bluuebunny/crossref_metadata_2025_split huggingface dataset:
A scalable, secure, and interoperable platform for deep data-driven health management
Authors: Bahmani Amir , Alavi Arash , Buergel Thore , Upadhyayula Sushil , Wang Qiwen , Ananthakrishnan Srinath Krishna , Alavi Amir , Celis Diego , Gillespie Dan , Young Gregory , Xing Ziye , Nguyen Minh Hoang Huynh , Haque Audrey , Mathur Ankit , Payne Josh , Mazaheri Ghazal , Li Jason Kenichi , Kotipalli Pramod , Liao Lisa , Bhasin Rajat , Cha Kexin , Rolnik Benjamin , Celli Alessandra , Dagan-Rosenfeld Orit , Higgs Emily , Zhou Wenyu , Berry Camille Lauren , Van Winkle Katherine Grace , Contrepois Kévin , Ray Utsab , Bettinger Keith , Datta Somalee , Li Xiao , Snyder Michael P. 
Published: October 2021

AbstractThe large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we illustrate the use of the PHD framework for large-scale applications in emerging multi-omics disease studies, such as collecting and visualization of diverse data types (wearable, clinical, omics) at a personal level, investigation of insulin resistance, and an infrastructure for the detection of presymptomatic COVID-19.
CD177 modulates the function and homeostasis of tumor-infiltrating regulatory T cells
Authors: Kim Myung-Chul , Borcherding Nicholas , Ahmed Kawther K. , Voigt Andrew P. , Vishwakarma Ajaykumar , Kolb Ryan , Kluz Paige N. , Pandey Gaurav , De Umasankar , Drashansky Theodore , Helm Eric Y. , Zhang Xin , Gibson-Corley Katherine N. , Klesney-Tait Julia , Zhu Yuwen , Lu Jinglu , Lu Jinsong , Huang Xian , Xiang Hongrui , Cheng Jinke , Wang Dongyang , Wang Zheng , Tang Jian , Hu Jiajia , Wang Zhengting , Liu Hua , Li Mingjia , Zhuang Haoyang , Avram Dorina , Zhou Daohong , Bacher Rhonda , Zheng Song Guo , Wu Xuefeng , Zakharia Yousef , Zhang Weizhou 
Published: October 2021

AbstractRegulatory T (Treg) cells are one of the major immunosuppressive cell types in cancer and a potential target for immunotherapy, but targeting tumor-infiltrating (TI) Treg cells has been challenging. Here, using single-cell RNA sequencing of immune cells from renal clear cell carcinoma (ccRCC) patients, we identify two distinct transcriptional fates for TI Treg cells, Fate-1 and Fate-2. The Fate-1 signature is associated with a poorer prognosis in ccRCC and several other solid cancers. CD177, a cell surface protein normally expressed on neutrophil, is specifically expressed on Fate-1 TI Treg cells in several solid cancer types, but not on other TI or peripheral Treg cells. Mechanistically, blocking CD177 reduces the suppressive activity of Treg cells in vitro, while Treg-specific deletion of Cd177 leads to decreased tumor growth and reduced TI Treg frequency in mice. Our results thus uncover a functional CD177+ TI Treg population that may serve as a target for TI Treg-specific immunotherapy.
Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients
Authors: Nguyen Sam , Chan Ryan , Cadena Jose , Soper Braden , Kiszka Paul , Womack Lucas , Work Mark , Duggan Joan M. , Haller Steven T. , Hanrahan Jennifer A. , Kennedy David J. , Mukundan Deepa , Ray Priyadip 
Published: October 2021

AbstractThe combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource constrained environments the clinical utility of such data-driven predictive tools may be limited by the cost or unavailability of certain laboratory tests. We leveraged EHR data to develop an ML-based tool for predicting adverse outcomes that optimizes clinical utility under a given cost structure. We further gained insights into the decision-making process of the ML models through an explainable AI tool. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Health System in northwest Ohio and southeastern Michigan. We tested the performance of various ML approaches for predicting either increasing ventilatory support or mortality. We performed post hoc analysis to obtain optimal feature sets under various budget constraints. We demonstrate that it is possible to achieve a significant reduction in cost at the expense of a small reduction in predictive performance. For example, when predicting ventilation, it is possible to achieve a 43% reduction in cost with only a 3% reduction in performance. Similarly, when predicting mortality, it is possible to achieve a 50% reduction in cost with only a 1% reduction in performance. This study presents a quick, accurate, and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.
Size-induced twinning in InSb semiconductor during room temperature deformation
Authors: Mignerot Florent , Kedjar Bouzid , Bahsoun Hadi , Thilly Ludovic 
Published: October 2021

AbstractRoom-temperature deformation mechanism of InSb micro-pillars has been investigated via a multi-scale experimental approach, where micro-pillars of 2 µm and 5 µm in diameter were first fabricated by focused ion beam (FIB) milling and in situ deformed in the FIB-SEM by micro-compression using a nano-indenter equipped with a flat tip. Strain rate jumps have been performed to determine the strain rate sensitivity coefficient and the related activation volume. The activation volume is found to be of the order of 3–5 b3, considering that plasticity is mediated by Shockley partial dislocations. Transmission electron microscopy (TEM) thin foils were extracted from deformed micro-pillars via the FIB lift-out technique: TEM analysis reveals the presence of nano-twins as major mechanism of plastic deformation, involving Shockley partial dislocations. The presence of twins was never reported in previous studies on the plasticity of bulk InSb: this deformation mechanism is discussed in the context of the plasticity of small-scale samples.
In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets
Authors: Bourdon Céline , Boussaha Mekki , Bardou Philippe , Sanchez Marie-Pierre , Le Guillou Sandrine , Tribout Thierry , Larroque Hélène , Boichard Didier , Rupp Rachel , Le Provost Fabienne , Tosser-Klopp Gwenola 
Published: October 2021

AbstractMicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.
Critically coupled Fabry–Perot cavity with high signal contrast for refractive index sensing
Authors: Park Gyeong Cheol , Park Kwangwook 
Published: October 2021

AbstractPerfect absorption at a resonance wavelength and extremely low absorption at the wavelength range of off-resonance in a one-port optical cavity is required for refractive index (RI) sensing with high signal contrast. Here, we propose and analyze an absorption-enhanced Fabry–Perot (MAFP) cavity based on a critical coupling condition in a near-infrared wavelength range. For a one-port cavity, a thick bottom Au is used as a mirror and an absorber. To achieve the critical coupling condition, a top dielectric metasurface is employed and tailored to balance the radiation coupling and the absorption coupling rates, and the one-port cavity is theoretically analyzed using temporal coupled-mode theory. We investigate two types of MAFP structures for gas and liquid. The gas MAFP cavity shows a sensitivity of ~ 1388 nm/RIU and a full-width at half-maximum of less than 0.7 nm. This MAFP cavity resolves the RI change of 5 × 10−4 with a reflectance signal margin of 50% and achieves a signal contrast of ~ 100%. The liquid MAFP cavity shows a sensitivity of ~ 996 nm/RIU when RI of liquid changes from 1.30 to 1.38. With tailoring the period of the metasurface maintaining its thickness, a signal contrast of ~ 100% is achieved for each specific RI range.
Three-dimensional culture method enhances the therapeutic efficacies of tonsil-derived mesenchymal stem cells in murine chronic colitis model
Authors: Song Eun Mi , Joo Yang Hee , Choe A. Reum , Park Yehyun , Tae Chung Hyun , Hong Ji Teak , Moon Chang Mo , Kim Seong-Eun , Jung Hye-Kyung , Shim Ki-Nam , Cho Kyung-Ah , Jo Inho , Jung Sung-Ae 
Published: October 2021

AbstractTonsil-derived mesenchymal stem cells (TMSCs) showed therapeutic effects on acute and chronic murine colitis models, owing to their immunomodulatory properties; therefore, we evaluated enhanced therapeutic effects of TMSCs on a murine colitis model using three-dimensional (3D) culture method. The expression of angiogenic factors, VEGF, and anti-inflammatory cytokines, IL-10, TSG-6, TGF-β, and IDO-1, was significantly higher in the 3D-TMSC-treated group than in the 2D-TMSC-treated group (P < 0.05). At days 18 and 30 after inducing chronic colitis, disease activity index scores were estimated to be significantly lower in the 3D-TMSC-treated group than in the colitis control (P < 0.001 and P < 0.001, respectively) and 2D-TMSC-treated groups (P = 0.022 and P = 0.004, respectively). Body weight loss was significantly lower in the 3D-TMSC-treated group than in the colitis control (P < 0.001) and 2D-TMSC-treated groups (P = 0.005). Colon length shortening was significantly recovered in the 3D-TMSC-treated group compared to that in the 2D-TMSC-treated group (P = 0.001). Histological scoring index was significantly lower in the 3D-TMSC-treated group than in the 2D-TMSC-treated group (P = 0.002). These results indicate that 3D-cultured TMSCs showed considerably higher therapeutic effects in a chronic murine colitis model than those of 2D-cultured TMSCs via increased anti-inflammatory cytokine expression.
Analyses of nicotine metabolism biomarker genetics stratified by sex in African and European Americans
Authors: Chenoweth Meghan J. , Cox Lisa Sanderson , Nollen Nikki L. , Ahluwalia Jasjit S. , Benowitz Neal L. , Lerman Caryn , Knight Jo , Tyndale Rachel F. 
Published: October 2021

AbstractNicotine is inactivated by the polymorphic CYP2A6 enzyme to cotinine and then to 3′hydroxycotinine. The Nicotine Metabolite Ratio (NMR; 3′hydroxycotinine/cotinine) is a heritable nicotine metabolism biomarker, varies with sex and ancestry, and influences smoking cessation and disease risk. We conducted sex-stratified genome-wide association studies of the NMR in European American (EA) and African American (AA) smokers (NCT01314001, NCT00666978). In EA females (n = 389) and males (n = 541), one significant (P < 5e−8) chromosome 19 locus was found (top variant: rs56113850, CYP2A6 (intronic), for C vs. T: females: beta = 0.67, P = 7.5e−22, 21.8% variation explained; males: beta = 0.75, P = 1.2e−37, 26.1% variation explained). In AA females (n = 503) and males (n = 352), the top variant was found on chromosome 19 but differed by sex (females: rs11878604, CYP2A6 (~ 16 kb 3′), for C vs. T: beta = − 0.71, P = 6.6e−26, 16.2% variation explained; males: rs3865454, CYP2A6 (~ 7 kb 3′), for G vs. T: beta = 0.64, P = 1.9e−19, 18.9% variation explained). In AA females, a significant region was found on chromosome 12 (top variant: rs12425845: P = 5.0e−9, TMEM132C (~ 1 Mb 5′), 6.1% variation explained) which was not significant in AA males. In AA males, significant regions were found on chromosomes 6 (top variant: rs9379805: P = 4.8e−9, SLC17A2 (~ 8 kb 5′), 8.0% variation explained) and 16 (top variant: rs77368288: P = 3.5e−8, ZNF469 (~ 92 kb 5′), 7.1% variation explained) which were not significant in AA females. Further investigation of these associations outside of chromosome 19 is required, as they did not replicate. Understanding how sex and ancestry influence nicotine metabolism genetics may improve personalized approaches for smoking cessation and risk prediction for tobacco-related diseases.
Acoustic emissions and kinematic instability of the osteoarthritic knee joint: comparison with radiographic findings
Authors: Nevalainen Mika T. , Veikkola Olli , Thevenot Jerome , Tiulpin Aleksei , Hirvasniemi Jukka , Niinimäki Jaakko , Saarakkala Simo S. 
Published: October 2021

AbstractTo evaluate the acoustic emissions (AE) and kinematic instability (KI) of the osteoarthritic (OA) knee joints, and to compare these signals to radiographic findings. Sixty-six female and 43 male participants aged 44–67 were recruited. On radiography, joint-space narrowing, osteophytes and Kellgren–Lawrence (KL) grade were evaluated. Based on radiography, 54 subjects (the study group) were diagnosed with radiographic OA (KL-grade ≥ 2) while the remaining 55 subjects (KL-grade < 2) formed the control group. AE and KI were recorded with a custom-made prototype and compared with radiographic findings using area-under-curve (AUC) and independent T-test. Predictive logistic regression models were constructed using leave-one-out cross validation. In females, the parameters reflecting consistency of the AE patterns during specific tasks, KI, BMI and age had a significant statistical difference between the OA and control groups (p = 0.001–0.036). The selected AE signals, KI, age and BMI were used to construct a predictive model for radiographic OA with AUC of 90.3% (95% CI 83.5–97.2%) which showed a statistical improvement of the reference model based on age and BMI, with AUC of 84.2% (95% CI 74.8–93.6%). In males, the predictive model failed to improve the reference model. AE and KI provide complementary information to detect radiographic knee OA in females.
Relationship between objective measures of hearing discrimination elicited by non-linguistic stimuli and speech perception in adults
Authors: Sohier Hugo , Bardy Fabrice , Ching Teresa Y. C. 
Published: October 2021

AbstractSome people using hearing aids have difficulty discriminating between sounds even though the sounds are audible. As such, cochlear implants may provide greater benefits for speech perception. One method to identify people with auditory discrimination deficits is to measure discrimination thresholds using spectral ripple noise (SRN). Previous studies have shown that behavioral discrimination of SRN was associated with speech perception, and behavioral discrimination was also related to cortical responses to acoustic change or ACCs. We hypothesized that cortical ACCs could be directly related to speech perception. In this study, we investigated the relationship between subjective speech perception and objective ACC responses measured using SRNs. We tested 13 normal-hearing and 10 hearing-impaired adults using hearing aids. Our results showed that behavioral SRN discrimination was correlated with speech perception in quiet and in noise. Furthermore, cortical ACC responses to phase changes in the SRN were significantly correlated with speech perception. Audibility was a major predictor of discrimination and speech perception, but direct measures of auditory discrimination could contribute information about a listener’s sensitivity to acoustic cues that underpin speech perception. The findings lend support for potential application of measuring ACC responses to SRNs for identifying people who may benefit from cochlear implants.
Controlling the thermal conductivity of multilayer graphene by strain
Authors: Nakagawa Kaito , Satoh Kazuo , Murakami Shuichi , Takei Kuniharu , Akita Seiji , Arie Takayuki 
Published: October 2021

AbstractStraintronics is a new concept to enhance electronic device performances by strain for next-generation information sensors and energy-saving technologies. The lattice deformation in graphene can modulate the thermal conductivity because phonons are the main heat carriers. However, the device fabrication process affects graphene’s heat transport properties due to its high stretchability. This study experimentally investigates the change in the thermal conductivity when biaxial tensile strain is applied to graphene. To eliminate non-strain factors, two mechanisms are considered: pressure-induced and electrostatic attraction–induced strain. Raman spectroscopy and atomic force microscopy precisely estimate the strain. The thermal conductivity of graphene decreases by approximately 70% with a strain of only 0.1%. Such thermal conductivity controllability paves the way for applying graphene as high-efficiency thermal switches and diodes in future thermal management devices.
Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing
Authors: Ikegami Hiroaki , Noguchi Shingo , Fukuda Kazumasa , Akata Kentaro , Yamasaki Kei , Kawanami Toshinori , Mukae Hiroshi , Yatera Kazuhiro 
Published: October 2021

AbstractNext-generation sequencing (NGS) technologies have been applied in bacterial flora analysis. However, there is no standardized protocol, and the optimal clustering threshold for estimating bacterial species in respiratory infection specimens is unknown. This study was conducted to investigate the optimal threshold for clustering 16S ribosomal RNA gene sequences into operational taxonomic units (OTUs) by comparing the results of NGS technology with those of the Sanger method, which has a higher accuracy of sequence per single read than NGS technology. This study included 45 patients with pneumonia with aspiration risks and 35 patients with lung abscess. Compared to Sanger method, the concordance rates of NGS technology (clustered at 100%, 99%, and 97% homology) with the predominant phylotype were 78.8%, 71.3%, and 65.0%, respectively. With respect to the specimens dominated by the Streptococcus mitis group, containing several important causative agents of pneumonia, Bray Curtis dissimilarity revealed that the OTUs obtained at 100% clustering threshold (versus those obtained at 99% and 97% thresholds; medians of 0.35, 0.69, and 0.71, respectively) were more similar to those obtained by the Sanger method, with statistical significance (p < 0.05). Clustering with 100% sequence identity is necessary when analyzing the microbiota of respiratory infections using NGS technology.
Toward understanding of the methoxylated flavonoid biosynthesis pathway in Dracocephalum kotschyi Boiss
Authors: Poursalavati Abdonaser , Rashidi-Monfared Sajad , Ebrahimi Amin 
Published: October 2021

AbstractNowadays, with the development and advancement of next-generation sequencing technologies, a new path has been provided for transcriptomic studies. In this study, the transcriptome of Dracocephalum kotschyi Boiss., as an endemic and endangered plant which is contained a large amount of valuable secondary metabolites with antioxidant and anticancer properties, was sequenced. Then functional annotation and gene ontology analysis for 165,597 assembled transcripts were performed, most were associated with the metabolic pathways. This might be because there are various active biochemical pathways in this plant. Furthermore, after comprehensive transcript annotation, the putative genes involved in the main metabolic pathways of D. kotschyi were identified. Then, the biosynthetic pathway of its valuable methoxylated flavones was proposed. Finally, the accumulations of important methoxylated-flavone metabolites in three different tissues were quantified by HPLC. The relative expression of the genes involved in the proposed pathway was investigated by qRT-PCR, which indicated high expression levels in the bud tissue. The present results may lead to the design strategies to preserve the genetic diversity of endangered D. kotschyi plants and apply the new methods for engineering its valuable methoxylated-flavones pathway.
Label-free fiber-optic spherical tip biosensor to enable picomolar-level detection of CD44 protein
Authors: Bekmurzayeva Aliya , Ashikbayeva Zhannat , Myrkhiyeva Zhuldyz , Nugmanova Aigerim , Shaimerdenova Madina , Ayupova Takhmina , Tosi Daniele 
Published: October 2021

AbstractIncreased level of CD44 protein in serum is observed in several cancers and is associated with tumor burden and metastasis. Current clinically used detection methods of this protein are time-consuming and use labeled reagents for analysis. Therefore exploring new label-free and fast methods for its quantification including its detection in situ is of importance. This study reports the first optical fiber biosensor for CD44 protein detection, based on a spherical fiber optic tip device. The sensor is easily fabricated from an inexpensive material (single-mode fiber widely used in telecommunication) in a fast and robust manner through a CO2laser splicer. The fabricated sensor responded to refractive index change with a sensitivity of 95.76 dB/RIU. The spherical tip was further functionalized with anti-CD44 antibodies to develop a biosensor and each step of functionalization was verified by an atomic force microscope. The biosensor detected a target of interest with an achieved limit of detection of 17 pM with only minor signal change to two control proteins. Most importantly, concentrations tested in this work are very broad and are within the clinically relevant concentration range. Moreover, the configuration of the proposed biosensor allows its potential incorporation into an in situ system for quantitative detection of this biomarker in a clinical setting.