bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long‐term SARS‐CoV‐2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China
Authors: Fang Cong , Yan Weiming , Chen Yuying , Dou Zhiyong , Liu Tingting , Luo Fengning , Chen Weiwei , Li Xitang , Chen Yajie , Wu Wenhui , Yuan Zhize , Niu Yuxin , Wang Peng , Zhu Wenzhen , Luo Xiaoping , Chen Tao , Bai Xiang , Wang Xiaojing , Ning Qin 
Published: August 2023

AbstractThe ongoing epidemic of SARS‐CoV‐2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS‐CoV‐2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare policies. Assessed at 3‐, 6‐, 12‐, and 18‐month postdischarge, we described the temporal change of IgG levels in 450 individuals with moderate to critical COVID‐19 infection. Moreover, a data imputation framework combined with a novel deep learning model was implemented to predict the long‐term Nab and IgG levels in these patients. Demographic characteristics, inspection reports, and CT scans during hospitalization were used in this model. Interpretability of the model was further validated with Shapely Additive exPlanation (SHAP) and Gradient‐weighted Class Activation Mapping (GradCAM). IgG levels peaked at 3 months and remained stable in 12 months postdischarge, followed by a significant decline in 18 months postdischarge. However, the Nab levels declined from 6 months postdischarge. By training on the cohort of 450 patients, our long‐term antibody prediction (LTAP) model could predict long‐term IgG levels with relatively high area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1‐score, which far exceeds the performance achievable by commonly used models. Several prognostic factors including FDP levels, the percentages of T cells, B cells and natural killer cells, older age, sex, underlying diseases, and so forth, served as important indicators for IgG prediction. Based on these top 15 prognostic factors identified in IgG prediction, a simplified LTAP model for Nab level prediction was established and achieved an AUC of 0.828, which was 8.9% higher than MLP and 6.6% higher than LSTM. The close correlation between IgG and Nab levels making it possible to predict long‐term Nab levels based on the factors selected by our LTAP model. Furthermore, our model identified that coagulation disorders and excessive immune response, which indicate disease severity, are closely related to the production of IgG and Nab. This universal model can be used as routine discharge tests to identify virus‐infected individuals at risk for recurrent infection and determine the optimal timing of vaccination for general populations.
Nasal discharge: A unique enhanced alternative for the detection of respiratory pathogens in adults
Authors: Fourie Elandri , Bording Eva S. , Euser Sjoerd M. , Badoux Paul , Haverkort Mildred E. , van Houten Marlies A. 
Published: August 2023

AbstractUpper respiratory tract infections are a significant cause of social‐ and disease burden worldwide. Currently, invasive and uncomfortable molecular detection methods are used for respiratory pathogen detection. We aimed to assess the ability and bearability of a rhinorrhea swab (RS) to detect respiratory pathogens in comparison to the combined nasopharyngeal and oropharyngeal swab (NP/OP). This study was performed at a Public Health Service severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) testing facility between November and December 2022 in the Netherlands. Adults aged 16 years and older, being subjected to a standard of care NP/OP swab with nasal discharge, were included and received an additional RS. Respiratory pathogen detection was evaluated using SARS‐CoV‐2 polymerase chain reaction (PCR) and multiplex ligation‐dependent probe amplification (MLPA) PCR. Bearability was evaluated using visual analog scale (VAS) scores and a questionnaire. A total of 100 adults with a mean age ± SD of 46 ± 16 years were included. The NP/OP swab detected 104 pathogens, the RS 83 pathogens (p < 0.001), and in total 108 respiratory pathogens were identified in 89 adults (89%). The ability to detect respiratory pathogens compared between the RS and the combined NP/OP swab revealed a sensitivity of 82% (95% CI 73%–89%) and specificity of 100% (95% CI 72%–100%). RS were significantly more bearable than the combined NP/OP swab (p value < 0.001). Therefore, nasal discharge found in adults can be used as an adequate reliable medium for respiratory pathogen detection using SARS‐CoV‐2 PCR and MLPA PCR.
Four conserved amino acids on human papillomavirus E6 predict clinical high‐risk types
Authors: Niiya Akari , Hamaguchi Yo , Mishima Hiroyuki , Miura Shoko , Komatsu Nahoko , Nagata Koh , Hasegawa Yuri , Miura Kiyonori , Yoshiura Koh‐ichiro 
Published: August 2023

AbstractHuman papillomavirus (HPV) types included in the genus alpha papillomavirus (alpha‐HPVs) are subdivided into high‐ and low‐risk HPVs associated with tumorigenicity. According to conventional risk classification, over 30 alpha‐HPVs remain unclassified and HPV groups phylogenetically classified using the L1 gene do not exactly correspond to the conventional risk classification groups. Here, we propose a novel cervical lesion progression risk classification strategy. Using four E6 risk distinguishable amino acids (E6‐RDAAs), we successfully expanded the conventional classification to encompass alpha‐HPVs and resolve discrepancies. We validated our classification system using alpha‐HPV‐targeted sequence data of 325 cervical swab specimens from participants in Japan. Clinical outcomes significantly correlated with the E6‐RDAA classification. Four of five HPV types in the data set that were not conventionally classified (HPV30, 34, 67, and 69) were high‐risk according to our classification criteria. This report sheds light on the carcinogenicity of rare genital HPV types using a novel risk classification strategy.
Testing a medicine information needs identification tool (MINI‐Q) with hospital inpatients in New Zealand
Authors: Aspden Trudi , Honey Michelle , Sneyd Sarah , Brackley Kim , Cavadino Alana , Chang Rosalie , Chan Amy HY 
Published: August 2023

AbstractBackgroundDetermining an individual's medicines information preferences and needs could enable health professionals to deliver more effective medicines information and help build patients' health literacy and ability to self‐manage their health.AimThis descriptive, cross‐sectional study aimed to test a new information needs assessment tool, the Medicine Information Needs for Individuals – Questionnaire (MINI‐Q), which elicits what individuals want to know about their medicines. This study aimed to explore the face validity, acceptability, and feasibility of using the tool in a hospital inpatient setting.MethodEthical approval was obtained from Health and Disability Ethics Committees (Reference no: 18/NTA/137). Following ethical approval, adult hospital inpatients from two service divisions in one large urban hospital in New Zealand were invited to self‐assess their medicines information needs using the 23‐item MINI‐Q via a tablet or on paper. Descriptive statistics were generated from the quantitative data and responses to a free‐text question were inductively analysed.ResultsThe MINI‐Q was completed by 228 inpatients, 137 (60%) of whom used a tablet. Participants requested information on 80.6% of the possible topics. The most common topic that participants wanted information about was possible side effects (92%). No additional topics to include in the MINI‐Q were identified from the free‐text responses. The median completion time of the tablet version was 9.2 min (interquartile range 6.7–14.6).ConclusionThe MINI‐Q shows promise to efficiently identify an individual's medicines information needs in an inpatient setting. The findings reinforce that most people want to know all the basic information about their medicines, with side effects being particularly important.
Predicting synkinesis caused by Bell's palsy or Ramsay Hunt syndrome using machine learning‐based logistic regression
Authors: Kishimoto‐Urata Megumi , Urata Shinji , Nishijima Hironobu , Baba Shintaro , Fujimaki Yoko , Kondo Kenji , Yamasoba Tatsuya 
Published: August 2023

AbstractObjectiveTo investigate whether machine learning (ML)‐based algorithms, namely logistic regression (LR), random forest (RF), k‐nearest neighbor (k‐NN), and gradient‐boosting decision tree (GBDT), utilizing early post‐onset parameters can predict facial synkinesis resulting from Bell's palsy or Ramsay Hunt syndrome more accurately than the conventional statistics‐based LR.MethodsThis retrospective study included 362 patients who presented to a facial palsy outpatient clinic. Median follow‐up of synkinesis‐positive and ‐negative patients was 388 (range, 177–1922) and 198 (range, 190–3021) days, respectively. Electrophysiological examinations were performed, and the rate of synkinesis in Bell's palsy and Ramsay Hunt syndrome was evaluated. Sensitivity and specificity were assessed using statistics‐based LR; and electroneurography (ENoG) value, the difference in the nerve excitability test (NET), and scores of the subjective Yanagihara scaling system were evaluated using early post‐onset parameters with ML‐based LR, RF, k‐NN, and GBDT.ResultsSynkinesis rate in Bell's palsy and Ramsay Hunt syndrome was 20.2% (53/262) and 40.0% (40/100), respectively. Sensitivity and specificity obtained with statistics‐based LR were 0.796 and 0.806, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.87. AUCs measured using ML‐based LR of “ENoG,” “difference in NET,” “Yanagihara,” and all three components (“all”) were 0.910, 0.834, 0.711, and 0.901, respectively.ConclusionML‐based LR model shows potential in predicting facial synkinesis probability resulting from Bell's palsy or Ramsay Hunt syndrome and has comparable reliability to the conventional statistics‐based LR.Level of Evidence3.
Spatiotemporal variability of dissolved inorganic macronutrients along the northern Antarctic Peninsula (1996–2019)
Authors: Monteiro Thiago , Henley Sian F. , Pollery Ricardo César Gonçalves , Mendes Carlos Rafael Borges , Mata Mauricio , Tavano Virginia Maria , Garcia Carlos Alberto Eiras , Kerr Rodrigo 
Published: August 2023

AbstractThe northern Antarctic Peninsula is a key region of the Southern Ocean due to its complex ocean dynamics, distinct water mass sources, and the climate‐driven changes taking place in the region. Despite the importance of macronutrients in supporting strong biological carbon uptake and storage, little is known about their spatiotemporal variability along the northern Antarctic Peninsula. Hence, we explored for the first time a 24‐year time series (1996–2019) in this region to understand the processes involved in the spatial and interannual variability of macronutrients. We found high macronutrient concentrations, even in surface waters and during strong phytoplankton blooms. Minimum concentrations of dissolved inorganic nitrogen (DIN; 16 μmol kg−1), phosphate (0.7 μmol kg−1), and silicic acid (40 μmol kg−1) in surface waters are higher than those recorded in surrounding regions. The main source of macronutrients is the intrusions of Circumpolar Deep Water and its modified variety, while local sources (organic matter remineralization, water mass mixing, and mesoscale structures) can enhance their spatiotemporal variability. However, we identified a depletion in silicic acid due to the influence of Dense Shelf Water from the Weddell Sea. Macronutrient concentrations show substantial interannual variability driven by the balance between the intrusions of modified Circumpolar Deep Water and advection of Dense Shelf Water, which is largely modulated by the Southern Annular Mode (SAM) and to some extent by El Niño‐Southern Oscillation (ENSO). These findings are critical to improving our understanding of the natural variability of this Southern Ocean ecosystem and how it is responding to climate changes.
Broadband Up‐Conversion Mid‐Infrared Time‐Stretch Spectroscopy
Authors: Wen Zhaoyang , Peng Bo , Yan Ming , Zheng Tingting , Wen Qi , Liu Tingting , Ren Xinyi , Huang Kun , Zeng Heping 
Published: August 2023

AbstractTime‐stretch spectroscopy is a powerful tool for studying transient and nonrepetitive physical events. Its extension to the fundamental molecular fingerprint region is promising for chemical and biological research but encounters difficulties in mid‐infrared photodetection and strong attenuation of aqueous environments. Here, mid‐infrared time‐stretch spectroscopy via coincidently‐pumped nonlinear frequency conversion for efficient mid‐infrared generation and detection is demonstrated. Broadband (≈200 cm−1) mid‐infrared spectra at 77.5 Mspectra s−1 with high signal‐to‐noise ratio are recorded. The single‐shot signal‐to‐noise ratio (SNR) measured within 2 ns exceeds 200. The method reveals fast spectral dynamics in a laser‐induced liquid evaporation process with a temporal resolution of 12.9 ns. Furthermore, probing transient spectra during evaporation opens up a new opportunity for interrogating chemicals inside or behind a thick water layer. Integrating high speed, broad bandwidth, high SNR, and the potential for operating under an aqueous environment, this method will benefit many applications including molecular dynamics, chemical reactions, and biological diagnostics.
Structure and Mechanical Behavior of Fully Substituted Acid Starch Esters
Authors: David Adelina , Stoclet Grégory , Joly Nicolas , Ribeiro Cédric , Descamps Nicolas , Lourdin Denis , Gaucher Valérie 
Published: August 2023

AbstractThis study deals with the evolution of structural, thermal, and mechanical properties of a series of fully substituted fatty acid starch esters (FASEs) according to side chain length (from 2 (C2) up to 16 (C16) Carbons). FASEs with C2 to C12 side chains are fully amorphous with a glass transition temperature depending on chain length while in the case of FASE with C16 side chains, a part of side chains is able to crystallize. Thermomechanical behavior depends strongly on both the alkyl chain length and crystallinity of samples. In particular, for FASE‐C16, the presence of crystals leads to a brittle behavior. During stretching, no macromolecular orientation is evidenced for short‐chain FASEs (<C8), whereas, for long‐chain starch ester from C8 to C16 length, an orientation of starch backbone in the drawing direction is observed.
Tailoring the Architecture of Molecular Bottlebrushes via Click Grafting‐Onto Strategy
Authors: Shi Yi , Hou Wangmeng , Li Zheqi , Chen Yongming 
Published: August 2023

AbstractMolecular bottlebrush (MBB) refer to a synthetic macromolecule, in which a mass of polymeric side chains (SCs) are covalently connected to a macromolecular backbone densely, representing an important type of unimolecular nanomaterial. The chemical composition, size, shape, and surface property of MBB can be precisely tailored by varying the backbones and SCs as well as the grafting density (Gdst). Meanwhile, the topological structure of backbones and SCs can also significantly affect the chemical and physical properties of MBBs. For the past few years, by combining the structure features of MBB, the polymers with diverse architectures using MBB as building block are synthesized, including linear, branched, and cyclic MBB etc. These promising architectural features will bring MBBs with diverse architectures and lots of applications in advanced materials. For this reason, this work is interested in giving a briefly summary of the recent progress on tailor of well‐defined MBBs with diverse architectures using grafting‐onto strategy combined with controlled polymerization technique.
Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T
Authors: Harrevelt Seb D. , Meliado Ettore F. M. , van Lier Astrid L. H. M. W. , Reesink Daan , Meijer Richard P. , Pluim Josien P. W. , Raaijmakers Alexander J. E. 
Published: August 2023

AbstractAt ultrahigh field strengths images of the body are hampered by B1‐field inhomogeneities. These present themselves as inhomogeneous signal intensity and contrast, which is regarded as a “bias field” to the ideal image. Current bias field correction methods, such as the N4 algorithm, assume a low frequency bias field, which is not sufficiently valid for T2w images at 7 T. In this work we propose a deep learning based bias field correction method to address this issue for T2w prostate images at 7 T. By combining simulated B1‐field distributions of a multi‐transmit setup at 7 T with T2w prostate images at 1.5 T, we generated artificial 7 T images for which the homogeneous counterpart was available. Using these paired data, we trained a neural network to correct the bias field. We predicted either a homogeneous image (t‐Image neural network) or the bias field (t‐Biasf neural network). In addition, we experimented with the single‐channel images of the receive array and the corresponding sum of magnitudes of this array as the input image. Testing was carried out on four datasets: the test split of the synthetic training dataset, volunteer and patient images at 7 T, and patient images at 3 T. For the test split, the performance was evaluated using the structural similarity index measure, Wasserstein distance, and root mean squared error. For all other test data, the features Homogeneity and Energy derived from the gray level co‐occurrence matrix (GLCM) were used to quantify the improvement. For each test dataset, the proposed method was compared with the current gold standard: the N4 algorithm. Additionally, a questionnaire was filled out by two clinical experts to assess the homogeneity and contrast preservation of the 7 T datasets. All four proposed neural networks were able to substantially reduce the B1‐field induced inhomogeneities in T2w 7 T prostate images. By visual inspection, the images clearly look more homogeneous, which is confirmed by the increase in Homogeneity and Energy in the GLCM, and the questionnaire scores from two clinical experts. Occasionally, changes in contrast within the prostate were observed, although much less for the t‐Biasf network than for the t‐Image network. Further, results on the 3 T dataset demonstrate that the proposed learning based approach is on par with the N4 algorithm. The results demonstrate that the trained networks were capable of reducing the B1‐field induced inhomogeneities for prostate imaging at 7 T. The quantitative evaluation showed that all proposed learning based correction techniques outperformed the N4 algorithm. Of the investigated methods, the single‐channel t‐Biasf neural network proves most reliable for bias field correction.
Rapid infant weight gain or point‐in‐time weight status: Which is the best predictor of later obesity and body composition?
Authors: Taylor Rachael W. , Haszard Jillian J. , Meredith‐Jones Kim A. , Heath Anne‐Louise M. , Galland Barbara C. , Gray Andrew R. , Fortune Sarah , Sullivan Trudy , Adebowale Taiwo , Taylor Barry J. 
Published: August 2023

AbstractObjectiveThe aim of this study was to determine which growth indicator (weight, weight‐for‐length, BMI) and time frame (6‐ or 12‐month intervals between 0 and 24 months) of rapid infant weight gain (RIWG) best predicted obesity risk and body composition at 11 years of age.MethodsRIWG (increase ≥0.67 z scores between two time points) was calculated from weight and length/height at birth, 0.5, 1, 1.5, and 2 years. The predictive value of each measure and time frame was calculated in relation to obesity (BMI ≥95th percentile) and body fat (fat mass index [FMI], dual‐energy X‐ray absorptiometry scan) at 11 years.ResultsThe sensitivity (1.5% to 62.1%) and positive predictive value (12.5% to 33.3%) of RIWG to predict obesity varied considerably. Having obesity at any time point appeared a stronger risk factor than any indicator of RIWG for obesity at 11 years. Obesity at any age during infancy consistently predicted a greater FMI of around 1.1 to 1.5 kg/m2 at 11 years, whereas differences for RIWG were inconsistent.ConclusionsA simple measure of obesity status at a single time point between 6 and 24 months of age appeared a stronger risk factor for later obesity and FMI than RIWG assessed by any indicator, over any time frame.
Utilization of Transcriptomic Profiling to Identify Molecular Markers Predicting Successful Recovery Following Endoscopic Sinus Surgery for Chronic Rhinosinusitis
Authors: Renteria Axel E. , Maniakas Anastasios , Pelletier Audrey , Filali‐Mouhim Ali , Brochiero Emmanuelle , Valera Fabiana C.P. , Adam Damien , Mfuna Leandra Endam , Desrosiers Martin 
Published: August 2023

AbstractObjectivesSuccessful recovery from chronic rhinosinusitis (CRS) following endoscopic sinus surgery (ESS) can be characterized by minimal presence of symptoms and absence of disease on endoscopy. However, molecular markers of surgical success remain to be characterized. These could allow for better tailoring of perioperative therapy. This study aims to identify novel molecular markers associated with surgery responsive patient.Study DesignProspective cohort study.SettingSingle academic hospital center.MethodOne hundred eighteen consecutive patients with CRS at high risk of recurrence after surgery were followed prospectively following ESS in an academic medical center. Symptomatic and endoscopic outcomes were assessed at 4 months, with success rigorously defined subjectively as minimal or no symptoms (no symptom greater than 1 on an ordinal scale of 0‐3) and objectively by the absence of nasal polyposis on sinus cavity endoscopy and Lund‐Kennedy endoscopic edema score no greater than 1. Samples were obtained at the time of surgery and at 4‐month postoperatively. Changes associated with surgery were determined by gene expression profiling using Affymetrix's Clariom S Human HT arrays.ResultsSuccessful ESS was characterized by a mild upregulation in Type 1 inflammation, upregulation of cell cycle progression, and epithelial barrier and proliferation‐associated genes and pathways. ESS failure was associated to very high levels of Type 1 inflammation along with downregulation of epithelial barrier function and regeneration genes and pathways.ConclusionSuccessful recovery from ESS involves restoration of epithelial function and regulated activation of Type 1 inflammation. Excessively elevated Type 1 inflammation is associated with epithelial barrier dysfunction.
Lateral crashing response of thin‐walled composite structures filled with carbon nanopowder
Authors: Hegazy Dalia A. , Awd Allah Mahmoud M. , Alshahrani Hassan , A. Sebaey Tamer , Abd El‐Baky Marwa A. 
Published: August 2023

AbstractIn this article, the performance of transversely loaded glass fiber reinforced epoxy (GFRE) tubular components containing carbon nanopowder (CNP) in terms of crashworthiness was investigated. The wet‐wrapping by hand lay‐up procedures were used to make GFRE tubes that included 0, 0.25, 0.50, 1, 2, 3, and 4 wt% of CNP. For the laterally loaded tubes, the crashing load and total absorbed energy (TAE) versus displacement responses were displayed. The histories of deformation were tracked in addition. As part of the crashworthiness analysis, the TAE and specific absorbed energy (SEA) were evaluated. Overall results demonstrated that CNP enhances both TAE and SEA up to 0.50 wt% of CNP; after that, a significant deterioration was noticed. CNP, at very low wt%, is considered a great choice for enhancing the crashworthiness performance of composite structures.Highlights
The designed tubes, that is, GFRE tubes filled with 0, 0.25, 0.50, 1, 2, 3, and 4 wt% of CNP, were created using wet‐wrapping by hand lay‐up techniques.
The fabricated tubes were subjected to lateral compression loads to investigate their crashworthiness behavior.
The crashing load and absorbed energy versus displacement responses for the laterally loaded tubes were exposed. The history of deformation for each specimen was also examined.
The experimental results were analyzed and discussed.