bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliability analysis of the cast-in-place bored pile with different defects
Authors: Yao Hua , Ma Lemin , Duan Zhiqiang , Guo Wei 
Published: February 2024

The defects of the cast-in-place bored piles heavily influence their integrities and bearing capacities. The bearing capacity and reliability index of the cast-in-place bored piles with different defects were studied using the finite element method. The accuracy of the numerical model is verified by the field test results of an in situ cast-in-place bored pile. Parametric studies are conducted to investigate the toe debris, mud cake, and necking and bulging defects on the ultimate bearing capacities of the cast-in-place bored piles. The results indicate that maximum reduction in the ultimate bearing capacities of the cast-in-place bored pile was observed, with the ultimate bearing capacity of the toe debris defect decreased by 17%, that of the mud cake defect decreased by 19%, that of the necking defect by 6.1%, and that of the pile bulging defect increased by 40.9%. The minimum reliability index can be 0.81 when the diameter of the pile necking defect is 0.2 m. The maximum reliability index can be 3.63 when the diameter of the pile necking defect is 2.0 m.
Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups
Authors: Saglietto Andrea , Baccega Daniele , Esposito Roberto , Anselmino Matteo , Dusi Veronica , Fiandrotti Attilio , De Ferrari Gaetano Maria 
Published: February 2024

BackgroundArtificial intelligence (AI) has shown promise in the early detection of various cardiac conditions from a standard 12-lead electrocardiogram (ECG). However, the ability of AI to identify abnormalities from single-lead recordings across a range of pathological conditions remains to be systematically investigated. This study aims to assess the performance of a convolutional neural network (CNN) using a single-lead (D1) rather than a standard 12-lead setup for accurate identification of ECG abnormalities.MethodsWe designed and trained a lightweight CNN to identify 20 different cardiac abnormalities on ECGs, using data from the PTB-XL dataset. With a relatively simple architecture, the network was designed to accommodate different combinations of leads as input (&lt;100,000 learnable parameters). We compared various lead setups such as the standard 12-lead, D1 alone, and D1 paired with an additional lead.ResultsThe CNN based on single-lead ECG (D1) achieved satisfactory performance compared to the standard 12-lead framework (average percentage AUC difference: −8.7%). Notably, for certain diagnostic classes, there was no difference in the diagnostic AUC between the single-lead and the standard 12-lead setups. When a second lead was detected in the CNN in addition to D1, the AUC gap was further reduced to an average percentage difference of −2.8% compared with that of the standard 12-lead setup.ConclusionsA relatively lightweight CNN can predict different classes of cardiac abnormalities from D1 alone and the standard 12-lead ECG. Considering the growing availability of wearable devices capable of recording a D1-like single-lead ECG, we discuss how our findings contribute to the foundation of a large-scale screening of cardiac abnormalities.
SRF material research using muon spin rotation and beta-detected nuclear magnetic resonance
Authors: Junginger Tobias , Laxdal Robert , MacFarlane W. A. , Suter Andreas 
Published: February 2024

Muon spins precess in transverse magnetic fields and emit a positron preferentially in the spin direction at the instant of decay, enabling muon spin rotation (μSR) as a precise probe of local magnetic fields in matter. μSR has been used to characterize superconducting radio-frequency (SRF) materials since 2010. At TRIUMF, a beam of 4.2 MeV μ+ is implanted at a material-dependent depth of approximately 150 μm. A dedicated spectrometer was developed to measure the field of first vortex penetration and pinning strength in SRF materials in parallel magnetic fields of up to 300 mT. A low-energy beam available at PSI implants μ+ at variable depth in the London layer allowing for direct measurements of the London penetration depth from which other material parameters relevant for SRF applications, such as the lower critical field and the superheating field, can be calculated. Beta-detected nuclear magnetic resonance (β-NMR) is a technique similar to low-energy μSR using beams of low-energy β radioactive ions. With a recent upgrade, it is capable of detecting the penetration of parallel magnetic vortices, depth resolved with nanometer resolution at applied fields of up to 200 mT. In this paper, we review the impact and capabilities of these techniques for SRF research.
Inflammatory biomarkers predict higher risk of hyperglycemic crises but not outcomes in diabetic patients with COVID-19
Authors: Tao Li-Chan , Shu Hong , Wang Ying , Hou Qian , Li Jian-Jun , Huang Xiao-Lin , Hua Fei 
Published: February 2024

BackgroundInflammation is a predictor of severe complications in patients with COVID-19 infection under a variety of clinical settings. A few studies suggested that COVID-19 infection was a trigger of hyperglycemic crises including diabetic ketoacidosis (DKA) and/or hyperglycemic hyperosmolar state (HHS). However, the association between inflammation and hyperglycemic crises in diabetic patients with COVID-19 infection is unclear.MethodsOne hundred and twenty-four patients with type 2 diabetes mellitus (T2DM) and COVID-19 infection from January 2023 to March 2023 were retrospectively analyzed. Demographic, clinical, and laboratory data, especially inflammatory markers including white blood cell (WBC), neutrophils, neutrophil-to-lymphocyte ratio (NLR), c-reactive protein (CRP) and procalcitonin (PCT) were collected and compared between patients with or without DKA and/or HHS. Multivariable logistic regression analysis was conducted to explore the association between inflammatory biomarkers and the prevalence of hyperglycemic crises. Patients were followed up 6 months for outcomes.ResultsAmong 124 diabetic patients with COVID-19, 9 were diagnosed with DKA or HHS. Comparing COVID-19 without acute diabetic complications (ADC), patients with DKA or HHS showed elevated levels of c-reactive protein (CRP, P=0.0312) and procalcitonin (PCT, P=0.0270). The power of CRP and PCT to discriminate DKA or HHS with the area under the receiver operating characteristics curve (AUROC) were 0.723 and 0.794, respectively. Multivariate logistic regression indicated 1.95-fold and 1.97-fold increased risk of DKA or HHS with 1-unit increment of CRP and PCT, respectively. However, neither CRP nor PCT could predict poor outcomes in diabetic patients with COVID-19.ConclusionIn this small sample size study, we firstly found that elevated serum CRP and PCT levels increased the risk of hyperglycemic crises in T2DM patients with COVID-19 infection. More study is needed to confirm our findings.
High-frequency multimodal training with a focus on Tai Chi in people with Parkinson’s disease: a pilot study
Authors: Toloraia Ketevan , Gschwandtner Ute , Fuhr Peter 
Published: February 2024

Background and objectivesCognitive decline is an important and common complication in patients with Parkinson’s disease (PD) since it significantly reduces the quality of life. A breakthrough in treating and preventing cognitive decline in PD remains to be achieved. This study aimed to evaluate the effectiveness of high-frequency and intensive multimodal training in improving motor and cognitive function.MethodsTwenty-eight patients diagnosed with idiopathic PD completed a comprehensive neuropsychological test battery and were neurologically examined. The patients of the intervention group (n = 15) underwent 2 weekly sessions of Tai Chi therapy over 4 weeks and participated in an individually tailored training program consisting of two modules (smartphone-based speech training and cognitive training). A matched control group consisted of n = 13 patients with PD who received computer-assisted cognitive training. The data were analyzed with repeated-measures ANOVA.ResultsFour weeks of high-frequency training showed significant effects on verbal and figural episodic memory and visuospatial function in the intervention group.Compared to the control group, the cognitive performance of the intervention group improved significantly in visuospatial function and figural episodic memory. A significant improvement was also shown in the intervention group in the Tinetti Mobility Test and the Epworth Sleepiness Scale. The significant effects in the Tinetti mobility test remained after the 6 months follow-up. After the intervention, the patients reported high motivation and satisfaction with the multimodal training.ConclusionIn patients with PD, a multimodal training program not only improves gait and stability but may also contribute to improving cognition.Clinical trial registrationClinicalTrials.gov Identifier: NCT04103255; https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&amp;cx=-jg9qo4.
Investigating the shared genetic architecture between frailty and insomnia
Authors: Song Zhiwei , Li Wangyu , Han Yupeng , Xu Yiya , Wang Yinzhou 
Published: February 2024

BackgroundThe epidemiological association between frailty and insomnia is well established, yet the presence of a common genetic etiology is still uncertain. Further exploration is needed to ascertain the causal relationship between frailty and insomnia.MethodsUtilizing data obtained from genome-wide association studies (GWAS) summaries, we utilized the linkage disequilibrium score regression (LDSC) to determine the genetic correlation existing between frailty and insomnia. The determination of causality was achieved through the application of two-sample Mendelian randomization. We investigated the enrichment of single nucleotide polymorphism (SNP) at various tissue types utilizing stratified LD score regression (S-LDSC) and multimarker analysis of genome annotation (MAGMA). Common risk SNPs were identified using Multi-Trait Analysis of GWAS (MTAG) and Cross-Phenotype Association (CPASSOC). We further investigated the expression profiles of risk genes in tissues using Summary-data-based Mendelian randomization(SMR) based on pooled data, to explore potential functional genes.ResultsOur findings indicated a significant genetic correlation between frailty and insomnia, highlighting SNPs sharing risk (rs34290943, rs10865954), with a pronounced correlation in the localized genomic region 3p21.31. Partitioned genetic analysis revealed 24 functional elements significantly associated with both frailty and insomnia. Furthermore, mendelian randomization revealed a causal connection between frailty and insomnia. The genetic correlation between frailty and insomnia showed enrichment in 11 brain regions (S-LDSC) and 9 brain regions (MAGMA), where four functional genes (RMB6, MST1R, RF123, and FAM212A) were identified.ConclusionThis study suggests the existence of a genetic correlation and common risk genes between frailty and insomnia, contributing to a deeper comprehension of their pathogenesis and assists in identifying potential therapeutic targets.
Factors affecting 30-day mortality in poor-grade aneurysmal subarachnoid hemorrhage: a 10-year single-center experience
Authors: Scibilia Antonino , Rustici Arianna , Linari Marta , Zenesini Corrado , Belotti Laura Maria Beatrice , Dall’Olio Massimo , Princiotta Ciro , Cuoci Andrea , Aspide Raffaele , Migliorino Ernesto , Moneti Manuel , Sturiale Carmelo , Castioni Carlo Alberto , Conti Alfredo , Bortolotti Carlo , Cirillo Luigi 
Published: February 2024

BackgroundThe management of patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH) is burdened by an unfavorable prognosis even with aggressive treatment. The aim of the present study is to investigate the risk factors affecting 30-day mortality in poor-grade aSAH patients.MethodsWe performed a retrospective analysis of a prospectively collected database of poor-grade aSAH patients (World Federation of Neurosurgical Societies, WFNS, grades IV and V) treated at our institution from December 2010 to December 2020. For all variables, percentages of frequency distributions were analyzed. Contingency tables (Chi-squared test) were used to assess the association between categorical variables and outcomes in the univariable analysis. Multivariable analysis was performed by using the multiple logistic regression method to estimate the odds ratio (OR) for 30-day mortality.ResultsA total of 149 patients were included of which 32% had WFNS grade 4 and 68% had WFNS grade 5. The overall 1-month mortality rate was 21%. On univariable analysis, five variables were found to be associated with the likelihood of death, including intraventricular hemorrhage (IVH ≥ 50 mL, p = 0.005), the total amount of intraventricular and intraparenchymal hemorrhage (IVH + ICH ≥ 90 mL, p = 0.019), the IVH Ratio (IVH Ratio ≥ 40%, p = 0.003), posterior circulation aneurysms (p = 0.019), presence of spot sign on initial CT scan angiography (p = 0.015).Nonetheless, when the multivariable analysis was performed, only IVH Ratio (p = 0.005; OR 3.97), posterior circulation aneurysms (p = 0.008; OR 4.05) and spot sign (p = 0.022; OR 6.87) turned out to be independent predictors of 30-day mortality.ConclusionThe risk of mortality in poor-grade aSAH remains considerable despite maximal treatment. Notwithstanding the limitations of a retrospective study, our report highlights some neuroradiological features that in the emergency setting, combined with leading clinical and anamnestic parameters, may support the multidisciplinary team in the difficult decision-making process and communication with family members from the earliest stages of poor-grade aSAH. Further prospective studies are warranted.
β-glucans from Agaricus bisporus mushroom products drive Trained Immunity
Authors: Case Sarah , O'Brien Tara , Ledwith Anna E. , Chen Shilong , Horneck Johnston Cian J. H. , Hackett Emer E. , O'Sullivan Michele , Charles-Messance Hugo , Dempsey Elaine , Yadav Supriya , Wilson Jude , Corr Sinead C. , Nagar Shipra , Sheedy Frederick J. 
Published: February 2024

IntroductionMacrofungi, such as edible mushrooms, have been used as a valuable medical resource for millennia as a result of their antibacterial and immuno-modulatory components. Mushrooms contain dietary fibers known as β-glucans, a class of polysaccharides previously linked to the induction of Trained Immunity. However, little is known about the ability of mushroom-derived β-glucans to induce Trained Immunity.Methods &amp; resultsUsing various powdered forms of the white button mushroom (Agaricus bisporus), we found that mouse macrophages pre-treated with whole mushroom powder (WMP) displayed enhanced responses to restimulation with TLR ligands, being particularly sensitive to Toll-like receptor (TLR)-2 stimulation using synthetic lipopeptides. This trained response was modest compared to training observed with yeast-derived β-glucans and correlated with the amount of available β-glucans in the WMP. Enriching for β-glucans content using either a simulated in-vitro digestion or chemical fractionation retained and boosted the trained response with WMP, respectively. Importantly, both WMP and digested-WMP preparations retained β-glucans as identified by nuclear magnetic resonance analysis and both displayed the capacity to train human monocytes and enhanced responses to restimulation. To determine if dietary incorporation of mushroom products can lead to Trained Immunity in myeloid cells in vivo, mice were given a regimen of WMP by oral gavage prior to sacrifice. Flow cytometric analysis of bone-marrow progenitors indicated alterations in hematopoietic stem and progenitor cells population dynamics, with shift toward myeloid-committed multi-potent progenitor cells. Mature bone marrow-derived macrophages derived from these mice displayed enhanced responses to restimulation, again particularly sensitive to TLR2.DiscussionTaken together, these data demonstrate that β-glucans from common macrofungi can train innate immune cells and could point to novel ways of delivering bio-available β-glucans for education of the innate immune system.
Caregiver strategies supporting community participation among children and youth with or at risk for disabilities: a mixed-methods study
Authors: Kaelin Vera C. , Saluja Shivani , Bosak Dianna L. , Anaby Dana , Werler Martha , Khetani Mary A. 
Published: February 2024

IntroductionThe purpose of this mixed-methods study is to examine the role of caregiver strategies to support community participation among children and youth with disabilities and those at risk, from the caregiver perspective. For the quantitative phase, we tested the hypothesized positive effect of participation-focused caregiver strategies on the relationship(s) between participation-related constructs and community participation attendance and involvement. For the qualitative phase, we solicited caregiver perspectives to explain the quantitative findings.MethodsAn explanatory sequential mixed-methods design (QUAN &gt; qual) was used. For the quantitative phase, we conducted secondary analyses of data collected during a second follow-up phase of a longitudinal cohort study, including 260 families of children and youth (mean age: 13.5 years) with disabilities and those at risk [i.e., 120 families of children and youth with craniofacial microsomia (CFM); 140 families of children and youth with other types of childhood-onset disabilities]. Data were collected through the Participation and Environment Measure—Children and Youth, the Pediatric Quality of Life Inventory, and the Child Behavior Checklist and analyzed using structural equation modeling. For the qualitative phase, we conducted semi-structured interviews with eight caregivers of children and youth with disabilities and those at risk (i.e., three caregivers of children and youth with CFM; five caregivers of children and youth with other childhood-onset disabilities). Interviews were transcribed verbatim and inductively content-analyzed.ResultsOur model reached acceptable to close model fit [CFI = 0.952; RMSEA = 0.068 (90% CI = 0.054–0.082); SRMR = 0.055; TLI = 0.936], revealing no significant effect of the number of participation-focused caregiver strategies on the relationships between participation-related constructs (e.g., activity competence, environment/context) and community participation in terms of attendance and involvement. The qualitative findings revealed three main categories for how caregivers explained these quantitative results: (1) caregiver workload and supports needed for implementing strategies; (2) caregivers careful strategy quality appraisal; and (3) community setting characteristics hindering successful strategy implementation.DiscussionThe findings suggest that the insignificant effect of the number of caregiver strategies may be explained by the intensified need for caregiver effort and support to develop and implement quality strategies that are responsive to community setting characteristics.
Identification of claudin-2 as a promising biomarker for early diagnosis of pre-diabetes
Authors: Songtao Yang , Fangyu Li , Jie Cao , Li Yuan 
Published: February 2024

Introduction: Pre-diabetes, a high-risk metabolic state, is situated between normal glucose homeostasis and diabetes. Early identification of pre-diabetes offers opportunities for intervention and diabetes reversal, highlighting the crucial need to investigate reliable biomarkers for this condition.Methods: We conducted an in-depth bioinformatics analysis of clinical samples from non-diabetic (ND), impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM) categories within the GSE164416 dataset. Thereafter the HFD and STZ treated mice were used for validation.Results: This analysis identified several codifferentially expressed genes (Co-DEGs) for IGT and T2DM, including CFB, TSHR, VNN2, APOC1, CLDN2, SLPI, LCN2, CXCL17, FAIM2, and REG3A. Validation of these genes and the determination of ROC curves were performed using the GSE76895 dataset. Thereafter, CLDN2 was selected for further verification. Gene expression analysis and immunofluorescence analysis revealed a significant upregulation of CLDN2 expression in the pancreas islets of mice in the high-fat diet and T2DM groups compared to the control group. Similarly, serum level of CLDN2 in patients with IGT and T2DM were significantly higher than those in the healthy group.Discussion: These results suggest that CLDN2 can serve as a novel biomarker for pre-diabetes, providing a new direction for future research in the prevention of type 2 diabetes.
Bi-directional hyperspectral reconstruction of cherry tomato: diagnosis of internal tissues maturation stage and composition
Authors: Tosin Renan , Cunha Mario , Monteiro-Silva Filipe , Santos Filipe , Barroso Teresa , Martins Rui 
Published: February 2024

IntroductionPrecision monitoring maturity in climacteric fruits like tomato is crucial for minimising losses within the food supply chain and enhancing pre- and post-harvest production and utilisation.ObjectivesThis paper introduces an approach to analyse the precision maturation of tomato using hyperspectral tomography-like.MethodsA novel bi-directional spectral reconstruction method is presented, leveraging visible to near-infrared (Vis-NIR) information gathered from tomato spectra and their internal tissues (skin, pulp, and seeds). The study, encompassing 118 tomatoes at various maturation stages, employs a multi-block hierarchical principal component analysis combined with partial least squares for bi-directional reconstruction. The approach involves predicting internal tissue spectra by decomposing the overall tomato spectral information, creating a superset with eight latent variables for each tissue. The reverse process also utilises eight latent variables for reconstructing skin, pulp, and seed spectral data.ResultsThe reconstruction of the tomato spectra presents a mean absolute percentage error of 30.44 % and 5.37 %, 5.25 % and 6.42 % and Pearson’s correlation coefficient of 0.85, 0.98, 0.99 and 0.99 for the skin, pulp and seed, respectively. Quality parameters, including soluble solid content (%), chlorophyll (a.u.), lycopene (a.u.), and puncture force (N), were assessed and modelled with PLS with the original and reconstructed datasets, presenting a range of R2 higher than 0.84 in the reconstructed dataset. An empirical demonstration of the tomato maturation in the internal tissues revealed the dynamic of the chlorophyll and lycopene in the different tissues during the maturation process.ConclusionThe proposed approach for inner tomato tissue spectral inference is highly reliable, provides early indications and is easy to operate. This study highlights the potential of Vis-NIR devices in precision fruit maturation assessment, surpassing conventional labour-intensive techniques in cost-effectiveness and efficiency. The implications of this advancement extend to various agronomic and food chain applications, promising substantial improvements in monitoring and enhancing fruit quality.