that uses the elastic net as its base learner in most scenarios. An application of the testing procedures to a real data set from a German cohort study suggests that there might be a GxE interaction involving exposure to air pollution regarding rheumatoid arthritis.
Optical hydrogen sensing with high-Q guided-mode resonance of Al2O3/WO3/Pd nanostructure
Authors: Kulikova Daria P. , Sgibnev Yevgeniy M. , Yankovskii Georgiy M. , Chubchev Eugeny D. , Lotkov Evgeniy S. , Ezenkova Daria A. , Dobronosova Alina A. , Baburin Aleksandr S. , Rodionov Ilya A. , Nechepurenko Igor A. , Baryshev Alexander V. , Dorofeenko Alexander V. 
Published: January 2023

AbstractNanostructure based on a dielectric grating (Al2O3), gasochromic oxide (WO3) and catalyst (Pd) is proposed as a hydrogen sensor working at the room temperature. In the fabricated structure, the Pd catalyst film was as thin as 1 nm that allowed a significant decrease in the optical absorption. A high-Q guided-mode resonance was observed in a transmission spectrum at normal incidence and was utilized for hydrogen detection. The spectra were measured at 0–0.12% of hydrogen in a synthetic air (≈ 80% $${\text{N}}_{2}$$

N
2

and 20% $${\text{O}}_{2}$$

O
2

). The detection limit below 100 ppm of hydrogen was demonstrated. Hydrogen was detected in the presence of oxygen, which provides the sensor recovery but suppresses the sensor response. Sensor response was treated by the principal component analysis (PCA), which effectively performs noise averaging. Influence of temperature and humidity was measured and processed by PCA, and elimination of the humidity and temperature effects was performed. Square root dependence of the sensor response on the hydrogen concentration (Sievert’s law) was observed. Sensor calibration curve was built, and the sensor resolution of 40 ppm was found. Long term stability of the sensor was investigated. Particularly, it was shown that the sensor retains its functionality after 6 months and dozens of acts of response to gas.
Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients
Authors: Bando Silvia Y. , Bertonha Fernanda B. , Vieira Sandra E. , de Oliveira Danielle B. L. , Chalup Vanessa N. , Durigon Edison L. , Palmeira Patricia , Curi Ana Cristina P. , Faria Caroline S. , Antonangelo Leila , Lauterbach Gerhard da P. , Regalio Fabiane A. , Cesar Jr Roberto M. , Moreira-Filho Carlos A. 
Published: January 2023

AbstractSince the molecular mechanisms determining COVID-19 severity are not yet well understood, there is a demand for biomarkers derived from comparative transcriptome analyses of mild and severe cases, combined with patients’ clinico-demographic and laboratory data. Here the transcriptomic response of human leukocytes to SARS-CoV-2 infection was investigated by focusing on the differences between mild and severe cases and between age subgroups (younger and older adults). Three transcriptional modules correlated with these traits were functionally characterized, as well as 23 differentially expressed genes (DEGs) associated to disease severity. One module, correlated with severe cases and older patients, had an overrepresentation of genes involved in innate immune response and in neutrophil activation, whereas two other modules, correlated with disease severity and younger patients, harbored genes involved in the innate immune response to viral infections, and in the regulation of this response. This transcriptomic mechanism could be related to the better outcome observed in younger COVID-19 patients. The DEGs, all hyper-expressed in the group of severe cases, were mostly involved in neutrophil activation and in the p53 pathway, therefore related to inflammation and lymphopenia. These biomarkers may be useful for getting a better stratification of risk factors in COVID-19.
Structural basis of bacterial effector protein azurin targeting tumor suppressor p53 and inhibiting its ubiquitination
Authors: Hu Jianjian , Jiang Wenxue , Zuo Jiaqi , Shi Dujuan , Chen Xiaoqi , Yang Xiao , Zhang Wenhui , Ma Lixin , Liu Zhu , Xing Qiong 
Published: January 2023

AbstractTumor suppressor p53 prevents tumorigenesis by promoting cell cycle arrest and apoptosis through transcriptional regulation. Dysfunction of p53 occurs frequently in human cancers. Thus, p53 becomes one of the most promising targets for anticancer treatment. A bacterial effector protein azurin triggers tumor suppression by stabilizing p53 and elevating its basal level. However, the structural and mechanistic basis of azurin-mediated tumor suppression remains elusive. Here we report the atomic details of azurin-mediated p53 stabilization by combining X-ray crystallography with nuclear magnetic resonance. Structural and mutagenic analysis reveals that the p28 region of azurin, which corresponds to a therapeutic peptide, significantly contributes to p53 binding. This binding stabilizes p53 by disrupting COP1-mediated p53 ubiquitination and degradation. Using the structure-based design, we obtain several affinity-enhancing mutants that enable amplifying the effect of azurin-induced apoptosis. Our findings highlight how the structure of the azurin-p53 complex can be leveraged to design azurin derivatives for cancer therapy.
Skin-specific mechanisms of body fluid regulation in hypertension
Authors: Chen Jun Yu , Chew Khai Syuen , Mary Sheon , Boder Philipp , Bagordo Domenico , Rossi Gian Paolo , Touyz Rhian M. , Delles Christian , Rossitto Giacomo 
Published: January 2023

AbstractIncreasing evidence suggests excess skin Na+ accumulation in hypertension; however, the role of skin-specific mechanisms of local Na+/water regulation remains unclear. We investigated the association between measures of sweat and trans-epidermal water loss (TEWL) with Na+ content in the skin ([Na+]skin) and clinical characteristics in consecutive hypertensive patients. We obtained an iontophoretic pilocarpine-induced sweat sample, a skin punch biopsy for chemical analysis, and measures of TEWL from the upper limbs. Serum vascular endothelial growth factor-c (VEGF-c) and a reflectance measure of haemoglobin skin content served as surrogates of skin microvasculature. In our cohort (n = 90; age 21–86 years; females = 49%), sweat composition was independent of sex and BMI. Sweat Na+ concentration ([Na+]sweat) inversely correlated with [K+]sweat and was higher in patients on ACEIs/ARBs (P &lt; 0.05). A positive association was found between [Na+]sweat and [Na+]skin, independent of sex, BMI, estimated Na+ intake and use of ACEi/ARBs (Padjusted = 0.025); both closely correlated with age (P &lt; 0.01). Office DBP, but not SBP, inversely correlated with [Na+]sweat independent of other confounders (Padjusted = 0.03). Total sweat volume and Na+ loss were lower in patients with uncontrolled office BP (Padjusted &lt; 0.005 for both); sweat volume also positively correlated with serum VEGF-c and TEWL. Lower TEWL was paralleled by lower skin haemoglobin content, which increased less after vasodilatory pilocarpine stimulation when BMI was higher (P = 0.010). In conclusion, measures of Na+ and water handling/regulation in the skin were associated with relevant clinical characteristics, systemic Na+ status and blood pressure values, suggesting a potential role of the skin in body-fluid homeostasis and therapeutic targeting of hypertension.
Predicting recurrence in osteosarcoma via a quantitative histological image classifier derived from tumour nuclear morphological features
Authors: Wang Zhan , Lu Haoda , Wu Yan , Ren Shihong , Diaty Diarra mohamed , Fu Yanbiao , Zou Yi , Zhang Lingling , Wang Zenan , Wang Fangqian , Li Shu , Huo Xinmi , Yu Weimiao , Xu Jun , Ye Zhaoming 
Published: January 2023

AbstractRecurrence is the key factor affecting the prognosis of osteosarcoma. Currently, there is a lack of clinically useful tools to predict osteosarcoma recurrence. The application of pathological images for artificial intelligence‐assisted accurate prediction of tumour outcomes is increasing. Thus, the present study constructed a quantitative histological image classifier with tumour nuclear features to predict osteosarcoma outcomes using haematoxylin and eosin (H&E)‐stained whole‐slide images (WSIs) from 150 osteosarcoma patients. We first segmented eight distinct tissues in osteosarcoma H&E‐stained WSIs, with an average accuracy of 90.63% on the testing set. The tumour areas were automatically and accurately acquired, facilitating the tumour cell nuclear feature extraction process. Based on six selected tumour nuclear features, we developed an osteosarcoma histological image classifier (OSHIC) to predict the recurrence and survival of osteosarcoma following standard treatment. The quantitative OSHIC derived from tumour nuclear features independently predicted the recurrence and survival of osteosarcoma patients, thereby contributing to precision oncology. Moreover, we developed a fully automated workflow to extract quantitative image features, evaluate the diagnostic values of feature sets and build classifiers to predict osteosarcoma outcomes. Thus, the present study provides a novel tool for predicting osteosarcoma outcomes, which has a broad application prospect in clinical practice.
A threshold‐based sorting algorithm for dense wireless sensor systems and communication networks
Authors: Shirvani Moghaddam Shahriar , Shirvani Moghaddam Kiaksar 
Published: January 2023

AbstractNowadays, time‐varying and high‐density data of wireless sensor systems and communication networks compel us to propose and realise low‐complexity and time‐efficient algorithms for searching, clustering, and sorting. A novel threshold‐based sorting algorithm applicable to dense and ultra‐dense networks is proposed in this study. Instead of sorting whole data in a large data set and selecting a certain number of them, the proposed algorithm sorts a specific number of elements that are larger or smaller than a threshold level or located between two threshold values. First, based on the mean value and standard deviation of the data, a theoretical analysis to find the exact and approximate thresholds, respectively for known (Gaussian, uniform, Rayleigh, and negative exponential) and unknown probability distributions is presented. Then, an algorithm to sort a predefined number of data is realised. Finally, the effectiveness of the proposed algorithm is shown in the view of the time complexity order, the running time, and the similarity measure. To do this, theoretical and numerical analyses are used to show the superiority of the proposed algorithm in known and unknown distributions to the well‐known conventional and gradual conventional versions of Merge, Quick, and K‐S mean‐based sorting algorithms.
GaiaData Release 3
Authors: Holl B. , Sozzetti A. , Sahlmann J. , Giacobbe P. , Ségransan D. , Unger N. , Delisle J.-B. , Barbato D. , Lattanzi M. G. , Morbidelli R. , Sosnowska D. 
Published: January 2023

Context.The astrometric discovery of sub-stellar mass companions orbiting stars is exceedingly hard due to the required sub-milliarcsecond precision, limiting the application of this technique to only a few instruments on a target-per-target basis and to the global astrometry space missions HIPPARCOSandGaia. The thirdGaiadata release (GaiaDR3) includes the firstGaiaastrometric orbital solutions whose sensitivity in terms of estimated companion mass extends down to the planetary-mass regime.Aims.We present the contribution of the exoplanet pipeline to theGaiaDR3 sample of astrometric orbital solutions by describing the methods used for fitting the orbits, the identification of significant solutions, and their validation. We then present an overview of the statistical properties of the solution parameters.Methods.Using both a Markov chain Monte Carlo and a genetic algorithm, we fitted the 34 months ofGaiaDR3 astrometric time series with a single Keplerian astrometric-orbit model that had 12 free parameters and an additional jitter term, and retained the solutions with the lowestχ2. Verification and validation steps were taken using significance tests, internal consistency checks using theGaiaradial velocity measurements (when available), as well as literature radial velocity and astrometric data, leading to a subset of candidates that were labelled “validated”.Results.We determined astrometric-orbit solutions for 1162 sources, and 198 solutions were assigned the “Validated” label. Precise companion-mass estimates require external information and are presented elsewhere. To broadly categorise the different mass regimes in this paper, we use the pseudo-companion massM̃cassuming a solar-mass host and define three solution groups: 17 (9 validated) solutions with companions in the planetary-mass regime (M̃c< 20MJ), 52 (29 validated) in the brown dwarf regime (20MJ≤M̃c≤ 120  MJ), and 1093 (160 validated) in the low-mass stellar companion regime (M̃c> 120MJ). From internal and external verification and validation, we estimate the level of spurious and incorrect solutions in our sample to be ∼5% and ∼10% in the ‘OrbitalAlternative’ and ‘OrbitalTargetedSearch’ candidate sample, respectively.Conclusions.We demonstrate thatGaiais able to confirm and sometimes refine the orbits of known orbital companions and to identify new candidates, providing us with a positive outlook for the expected harvest from the full mission data in future data releases.
Filaments in the OMC-3 cloud and uncertainties in estimates of filament profiles
Authors: Juvela M. , Mannfors E. 
Published: January 2023

Context.Filamentary structures are an important part of star-forming interstellar clouds. The properties of filaments hold clues to their formation mechanisms and their role in the star-formation process.Aims.We compare the properties of filaments in the Orion Molecular Cloud 3 (OMC-3), as seen in mid-infrared (MIR) absorption and far-infrared (FIR) dust emission. We also wish to characterise some potential sources of systematic errors in filament studies.Methods.We calculated optical depth maps of the OMC-3 filaments based on the MIR absorption seen inSpitzerdata and FIR dust emission observed withBerscheland the ArTéMiS instrument. We then compared the filament properties extracted from the data. Potential sources of error were investigated more generally with the help of radiative transfer models.Results.The widths of the selected OMC-3 filament segments are in the range 0.03–0.1 pc, with similar average values seen in both MIR and FIR analyses. Compared to the widths, the individual parameters of the fitted Plummer functions are much more uncertain. The asymptotic power-law index has typically valuesp ~3 but with a large scatter. Modelling shows that the FIR observations can systematically overestimate the filament widths. The effect is potentially tens of per cent at column densities aboveN(H2) ~ 1022cm–2but is reduced in more intense radiation fields, such as the Orion region. Spatial variations in dust properties could cause errors of similar magnitude. In the MIR analysis, dust scattering should generally not be a significant factor, unless there are high-mass stars nearby or the dust MIR scattering efficiency is higher than in the tested dust models. Thermal MIR dust emission can be a more significant source of error, especially close to embedded sources.Conclusions.The analysis of interstellar filaments can be affected by several sources of systematic error, but mainly at high column densities and, in the case of FIR observations, in weak radiation fields. The widths of the OMC-3 filaments were consistent between the MIR and FIR analyses and did not reveal any systematic dependence on the angular resolution of the observations.
The SOUL view of IRAS 20126+4104
Authors: Massi F. , Caratti o Garatti A. , Cesaroni R. , Sridharan T. K. , Ghose E. , Pinna E. , Beltrán M. T. , Leurini S. , Moscadelli L. , Sanna A. , Agapito G. , Briguglio R. , Christou J. , Esposito S. , Mazzoni T. , Miller D. , Plantet C. , Power J. , Puglisi A. , Rossi F. , Rothberg B. , Taylor G. , Veillet C. 
Published: January 2023

Context. We exploit the increased sensitivity of the recently installed adaptive optics SOUL at the LBT to obtain new high-spatial-resolution near-infrared images of the massive young stellar object IRAS20126+4104 and its outflow.
Aims. We aim to derive the jet proper motions and kinematics, as well as to study its photometric variability by combining the novel performances of SOUL together with previous near-infrared images.
Methods. We used both broad-band (Ks, K′) and narrow-band (Brγ, H2) observations from a number of near-infrared cameras (UKIRT/UFTI, SUBARU/CIAO, TNG/NICS, LBT/PISCES, and LBT/LUCI1) to derive maps of the continuum and the H2 emission in the 2.12 µm line. Three sets of images, obtained with adaptive optics (AO) systems (CIAO, in 2003; FLAO, in 2012; SOUL, in 2020), allowed us to derive the proper motions of a large number of H2 knots along the jet. Photometry from all images was used to study the jet variability.
Results. We derived knot proper motions in the range of 1.7–20.3 mas yr−1 (i.e. 13–158 km s−1 at 1.64 kpc), implying an average outflow tangential velocity of ~80 km s−1. The derived knot dynamical age spans a ~200–4000 yr interval. A ring-like H2 feature near the protostar location exhibits peculiar kinematics and may represent the outcome of a wide-angle wind impinging on the outflow cavity. Both H2 geometry and velocities agree with those inferred from proper motions of the H2O masers, located at a smaller distance from the protostar. Although the total H2 line emission from the knots does not exhibit time variations at a ⪞0.3 mag level, we have found a clear continuum flux variation (radiation scattered by the dust in the cavity opened by the jet) which is anti-correlated between the blue-shifted and red-shifted lobes and may be periodic (with a period of ~12–18 yr). We suggest that the continuum variability might be related to inner-disc oscillations which have also caused the jet precession.
Conclusions. Our analysis shows that multi-epoch high-spatial-resolution imaging in the near-infrared is a powerful tool to unveil the physical properties of highly embedded massive protostars.
Importance de Mycoplasma bovis dans les affections respiratoires en fonction des systèmes de production
Authors: Belbis Guillaume 
Published: January 2023

Mycoplasma bovis est une bactérie fréquemment impliquée dans les troubles respiratoires des jeunes bovins. Si elle peut à elle seule conduire à des lésions pulmonaires, elle est souvent considérée comme un agent potentialisateur, favorisant le développement d’autres agents secondaires. Son impact diffère selon les systèmes de production : des études de séroprévalence montrent une importance modérée mais variable en système naisseur, alors que son impact est plus fort dans les ateliers d’engraissement de veaux de boucherie.