bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent computing with Levenberg–Marquardt artificial neural network for Carbon nanotubes-water between stretchable rotating disks
Authors: Ali Faizan , Awais Muhammad , Ali Aamir , Vrinceanu Narcisa , Shah Zahir , Tirth Vineet 
Published: March 2023

AbstractHybrid Nano fluid has emerged to be an important field of study due to its better thermal performance compared to other Nano fluids. The problem of carbon nanotubes rotating between two stretchable discs while suspended in water is investigated in this research. Due to numerous uses of this problem, such as metal mining, drawing plastic films, and cooling continuous filaments, this problem is essential to industry. Considerations here include suction/injection, heat radiation, and the Darcy-Forchheimer scheme with convective boundary conditions. The partial differential equations are reduced to ordinary differential equations by using appropriate transformation. To examine the approximate solution validation, training and testing procedures are interpreted and the performance is verified through error histogram and mean square error results. To describe the behavior of flow quantities, several tabular and graphical representations of a variety of physical characteristics of importance are presented and discussed in detail. The basic aim of this research is to examine the behaviour of carbon nanotubes (nanoparticles) between stretchable disks while considering the heat generation/absorption parameter by using the Levenberg–Marquardt technique of artificial neural network. Heat transfer rate is accelerated by a decrease in velocity and temperature and an increase in the nanoparticle volume fraction parameter which is a significant finding of the current study.
Preparing pathological data to develop an artificial intelligence model in the nonclinical study
Authors: Hwang Ji-Hee , Lim Minyoung , Han Gyeongjin , Park Heejin , Kim Yong-Bum , Park Jinseok , Jun Sang-Yeop , Lee Jaeku , Cho Jae-Woo 
Published: March 2023

AbstractArtificial intelligence (AI)-based analysis has recently been adopted in the examination of histological slides via the digitization of glass slides using a digital scanner. In this study, we examined the effect of varying the staining color tone and magnification level of a dataset on the result of AI model prediction in hematoxylin and eosin stained whole slide images (WSIs). The WSIs of liver tissues with fibrosis were used as an example, and three different datasets (N20, B20, and B10) were prepared with different color tones and magnifications. Using these datasets, we built five models trained Mask R-CNN algorithm by a single or mixed dataset of N20, B20, and B10. We evaluated their model performance using the test dataset of three datasets. It was found that the models that were trained with mixed datasets (models B20/N20 and B10/B20), which consist of different color tones or magnifications, performed better than the single dataset trained models. Consequently, superior performance of the mixed models was obtained from the actual prediction results of the test images. We suggest that training the algorithm with various staining color tones and multi-scaled image datasets would be more optimized for consistent remarkable performance in predicting pathological lesions of interest.
Fractal dimension based geographical clustering of COVID-19 time series data
Authors: Natalia Yessika Adelwin , Faes Christel , Neyens Thomas , Chys Pieter , Hammami Naïma , Molenberghs Geert 
Published: March 2023

AbstractUnderstanding the local dynamics of COVID-19 transmission calls for an approach that characterizes the incidence curve in a small geographical unit. Given that incidence curves exhibit considerable day-to-day variation, the fractal structure of the time series dynamics is investigated for the Flanders and Brussels Regions of Belgium. For each statistical sector, the smallest administrative geographical entity in Belgium, fractal dimensions of COVID-19 incidence rates, based on rolling time spans of 7, 14, and 21 days were estimated using four different estimators: box-count, Hall-Wood, variogram, and madogram. We found varying patterns of fractal dimensions across time and location. The fractal dimension is further summarized by its mean, variance, and autocorrelation over time. These summary statistics are then used to cluster regions with different incidence rate patterns using k-means clustering. Fractal dimension analysis of COVID-19 incidence thus offers important insight into the past, current, and arguably future evolution of an infectious disease outbreak.
Fiber enhancement and 3D orientation analysis in label-free two-photon fluorescence microscopy
Authors: Sorelli Michele , Costantini Irene , Bocchi Leonardo , Axer Markus , Pavone Francesco Saverio , Mazzamuto Giacomo 
Published: March 2023

AbstractFluorescence microscopy can be exploited for evaluating the brain’s fiber architecture with unsurpassed spatial resolution in combination with different tissue preparation and staining protocols. Differently from state-of-the-art polarimetry-based neuroimaging modalities, the quantification of fiber tract orientations from fluorescence microscopy volume images entails the application of specific image processing techniques, such as Fourier or structure tensor analysis. These, however, may lead to unreliable outcomes as they do not isolate myelinated fibers from the surrounding tissue. In this work, we describe a novel image processing pipeline that enables the computation of accurate 3D fiber orientation maps from both grey and white matter regions, exploiting the selective multiscale enhancement of tubular structures of varying diameters provided by a 3D implementation of the Frangi filter. The developed software tool can efficiently generate orientation distribution function maps at arbitrary spatial scales which may support the histological validation of modern diffusion-weighted magnetic resonance imaging tractography. Despite being tested here on two-photon scanning fluorescence microscopy images, acquired from tissue samples treated with a label-free technique enhancing the autofluorescence of myelinated fibers, the presented pipeline was developed to be employed on all types of 3D fluorescence images and fiber staining.
Exogenous melatonin induces phenolic compounds production in Linum album cells by altering nitric oxide and salicylic acid
Authors: Esmaeili Sara , Sharifi Mohsen , Ghanati Faezeh , Soltani Bahram M. , Samari Elaheh , Sagharyan Mostafa 
Published: March 2023

AbstractMelatonin is a pleiotropic molecule that can influence various aspects of plant performance. Recent studies have exhibited that it mediates plant defensive responses, probably through managing redox homeostasis. We tried to track the regulatory effects of melatonin on the antioxidant machinery of Linum album cell culture. To this, different concentrations of melatonin were applied, and the oxidative status of cells was investigated by measuring the levels of oxidative molecules and antioxidant agents. The results showed that H2O2 content did not change at the low melatonin levels, while it increased at the high concentrations. It can be correlated with the low melatonin dosages capacity to remove excessive amounts of H2O2, while the high melatonin dosages exhibit toxicity effects. In contrast, the NO enhancement occurred at 50 μM melatonin, proposing its role in triggering melatonin-induced defensive responses. The MDA results stated that NO led to oxidative stress in melatonin-treated cells at 50 μM melatonin. Antioxidant enzyme POD was activated by melatonin treatment, while SOD enzyme behaved reversely which can explain the changes in the H2O2 level. In addition, the analysis of the phenolics profile showed that the contents of phenolic acids, flavonoids, and lignans enhanced following an increase in PAL enzyme activity. The increased level of phenolic hormone SA can indicate that melatonin affects the defensive responses in L. album cells through a SA-dependent pathway. In general, it seems that melatonin, by modulating NO and SA levels, can induce the activity of antioxidant enzymes and the production of phenolics, especially lignans, in L. album cells.
Diel variations in planktonic ciliate community structure in the northern South China Sea and tropical Western Pacific
Authors: Wang Chaofeng , Dong Yi , Denis Michel , Wei Yuanyuan , Li Haibo , Zheng Shan , Zhang Wuchang , Xiao Tian 
Published: March 2023

AbstractThough diel variations are geographically widespread phenomena among phytoplankton and zooplankton, knowledge is limited regarding diel variations in planktonic ciliate (microzooplankton) community structure. In this study, we analyzed diel variations in community structure of planktonic ciliates in the northern South China Sea (nSCS) and tropical Western Pacific (tWP). Hydrological characteristics during day and night were slightly different over both the nSCS and tWP, while ciliate average abundance at night was clearly higher than in the day in the upper 200 m. In both the nSCS and tWP, abundance proportions of large size-fraction (> 30 μm) aloricate ciliates at night were higher than in the day. While for tintinnids, abundance proportion of large lorica oral diameter at night were lower than in the day. The relationship between environmental factors and ciliate abundance pointed out that depth and temperature were main factors influencing aloricate ciliate and tintinnid in both day and night. For some dominant tintinnid species, chlorophyllawas another important factor influencing their diel vertical distribution. Our results provide fundamental data for better understanding the mechanisms of planktonic ciliate community diel variation in the tropical Western Pacific Ocean.
Analysis of available animal testing data to propose peer-derived quantitative thresholds for determining adequate surveillance capacity for rabies
Authors: Minhaj Faisal S. , Bonaparte Sarah C. , Boutelle Cassandra , Wallace Ryan M. 
Published: March 2023

AbstractHistorical targets for country-level animal rabies testing volumes were abandoned due to ethical and welfare concerns, and interpretation challenges of testing healthy animals. To-date, no quantitative threshold has been established for evaluating adequate surveillance capacity specific to suspected rabid animals. The purpose here is to establish quantitative testing thresholds for rabies suspected animals to assess a country’s rabies surveillance capacity. Animal rabies testing data was obtained from official and unofficial rabies surveillance platforms from 2010 to 2019 and supplemented with official country reports and published literature. Testing rates were determined for all-animal and domestic animals, and standardized per 100,000 estimated human population; the domestic animal rate was also standardized per 100,000 estimated dog population. There were 113 countries that reported surveillance data eligible for analysis. Countries reporting the most data were under WHO categories as having endemic human rabies or no dog rabies. The annual median all-animal testing rate for all countries was 1.53 animals/100,000 human population (IQR 0.27–8.78). Three proposed testing rate thresholds are an all-animal rate of 1.9 animals/100,000 humans, a domestic animal per human rate of 0.8 animals/100,000 humans, and a domestic animal per dog rate of 6.6 animals/100,000 dogs. These three peer-derived rabies testing thresholds for passive surveillance can be used to facilitate assessment of a country’s rabies surveillance capacity.
Novel architecture for gated recurrent unit autoencoder trained on time series from electronic health records enables detection of ICU patient subgroups
Authors: Merkelbach Kilian , Schaper Steffen , Diedrich Christian , Fritsch Sebastian Johannes , Schuppert Andreas 
Published: March 2023

AbstractElectronic health records (EHRs) are used in hospitals to store diagnoses, clinician notes, examinations, lab results, and interventions for each patient. Grouping patients into distinct subsets, for example, via clustering, may enable the discovery of unknown disease patterns or comorbidities, which could eventually lead to better treatment through personalized medicine. Patient data derived from EHRs is heterogeneous and temporally irregular. Therefore, traditional machine learning methods like PCA are ill-suited for analysis of EHR-derived patient data. We propose to address these issues with a new methodology based on training a gated recurrent unit (GRU) autoencoder directly on health record data. Our method learns a low-dimensional feature space by training on patient data time series, where the time of each data point is expressed explicitly. We use positional encodings for time, allowing our model to better handle the temporal irregularity of the data. We apply our method to data from the Medical Information Mart for Intensive Care (MIMIC-III). Using our data-derived feature space, we can cluster patients into groups representing major classes of disease patterns. Additionally, we show that our feature space exhibits a rich substructure at multiple scales.
Stress native T1 and native T2 mapping compared to myocardial perfusion reserve in long-term follow-up of severe Covid-19
Authors: Nickander Jannike , Steffen Johansson Rebecka , Lodin Klara , Wahrby Anton , Loewenstein Daniel , Bruchfeld Judith , Runold Michael , Xue Hui , Kellman Peter , Engblom Henrik 
Published: March 2023

AbstractSevere Covid-19 may cause a cascade of cardiovascular complications beyond viral pneumonia. The severe inflammation may affect the microcirculation which can be assessed by cardiovascular magnetic resonance (CMR) imaging using quantitative perfusion mapping and calculation of myocardial perfusion reserve (MPR). Furthermore, native T1 and T2 mapping have previously been shown to identify changes in myocardial perfusion by the change in native T1 and T2 during adenosine stress. However, the relationship between native T1, native T2, ΔT1 and ΔT2 with myocardial perfusion and MPR during long-term follow-up in severe Covid-19 is currently unknown. Therefore, patients with severe Covid-19 (n = 37, median age 57 years, 24% females) underwent 1.5 T CMR median 292 days following discharge. Quantitative myocardial perfusion (ml/min/g), and native T1 and T2 maps were acquired during adenosine stress, and rest, respectively. Both native T1 (R2 = 0.35, p < 0.001) and native T2 (R2 = 0.28, p < 0.001) correlated with myocardial perfusion. However, there was no correlation with ΔT1 or ΔT2 with MPR, respectively (p > 0.05 for both). Native T1 and native T2 correlate with myocardial perfusion during adenosine stress, reflecting the coronary circulation in patients during long-term follow-up of severe Covid-19. Neither ΔT1 nor ΔT2 can be used to assess MPR in patients with severe Covid-19.
Extraction-free clinical detection of SARS-CoV-2 virus from saline gargle samples using Hamilton STARlet liquid handler
Authors: Gadkar Vijay J. , Goldfarb David M. , Al-Rawahi Ghada N. , Srigley Jocelyn A. , Smailus Duane E. , Coope Robin J. N. , Pleasance Stephen , Watson Nicole , Chen Tammy , Lam Sunny , Hoang Linda , Tilley Peter A. G. 
Published: March 2023

AbstractAs part of the COVID-19 pandemic, clinical laboratories have been faced with massive increases in testing, resulting in sample collection systems, reagent, and staff shortages. We utilized self-collected saline gargle samples to optimize high throughput SARS-CoV-2 multiplex polymerase chain reaction (PCR) testing in order to minimize cost and technologist time. This was achieved through elimination of nucleic acid extraction and automation of sample handling on a widely available robotic liquid handler, Hamilton STARlet. A customized barcode scanning script for reading the sample ID by the Hamilton STARlet’s software system was developed to allow primary tube sampling. Use of pre-frozen SARS-CoV-2 assay reaction mixtures reduced assay setup time. In both validation and live testing, the assay produced no false positive or false negative results. Of the 1060 samples tested during validation, 3.6% (39/1060) of samples required retesting as they were either single gene positive, had internal control failure or liquid aspiration error. Although the overall turnaround time was only slightly faster in the automated workflow (185 min vs 200 min), there was a 76% reduction in hands-on time, potentially reducing staff fatigue and burnout. This described process from sample self-collection to automated direct PCR testing significantly reduces the total burden on healthcare systems in terms of human resources and reagent requirements.
New pattern in regular nuclei based on their experimental quadrupole transition rates and some new candidates
Authors: Hosseinnezhad Asgar , Seidi Masoud , Sabri Hadi 
Published: March 2023

AbstractIn this paper, we tried to get a new signature of regular nuclei based on their quadrupole transition rates. We have analyzed the experimental electric quadrupole transition probabilities of well-known "regular nuclei". The results indicate finding specific repetition patterns for E2 transition rates, similar to what has been reported for the energy levels of these nuclei. We also tested the existence of this observed repetition scheme for all known isotopes whose experimental transition rates are available and introduced several new candidates as regular nuclei. Then, the energy spectra (Experimental) of these new suggested "regular nuclei" are investigated in the framework of the Interacting Boson Model, in which the parameters of Hamiltonian confirm the placement of these nuclei in the "Alhassid-Whelan arc of regularity" region. In order to further study the statistical distribution of experimental energy levels related to the electromagnetic transitions we are considering, we studied using the random matrix theory. The results confirmed their regularity.
An exploratory approach to identify microRNAs as circulatory biomarker candidates for epilepsy-associated psychiatric comorbidities in an electrical post-status epilepticus model
Authors: von Rüden Eva-Lotta , Janssen-Peters Heike , Reiber Maria , van Dijk Roelof Maarten , Xiao Ke , Seiffert Isabel , Koska Ines , Hubl Christina , Thum Thomas , Potschka Heidrun 
Published: March 2023

AbstractPatients with epilepsy have a high risk of developing psychiatric comorbidities, and there is a particular need for early detection of these comorbidities. Here, in an exploratory, hypothesis-generating approach, we aimed to identify microRNAs as potential circulatory biomarkers for epilepsy-associated psychiatric comorbidities across different rat models of epilepsy. The identification of distress-associated biomarkers can also contribute to animal welfare assessment. MicroRNA expression profiles were analyzed in blood samples from the electrical post-status epilepticus (SE) model. Preselected microRNAs were correlated with behavioral and biochemical parameters in the electrical post-SE model, followed by quantitative real-time PCR validation in three additional well-described rat models of epilepsy. Six microRNAs (miR-376a, miR-429, miR-494, miR-697, miR-763, miR-1903) were identified showing a positive correlation with weight gain in the early post-insult phase as well as a negative correlation with social interaction, saccharin preference, and plasma BDNF. Real-time PCR validation confirmed miR-203, miR-429, and miR-712 as differentially expressed with miR-429 being upregulated across epilepsy models. While readouts from the electrical post-SE model suggest different microRNA candidates for psychiatric comorbidities, cross-model analysis argues against generalizability across models. Thus, further research is necessary to compare the predictive validity of rodent epilepsy models for detection and management of psychiatric comorbidities.
Cost consequence analysis of waiting for lumbar disc herniation surgery
Authors: Dandurand Charlotte , Mashayekhi Mohammad Sadegh , McIntosh Greg , Singh Supriya , Paquet Jerome , Chaudhry Hasaan , Abraham Edward , Bailey Christopher S. , Weber Michael H. , Johnson Michael G. , Nataraj Andrew , Attabib Najmedden , Kelly Adrienne , Hall Hamilton , Rampersaud Y. Raja , Manson Neil , Phan Philippe , Thomas Ken , Fisher Charles , Charest-Morin Raphaele , Soroceanu Alex , LaRue Bernard , Dea Nicolas 
Published: March 2023

AbstractThe economic repercussions of waiting for lumbar disc surgery have not been well studied. The primary goal of this study was to perform a cost-consequence analysis of patients receiving early vs late surgery for symptomatic disc herniation from a societal perspective. Secondarily, we compared patient factors and patient-reported outcomes. This is a retrospective analysis of prospectively collected data from the CSORN registry. A cost-consequence analysis was performed where direct and indirect costs were compared, and different outcomes were listed separately. Comparisons were made on an observational cohort of patients receiving surgery less than 60 days after consent (short wait) or 60 days or more after consent (long wait). This study included 493 patients with surgery between January 2015 and October 2021 with 272 patients (55.2%) in the short wait group and 221 patients (44.8%) classified as long wait. There was no difference in proportions of patients who returned to work at 3 and 12-months. Time from surgery to return to work was similar between both groups (34.0 vs 34.9 days, p = 0.804). Time from consent to return to work was longer in the longer wait group corresponding to an additional $11,753.10 mean indirect cost per patient. The short wait group showed increased healthcare usage at 3 months with more emergency department visits (52.6% vs 25.0%, p < 0.032), more physiotherapy (84.6% vs 72.0%, p < 0.001) and more MRI (65.2% vs 41.4%, p < 0.043). This corresponded to an additional direct cost of $518.21 per patient. Secondarily, the short wait group had higher baseline NRS leg, ODI, and lower EQ5D and PCS. The long wait group had more patients with symptoms over 2 years duration (57.6% vs 34.1%, p < 0.001). A higher proportion of patients reached MCID in terms of NRS leg pain at 3-month follow up in the short wait group (84.0% vs 75.9%, p < 0.040). This cost-consequence analysis of an observational cohort showed decreased costs associated with early surgery of $11,234.89 per patient when compared to late surgery for lumbar disc herniation. The early surgery group had more severe symptoms with higher healthcare utilization. This is counterbalanced by the additional productivity loss in the long wait group, which likely have a more chronic disease. From a societal economic perspective, early surgery seems beneficial and should be promoted.