bluuebunny/crossref_metadata_2025_split huggingface dataset:
Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality
Authors: Nadimi Esmaeil S. , Majtner Tomas , Yderstraede Knud B. , Blanes-Vidal Victoria 
Published: October 2020

AbstractRubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In clinical practice, facial erythema of patients with diabetes is evaluated based on subjective observations of visible redness, which often goes unnoticed leading to microangiopathic complications. To address this major shortcoming, we designed a contactless, non-invasive diagnostic point-of-care-device (POCD) consisting of a digital camera and a screen. Our solution relies on (1) recording videos of subject’s face (2) applying Eulerian video magnification to videos to reveal important subtle color changes in subject’s skin that fall outside human visual limits (3) obtaining spatio-temporal tensor expression profile of these variations (4) studying empirical spectral density (ESD) function of the largest eigenvalues of the tensors using random matrix theory (5) quantifying ESD functions by modeling the tails and decay rates using power law in systems exhibiting self-organized-criticality and (6) designing an optimal ensemble of learners to classify subjects into those with diabetic neuropathy and those of a control group. By analyzing a short video, we obtained a sensitivity of 100% in detecting subjects diagnosed with diabetic neuropathy. Our POCD paves the way towards the development of an inexpensive home-based solution for early detection of diabetic neuropathy and its associated complications.
Prediction of fall events during admission using eXtreme gradient boosting: a comparative validation study
Authors: Hsu Yin-Chen , Weng Hsu-Huei , Kuo Chiu-Ya , Chu Tsui-Ping , Tsai Yuan-Hsiung 
Published: October 2020

AbstractAs the performance of current fall risk assessment tools is limited, clinicians face significant challenges in identifying patients at risk of falling. This study proposes an automatic fall risk prediction model based on eXtreme gradient boosting (XGB), using a data-driven approach to the standardized medical records. This study analyzed a cohort of 639 participants (297 fall patients and 342 controls) from Chang Gung Memorial Hospital, Chiayi Branch, Taiwan. A derivation cohort of 507 participants (257 fall patients and 250 controls) was collected for constructing the prediction model using the XGB algorithm. A comparative validation of XGB and the Morse Fall Scale (MFS) was conducted with a prospective cohort of 132 participants (40 fall patients and 92 controls). The areas under the curves (AUCs) of the receiver operating characteristic (ROC) curves were used to compare the prediction models. This machine learning method provided a higher sensitivity than the standard method for fall risk stratification. In addition, the most important predictors found (Department of Neuro-Rehabilitation, Department of Surgery, cardiovascular medication use, admission from the Emergency Department, and bed rest) provided new information on in-hospital fall event prediction and the identification of patients with a high fall risk.
Thermostability of a recombinant G protein-coupled receptor expressed at high level in mammalian cell culture
Authors: Yeliseev Alexei , van den Berg Arjen , Zoubak Lioudmila , Hines Kirk , Stepnowski Sam , Williston Kyle , Yan Wanhua , Gawrisch Klaus , Zmuda Jonathan 
Published: October 2020

AbstractRational design of pharmaceutical drugs targeting integral membrane G protein-coupled receptors (GPCR) requires thorough understanding of ligand binding and mechanism of activation through high resolution structural studies of purified proteins. Due to inherent conformational flexibility of GPCR, stabilization of these proteins solubilized from cell membranes into detergents is a challenging task. Here, we take advantage of naturally occurring post-translational modifications for stabilization of purified GPCR in detergent micelles. The recombinant cannabinoid CB2 receptor was expressed at high yield in Expi293F mammalian cell cultures, solubilized and purified in Façade detergent. We report superior stability of the mammalian cell-expressed receptor compared to its E.coli-expressed counterpart, due to contributions from glycosylation of the N terminus and palmitoylation of the C terminus of CB2. Finally, we demonstrate that the mammalian Expi293F amino acid labelling kit is suitable for preparation of multi-milligram quantities of high quality, selectively stable isotope-labeled GPCR for studies by nuclear magnetic resonance.
Real-time on-machine observations close to interelectrode gap in a tool-based hybrid laser-electrochemical micromachining process
Authors: Saxena Krishna Kumar , Chen Xiaolei , Vetrano Maria Rosaria , Qian Jun , Reynaerts Dominiek 
Published: October 2020

AbstractA tool-based hybrid laser-electrochemical micromachining process involves concurrent application of two process energies i.e. electrochemical and laser in the same machining zone by means of a hybrid tool which serves as an ECM tool as well as a multimode waveguide. It is a relatively novel process finding applications in defect-free machining of difficult-to-cut materials without affecting their microstructure. In order to understand the physical phenomena occurring during this process, in-situ observations are required. Therefore, in this work, a real time observation was carried out of a novel tool-based hybrid laser electrochemical micromachining process. A combination of high-speed imaging and Large Scale Particle Image Velocimetry (LSPIV) was used to visualize the tool-based hybrid laser-ECM process in real time. It also allowed to carry out experimental investigations on the by-products and bubble generation which have a direct effect on process performance in terms of accuracy and efficiency. The real-time on-machine observations are unique of its kind and they will facilitate the understanding of underlying mechanisms governing this hybrid laser-electrochemical micromachining process. This will ultimately help in improving the quality of parts manufactured. This research is also a step forward towards making these physics-based hybrid processes deterministic by employing high-speed imaging in a closed loop control.
Swirlonic state of active matter
Authors: Brilliantov Nikolai V. , Abutuqayqah Hajar , Tyukin Ivan Yu , Matveev Sergey A. 
Published: October 2020

AbstractWe report a novel state of active matter—a swirlonic state. It is comprised of swirlons, formed by groups of active particles orbiting their common center of mass. These quasi-particles demonstrate a surprising behavior: In response to an external load they move with a constant velocity proportional to the applied force, just as objects in viscous media. The swirlons attract each other and coalesce forming a larger, joint swirlon. The coalescence is extremely slow, decelerating process, resulting in a rarified state of immobile quasi-particles. In addition to the swirlonic state, we observe gaseous, liquid and solid states, depending on the inter-particle and self-driving forces. Interestingly, in contrast to molecular systems, liquid and gaseous states of active matter do not coexist. We explain this unusual phenomenon by the lack of fast particles in active matter. We perform extensive numerical simulations and theoretical analysis. The predictions of the theory agree qualitatively and quantitatively with the simulation results.
Effects of seasonality and previous logging on faecal helminth-microbiota associations in wild lemurs
Authors: de Winter I. I. , Umanets A. , Gort G. , Nieuwland W. H. , van Hooft P. , Heitkönig I. M. A. , Kappeler P. M. , Prins H. H. T. , Smidt H. 
Published: October 2020

AbstractGastrointestinal helminth-microbiota associations are shaped by various ecological processes. The effect of the ecological context of the host on the bacterial microbiome and gastrointestinal helminth parasites has been tested in a number of ecosystems and experimentally. This study takes the important step to look at these two groups at the same time and to start to examine how these communities interact in a changing host environment. Fresh faecal samples (N = 335) from eight wildEulemurpopulations were collected over 2 years across Madagascar. We used 16S ribosomal RNA gene sequencing to characterise the bacterial microbiota composition, and faecal flotation to isolate and morphologically identify nematode eggs. Infections with nematodes of the generaCallistouraandLemuricolaoccurred in all lemur populations. Seasonality significantly contributed to the observed variation in microbiota composition, especially in the dry deciduous forest. Microbial richness andLemuricolaspp. infection prevalence were highest in a previously intensely logged site, whereasCallistouraspp. showed no such pattern. In addition, we observed significant correlations between gastrointestinal parasites and bacterial microbiota composition in these lemurs, with 0.4–0.7% of the variation in faecal bacterial microbiota composition being explained by helminth infections. With this study, we show effects of environmental conditions on gastrointestinal nematodes and bacterial interactions in wild lemurs and believe it is essential to consider the potential role of microbiome-parasite associations on the hosts’ GI stability, health, and survival.
ZIF-8 as a promising drug delivery system for benznidazole: development, characterization, in vitro dialysis release and cytotoxicity
Authors: de Moura Ferraz Leslie Raphael , Tabosa Alinne Élida Gonçalves Alves , da Silva Nascimento Débora Dolores Souza , Ferreira Aline Silva , de Albuquerque Wanderley Sales Victor , Silva José Yago Rodrigues , Júnior Severino Alves , Rolim Larissa Araújo , de Souza Pereira Jorge José , Rolim-Neto Pedro José 
Published: October 2020

AbstractChagas disease (CD), caused by the flagellate protozoan Trypanosoma cruzi, is one of the major public health problems in developing countries. Benznidazole (BNZ) is the only drug available for CD treatment in most countries, however, it presents high toxicity and low bioavailability. To address these problems this study used Zeolitic Imidazolate Framework-8 (ZIF-8), which has garnered considerable attention due to its potential applications, enabling the controlled delivery of drugs. The present work developed and characterized a BNZ@ZIF-8 system, and the modulation of BNZ release from the ZIF-8 framework was evaluated through the in vitro dialysis release method under sink conditions at different pH values. Moreover, the in vitro evaluation of cell viability and cytotoxicity by MTT assay were also performed. The dissolution studies corroborated that a pH sensitive Drug Delivery System capable of vectorizing the release of BNZ was developed, may leading to the improvement in the bioavailability of BNZ. The MTT assay showed that no statistically significant toxic effects occurred in the developed system, nor significant effects on cell viability.
The rapid CD4 + T-lymphocyte decline and human immunodeficiency virus progression in females compared to males
Authors: Parsa Nader , Zaheri Pari Mahlagha , Hewitt Ross G. , Karimi Akhormeh Ali , Taravatmanesh Samira , Wallin Lisa 
Published: October 2020

AbstractCD4 + T-lymphocyte counts are used to assess CD4 + decline and the stage of human immunodeficiency virus (HIV) progression in HIV-infected patients. Clinical observation suggests that HIV progress more rapid in females than males. Of the original 5000 HIV-infected population of Western New York HIV/AIDS, Referral Center at Erie County Medical Center (ECMC), 1422 participated in the cohort study. We identified 333 HIV-infected patients with CD4 + T-cell-counts ≥ 500/µƖ, among them 178 met the inclusion criteria for the 10-year study. Females had higher mode (600 vs. 540) and mean (741.9 vs. 712.2) CD4 + counts than males at baseline. However, CD4 + declined faster among females in a shorter time than males (234.5 vs. 158.6, P < 0.004), with rapid HIV progression. Univariate analyses determined that females had a 40% higher risk for CD4 + decline than males. The bivariate analyses specified CD4 + decline remained greater in females than males. Multivariate analyses which employed Cox’s proportional Hazard-Model to adjust for numerous variables simultaneously identified women had almost twice the risk for CD4 + decline and rapid HIV progression than males (RR = 1.93; 95%CI 1.24, 2.99). Although the biological mechanism remains unknown, findings suggest gender differences in CD4 + decline, with a higher risk of rapid HIV progression and shorter longevity in females.
Disease progression modeling of Alzheimer’s disease according to education level
Authors: Kim Ko Woon , Woo Sook Young , Kim Seonwoo , Jang Hyemin , Kim Yeshin , Cho Soo Hyun , Kim Si Eun , Kim Seung Joo , Shin Byoung-Soo , Kim Hee Jin , Na Duk L. , Seo Sang Won 
Published: October 2020

AbstractTo develop a disease progression model of Alzheimer’s disease (AD) that shows cognitive decline from subjective cognitive impairments (SCI) to the end stage of AD dementia (ADD) and to investigate the effect of education level on the whole disease spectrum, we enrolled 565 patients who were followed up more than three times and had a clinical dementia rating sum of boxes (CDR-SB). Three cohorts, SCI (n = 85), amnestic mild cognitive impairment (AMCI, n = 240), and ADD (n = 240), were overlapped in two consecutive cohorts (SCI and AMCI, AMCI and ADD) to construct a model of disease course, and a model with multiple single-cohorts was estimated using a mixed-effect model. To examine the effect of education level on disease progression, the disease progression model was developed with data from lower (≤ 12) and higher (> 12) education groups. Disease progression takes 274.3 months (22.9 years) to advance from 0 to 18 points using the CDR-SB. Based on our predictive equation, it takes 116.5 months to progress from SCI to AMCI and 56.2 months to progress from AMCI to ADD. The rate of CDR-SB progression was different according to education level. The lower-education group showed faster CDR-SB progression from SCI to AMCI compared to the higher-education group, and this trend disappeared from AMCI to ADD. In the present study, we developed a disease progression model of AD spectrum from SCI to the end stage of ADD. Our disease modeling provides us with more understanding of the effect of education on cognitive trajectories.
The wasted chewing gum bacteriome
Authors: Satari Leila , Guillén Alba , Vidal-Verdú Àngela , Porcar Manuel 
Published: October 2020

AbstractHere we show the bacteriome of wasted chewing gums from five different countries and the microbial successions on wasted gums during three months of outdoors exposure. In addition, a collection of bacterial strains from wasted gums was set, and the biodegradation capability of different gum ingredients by the isolates was tested. Our results reveal that the oral microbiota present in gums after being chewed, characterised by the presence of species such as Streptococcus spp. or Corynebacterium spp., evolves in a few weeks to an environmental bacteriome characterised by the presence of Acinetobacter spp., Sphingomonas spp. and Pseudomonas spp. Wasted chewing gums collected worldwide contain a typical sub-aerial biofilm bacteriome, characterised by species such as Sphingomonas spp., Kocuria spp., Deinococcus spp. and Blastococcus spp. Our findings have implications for a wide range of disciplines, including forensics, contagious disease control, or bioremediation of wasted chewing gum residues.
Targeted delivery of 5-fluorouracil-1-acetic acid (5-FA) to cancer cells overexpressing epithelial growth factor receptor (EGFR) using virus-like nanoparticles
Authors: Gan Bee Koon , Rullah Kamal , Yong Chean Yeah , Ho Kok Lian , Omar Abdul Rahman , Alitheen Noorjahan Banu , Tan Wen Siang 
Published: October 2020

AbstractChemotherapy is widely used in cancer treatments. However, non-specific distribution of chemotherapeutic agents to healthy tissues and normal cells in the human body always leads to adverse side effects and disappointing therapeutic outcomes. Therefore, the main aim of this study was to develop a targeted drug delivery system based on the hepatitis B virus-like nanoparticle (VLNP) for specific delivery of 5-fluorouracil-1-acetic acid (5-FA) to cancer cells expressing epithelial growth factor receptor (EGFR). 5-FA was synthesized from 5-fluorouracil (5-FU), and it was found to be less toxic than the latter in cancer cells expressing different levels of EGFR. The cytotoxicity of 5-FA increased significantly after being conjugated on the VLNP. A cell penetrating peptide (CPP) of EGFR was displayed on the VLNP via the nanoglue concept, for targeted delivery of 5-FA to A431, HT29 and HeLa cells. The results showed that the VLNP displaying the CPP and harboring 5-FA internalized the cancer cells and killed them in an EGFR-dependent manner. This study demonstrated that the VLNP can be used to deliver chemically modified 5-FU derivatives to cancer cells overexpressing EGFR, expanding the applications of the VLNP in targeted delivery of chemotherapeutic agents to cancer cells overexpressing this transmembrane receptor.
Genome-wide genetic diversity yields insights into genomic responses of candidate climate-selected loci in an Andean wetland plant
Authors: Bertin Angéline , Espinosa Mara I. , Bustamante Catalina A. , Troncoso Alejandra J. , Gouin Nicolas 
Published: October 2020

AbstractAssessing population evolutionary potential has become a central tenet of conservation biology. Since adaptive responses require allelic variation at functional genes, consensus has grown that genetic variation at genes under selection is a better surrogate for adaptive evolutionary potential than neutral genetic diversity. Although consistent with prevailing theory, this argument lacks empirical support and ignores recent theoretical advances questioning the very concept of neutral genetic diversity. In this study, we quantified genome-wide responses of single nucleotide polymorphism loci linked to climatic factors over a strong latitudinal gradient in natural populations of the high Andean wetland plant, Carex gayana, and then assessed whether genetic variation of candidate climate-selected loci better predicted their genome-wide responses than genetic variation of non-candidate loci. Contrary to this expectation, genomic responses of climate-linked loci only related significantly to environmental variables and genetic diversity of non-candidate loci. The effects of genome-wide genetic diversity detected in this study may be a result of either the combined influence of small effect variants or neutral and demographic factors altering the adaptive evolutionary potential of C. gayana populations. Regardless of the processes involved, our results redeem genome-wide genetic diversity as a potentially useful indicator of population adaptive evolutionary potential.
The SensorOverlord predicts the accuracy of measurements with ratiometric biosensors
Authors: Stanley Julian A. , Johnsen Sean B. , Apfeld Javier 
Published: October 2020

AbstractTwo-state ratiometric biosensors change conformation and spectral properties in response to specific biochemical inputs. Much effort over the past two decades has been devoted to engineering biosensors specific for ions, nucleotides, amino acids, and biochemical potentials. The utility of these biosensors is diminished by empirical errors in fluorescence-ratio signal measurement, which reduce the range of input values biosensors can measure accurately. Here, we present a formal framework and a web-based tool, the SensorOverlord, that predicts the input range of two-state ratiometric biosensors given the experimental error in measuring their signal. We demonstrate the utility of this tool by predicting the range of values that can be measured accurately by biosensors that detect pH, NAD+, NADH, NADPH, histidine, and glutathione redox potential. The SensorOverlord enables users to compare the predicted accuracy of biochemical measurements made with different biosensors, and subsequently select biosensors that are best suited for their experimental needs.
Preemptive interleukin-6 blockade in patients with COVID-19
Authors: Guillén Lucía , Padilla Sergio , Fernández Marta , Agulló Vanesa , García José Alberto , Telenti Guillermo , García-Abellán Javier , Botella Ángela , Gutiérrez Félix , Masiá Mar 
Published: October 2020

AbstractExcessive interleukin-6 signaling is a key factor contributing to the cytokine release syndrome implicated in clinical manifestations of COVID-19. Preliminary results suggest that tocilizumab, a humanized monoclonal anti-interleukin-6 receptor antibody, may be beneficial in severely ill patients, but no data are available on earlier stages of disease. An anticipated blockade of interleukin-6 might hypothetically prevent the catastrophic consequences of the overt cytokine storm. We evaluated early-given tocilizumab in patients hospitalized with COVID-19, and identified outcome predictors. Consecutive patients with initial Sequential-Organ-Failure-Assessment (SOFA) score < 3 fulfilling pre-defined criteria were treated with tocilizumab. Serial plasma biomarkers and nasopharyngeal swabs were collected. Of 193 patients admitted with COVID-19, 64 met the inclusion criteria. After tocilizumab, 49 (76.6%) had an early favorable response. Adjusted predictors of response were gender, SOFA score, neutrophil/lymphocyte ratio, Charlson comorbidity index and systolic blood pressure. At week-4, 56.1% of responders and 30% of non-responders had cleared the SARS-CoV-2 from nasopharynx. Temporal profiles of interleukin-6, C-reactive protein, neutrophil/lymphocyte ratio, NT-ProBNP, D-dimer, and cardiac-troponin-I differed according to tocilizumab response and discriminated final in-hospital outcome. No deaths or disease recurrences were observed. Preemptive therapy with tocilizumab was safe and associated with favorable outcomes in most patients. Biological and clinical markers predicted outcomes.
Tracking cortical representations of facial attractiveness using time-resolved representational similarity analysis
Authors: Kaiser Daniel , Nyga Karen 
Published: October 2020

AbstractWhen we see a face, we rapidly form an impression of its attractiveness. Here, we investigated how rapidly representations of facial attractiveness emerge in the human brain. In an EEG experiment, participants viewed 100 face photographs and rated them for their attractiveness. Using time-resolved representational similarity analysis on the EEG data, we reveal representations of facial attractiveness after 150–200 ms of cortical processing. Interestingly, we show that these representations are related to individual participants’ personal attractiveness judgments, suggesting that already early perceptual representations of facial attractiveness convey idiosyncratic attractiveness preferences. Further, we show that these early representations are genuinely related to attractiveness, as they are neither explained by other high-level face attributes, such as face sex or age, nor by features extracted by an artificial deep neural network model of face processing. Together, our results demonstrate early, individually specific, and genuine representations of facial attractiveness, which may underlie fast attractiveness judgments.