bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning
Authors: Mueller Yvonne M. , Schrama Thijs J. , Ruijten Rik , Schreurs Marco W. J. , Grashof Dwin G. B. , van de Werken Harmen J. G. , Lasinio Giovanna Jona , Álvarez-Sierra Daniel , Kiernan Caoimhe H. , Castro Eiro Melisa D. , van Meurs Marjan , Brouwers-Haspels Inge , Zhao Manzhi , Li Ling , de Wit Harm , Ouzounis Christos A. , Wilmsen Merel E. P. , Alofs Tessa M. , Laport Danique A. , van Wees Tamara , Kraker Geoffrey , Jaimes Maria C. , Van Bockstael Sebastiaan , Hernández-González Manuel , Rokx Casper , Rijnders Bart J. A. , Pujol-Borrell Ricardo , Katsikis Peter D. 
Published: February 2022

AbstractQuantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient’s immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy.
The histone demethylase Kdm6b regulates subtype diversification of mouse spinal motor neurons during development
Authors: Wang Wenxian , Cho Hyeyoung , Lee Jae W. , Lee Soo-Kyung 
Published: February 2022

AbstractHow a single neuronal population diversifies into subtypes with distinct synaptic targets is a fundamental topic in neuroscience whose underlying mechanisms are unclear. Here, we show that the histone H3-lysine 27 demethylase Kdm6b regulates the diversification of motor neurons to distinct subtypes innervating different muscle targets during spinal cord development. In mouse embryonic motor neurons, Kdm6b promotes the medial motor column (MMC) and hypaxial motor column (HMC) fates while inhibiting the lateral motor column (LMC) and preganglionic motor column (PGC) identities. Our single-cell RNA-sequencing analyses reveal the heterogeneity of PGC, LMC, and MMC motor neurons. Further, our single-cell RNA-sequencing data, combined with mouse model studies, demonstrates that Kdm6b acquires cell fate specificity together with the transcription factor complex Isl1-Lhx3. Our study provides mechanistic insight into the gene regulatory network regulating neuronal cell-type diversification and defines a regulatory role of Kdm6b in the generation of motor neuron subtypes in the mouse spinal cord.
Programming cell-free biosensors with DNA strand displacement circuits
Authors: Jung Jaeyoung K. , Archuleta Chloé M. , Alam Khalid K. , Lucks Julius B. 
Published: February 2022

AbstractCell-free biosensors are powerful platforms for monitoring human and environmental health. Here, we expand their capabilities by interfacing them with toehold-mediated strand displacement circuits, a dynamic DNA nanotechnology that enables molecular computation through programmable interactions between nucleic acid strands. We develop design rules for interfacing a small molecule sensing platform called ROSALIND with toehold-mediated strand displacement to construct hybrid RNA–DNA circuits that allow fine-tuning of reaction kinetics. We use these design rules to build 12 different circuits that implement a range of logic functions (NOT, OR, AND, IMPLY, NOR, NIMPLY, NAND). Finally, we demonstrate a circuit that acts like an analog-to-digital converter to create a series of binary outputs that encode the concentration range of the molecule being detected. We believe this work establishes a pathway to create ‘smart’ diagnostics that use molecular computations to enhance the speed and utility of biosensors.
A human tau seeded neuronal cell model recapitulates molecular responses associated with Alzheimer’s disease
Authors: Ficulle Elena , Kananathan Sarubini , Airey David , Gharbi Severine I. , Humphryes-Kirilov Neil , Scherschel James , Dunbar Charlotte , Eastwood Brian J. , Laing Emma , Collier David A. , Bose Suchira 
Published: February 2022

AbstractCellular models recapitulating features of tauopathies are useful tools to investigate the causes and consequences of tau aggregation and the identification of novel treatments. We seeded rat primary cortical neurons with tau isolated from Alzheimer’s disease brains to induce a time-dependent increase in endogenous tau inclusions. Transcriptomics of seeded and control cells identified 1075 differentially expressed genes (including 26 altered at two time points). These were enriched for lipid/steroid metabolism and neuronal/glial cell development genes. 50 genes were correlated with tau inclusion formation at both transcriptomic and proteomic levels, including several microtubule and cytoskeleton-related proteins such as Tubb2a, Tubb4a, Nefl and Snca. Several genes (such as Fyn kinase and PTBP1, a tau exon 10 repressor) interact directly with or regulate tau. We conclude that this neuronal model may be a suitable platform for high-throughput screens for target or hit compound identification and validation.
The burden of stroke and its attributable risk factors in the Middle East and North Africa region, 1990–2019
Authors: Jaberinezhad Mehran , Farhoudi Mehdi , Nejadghaderi Seyed Aria , Alizadeh Mahasti , Sullman Mark J. M. , Carson-Chahhoud Kristin , Collins Gary S. , Safiri Saeid 
Published: February 2022

AbstractStroke is one of the leading causes of mortality and morbidity across the globe. Providing comprehensive data on the burden of stroke in the Middle East and North Africa (MENA) could be useful for health policy makers in the region. Therefore, this article reported the burden of stroke and its attributable risk factors between 1990 and 2019 by age, sex, type of stroke, and socio-demographic index. Data on the point prevalence, death, and disability-adjusted life-years (DALYs), due to stroke, were retrieved from the Global Burden of Disease study 2019 for the 21 countries located in the MENA region from 1990 to 2019. The counts and age-standardised rates (per 100,000) were presented, along with their corresponding 95% uncertainty intervals (UIs). In 2019, the regional age-standardised point prevalence and death rates of stroke were 1537.5 (95% UI: 1421.9–1659.9) and 87.7 (78.2–97.6) per 100,000, which represent a 0.5% (− 2.3 to 1.1) and 27.8% (− 35.4 to − 16) decrease since 1990, respectively. Moreover, the regional age-standardised DALY rate in 2019 was 1826.2 (1635.3–2026.2) per 100,000, a 32.0% (− 39.1 to − 23.3) decrease since 1990. In 2019, Afghanistan [3498.2 (2508.8–4500.4)] and Lebanon [752.9 (593.3–935.9)] had the highest and lowest age-standardised DALY rates, respectively. Regionally, the total number of stroke cases were highest in the 60–64 age group and was more prevalent in women in all age groups. In addition, there was a general negative association between SDI and the burden of stoke from 1990 to 2019. Also, in 2019, high systolic blood pressure [53.5%], high body mass index [39.4%] and ambient particulate air pollution [27.1%] made the three largest contributions to the burden of stroke in the MENA region. The stroke burden has decreased in the MENA region over the last three decades, although there are large inter-country differences. Preventive programs should be implemented which focus on metabolic risk factors, especially among older females in low SDI countries.
Characterization of the canine CD20 as a therapeutic target for comparative passive immunotherapy
Authors: Dias Joana N. R. , Almeida André , André Ana S. , Aguiar Sandra I. , Bule Pedro , Nogueira Sara , Oliveira Soraia S. , Carrapiço Belmira , Gil Solange , Tavares Luís , Aires-da-Silva Frederico 
Published: February 2022

AbstractAnti-CD20 therapies have revolutionized the treatment of B-cell malignancies. Despite these advances, relapsed and refractory disease remains a major treatment challenge. The optimization of CD20-targeted immunotherapies is considered a promising strategy to improve current therapies. However, research has been limited by the scarcity of preclinical models that recapitulate the complex interaction between the immune system and cancers. The addition of the canine lymphoma (cNHL) model in the development of anti-CD20 therapies may provide a clinically relevant approach for the translation of improved immunotherapies. Still, an anti-CD20 therapy for cNHL has not been established stressing the need of a comprehensive target characterization. Herein, we performed an in-depth characterization on canine CD20 mRNA transcript and protein expression in a cNHL biobank and demonstrated a canine CD20 overexpression in B-cell lymphoma samples. Moreover, CD20 gene sequencing analysis identified six amino acid differences in patient samples (C77Y, L147F, I159M, L198V, A201T and G273E). Finally, we reported the use of a novel strategy for the generation of anti-CD20 mAbs, with human and canine cross-reactivity, by exploring our rabbit derived single-domain antibody platform. Overall, these results support the rationale of using CD20 as a target for veterinary settings and the development of novel therapeutics and immunodiagnostics.
MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink
Authors: Dagal Idriss , Akın Burak , Akboy Erdem 
Published: February 2022

AbstractIn this paper, a battery charging model is developed for solar PV system applications. As a means of photovoltaic power controlling system, buck-boost converter with a Maximum Power Point Tracking (MPPT) mechanism is developed in this paper for maximum efficiency. This paper proposed a novel combined technique of hybrid Particle Swarm Optimisation (PSO) and Salp Swarm Optimization (SSO) models to perform Maximum Power Point Tracking mechanisms and obtain a higher efficiency for battery charging. In order to retrieve the maximum power from the PV array, the Maximum Power Point Tracking mechanism is observed which reaches the maximum efficiency and the maximum power is fed through the buck-boost converter into the load. The buck-boost converter steps up the voltage to essential magnitude. The energy drawn from the PV array is used for the battery charging by means of an isolated buck converter since the buck-boost converter is not directly connected to the battery. The Fractional Order Proportional Integral Derivative (FOPID) controller handles the isolated buck converter and battery to enhance the efficiency obtained through the Maximum Power Point Tracking mechanism. The simulation results show higher steady efficiency by using the hybrid PSOSSO algorithm in all stages. The battery is charged without losing the efficiency obtained from the hybrid PSOSSO algorithm-based Maximum Power Point Tracking mechanism. The higher efficiency was obtained as 99.99% at Standard Test Conditions (STC) and 99.52% at PV partial shading conditions (PSCs) by using the new hybrid algorithm.
Décollement geometry controls on shallow very low frequency earthquakes
Authors: Hashimoto Yoshitaka , Sato Shigeyuki , Kimura Gaku , Kinoshita Masataka , Miyakawa Ayumu , Moore Gregory F. , Nakano Masaru , Shiraishi Kazuya , Yamada Yasuhiro 
Published: February 2022

AbstractRecent studies have documented the occurrence of shallow very low frequency earthquakes (VLFE) in subduction zones. The heterogeneity of the materials or stresses that act on the plate interface results in the variable slip rate. Stress on the décollement can be controlled by the décollement geometry and the regional stress, which is also able to control the material properties. We determined the distribution of stress along the shallow portion of the décollement in the Nankai Trough using a three-dimensional (3D) seismic survey and regional stress analysis to construct maps of normalized slip tendency (Ts′) and dilation tendency (Td). Alignments of VLFEs trend parallel to the trends of$${T}_{s}^{^{\prime}}$$Ts′and$${T}_{d}$$Td. On the other hand, very low$${T}_{s}^{^{\prime}}$$Ts′and$${T}_{d}$$Tdareas probably act as barriers that limit the number of VLFEs that can migrate towards the trench. Because the$${T}_{s}^{^{\prime}}$$Ts′and$${T}_{d}$$Tddistributions are derived only from the décollement geometry and the regional stress without incorporating any data on sediment properties, the consistency between the trends suggests that the décollement geometry is the primary control on VLFE activity.
Revealing the surface structural cause of scratch formation on soda-lime-silica glass
Authors: Roy Barsheek , Rosin Andreas , Gerdes Thorsten , Schafföner Stefan 
Published: February 2022

AbstractScratch formation on glass surfaces is a ubiquitous phenomenon induced by plastic deformation, often accompanied by radial, lateral or median cracks with consequent chipping and brittle fracture caused during and after the event of dynamic abrasion instigated by shear stress by a harder material. This paper addresses the fundamental aspect of scratch formation on soda-lime-silica (SLS) glass surfaces. A constructive combination of surface-sensitive characterization tools, including field emission scanning electron microscopy (FESEM), laser scanning microscopy (LSM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy and instrumented indentation technique (IIT), helped to investigate the structural cause of generation of visible scratches on SLS glass surfaces. The experimental results indicate that a silicate network possessing a mechanically weakening structural characteristic in terms of network connectivity confined to the region between 5 and 100 nm below the glass surface is likely to cause a destructive surface scratch eminently visible to the naked eye.
Sugariness prediction of Syzygium samarangense using convolutional learning of hyperspectral images
Authors: Chen Chih-Jung , Yan Yung-Jhe , Huang Chi-Cho , Chien Jen-Tzung , Chu Chang-Ting , Jang Je-Wei , Chen Tzung-Cheng , Lin Shiou-Gwo , Shih Ruei-Siang , Ou-Yang Mang 
Published: February 2022

AbstractSugariness is one of the most important indicators to measure the quality of Syzygium samarangense, which is also known as the wax apple. In general, farmers used to measure sugariness by testing the extracted juice of the wax apple products. Such a destructive way to measure sugariness is not only labor-consuming but also wasting products. Therefore, non-destructive and quick techniques for measuring sugariness would be significant for wax apple supply chains. Traditionally, the non-destructive method to predict the sugariness or the other indicators of the fruits was based on the reflectance spectra or Hyperspectral Images (HSIs) using linear regression such as Multi-Linear Regression (MLR), Principal Component Regression (PCR), and Partial Least Square Regression (PLSR), etc. However, these regression methods are usually too simple to precisely estimate the complicated mapping between the reflectance spectra or HSIs and the sugariness. This study presents the deep learning methods for sugariness prediction using the reflectance spectra or HSIs from the bottom of the wax apple. A non-destructive imaging system fabricated with two spectrum sensors and light sources is implemented to acquire the visible and infrared lights with a range of wavelengths. In particular, a specialized Convolutional Neural Network (CNN) with hyperspectral imaging is proposed by investigating the effect of different wavelength bands for sugariness prediction. Rather than extracting spatial features, the proposed CNN model was designed to extract spectral features of HSIs. In the experiments, the ground-truth value of sugariness is obtained from a commercial refractometer. The experimental results show that using the whole band range between 400 and 1700 nm achieves the best performance in terms of °Brix error. CNN models attain the °Brix error of ± 0.552, smaller than ± 0.597 using Feedforward Neural Network (FNN). Significantly, the CNN’s test results show that the minor error in the interval 0 to 10°Brix and 10 to 11°Brix are ± 0.551 and ± 0.408, these results indicate that the model would have the capability to predict if sugariness is below 10°Brix or not, which would be similar to the human tongue. These results are much better than ± 1.441 and ± 1.379 by using PCR and PLSR, respectively. Moreover, this study provides the test error in each °Brix interval within one Brix, and the results show that the test error is varied considerably within different °Brix intervals, especially on PCR and PLSR. On the other hand, FNN and CNN obtain robust results in terms of test error.
A laboratory evaluation of nozzle tip damage in four generations of intraocular lens injector systems using a self-developed damage scale
Authors: Fang Hui , Zhang Lu , Schickhardt Sonja , Merz Patrick R. , Yan Weijia , Leroux Mélanie , Auffarth Gerd U. 
Published: February 2022

AbstractDuring intraocular lens (IOL) implantation it is not uncommon for the injector’s nozzle-tip to get damaged. However, the damage has not been systematically described or evaluated using an objective scale. In this study we developed our own system—the Heidelberg Score for IOL Injector Damage (“HeiScore”), which was used to grade 60 injectors from four generations of injector models (Monarch III D, AcrySert C, UltraSert, AutonoMe) made by the same manufacturer. (Alcon Laboratories Inc.) HeiScore has six grades of nozzle-tip damage: no damage (which was graded 0); slight scratches (1), deep scratches (2), extensions (3), cracks (4) and bursts (graded number 5). The score for each injector model was the sum of all grades (total number), and we could compare the four injector models. The injectors showed varying damage profiles, from “no damage” to “crack”. A tendency of a lower damage score in the newer generations of IOL injectors was noted. However, a statistically significant difference was observed only between Monarch III D and AutonoMe. The “Heidelberg Score for IOL Injector Damage” could efficiently and effectively evaluate the damage to IOL injector systems, which might help manufacturers optimize the positioning of the IOL in the injector during pre-loading.
A pilot study of a novel method to visualize three-dimensional dose distribution on skin surface images to evaluate radiation dermatitis
Authors: Park Ye-In , Choi Seo Hee , Hong Chae-Seon , Cho Min-Seok , Son Junyoung , Jang Ji Won , Kim Jihun , Kim Hojin , Kim Dong Wook , Kim Jin Sung 
Published: February 2022

AbstractPredicting the radiation dose‒toxicity relationship is important for local tumor control and patients’ quality of life. We developed a first intuitive evaluation system that directly matches the three-dimensional (3D) dose distribution with the skin surface image of patients with radiation dermatitis (RD) to predict RD in patients undergoing radiotherapy. Using an RGB-D camera, 82 3D skin surface images (3DSSIs) were acquired from 19 patients who underwent radiotherapy. 3DSSI data acquired included 3D skin surface shape and optical imaging of the area where RD occurs. Surface registration between 3D skin dose (3DSD) and 3DSSI is performed using the iterative closest point algorithm, then reconstructed as a two-dimensional color image. The developed system successfully matched 3DSSI and 3DSD, and visualized the planned dose distribution onto the patient's RD image. The dose distribution pattern was consistent with the occurrence pattern of RD. This new approach facilitated the evaluation of the direct correlation between skin-dose distribution and RD and, therefore, provides a potential to predict the probability of RD and thereby decrease RD severity by enabling informed treatment decision making by physicians. However, the results need to be interpreted with caution due to the small sample size.
Photosynthetic performance of symbiont-bearing foraminifera Heterostegina depressa affected by sunscreens
Authors: Lintner Michael , Schagerl Michael , Lintner Bianca , Nagy Matthias , Heinz Petra 
Published: February 2022

AbstractForaminifera are abundant unicellular organisms that play an important role in marine element cycles. A large benthic foraminifer obligatory bearing photosymbionts is Heterostegina depressa. We studied potential impacts of sunscreens available on the market on the activity of photosymbionts on H. depressa by means of pulse-amplitude modulated (PAM) fluorescence microscopy. We included four different sunscreens, with two of them sold as “conventional” and two more stated as “eco-friendly”. Further, the impact of pure Ensulizole (phenylbenzimidazole sulfonic acid) was tested, which is a common agent of sunscreens. Foraminifera were incubated at varying concentrations (10, 50 and 200 mgL−1) of different sunscreens and the pure Ensulizole for 14 days. The photosynthetic performance was measured after 1,3, 7 and 14 days. Pure Ensulizole had a strong negative impact on the photobionts, which was reflected by a significant reduction of the areal fluorescence signal. “Eco-friendly” sunscreens affected the health of foraminifera more severely compared to “conventional” ones. We assume that metal nanoparticles like titanium dioxide or zinc oxide of “eco-friendly” sunscreens are causing this impact, because these substances were already classified as toxic for several microorganisms.
The association between prolonged sedentary time and coronary artery calcification in young healthy men in Korea: a cohort study
Authors: Nam Min-Woo , Lee Yesung , Lee Woncheol 
Published: February 2022

AbstractCoronary artery calcium score (CACS) is a useful method for predicting coronary artery disease in asymptomatic adults. In this study, we investigated the association between prolonged sedentary time and CACS. A cohort study was conducted in 14949 men with negative CACS (CACS = 0) at baseline who were followed up at least once. Sedentary time was categorized into < 7, 7–8, and ≥ 9 h/day. CACS was calculated by cardiac tomography. During 60,112.1 person-years of follow-up, 569 participants developed positive CACS. The multivariable adjusted hazard ratios (95% confidence intervals) for incident positive CACS comparing sedentary times of 7–8 h/day and ≥ 9 h/day to sedentary time of < 7 h/day were 1.25 (0.97–1.62) and 1.28 (1.03–1.59), respectively. This association was more strongly observed in the non-obese group (BMI < 25 kg/m2). In contrast, in the obese group (BMI ≥ 25 kg/m2), there was no significant association between sedentary time and incidence of positive CACS. Prolonged sedentary time was significantly associated with incidence of positive CACS in the study. CACS is also an effective screening tool for predicting future cardiovascular events in asymptomatic patients. Therefore, CACS can be an effective screening method for predicting coronary artery diseases in people with prolonged sedentary time, especially in metabolically healthy people.