bluuebunny/crossref_metadata_2025_split huggingface dataset:
In situ process quality monitoring and defect detection for direct metal laser melting
Authors: Felix Sarah , Ray Majumder Saikat , Mathews H. Kirk , Lexa Michael , Lipsa Gabriel , Ping Xiaohu , Roychowdhury Subhrajit , Spears Thomas 
Published: May 2022

AbstractQuality control and quality assurance are challenges in direct metal laser melting (DMLM). Intermittent machine diagnostics and downstream part inspections catch problems after undue cost has been incurred processing defective parts. In this paper we demonstrate two methodologies for in-process fault detection and part quality prediction that leverage existing commercial DMLM systems with minimal hardware modification. Novel features were derived from the time series of common photodiode sensors along with standard machine control signals. In one methodology, a Bayesian approach attributes measurements to one of multiple process states as a means of classifying process deviations. In a second approach, a least squares regression model predicts severity of certain material defects.
Performance of PROPELLER FSE T2WI in reducing metal artifacts of material porcelain fused to metal crown: a clinical preliminary study
Authors: Li Wenjin , Shi Jing , Bian Wenjin , Li Jianting , Chen Xiaoqing , Feng Juan , Yu Jiali , Wang Jun , Niu Jinliang 
Published: May 2022

AbstractThis study aimed to compare MRI quality between conventional fast spin echo T2 weighted imaging (FSE T2WI) with periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) FSE T2WI for patients with various porcelain fused to metal (PFM) crown and analyze the value of PROPELLER technique in reducing metal artifacts. Conventional FSE T2WI and PROPELLER FSE T2WI sequences for axial imaging of head were applied in participants with different PFM crowns: cobalt-chromium (Co–Cr) alloy, pure titanium (Ti), gold–palladium (Au–Pd) alloy. Two radiologists evaluated overall image quality of section in PFM using a 5-point scale qualitatively and measured the maximum artifact area and artifact signal-to-noise ratio (SNR) quantitatively. Fifty-nine participants were evaluated. The metal crown with the least artifacts and the optimum image quality shown in conventional FSE T2WI and PROPELLER FSE T2WI were in Au–Pd alloy, Ti, and Co–Cr alloy order. PROPELLER FSE T2WI was superior to conventional FSE T2WI in improving image quality and reducing artifact area for Co-Cr alloy (17.0 ± 0.2% smaller artifact area, p < 0.001) and Ti (11.6 ± 0.7% smaller artifact area, p = 0.005), but had similar performance compared to FSE T2WI for Au–Pd alloy. The SNRs of the tongue and masseter muscle were significantly higher on PROPELLER FSE T2WI compared with conventional FSE T2WI (tongue: 29.76 ± 8.45 vs. 21.54 ± 9.31, p = 0.007; masseter muscle: 19.11 ± 8.24 vs. 15.26 ± 6.08, p = 0.016). Therefore, the different PFM crown generate varying degrees of metal artifacts in MRI, and the PROPELLER can effectively reduce metal artifacts especially in the PFM crown of Co-Cr alloy.
Genetic identification and diversity of stocks of the African bonytongue, Heterotis niloticus (Osteoglossiformes: Arapaiminae), in Nigeria, West Africa
Authors: Oladimeji Tofunmi E. , Caballero Isabel C. , Mateos Mariana , Awodiran Michael O. , Winemiller Kirk O. , Adite Alphonse , Hurtado Luis A. 
Published: May 2022

AbstractInland fisheries are an important source of protein and income for people in Africa. Their sustainable management can greatly benefit from identification of regional genetic stocks and characterization of their genetic diversity, but such information is lacking for most African freshwater fisheries. The African bonytongue,Heterotis niloticus, is an important component of inland fisheries in West Africa. Nigeria has the largest fishery for African bonytongues, representing ~ 86% of the global total. Recent declines in yields at some Nigerian locations, however, suggest current levels of exploitation may be unsustainable. Habitat degradation also may be impacting some stocks. Despite its commercial and nutritional importance, the African bonytongue has been the subject of scant genetic research to support management. We examined patterns of genetic diversity in natural populations ofH. niloticusat four locations in Nigeria, including Kainji Lake, a reservoir on the Niger River in north-central Nigeria, and three southern localities (Ethiope River, Igbokoda River, and Epe Lagoon), as well fish from the Ouémé River delta near Porto Novo, Benin. Eighty-five specimens were genotyped for nine microsatellite-loci. Genetic diversity estimates were highest at Kainji Lake, and substantially lower at southern localities. High levels of genetic differentiation were detected between samples from Kainji Lake and those from southern localities. Low, yet significantFSTvalues were observed among samples from southern Nigerian localities that were more differentiated from the sample from nearby coastal Benin. We thus recommend that African bonytongues from the five locations be considered distinct genetic stocks and managed accordingly.
Development of an artificial intelligence-assisted computed tomography diagnosis technology for rib fracture and evaluation of its clinical usefulness
Authors: Niiya Akifumi , Murakami Kouzou , Kobayashi Rei , Sekimoto Atsuhito , Saeki Miho , Toyofuku Kosuke , Kato Masako , Shinjo Hidenori , Ito Yoshinori , Takei Mizuki , Murata Chiori , Ohgiya Yoshimitsu 
Published: May 2022

AbstractArtificial intelligence algorithms utilizing deep learning are helpful tools for diagnostic imaging. A deep learning-based automatic detection algorithm was developed for rib fractures on computed tomography (CT) images of high-energy trauma patients. In this study, the clinical effectiveness of this algorithm was evaluated. A total of 56 cases were retrospectively examined, including 46 rib fractures and 10 control cases from our hospital, between January and June 2019. Two radiologists annotated the fracture lesions (complete or incomplete) for each CT image, which is considered the “ground truth.” Thereafter, the algorithm’s diagnostic results for all cases were compared with the ground truth, and the sensitivity and number of false positive (FP) results per case were assessed. The radiologists identified 199 images with a fracture. The sensitivity of the algorithm was 89.8%, and the number of FPs per case was 2.5. After additional learning, the sensitivity increased to 93.5%, and the number of FPs was 1.9 per case. FP results were found in the trabecular bone with the appearance of fracture, vascular grooves, and artifacts. The sensitivity of the algorithm used in this study was sufficient to aid the rapid detection of rib fractures within the evaluated validation set of CT images.
Green synthesis and characterization of silver nanoparticles using Eugenia roxburghii DC. extract and activity against biofilm-producing bacteria
Authors: Giri Alok Kumar , Jena Biswajit , Biswal Bhagyashree , Pradhan Arun Kumar , Arakha Manoranjan , Acharya Saumyaprava , Acharya Laxmikanta 
Published: May 2022

AbstractThe green synthesis of silver nanoparticles (AgNPs) and their applications have attracted many researchers as the AgNPs are used effectively in targeting specific tissues and pathogenic microorganisms. The purpose of this study is to synthesize and characterize silver nanoparticles from fully expanded leaves of Eugenia roxburghii DC., as well as to test their effectiveness in inhibiting biofilm production. In this study, at 0.1 mM concentration of silver nitrate (AgNO3), stable AgNPs were synthesized and authenticated by monitoring the color change of the solution from yellow to brown, which was confirmed with spectrophotometric detection of optical density. The crystalline nature of these AgNPs was detected through an X-Ray Diffraction (XRD) pattern. AgNPs were characterized through a high-resolution transmission electron microscope (HR-TEM) to study the morphology and size of the nanoparticles (NPs). A new biological approach was undertaken through the Congo Red Agar (CRA) plate assay by using the synthesized AgNPs against biofilm production. The AgNPs effectively inhibit biofilm formation and the biofilm-producing bacterial colonies. This could be a significant achievement in contending with many dynamic pathogens.
Impact of educational level and travel burden on breast cancer stage at diagnosis in the state of Sao Paulo, Brazil
Authors: de Almeida Raissa Janine , de Moraes Luizaga Carolina Terra , Eluf-Neto José , de Carvalho Nunes Hélio Rubens , Pessoa Eduardo Carvalho , Murta-Nascimento Cristiane 
Published: May 2022

AbstractWe describe the characteristics of cases of breast cancer among women assisted at hospitals affiliated to the public health system in the state of São Paulo (Brazil), analysing the effects of level of education and travel burden to point of treatment. We conducted a retrospective analysis of invasive breast cancer among women diagnosed between 2000 and 2015. Data were extracted from the hospital-based cancer registries of Fundação Oncocentro de São Paulo—FOSP. The outcome was clinical stage at diagnosis (stage III–IV versus I–II). The explanatory variables were educational level and travel burden. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated. Multiple imputations were used for missing educational level (31%). The study included 81,669 women with invasive breast cancer diagnosed between 2000 and 2015. The mean age of patients at diagnosis was 56.8 years (standard deviation 13.6 years). 38% of patients were at an advanced stage at diagnosis (stage III–IV). Women with lower levels of education and those who received cancer care in municipalities other than where they lived were more likely to be diagnosed at an advanced stage. In conclusion, promotion of breast cancer awareness and improving pathways to expedite breast cancer diagnosis and treatment could help identify breast tumors at earlier stages.
Leveraging clinical data across healthcare institutions for continual learning of predictive risk models
Authors: Amrollahi Fatemeh , Shashikumar Supreeth P. , Holder Andre L. , Nemati Shamim 
Published: May 2022

AbstractThe inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specific training) comes at the cost of performance degradation when applied to external patient cohorts. To exploit the full potential of cross-institutional clinical big data, machine learning systems must gain the ability to transfer their knowledge across institutional boundaries and learn from new episodes of patient care without forgetting previously learned patterns. In this work, we developed a privacy-preserving learning algorithm named WUPERR (Weight Uncertainty Propagation and Episodic Representation Replay) and validated the algorithm in the context of early prediction of sepsis using data from over 104,000 patients across four distinct healthcare systems. We tested the hypothesis, that the proposed continual learning algorithm can maintain higher predictive performance than competing methods on previous cohorts once it has been trained on a new patient cohort. In the sepsis prediction task, after incremental training of a deep learning model across four hospital systems (namely hospitals H-A, H-B, H-C, and H-D), WUPERR maintained the highest positive predictive value across the first three hospitals compared to a baseline transfer learning approach (H-A:39.27%vs.31.27%, H-B:25.34%vs.22.34%, H-C:30.33% vs.28.33%). The proposed approach has the potential to construct more generalizable models that can learn from cross-institutional clinical big data in a privacy-preserving manner.
Noise resilient leaky integrate-and-fire neurons based on multi-domain spintronic devices
Authors: Wang Cheng , Lee Chankyu , Roy Kaushik 
Published: May 2022

AbstractThe capability of emulating neural functionalities efficiently in hardware is crucial for building neuromorphic computing systems. While various types of neuro-mimetic devices have been investigated, it remains challenging to provide a compact device that can emulate spiking neurons. In this work, we propose a non-volatile spin-based device for efficiently emulating a leaky integrate-and-fire neuron. By incorporating an exchange-coupled composite free layer in spin-orbit torque magnetic tunnel junctions, multi-domain magnetization switching dynamics is exploited to realize gradual accumulation of membrane potential for a leaky integrate-and-fire neuron with compact footprints. The proposed device offers significantly improved scalability compared with previously proposed spin-based neuro-mimetic implementations while exhibiting high energy efficiency and good controllability. Moreover, the proposed neuron device exhibits a varying leak constant and a varying membrane resistance that are both dependent on the magnitude of the membrane potential. Interestingly, we demonstrate that such device-inspired dynamic behaviors can be incorporated to construct more robust spiking neural network models, and find improved resiliency against various types of noise injection scenarios. The proposed spintronic neuro-mimetic devices may potentially open up exciting opportunities for the development of efficient and robust neuro-inspired computational hardware.
PCBP1 is associated with rheumatoid arthritis by affecting RNA products of genes involved in immune response in Th1 cells
Authors: Cao Xue , Li Panlong , Song Xiaojuan , Shi Lipu , Qin Lijie , Chen Dong , Chu Tianshu , Cheng Yanwei 
Published: May 2022

AbstractRheumatoid arthritis (RA) is an autoimmune disease characterized by persistent synovitis, in which T helper 1 (Th1) can promote the development of a pro-inflammatory microenvironment. Poly(rC)-binding protein 1 (PCBP1) has been identified as a promising biomarker of RA, while its molecular mechanisms in RA development are unknown. As a canonical RNA binding protein, we propose that PCBP1 could play roles in RA by affecting both expression and alternative splicing levels in Th1 cells. Here, microarray datasets (GSE15573 and GSE23561), including 102 peripheral blood mononuclear cell samples from 39 RA patients and 63 controls, were used to evaluate the PCBP1 expression changes in RA patients. High throughput sequencing data (GSE84702) of iron driven pathogenesis in Th1 cells were downloaded and reanalyzed, including two Pcbp1 deficiency samples and two control samples in Th1 cells. In addition, CLIP-seq data of PCBP1 in Jurkat T cells was also analyzed to investigate the regulatory mechanisms of PCBP1. We found PCBP1 were down-regulated in RA specimens compared with control. The result of differentially expressed genes (DEGs) showed that Pcbp1 silencing in Th1 cells affected the expression of genes involved in immune response pathway. Alternative splicing analysis also revealed that PCBP1-regulated alternative splicing genes (RASGs) were enriched in TNF-a/NF-κB signaling pathway, T cell activation, T cell differentiation and T cell differentiation associated immune response pathways, which were highly associated with RA. DEGs and RASGs by Pcbp1 deficiency in mice were validated in PBMCs specimens of RA patients by RT-qPCR. Investigation of the CLIP-seq data revealed PCBP1 preferred to bind to 3′UTR and intron regions. PCBP1-bound genes were also significantly associated with RASGs, identifying 102 overlapped genes of these two gene sets. These genes were significantly enriched in several immune response related pathways, including myeloid cell differentiation and positive regulation of NF-κB transcription factor activity. Two RA-related genes, PML and IRAK1, were screened from the above immune related pathways. These results together support our hypothesis that PCBP1 can regulate the expression of genes involved in immune response pathway, and can bind to and regulate the alternative splicing of immune response related genes in immune T cells, and ultimately participate in the molecular mechanism of RA, providing new research ideas and directions for clinical diagnosis and treatment.
Insect vector manipulation by a plant virus and simulation modeling of its potential impact on crop infection
Authors: Lee Hyoseok , Stephanus Andrew P. , Fowles Trevor M. , Wintermantel William M. , Trumble John T. , Gilbertson Robert L. , Nansen Christian 
Published: May 2022

AbstractThere is widespread evidence of plant viruses manipulating behavior of their insect vectors as a strategy to maximize infection of plants. Often, plant viruses and their insect vectors have multiple potential host plant species, and these may not overlap entirely. Moreover, insect vectors may not prefer plant species to which plant viruses are well-adapted. In such cases, can plant viruses manipulate their insect vectors to preferentially feed and oviposit on plant species, which are suitable for viral propagation but less suitable for themselves? To address this question, we conducted dual- and no-choice feeding studies (number and duration of probing events) and oviposition studies with non-viruliferous and viruliferous [carrying beet curly top virus (BCTV)] beet leafhoppers [Circulifer tenellus(Baker)] on three plant species: barley (Hordeum vulgareL.), ribwort plantain (Plantago lanceolataL.), and tomato (Solanum lycopersicumL.). Barley is not a host of BCTV, whereas ribwort plantain and tomato are susceptible to BCTV infection and develop a symptomless infection and severe curly top symptoms, respectively. Ribwort plantain plants can be used to maintain beet leafhopper colonies for multiple generations (suitable), whereas tomato plants cannot be used to maintain beet leafhopper colonies (unsuitable). Based on dual- and no-choice experiments, we demonstrated that BCTV appears to manipulate probing preference and behavior by beet leafhoppers, whereas there was no significant difference in oviposition preference. Simulation modeling predicted that BCTV infection rates would to be higher in tomato fields with barley compared with ribwort plantain as a trap crop. Simulation model results supported the hypothesis that manipulation of probing preference and behavior may increase BCTV infection in tomato fields. Results presented were based on the BCTV-beet leafhopper pathosystem, but the approach taken (combination of experimental studies with complementary simulation modeling) is widely applicable and relevant to other insect-vectored plant pathogen systems involving multiple plant species.
Genomic biosurveillance detects a sexual hybrid in the sudden oak death pathogen
Authors: Hamelin Richard C. , Bilodeau Guillaume J. , Heinzelmann Renate , Hrywkiw Kelly , Capron Arnaud , Dort Erika , Dale Angela L. , Giroux Emilie , Kus Stacey , Carleson Nick C. , Grünwald Niklaus J. , Feau Nicolas 
Published: May 2022

AbstractInvasive exotic pathogens pose a threat to trees and forest ecosystems worldwide, hampering the provision of essential ecosystem services such as carbon sequestration and water purification. Hybridization is a major evolutionary force that can drive the emergence of pathogens.Phytophthora ramorum, an emergent pathogen that causes the sudden oak and larch death, spreads as reproductively isolated divergent clonal lineages. We use a genomic biosurveillance approach by sequencing genomes ofP. ramorumfrom survey and inspection samples and report the discovery of variants ofP. ramorumthat are the result of hybridization via sexual recombination between North American and European lineages. We show that these hybrids are viable, can infect a host and produce spores for long-term survival and propagation. Genome sequencing revealed genotypic combinations at 54,515 single nucleotide polymorphism loci not present in parental lineages. More than 6,000 of those genotypes are predicted to have a functional impact in genes associated with host infection, including effectors, carbohydrate-active enzymes and proteases. We also observed post-meiotic mitotic recombination that could generate additional genotypic and phenotypic variation and contribute to homoploid hybrid speciation. Our study highlights the importance of plant pathogen biosurveillance to detect variants, including hybrids, and inform management and control.
Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein–ligand binding affinities
Authors: Yasuda Ikki , Endo Katsuhiro , Yamamoto Eiji , Hirano Yoshinori , Yasuoka Kenji 
Published: May 2022

AbstractPrediction of protein–ligand binding affinity is a major goal in drug discovery. Generally, free energy gap is calculated between two states (e.g., ligand binding and unbinding). The energy gap implicitly includes the effects of changes in protein dynamics induced by ligand binding. However, the relationship between protein dynamics and binding affinity remains unclear. Here, we propose a method that represents ligand-binding-induced protein behavioral change with a simple feature that can be used to predict protein–ligand affinity. From unbiased molecular simulation data, an unsupervised deep learning method measures the differences in protein dynamics at a ligand-binding site depending on the bound ligands. A dimension reduction method extracts a dynamic feature that strongly correlates to the binding affinities. Moreover, the residues that play important roles in protein–ligand interactions are specified based on their contribution to the differences. These results indicate the potential for binding dynamics-based drug discovery.
Histone macroH2A1 is a stronger regulator of hippocampal transcription and memory than macroH2A2 in mice
Authors: Singh Gurdeep , Stefanelli Gilda , Narkaj Klotilda , Brimble Mark A. , Creighton Samantha D. , McLean Timothy A. B. , Hall Meaghan , Mitchnick Krista A. , Zakaria Jacqueline , Phung Thanh , Reda Anas , Leonetti Amanda M. , Monks Ashley , Ianov Lara , Winters Boyer D. , Walters Brandon J. , Davidoff Andrew M. , Mitchell Jennifer A. , Zovkic Iva B. 
Published: May 2022

AbstractHistone variants H2A.Z and H3.3 are epigenetic regulators of memory, but roles of other variants are not well characterized. macroH2A (mH2A) is a structurally unique histone that contains a globular macrodomain connected to the histone region by an unstructured linker. Here we assessed if mH2A regulates memory and if this role varies for the two mH2A-encoding genes,H2afy(mH2A1) andH2afy2(mH2A2). We show that fear memory is impaired in mH2A1, but not in mH2A2-deficient mice, whereas both groups were impaired in a non-aversive spatial memory task. However, impairment was larger for mH2A1- deficient mice, indicating a preferential role for mH2A1 over mH2A2 in memory. Accordingly, mH2A1 depletion in the mouse hippocampus resulted in more extensive transcriptional de-repression compared to mH2A2 depletion. mH2A1-depleted mice failed to induce a normal transcriptional response to fear conditioning, suggesting that mH2A1 depletion impairs memory by altering transcription. Using chromatin immunoprecipitation (ChIP) sequencing, we found that both mH2A proteins are enriched on transcriptionally repressed genes, but only mH2A1 occupancy was dynamically modified during learning, displaying reduced occupancy on upregulated genes after training. These data identify mH2A as a regulator of memory and suggest that mH2A1 supports memory by repressing spurious transcription and promoting learning-induced transcriptional activation.