bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative analytical model for temperature prediction of front-end accessory drive
Authors: Liu Xingchen , Behdinan Kamran 
Published: January 2021

AbstractThe front-end accessory drive belt drive system is a critical component in the vehicle engine. To avoid thermal deterioration under static state operating conditions, the thermal distribution for the belt drive system at each condition must be determined in an efficient manner. Due to the numerical approach is not feasible to address this concern because of its high computational cost, this paper proposes a reliable and efficient novel analytical thermal model to achieve this goal. This work develops the state-of-the-art heat transfer ordinary differential equations (ODEs) describing the thermal flow and heat dissipations on the complex structures of pulleys. Then it integrates these ODEs with heat transfer governing equations of the belt and heat exchanges to establish an innovative system of equations that can be solved within a few seconds to provide temperature plots. Moreover, experiments were conducted on a dynamometer to verify the accuracy of the proposed model under a wide range of conditions. The results indicate that the measured temperatures are in good agreement with the corresponding analytical results. Owing to its efficiency, the proposed model can be integrated with other mechanical characterizations of the belt drive system in terms of design, optimization, and thermal fatigue analyses.
Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
Authors: Pan Xinpeng , Zhang Dazhou , Zhang Pengfei 
Published: January 2021

AbstractDetection of fracture properties can be implemented using azimuth-dependent seismic inversion for optimal model parameters in time or frequency domain. Considering the respective potentials for sensitivities of inversion resolution and anti-noise performance in time and frequency domain, we propose a more robust azimuth-dependent seismic inversion method to achieve fracture detection by combining the Bayesian inference and joint time–frequency-domain inversion theory. Both Cauchy Sparse and low-frequency constraint regularizations are introduced to reduce multi-solvability of model space and improve inversion reliability of model parameters. Synthetic data examples demonstrate that the frequency bandwidth of inversion result is almost the same for time, frequency and joint time–frequency domain inversion in seismic dominant frequency band using the noise-free data, but the frequency bandwidth in joint time–frequency domain is larger than that in time and frequency domains using low- signal-to-noise-ratio (SNR) data. The results of cross-correlation coefficients validate that the joint time–frequency-domain inversion retains both the excellent characteristics of high resolution in frequency-domain inversion and the advantage of strong anti-noise ability in time-domain inversion. A field data example further demonstrates that our proposed inversion approach in joint time–frequency domain may provide a more stable technique for fracture detection in fractured reservoirs.
Development of a predictive model utilizing the neutrophil to lymphocyte ratio to predict neoadjuvant chemotherapy efficacy in early breast cancer patients
Authors: Zhu Jiujun , Jiao Dechuang , Zhao Yajie , Guo Xuhui , Yang Yue , Xiao Hui , Liu Zhenzhen 
Published: January 2021

AbstractNeutrophils and lymphocytes are key regulators of breast cancer (BC) development and progression. Neutrophil to lymphocyte ratio (NLR) values have been found to offer clear prognostic utility when evaluating BC patients. In this study, we sought to determine whether BC patient baseline NLR values are correlated with pathological complete response (pCR) following neoadjuvant chemotherapy (NCT) treatment. In total, 346 BC patients underwent NCT at our hospital from January 1, 2014 to October 31, 2019, and data pertaining to these patients were retrospectively analyzed. Correlations between clinicopathological characteristics and pCR rates were assessed via multivariate logistic regression analyses. A predictive scoring model was used to gauge the likelihood of pCR based upon regression coefficient (β) values for each significant variable identified through these analyses. NLR cut-off values suitable for identifying patients likely to achieve pCR following NCT treatment were calculated using receiver operating characteristic (ROC) curves. All patients in the present study were females with a median age of 48 years old (range 22–77). An optimal NLR cut-off value of 1.695 was identified and was associated with respective sensitivity and specificity values of 63.6% and 45.5%. We found that higher NLR values were significantly associated with younger age, premenopausal status, and non-pCR status. Logistic regression analyses indicated that NLR, tumor size, hormone receptor (HR) status, and Ki-67 expression were all independent predictors of pCR. The area under the curve (AUC) for the resultant predictive scoring model was 0.705, and this model was assessed via K-fold cross-validation (k = 10) and bootstrapping validation, yielding respective AUC values of 0.68 and 0.694. Moreover, the incorporation of NLR into this predictive model incrementally improved its overall prognostic value relative to that of a model not incorporating NLR (AUC = 0.674). BC patients with a lower baseline NLR are more likely to exhibit pCR following NCT treatment, indicating that NLR may be a valuable biomarker for BC patient prognostic evaluation and treatment planning. Overall, our results demonstrate that this NLR-based predictive model can efficiently predict NCT efficacy in early BC patients with a high degree of accuracy.
THz guided-mode resonance notch filter with variable filtering strength
Authors: Bark Hyeon Sang , Jang Kyu-Ha , Lee Kitae , Jeong Young Uk , Jeon Tae-In 
Published: January 2021

AbstractIn this paper, we propose a terahertz (THz) guided-mode resonance (GMR) notch filter made of a monolithic polyethylene terephthalate (PET) film, which has a monolayer grating structure. The proposed configuration shows both polarization-dependent and polarization-independent notch filter characteristics for the incident THz wave depending on the rotation angle of the second grating film. When the rotation angle is 0°, the filtering strength (transmittance) at resonance frequency changes from 0.4 (0.996) to 99.0% (0.010) according to the incident polarization. The transmittance continuously decreases with increasing rotation angle until 90°. When the rotation angle is 90°, the transmittance converges to 0.065 (± 0.015) independent of the incident wave polarization. When the incident polarization angle ranges from 90° to 180°, paradoxically, the transmittance through the two GMR grating films is greater than the transmittance through only the first GMR grating film due to the enhancement of the vertical component of the THz wave. These results agree well with a calculation using a polar coordinate system.
Deuterium-labeled Raman tracking of glucose accumulation and protein metabolic dynamics in Aspergillus nidulans hyphal tips
Authors: Yasuda Mitsuru , Takeshita Norio , Shigeto Shinsuke 
Published: January 2021

AbstractFilamentous fungi grow exclusively at their tips, where many growth-related fungal processes, such as enzyme secretion and invasion into host cells, take place. Hyphal tips are also a site of active metabolism. Understanding metabolic dynamics within the tip region is therefore important for biotechnology and medicine as well as for microbiology and ecology. However, methods that can track metabolic dynamics with sufficient spatial resolution and in a nondestructive manner are highly limited. Here we present time-lapse Raman imaging using a deuterium (D) tracer to study spatiotemporally varying metabolic activity within the hyphal tip of Aspergillus nidulans. By analyzing the carbon–deuterium (C–D) stretching Raman band with spectral deconvolution, we visualize glucose accumulation along the inner edge of the hyphal tip and synthesis of new proteins from the taken-up D-labeled glucose specifically at the central part of the apical region. Our results show that deuterium-labeled Raman imaging offers a broadly applicable platform for the study of metabolic dynamics in filamentous fungi and other relevant microorganisms in vivo.
Preference, performance, and chemical defense in an endangered butterfly using novel and ancestral host plants
Authors: Haan Nathan L. , Bowers M. Deane , Bakker Jonathan D. 
Published: January 2021

AbstractAdoption of novel host plants by herbivorous insects can require new adaptations and may entail loss of adaptation to ancestral hosts. We examined relationships between an endangered subspecies of the butterflyEuphydryas editha(Taylor’s checkerspot) and three host plant species. Two of the hosts (Castilleja hispida, Castilleja levisecta) were used ancestrally while the other,Plantago lanceolata, is exotic and was adopted more recently. We measured oviposition preference, neonate preference, larval growth, and secondary chemical uptake on all three hosts. Adult females readily laid eggs on all hosts but favoredPlantagoand tended to avoidC. levisecta.Oviposition preference changed over time. Neonates had no preference among host species, but consistently chose bracts over leaves within bothCastillejaspecies. Larvae developed successfully on all species and grew to similar size on all of them unless they ate onlyCastillejaleaves (rather than bracts) which limited their growth. Diet strongly influenced secondary chemical uptake by larvae. Larvae that atePlantagoorC. hispidaleaves contained the highest concentrations of iridoid glycosides, and iridoid glycoside composition varied with host species and tissue type. Despite having largely switched to a novel exotic host and generally performing better on it, this population has retained breadth in preference and ability to use other hosts.
Distribution of cortactin in cerebellar Purkinje cell spines
Authors: Szabó Lilla E. , Marcello G. Mark , Süth Miklós , Sótonyi Péter , Rácz Bence 
Published: January 2021

AbstractDendritic spines are the primary sites of excitatory transmission in the mammalian brain. Spines of cerebellar Purkinje Cells (PCs) are plastic, but they differ from forebrain spines in a number of important respects, and the mechanisms of spine plasticity differ between forebrain and cerebellum. Our previous studies indicate that in hippocampal spines cortactin—a protein that stabilizes actin branch points—resides in the spine core, avoiding the spine shell. To see whether the distribution of cortactin differs in PC spines, we examined its subcellular organization using quantitative preembedding immunoelectron microscopy. We found that cortactin was enriched in the spine shell, associated with the non-synaptic membrane, and was also situated within the postsynaptic density (PSD). This previously unrecognized distribution of cortactin within PC spines may underlie structural and functional differences in excitatory spine synapses between forebrain, and cerebellum.
Positive-charge tuned gelatin hydrogel-siSPARC injectable for siRNA anti-scarring therapy in post glaucoma filtration surgery
Authors: Chun Yong Yao , Yap Zhu Li , Seet Li Fong , Chan Hiok Hong , Toh Li Zhen , Chu Stephanie W. L. , Lee Ying Shi , Wong Tina T. , Tan Timothy T. Y. 
Published: January 2021

AbstractSmall interfering RNA (siRNA) therapy is a promising epigenetic silencing strategy. However, its widespread adoption has been severely impeded by its ineffective delivery into the cellular environment. Here, a biocompatible injectable gelatin-based hydrogel with positive-charge tuned surface charge is presented as an effective platform for siRNA protection and delivery. We demonstrate a two-step synthesis of a gelatin-tyramine (Gtn-Tyr) hydrogel with simultaneous charge tunability and crosslinking ability. We discuss how different physiochemical properties of the hydrogel interact with siSPARC (siRNA for secreted protein, acidic and rich in cysteine), and study the positive-charge tuned gelatin hydrogel as an effective delivery platform for siSPARC in anti-fibrotic treatment. Through in vitro studies using mouse tenon fibroblasts, the positive-charge tuned Gtn-Tyr hydrogel shows sustained siSPARC cellular internalization and effective SPARC silencing with excellent biocompatibility. Similarly, the same hydrogel platform delivering siSPARC in an in vivo assessment employing a rabbit model shows an effective reduction in subconjunctival scarring in post glaucoma filtration surgery, and is non-cytotoxic compared to a commonly used anti-scarring agent, mitomycin-C. Overall, the current siRNA delivery strategy involving the positive-charge tuned gelatin hydrogel shows effective delivery of gene silencing siSPARC for anti-fibrotic treatment. The current charge tunable hydrogel delivery system is simple to fabricate and highly scalable. We believe this delivery platform has strong translational potential for effective siRNA delivery and epigenetic silencing therapy.
Potential repurposing of four FDA approved compounds with antiplasmodial activity identified through proteome scale computational drug discovery and in vitro assay
Authors: Diallo Bakary N’tji , Swart Tarryn , Hoppe Heinrich C. , Tastan Bishop Özlem , Lobb Kevin 
Published: January 2021

AbstractMalaria elimination can benefit from time and cost-efficient approaches for antimalarials such as drug repurposing. In this work, 796 DrugBank compounds were screened against 36Plasmodium falciparumtargets using QuickVina-W. Hits were selected after rescoring using GRaph Interaction Matching (GRIM) and ligand efficiency metrics: surface efficiency index (SEI), binding efficiency index (BEI) and lipophilic efficiency (LipE). They were further evaluated in Molecular dynamics (MD). Twenty-five protein–ligand complexes were finally retained from the 28,656 (36 × 796) dockings. Hit GRIM scores (0.58 to 0.78) showed their molecular interaction similarity to co-crystallized ligands. Minimum LipE (3), SEI (23) and BEI (7) were in at least acceptable thresholds for hits. Binding energies ranged from −6 to −11 kcal/mol. Ligands showed stability in MD simulation with good hydrogen bonding and favorable protein–ligand interactions energy (the poorest being −140.12 kcal/mol). In vitro testing showed 4 active compounds with two having IC50values in the single-digit μM range.
Infant circulating MicroRNAs as biomarkers of effect in fetal alcohol spectrum disorders
Authors: Mahnke Amanda H. , Sideridis Georgios D. , Salem Nihal A. , Tseng Alexander M. , Carter R. Colin , Dodge Neil C. , Rathod Aniruddha B. , Molteno Christopher D. , Meintjes Ernesta M. , Jacobson Sandra W. , Miranda Rajesh C. , Jacobson Joseph L. 
Published: January 2021

AbstractPrenatal alcohol exposure (PAE) can result in cognitive and behavioral disabilities and growth deficits. Because alcohol-related neurobehavioral deficits may occur in the absence of overt dysmorphic features or growth deficits, there is a need to identify biomarkers of PAE that can predict neurobehavioral impairment. In this study, we assessed infant plasma extracellular, circulating miRNAs (exmiRNAs) obtained from a heavily exposed Cape Town cohort to determine whether these can be used to predict PAE-related growth restriction and cognitive impairment. PAE, controlling for smoking as a covariate, altered 27% of expressed exmiRNAs with clinically-relevant effect sizes (Cohen’s d ≥ 0.4). Moreover, at 2 weeks, PAE increased correlated expression of exmiRNAs across chromosomes, suggesting potential co-regulation. In confirmatory factor analysis, the variance in expression for PAE-altered exmiRNAs at 2 weeks and 6.5 months was best described by three-factor models. Pathway analysis found that factors at 2 weeks were associated with (F1) cell maturation, cell cycle inhibition, and somatic growth, (F2) cell survival, apoptosis, cardiac development, and metabolism, and (F3) cell proliferation, skeletal development, hematopoiesis, and inflammation, and at 6.5 months with (F1) neurodevelopment, neural crest/mesoderm-derivative development and growth, (F2) immune system and inflammation, and (F3) somatic growth and cardiovascular development. Factors F3 at 2 weeks and F2 at 6.5 months partially mediated PAE-induced growth deficits, and factor F3 at 2 weeks partially mediated effects of PAE on infant recognition memory at 6.5 months. These findings indicate that infant exmiRNAs can help identify infants who will exhibit PAE-related deficits in growth and cognition.
In vivo multimodal optical imaging of dermoscopic equivocal melanocytic skin lesions
Authors: Elagin V. , Gubarkova E. , Garanina O. , Davydova D. , Orlinskaya N. , Matveev L. , Klemenova I. , Shlivko I. , Shirmanova M. , Zagaynova E. 
Published: January 2021

AbstractThere is a wide range of equivocal melanocytic lesions that can be clinically and dermoscopically indistinguishable from early melanoma. In the present work, we assessed the possibilities of combined using of multiphoton microscopy (MPM) and optical coherence angiography (OCA) for differential diagnosis of the equivocal melanocytic lesions. Clinical and dermoscopic examinations of 60 melanocytic lesions revealed 10 benign lesions and 32 melanomas, while 18 lesions remained difficult to diagnose. Histopathological analysis of these lesions revealed 4 intradermal, 3 compound and 3 junctional nevi in the “benign” group, 7 superficial spreading, 14 lentigo maligna and 11 nodular melanomas in the “melanoma” group and 2 lentigo simplex, 4 dysplastic nevi, 6 melanomas in situ, 4 invasive lentigo melanomas and 2 invasive superficial spreading melanomas in the “equivocal” group. On the basis of MPM, a multiphoton microscopy score (MPMS) has been developed for quantitative assessment of melanoma features at the cellular level, that showed lower score for benign lesions compare with malignant ones. OCA revealed that the invasive melanoma has a higher vessel density and thicker blood vessels than melanoma in situ and benign lesions. Discriminant functions analysis of MPM and OCA data allowed to differentiate correctly between all equivocal melanocytic lesions. Therefore, we demonstrate, for the first time, that a combined use of MPM and OCA has the potential to improve early diagnosis of melanoma.
Gut microbiota modulation induced by Zika virus infection in immunocompetent mice
Authors: Corrêa Rafael , de Oliveira Santos Igor , Braz-de-Melo Heloísa Antoniella , de Sant’Ana Lívia Pimentel , das Neves Almeida Raquel , Pasquarelli-do-Nascimento Gabriel , Prado Paulo Sousa , Kobinger Gary P. , Maurice Corinne F. , Magalhães Kelly Grace 
Published: January 2021

AbstractGut microbiota composition can modulate neuroendocrine function, inflammation, and cellular and immunological responses against different pathogens, including viruses. Zika virus (ZIKV) can infect adult immunocompetent individuals and trigger brain damage and antiviral responses. However, it is not known whether ZIKV infection could impact the gut microbiome from adult immunocompetent mice. Here, we investigated modifications induced by ZIKV infection in the gut microbiome of immunocompetent C57BL/6J mice. Adult C57BL/6J mice were infected with ZIKV and the gut microbiota composition was analyzed by next-generation sequencing of the V4 hypervariable region present in the bacterial 16S rDNA gene. Our data showed that ZIKV infection triggered a significant decrease in the bacteria belonging to Actinobacteria and Firmicutes phyla, and increased Deferribacteres and Spirochaetes phyla components compared to uninfected mice. Interestingly, ZIKV infection triggered a significant increase in the abundance of bacteria from the Spirochaetaceae family in the gut microbiota. Lastly, we demonstrated that modulation of microbiota induced by ZIKV infection may lead to intestinal epithelium damage and intense leukocyte recruitment to the intestinal mucosa. Taken together, our data demonstrate that ZIKV infection can impact the gut microbiota composition and colon tissue homeostasis in adult immunocompetent mice.
Non-invasive synchronous monitoring of neutrophil migration using whole body near-infrared fluorescence-based imaging
Authors: Leslie Jack , Robinson Stuart M. , Oakley Fiona , Luli Saimir 
Published: January 2021

AbstractAdvances in fluorescence imaging coupled with the generation of near infrared probes have significantly improved the capabilities of non-invasive, real-time imaging in whole animals. In this study we were able to overcome a limitation of in vivo fluorescence imaging and have established a dual cell tracking method where two different cell types can be monitored according to the spectral signature of the cell labelling fluorophore. Using a mouse model of acute liver injury, we have characterised the in vivo migration patterns of wild type and transgenic neutrophils with impaired chemotaxis. Here, we were able to demonstrate that IVIS provides a sensitive multiplexing technology to differentiate two different cell populations based on the spectral signature of the cell labelling fluorophores. This spectral unmixing methodology has the potential to uncover multidimensional cellular interactions involved in many diseases such as fibrosis and cancer. In vivo spectral un-mixing provides a useful tool for monitoring multiple biological process in real-time in the same animal.
G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes
Authors: Le Borgne Florent , Chatton Arthur , Léger Maxime , Lenain Rémi , Foucher Yohann 
Published: January 2021

AbstractIn clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.