bluuebunny/crossref_metadata_2025_split huggingface dataset:
Elucidating the molecular role of MUC5B in progressive lung adenocarcinoma: Prospects for early diagnosis
Authors: Ashok Gayathri , Soundararajan Abirami , Anbarasu Anand , Ramaiah Sudha 
Published: October 2023

AbstractGel‐forming mucin MUC5B is significantly deregulated in lung adenocarcinoma (LUAD), however, its role in tumor progression is not yet clearly understood. Here, we used an integrated computational‐pipeline‐initiated with gene expression analysis followed by network, functional‐enrichment, O‐linked glycosylation analyses, mutational profiling, and immune cell infiltration estimation to functionally characterize MUC5B gene in LUAD. Thereafter, clinical biomarker validation was supported by the overall survival (OA) and comparative expression profiling across clinical stages using computational algorithms. The gene expression profile of LUAD identified MUC5B to be significantly up‐regulated (logFC: 2.36; p‐value: 0.01). Network analysis on LUAD interactome screened MUC5B‐related genes, having key enrichment in immune suppression and O‐linked glycosylation with serine–threonine‐rich tandem repeats being highly glycosylated. Furthermore, positive correlation of mutant MUC5B with immune cells in tumor microenvironment (TME) such as cancer‐associated fibroblasts and myeloid‐derived suppressor cells indicates TME‐mediated tumor progression. The positive correlation with immune inhibitors suggested the enhanced tumor proliferation mediated by MUC5B. Structural stability due to genetic alterations identified overall rigid N–H‐backbone dynamics (S2: 0.756), indicating an overall stable mutant protein. Moreover, the low median OA (<50 months) with a hazard ratio of 1.4 and clinical profile of MUC5B gene showed high median expression corresponding to lymph node (N2) and tumor (T3) stages. Our study concludes by highlighting the functional role of O‐glycosylated and mutant MUC5B in promoting LUAD by immune suppression. Further, clinical gene expression validation of MUC5B suggests its potential role as a diagnostic biomarker for LUAD metastasis.
Picture Perfect: The Status of Image Quality in Prostate MRI
Authors: Woernle Alexandre , Englman Cameron , Dickinson Louise , Kirkham Alex , Punwani Shonit , Haider Aiman , Freeman Alex , Kasivisivanathan Veeru , Emberton Mark , Hines John , Moore Caroline M. , Allen Clare , Giganti Francesco 
Published: October 2023

Magnetic resonance imaging is the gold standard imaging modality for the diagnosis of prostate cancer (PCa). Image quality is a fundamental prerequisite for the ability to detect clinically significant disease. In this critical review, we separate the issue of image quality into quality improvement and quality assessment. Beginning with the evolution of technical recommendations for scan acquisition, we investigate the role of patient preparation, scanner factors, and more advanced sequences, including those featuring Artificial Intelligence (AI), in determining image quality. As means of quality appraisal, the published literature on scoring systems (including the Prostate Imaging Quality score), is evaluated. Finally, the application of AI and teaching courses as ways to facilitate quality assessment are discussed, encouraging the implementation of future image quality initiatives along the PCa diagnostic and monitoring pathway.Evidence Level3Technical EfficacyStage 3
Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI
Authors: Coll Llucia , Pareto Deborah , Carbonell‐Mirabent Pere , Cobo‐Calvo Álvaro , Arrambide Georgina , Vidal‐Jordana Ángela , Comabella Manuel , Castilló Joaquín , Rodrı́guez‐Acevedo Breogán , Zabalza Ana , Galán Ingrid , Midaglia Luciana , Nos Carlos , Auger Cristina , Alberich Manel , Río Jordi , Sastre‐Garriga Jaume , Oliver Arnau , Montalban Xavier , Rovira Àlex , Tintoré Mar , Lladó Xavier , Tur Carmen 
Published: October 2023

BackgroundThe combination of anatomical MRI and deep learning‐based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect of different input strategies on model's performance are lacking.PurposeTo compare whole‐brain input sampling strategies and regional/specific‐tissue strategies, which focus on a priori known relevant areas for disability accrual, to stratify MS patients based on their disability level.Study TypeRetrospective.SubjectsThree hundred nineteen MS patients (382 brain MRI scans) with clinical assessment of disability level performed within the following 6 months (~70% training/~15% validation/~15% inference in‐house dataset) and 440 MS patients from multiple centers (independent external validation cohort).Field Strength/SequenceSingle vendor 1.5 T or 3.0 T. Magnetization‐Prepared Rapid Gradient‐Echo and Fluid‐Attenuated Inversion Recovery sequences.AssessmentA 7‐fold patient cross validation strategy was used to train a 3D‐CNN to classify patients into two groups, Expanded Disability Status Scale score (EDSS) ≥ 3.0 or EDSS < 3.0. Two strategies were investigated: 1) a global approach, taking the whole brain volume as input and 2) regional approaches using five different regions‐of‐interest: white matter, gray matter, subcortical gray matter, ventricles, and brainstem structures. The performance of the models was assessed in the in‐house and the independent external cohorts.Statistical TestsBalanced accuracy, sensitivity, specificity, area under receiver operating characteristic (ROC) curve (AUC).ResultsWith the in‐house dataset, the gray matter regional model showed the highest stratification accuracy (81%), followed by the global approach (79%). In the external dataset, without any further retraining, an accuracy of 72% was achieved for the white matter model and 71% for the global approach.Data ConclusionThe global approach offered the best trade‐off between internal performance and external validation to stratify MS patients based on accumulated disability.Evidence Level4Technical EfficacyStage 2
Reduced neutralization and Fc effector function to Omicron subvariants in sera from SARS‐CoV‐1 survivors after two doses of CoronaVac plus one dose subunit vaccine
Authors: Chen Danying , Li Xinglin , Hao Xiaohua , Qiu Yaruo , Song Yanjun , Sun Hui , Liu Yongmei , Du Juan , Zhang Yuanyuan , Xiao Fan , Song Chuan , Yan Yonghong , Song Rui , Wang Xi , Zhao Xuesen , Jin Ronghua 
Published: October 2023

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) Omicron harbors more than 30 mutations of the spike protein and exhibits substantial immune evasion. Although previous study indicated that BNT162b2 messenger RNA vaccine induces potent cross‐clade pan‐sarbecovirus neutralizing antibodies in survivors of the infection by SARS‐CoV‐1, the neutralization activity and Fc‐mediated effector functions of these cross‐reactive antibodies elicited in SARS‐CoV‐1 survivors to Omicron subvariants still remain largely unknown. In this study, the neutralization activity and Fc‐mediated effector functions of antibodies boosted by a third dose vaccination were characterized in SARS‐CoV‐1 convalescents and healthy individuals. Potent cross‐clade broadly neutralizing antibodies were observed in SARS‐CoV‐1 survivors who received a three‐dose vaccination regimen consisting of two priming doses of CoronaVac followed by one booster dose of the protein subunit vaccine ZF2001. However, the induced antibodies exhibited both reduced neutralization and impaired Fc effector functions targeting multiple Omicron subvariants. Importantly, the data also support the notion that immune imprints resulted from SARS‐CoV‐1 infection may exacerbate the impairment of neutralization activity and Fc‐mediated effector functions to Omicron subvariants and provided invaluable information to vaccination strategy in future.
Amplicon size and non‐encapsidated DNA fragments define plasma cytomegalovirus DNA loads by automated nucleic acid testing platforms: A marker of viral cytopathology?
Authors: Leuzinger Karoline , Hirsch Hans H. 
Published: October 2023

AbstractManagement of cytomegalovirus (CMV) in transplant patients relies on measuring plasma CMV‐loads using quantitative nucleic acid testing (QNAT). We prospectively compared the automated Roche‐cobas®6800‐CMV and Roche‐CAP/CTM‐CMV with laboratory‐developed Basel‐CMV‐UL54‐95bp, and Basel‐CMV‐UL111a‐77bp. Roche‐cobas®6800‐CMV and Roche‐CAP/CTM‐CMV were qualitatively concordant in 142/150 cases (95%). In‐depth comparison revealed higher CMV‐loads of the laboratory‐developed assay and correlated with smaller amplicon size. After calibration to the 1.WHO‐approved CMV international standard, differences were reduced but remained significant. DNase‐I pretreatment significantly reduced CMV‐loads for both automated Roche‐CAP/CTM‐CMV and Roche‐cobas®6800‐CMV assays, whereby 90% and 95% of samples became undetectable. DNase‐I pretreatment also reduced CMV‐loads quantified by Basel‐CMV‐UL54‐95bp and Basel‐CMV‐UL111a‐77bp, but remaining detectable in 20% and 35%, respectively. Differences were largest for 110 samples with low‐level CMV‐DNAemia being detectable but not‐quantifiable by Roche‐cobas®6800‐CMV, whereby the smaller amplicon sizes yielded higher viral loads for concordant positives. We conclude that non‐encapsidated fragmented CMV‐DNA is the major form of plasma CMV‐loads also measured by fully‐automated platforms. Amplicons of <150 bp and calibrators are needed for reliable and commutable QNAT‐results. We hypothesize that non‐encapsidated fragmented CMV‐DNA results from lysis of CMV‐replicating cells and represent a direct marker of viral cell damage, which contribute to delayed viral load responses despite effective antivirals.
Repurposing Navitoclax to block SARS‐CoV‐2 fusion and entry by targeting heptapeptide repeat sequence 1 in S2 protein
Authors: Jiao Fanke , Andrianov Alexander M. , Wang Lijue , Furs Konstantin V. , Gonchar Anna V. , Wang Qian , Xu Wei , Lu Lu , Xia Shuai , Tuzikov Alexander V. , Jiang Shibo 
Published: October 2023

AbstractAlong with the long pandemic of COVID‐19 caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has come the dilemma of emerging viral variants of concern (VOC), particularly Omicron and its subvariants, able to deftly escape immune surveillance and the otherwise protective effect of current vaccines and antibody drugs. We previously identified a peptide‐based pan‐CoV fusion inhibitor, termed as EK1, able to bind the HR1 region in viral spike (S) protein S2 subunit. This effectively blocked formation of the six‐helix bundle (6‐HB) fusion core and, thus, showed efficacy against all human coronaviruses (HCoVs). EK1 is now in phase 3 clinical trials. However, the peptide drug generally lacks oral availability. Therefore, we herein performed a structure‐based virtual screening of the libraries of biologically active molecules and identified nine candidate compounds. One is Navitoclax, an orally active anticancer drug by inhibition of Bcl‐2. Like EK1 peptide, it could bind HR1 and block 6‐HB formation, efficiently inhibiting fusion and infection of all SARS‐CoV‐2 variants tested, as well as SARS‐CoV and MERS‐CoV, with IC50 values ranging from 0.5 to 3.7 μM. These findings suggest that Navitoclax is a promising repurposed drug candidate for development as a safe and orally available broad‐spectrum antiviral drug to combat the current SARS‐CoV‐2 and its variants, as well as other HCoVs.
Transmissibility quantification of norovirus outbreaks in 2016−2021 in Beijing, China
Authors: Wang Yu , Gao Zhiyong , Lu Qingbin , Liu Baiwei , Jia Lei , Shen Lingyu , Tian Yi , Li Weihong , Yan Hanqiu , Zhang Daitao , Yang Peng , Fang Liqun , Wang Quanyi , Cui Fuqiang 
Published: October 2023

AbstractThe transmissibility is a crucial feature for norovirus, yet its quantitative estimation has been limited. Our objective was to estimate the basic reproduction number (R0) of norovirus and investigate its variation characteristics. Norovirus outbreaks reported from September 2016 to August 2021 in Beijing were analyzed. The susceptible‐infected‐removed compartment model was established to estimate R0. Linear regression models and logistic regression models were used to explore the factors affecting the transmissibility of norovirus. The overall median R0 of norovirus was estimated as 2.1 (interquartile range [IQR] 1.8–2.5), with 650 norovirus outbreaks. The transmissibility of norovirus varied by year, outbreak setting and genotype. The R0 of norovirus during September 2019 to August 2020 (median 2.1, IQR 1.8–2.4) and September 2020 to August 2021 (median 2.0, IQR 1.7–2.3) was lower than that of September 2016 to August 2017 (median 2.3, IQR 1.8–2.7) (β = 0.94, p = 0.05; β = 0.93, p = 0.008). The R0 of norovirus for all other settings was lower than that for kindergarten (median 2.4, IQR 2.0–2.9) (primary school: median 2.0, IQR 1.7–2.4, β = 0.94, p = 0.001; secondary school: median 1.7, IQR 1.5–2.0, β = 0.87, p < 0.001; college: median 1.7, IQR 1.5–1.8, β = 0.89, p = 0.03; other closed settings: median 1.8, IQR 1.5–2.0, β = 0.90, p = 0.004). GⅡ.2[P16] outbreaks had a median R0 of 2.2 (IQR 1.8–2.7), which was higher than that for GⅡ.6[P7] outbreaks (median 1.8, IQR: 1.8–2.0, odds ratio = 0.19, p = 0.03; GⅡ.2[P16] as reference) and mixed‐genotype outbreaks (median 1.7, IQR: 1.5–1.8, β = 0.92, p = 0.02; mixed‐genotype as reference). In kindergartens and primary schools, norovirus shows increased transmissibility, emphasizing the vulnerable population and high‐risk settings. Furthermore, the transmissibility of norovirus may change over time and with virus evolution, necessitating additional research to uncover the underlying mechanisms.
Quantification of uncertainties in projections of extreme daily precipitation simulated by CMIP6 GCMs over homogeneous regions of India
Authors: Nair Meera M. , Rajesh A. Naga , Sahai A. K. , Lakshmi Kumar T. V. 
Published: October 2023

AbstractGlobal climate model (GCM) projections are subject to significant uncertainties. Quantifying uncertainties in climate change projections improves credibility and makes climate data more reliable. This study aims to quantify the uncertainties in projected extreme precipitation during the 21st century over the homogeneous rainfall regions of India simulated by Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs. The percentile‐based square root error variance (SREV) method estimates model, scenario and ensemble uncertainties in projections of extreme precipitation. The uncertainty is investigated at four thresholds: 95th, 99th, 99.9th and 100th percentiles. The results show that the wet northeast region has a greater SREV, which is consistent with previous studies. At 99th and 99.9th percentiles, relative model SREV is dominant over the northeast (NE) region. However, at the 95th percentile high relative model SREV is found over the northwest (NW) region during southwest (June, July, August and September) and NE (October, November and December) monsoon seasons. Model uncertainty is the main source of uncertainty, followed by scenario and ensemble uncertainties. The study indicates that the arid NW region in India has a higher level of uncertainty than other regions with homogeneous rainfall. These findings will assist policymakers in planning infrastructure development in arid regions of India.
In‐between self‐marketing and collaboration: Researcher identity formation in the usage of academic social network sites
Authors: Söldner Jens‐Henrik 
Published: October 2023

AbstractAcademic social network sites (ASNS) are a special case of social networking sites, providing a professional identity for management scholars online. Due to the particular requirements of academic work, usage patterns deviate from those on other social networking sites. The study presented here takes an in‐depth look at needs and gratifications in the usage of ASNS. In contrast to earlier studies of the same kind, it includes social influence from the academic community as another theoretical lens to identify cross‐individual effects. Based on 19 interviews with members of a community in business and management research, the study discusses knowledge and information transfer, enjoyment and entertainment, social interaction and professional belonging, self‐promotion and escapism as critical issues in using ASNS. For each of these issues, the study reveals various patterns in which gratifications are affected by social influence. They can be considered as specific characteristic of ASNS in the contexts of scientific research and teaching that contribute to a better understanding of the specificities of social media usage in academia.
Seed biopriming as a promising approach for stress tolerance and enhancement of crop productivity: a review
Authors: Srivastava Sonal , Tyagi Rashi , Sharma Shilpi 
Published: October 2023

AbstractChemicals are used extensively in agriculture to increase crop production to meet the nutritional needs of an expanding world population. However, their injudicious application adversely affects the soil's physical, chemical and biological properties, subsequently posing a substantial threat to human health and global food security. Beneficial microorganisms improve plant health and productivity with minimal impact on the environment; however, their efficacy greatly relies on the application technique. Biopriming is an advantageous technique that involves the treatment of seeds with beneficial biological agents. It exhibits immense potential in improving the physiological functioning of seeds, thereby playing a pivotal role in their uniform germination and vigor. Biopriming‐mediated molecular and metabolic reprogramming imparts stress tolerance to plants, improves plant health, and enhances crop productivity. Furthermore, it is also associated with rehabilitating degraded land, and improving soil fertility, health and nutrient cycling. Although biopriming has vast applications in the agricultural system, its commercialization and utilization by farmers is still in its infancy. This review aims to critically analyze the recent studies based on biopriming‐mediated stress mitigation by alteration in physiological, metabolic and molecular processes in plants. Additionally, considering the necessity of popularizing this technique, the major challenges and prospects linked to the commercialization and utilization of this technique in agricultural systems have also been discussed. © 2023 Society of Chemical Industry.
Inequities in cancer surgical research capacity in the global south and strategies to address them
Authors: Murthy Shilpa S. , Are Chandrakanth 
Published: October 2023

AbstractGlobally, cancer is a leading cause of premature mortality and incidence is rising rapidly. To mitigate the cancer burden establishing research programs that are country and/or region specific will inform evidence‐based cancer control policies and programs. However inequities in surgical cancer research in the global south exist and in this article we discuss gaps and potential solutions through frameworks focusing on research training, building infrastructure, economic strategies, and research ethics.
An additively manufactured model for preclinical testing of cervical devices
Authors: Wahbeh Jenna M. , Hookasian Erika , Lama John , Alam Labiba , Park Sang‐Hyun , Sangiorgio Sophia N. , Ebramzadeh Edward 
Published: October 2023

AbstractPurposeComposite models have become commonplace for the assessment of fixation and stability of total joint replacements; however, there are no comparable models for the cervical spine to evaluate fixation. The goal of this study was to create the framework for a tunable non‐homogeneous model of cervical vertebral body by identifying the relationships between strength, in‐fill density, and lattice structure and creating a final architectural framework for specific strengths to be applied to the model.MethodsThe range of material properties for cervical spine were identified from literature. Using additive manufacturing software, rectangular prints with three lattice structures, gyroid, triangle, zig‐zag, and a range of in‐fill densities were 3D‐printed. The compressive and shear strengths for all combinations were calculated in the axial and coronal planes. Eleven unique vertebral regions were selected to represent the distribution of density. Each bone density was converted to strength and subsequently correlated to the lattice structure and in‐fill density with the desired material properties. Finally, a complete cervical vertebra model was 3D‐printed to ensure sufficient print quality.ResultsMaterials testing identified a relationship between in‐fill densities and strength for all lattice structures. The axial compressive strength of the gyroid specimens ranged from 1.5 MPa at 10% infill to 31.3 MPa at 100% infill and the triangle structure ranged from 2.7 MPa at 10% infill to 58.4 MPa at 100% infill. Based on these results, a cervical vertebra model was created utilizing cervical cancellous strength values and the corresponding in‐fill density and lattice structure combination. This model was then printed with 11 different in‐fill densities ranging from 33% gyroid to 84% triangle to ensure successful integration of the non‐homogeneous in‐fill densities and lattice structures.ConclusionsThe findings from this study introduced a framework for using additive manufacturing to create a tunable, customizable biomimetic model of a cervical vertebra.
Ultrasound and surfactant‐assisted dispersive liquid–liquid microextraction prior to poly(ethylene oxide)‐mediated stacking in CE for highly sensitive determination of barbiturates in human fluids
Authors: Tseng Li Hsin , Liang Pei‐Chi , Chiu Tai‐Chia , Hsieh Ming‐Mu 
Published: October 2023

This study developed a facile, highly sensitive technique for extracting and quantifying barbiturates in serum samples. This method combined ultrasound and surfactant‐assisted dispersive liquid–liquid microextraction with poly(ethylene oxide)‐mediated stacking in capillary electrophoresis. Factors influencing the extraction and stacking performance, such as the type and volume of extraction solvents, the type and concentration of surfactant, extraction time, salt additives, sample matrix, solution pH, and composition of the background electrolyte, were carefully studied and optimized to achieve the optimal detection sensitivity. Under the optimized extraction (injecting 140 μL C2H4Cl2 into 1 mL of sample with pH 4 (5 mM sodium phosphate containing 0.05 mM Tween 20 and sonication for 1 min) and separation conditions (150 mM tris(hydroxymethyl)aminomethane‐borate with pH 8.5 containing 0.5% (m/v) poly(ethylene oxide)), the limits of detection (signal‐to‐noise ratio = 3) of five barbiturates ranged from 0.20 to 0.33 ng/mL, and the calculated sensitivity improvement ranged from 868‐ to 1700‐fold. The experimental results revealed excellent linearity (R2 > 0.99), with relative standard deviations of 2.1%–3.4% for the migration time and 4.3%–5.7% for the peak area. The recoveries of the spiked serum samples were 97.1% –110.3%. Our proposed approach offers a rapid and practical method for quantifying barbiturates in biological fluids.