bluuebunny/crossref_metadata_2025_split huggingface dataset:
The relationship between high-sensitivity C-reactive protein and gallstones: a cross-sectional analysis
Authors: Jiang Zhimeng , Jiang Huixin , Zhu Xingyu , Zhao Donglin , Su Feifei 
Published: November 2024

Background and objectiveHigh-sensitivity C-reactive protein (hs-CRP), a classical indicator of inflammation, holds significant clinical value in various diseases. The relationship between hs-CRP and gallstones, however, remains poorly studied at present. The relationship between hs-CRP and gallstones will be investigated in this study.MethodsData from the 2017–2020 National Health and Nutrition Examination Survey (NHANES) were analyzed, focusing on participants aged 20 years and older who provided complete hs-CRP and gallstone information. Due to the skewed distribution of hs-CRP, the data were log-transformed [Log (hs-CRP)] to achieve normalization. Logistic regression analysis, subgroup analysis, and smoothed fitted curves were applied to determine the relationship between Log (hs-CRP) and the presence of gallstones.ResultsThe study included 4,484 participants with an average Log (hs-CRP) of 1.18 ± 0.74. The prevalence of gallstones was 11.15%, increasing with higher Log (hs-CRP) levels (quartile 1: 8.31%; quartile 2: 8.76%; quartile 3: 11.98%; quartile 4: 16.36%; p &lt; 0.0001). Adjusting for all covariates in Model 3, each 10-fold increase in hs-CRP [corresponding to a one-unit increase in log10 (hs-CRP)] corresponded to a 29% increased odds of gallstones prevalence [1.29 (1.12–1.49)]. The smoothed fitted curve showed a positive linear relationship between Log (hs-CRP) and gallstones prevalence. The results of subgroup analyses exhibited a more pronounced positive correlation in the 20–40 age group [1.70 (1.33, 2.16)], compared to those aged 40–60 years [1.22 (1.01, 1.48)], and 60–80 years [1.14 (0.98, 1.34)].ConclusionHigher Log (hs-CRP) levels are linked to a greater prevalence of gallstones. We still need to carry out further large prospective research to explore the causal relationship of this association.
Gluing osteochondral fragments: development of a novel strategy for dual adhesive application in a preclinical model
Authors: Bojan Alicja J. , Karami Peyman , Procter Philip , Pioletti Dominique P. 
Published: November 2024

This study proposes a novel dual adhesive approach for fixing osteochondral fractures, aiming to address the limitations of current fixation methods by incorporating both a bone adhesive (phosphoserine modified calcium phosphate cement PM-CPC) and a cartilage adhesive (methacrylated phosphoserine-containing gelatin MePGa hydrogel). The feasibility and efficacy of this approach were investigated using an ex vivo bovine knee model. Results indicate successful gluing of osteochondral cylinders with both adhesives, with no significant difference in adhesion strength between the groups (adhesion strength mean of 1211.6 kPa, SD 602.4 kPa, and mean of 1299.6 kPa, SD 850.9 kPa for groups 1 and 2 respectively). Importantly, the inclusion of the hydrogel component in the dual adhesive system aims to enhance cartilage repair potential, complementing the mechanical support provided by the bone adhesive. Each adhesive offers distinctive benefits: PM-CPC for mechanical support and bone repair, and MePGa hydrogel for cartilage repair. The study demonstrates the potential of the dual adhesive strategy for osteochondral repair, though further refinement and in vivo validation are needed.
Molecular detection and sequencing of beet necrotic yellow vein virus and beet cryptic virus 2 in sugar beet from Kazakhstan
Authors: Pozharskiy Alexandr , Mendybayeva Aruzhan , Moisseyev Ruslan , Khusnitdinova Marina , Nizamdinova Gulnaz , Gritsenko Dilyara 
Published: November 2024

IntroductionBeet necrotic yellow vein virus (BNYVV) is a common viral pathogen that causes considerable economic loss globally. In the present study, a commercial realtime PCR test system and custom loop mediated amplification primers were used to detect the virus in asymptomatic sugar beet samples.MethodsA total of 107 of 124 samples tested positive for the presence of the A type BNYVV coat protein gene. Near complete sequences of RNA-3 and RNA-4 were obtained using reverse transcription, followed by nanopore sequencing of 14 samples.Results and discussionA comparison with available sequences, including previously published isolates Kas2 and Kas3 from Kazakhstan, identified RNA-3 as similar to such of the P-type isolates Puthiviers and Kas3. RNA-5 was not detected using real-time PCR or cDNA amplification. Unique variable sites were identified in the p25 protein sequence translated from RNA-3. Another virus, beet cryptic virus 2 (BCV2), was identified and sequenced in samples infected with BNYVV. With 85.28% genome coverage, the identified BCV2 samples were very similar to the previously reported isolates from Hungary and Germany
Causal relationship between immune cells and Guillain-Barré syndrome: a Mendelian randomization study
Authors: Liu Huaiquan , Shao Shuoshuo , Chen Bo , Yang Shili , Zhang Xinyan 
Published: November 2024

ObjectiveThe aim of this study was to investigate the causal effect of immune cell phenotype on GBS using two-sample Mendelian randomization (MR) approach.MethodsThis study used MR to investigate the causal relationship between 731 immune cell phenotypes and GBS. We used Inverse variance weighted, Weighted median, MR Egger, Simple mode, Weighted mode for MR analysis. We also used the Cochran Q test, MR-Egger intercept test, IVW regression and MR-PRESSO, leave-one-out analysis to assess the presence of horizontal pleiotropy, heterogeneity and stability, respectively.ResultsOur study revealed a causal relationship between 33 immune cell phenotypes and GBS. Twenty immunophenotypes were observed to be associated with GBS as risk factors. For example, CD20 on IgD+ CD38dim in the B cell group (OR = 1.313, 95%CI:1.042–1.654, p = 0.021), CD3 on CD4 Treg in Treg cell group (OR = 1.395, 95%CI:1.069–1.819, p = 0.014), CD3 on TD CD8br in Maturation stages of T cell group (OR = 1.486, 95%CI:1.025–2.154, p = 0.037), CD16 on CD14+ CD16+ monocyte in Monocyte group (OR = 1.285, 95%CI:1.018–1.621, p = 0.035), CD33dim HLA DR+ CD11b + %CD33dim HLA DR+ in Myeloid cell group (OR = 1.262, 95%CI:1.020–1.561, p = 0.032), HLA DR+ NK AC in TBNK cell group (OR = 1.568, 95%CI:1.100–2.237, p = 0.013). Thirteen immune phenotypes are associated with GBS as protective factors. For example, CD19 on PB/PC in the B cell group (OR = 0.577, 95%CI:0.370–0.902, p = 0.016), CD4 Treg AC in Treg cell group (OR = 0.727, 95%CI:0.538–0.983, p = 0.038), CD11c + monocyte %monocyte in cDC group (OR = 0.704, 95%CI:0.514–0.966, p = 0.030), CX3CR1 on CD14+ CD16− monocyte in Monocyte group (OR = 0.717, 95%CI:0.548–0.939, p = 0.016), Mo MDSC AC in Myeloid cell group (OR = 0.763, 95%CI:0.619–0.939, p = 0.011), CD45 on granulocyte in TBNK group (OR = 0.621, 95%CI:0.391–0.984, p = 0.042).ConclusionThe findings suggest that certain specific immune cell phenotypes, particularly B cell and Treg cell subpopulations, are causally associated with GBS, providing potential targets for the clinical treatment of GBS.
Quantitative assessment of neurodevelopmental maturation: a comprehensive systematic literature review of artificial intelligence-based brain age prediction in pediatric populations
Authors: Dragendorf Eric , Bültmann Eva , Wolff Dominik 
Published: November 2024

IntroductionOver the past few decades, numerous researchers have explored the application of machine learning for assessing children’s neurological development. Developmental changes in the brain could be utilized to gauge the alignment of its maturation status with the child’s chronological age. AI is trained to analyze changes in different modalities and estimate the brain age of subjects. Disparities between the predicted and chronological age can be viewed as a biomarker for a pathological condition. This literature review aims to illuminate research studies that have employed AI to predict children’s brain age.MethodsThe inclusion criteria for this study were predicting brain age via AI in healthy children up to 12 years. The search term was centered around the keywords “pediatric,” “artificial intelligence,” and “brain age” and was utilized in PubMed and IEEEXplore. The selected literature was then examined for information on data acquisition methods, the age range of the study population, pre-processing, methods and AI techniques utilized, the quality of the respective techniques, model explanation, and clinical applications.ResultsFifty one publications from 2012 to 2024 were included in the analysis. The primary modality of data acquisition was MRI, followed by EEG. Structural and functional MRI-based studies commonly used publicly available datasets, while EEG-based studies typically relied on self-recruitment. Many studies utilized pre-processing pipelines provided by toolkit suites, particularly in MRI-based research. The most frequently used model type was kernel-based learning algorithms, followed by convolutional neural networks. Overall, prediction accuracy may improve when multiple acquisition modalities are used, but comparing studies is challenging. In EEG, the prediction error decreases as the number of electrodes increases. Approximately one-third of the studies used explainable artificial intelligence methods to explain the model and chosen parameters. However, there is a significant clinical translation gap as no study has tested their model in a clinical routine setting.DiscussionFurther research should test on external datasets and include low-quality routine images for MRI. T2-weighted MRI was underrepresented. Furthermore, different kernel types should be compared on the same dataset. Implementing modern model architectures, such as convolutional neural networks, should be the next step in EEG-based research studies.
Association of plant and animal protein intake with sleep quality and quality of life in hemodialysis patients: a multicenter cross-sectional study
Authors: Jafari Maskouni Saber , Bavi Behbahani Hossein , Alipour Meysam , Zare Javid Ahmad , Fayazfar Fatemeh , Tofighzadeh Pardis , Shokri Shiva , Keramatzadeh Sara , Soltaniyan Dehkordi Haleh , Sharifat Morteza , Babajafari Esfandabad Siavash , Shayanpour Shokouh 
Published: November 2024

BackgroundThe current study aimed to evaluate the association between the intake of plant-based protein, animal-based protein, total protein, and the ratio of plant to animal protein with sleep quality and quality of life in patients undergoing hemodialysis.MethodsIn this cross-sectional study, 479 adult patients undergoing dialysis for a minimum of 3 months were included. The dietary intake was calculated using information from a validated 168-item semi-quantitative food frequency questionnaire. Quality of life (QOL) was assessed using the Kidney Disease Quality of Life Short Form (KDQOL-SF 1.3). and the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality.ResultsIn this study, the mean age of the participants was 58.18 years (± 14.25 years), with the majority being male (58.2%). After adjusting for potential confounders, significant positive associations were observed between total protein intake (β = 0.12, p = 0.03) and quality of life (QOL). Conversely, there were significant negative associations between the ratio of plant to animal protein intake (β = −0.94, p &lt; 0.01) and QOL. Furthermore, significant negative associations were found between total protein intake (β = −0.02, p &lt; 0.05) and animal protein intake (β = −0.19, p &lt; 0.05) with poor sleep quality. Additionally, there were significant positive associations between the ratio of plant to animal protein intake (β = 0.188, p &lt; 0.05) and poor sleep quality.ConclusionIncreased consumption of animal protein is associated with improved sleep quality and Quality of Life (QOL) in patients undergoing hemodialysis (HD). Further research, especially prospective studies, is required to confirm these associations.
The effect of vitamin D supplementation on antibiotic use: a meta-analysis based on randomized controlled trials
Authors: Wang Mian , Wu Yixuan , Xiang Zhiyi , Zhang Yueming , Huang Tingyi , Chen Bangsheng 
Published: November 2024

ObjectiveThis meta-analysis explores the impact of vitamin D supplementation on antibiotic utilization.MethodsWe systematically searched for relevant randomized controlled trials (RCTs) in PubMed, Web of Science, EMBASE, and Science Direct from inception to April 2024. These trials compared antibiotic use rates between groups receiving vitamin D supplements and placebo.ResultsWe included seven RCTs involving 35,160 participants. There was no significant difference in antibiotic use between the two groups in the general population (Odds Ratio [OR] = 0.98, p = 0.232), including elderly participants (OR = 0.98, p = 0.295). However, antibiotic use was lower in the intervention group compared to the placebo group among participants under 70 years of age (OR = 0.95, p = 0.015), those with relative vitamin D deficiency [25(OH)D &lt; 75 nmol/L, OR = 0.95, p = 0.024; 25(OH)D &lt; 50 nmol/L, OR = 0.96, p = 0.026], and those with respiratory tract infections (RTIs) (OR = 0.51, 95% CI: 0.24–1.08, p = 0.080), although these differences were not statistically significant for RTIs.ConclusionVitamin D supplementation does not affect antibiotic use in the general population. However, it does reduce antibiotic utilization in individuals with RTIs, relative vitamin D deficiency, or aged below 70 years.Systematic review registrationThis meta-analysis adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and is registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number CRD42024543246.
Hotspots and future trends of dermatofibrosarcoma protuberans
Authors: Meng Zhen , Zhang Rui , Sun Zhihong , Fu Cong , Li Zhiyu , Wang Luying , Huo Ran , Xue Feng 
Published: November 2024

ObjectiveDermatofibrosarcoma protuberans (DFSP) is a moderately malignant soft tissue sarcoma with localized infiltrative growth. The extensive surgical scope and high recurrence rate of DFSP brings dysfunctional, aesthetic, psychological and economic problems to patients. The aim of this study is to explore the global publication characteristics, research hotspots and future trends of DFSP over the past 32 years via an intuitive visualized way.MethodsThe Web of Science Core Collection (WoSCC) database was searched for papers related to DFSP published from 1990 to 2022. Then bibliometric analysis of these publications was performed, including collaborative networks, co-citation analysis of journals and references, and cluster analysis of keywords.ResultsA total of 1588 papers were retrieved between 1990-2022. The United States was the most prolific country, followed by China. The article Imatinib Mesylate in Advanced Dermatofibrosarcoma Protuberans: Pooled Analysis of Two Phase II Clinical Trials, received most citations. Research hotspots and future trends are mainly focused on disease diagnosis, COL1A1-PDGFB fusion gene, drug and surgical treatment, fibrosarcomatous transformation, and immunotherapy.ConclusionThe research on DFSP faces several clinical challenges. This study provides novel insights into future research directions and scientific decisions for DFSP.
Adrenal indeterminate nodules: CT-based radiomics analysis of different machine learning models for predicting adrenal metastases in lung cancer patients
Authors: Cao Lixiu , Yang Haoxuan , Wu Huijing , Zhong Hongbo , Cai Haifeng , Yu Yixing , Zhu Lei , Liu Yongliang , Li Jingwu 
Published: November 2024

ObjectiveThere is a paucity of research using different machine learning algorithms for distinguishing between adrenal metastases and benign tumors in lung cancer patients with adrenal indeterminate nodules based on plain and biphasic-enhanced CT radiomics.Materials and MethodsThis study retrospectively enrolled 292 lung cancer patients with adrenal indeterminate nodules (training dataset, 205 (benign, 96; metastases, 109); testing dataset, 87 (benign, 42; metastases, 45)). Radiomics features were extracted from the plain, arterial, and portal CT images, respectively. The independent risk radiomics features selected by least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression (LR) were used to construct the single-phase and combined-phase radiomics models, respectively, by support vector machine (SVM), decision tree (DT), random forest (RF), and LR. The independent clinical-pathological and radiological risk factors for predicting adrenal metastases selected by using univariate and multivariate LR were used to develop the traditional model. The optimal model was selected by ROC curve, and the models’ clinical values were estimated by decision curve analysis (DCA).ResultsIn the testing dataset, all SVM radiomics models showed the best robustness and efficiency, and then RF, LR, and DT models. The combined radiomics model had the best ability in predicting adrenal metastases (AUC=0.938), and then the plain (AUC=0.935), arterial (AUC=0.870), and portal radiomics model (AUC=0.851). Besides, compared to clinical-pathological-radiological model (AUC=0.870), the discriminatory capability of the plain and combined radiomics model were further improved. All radiomics models had good calibration curves and DCA showed the plain and combined radiomics models had more optimal clinical efficacy compared to other models, with the combined radiomics model having the largest net benefit.ConclusionsThe combined SVM radiomics model can non-invasively and efficiently predict adrenal metastatic nodules in lung cancer patients. In addition, the plain radiomics model with high predictive performance provides a convenient and accurate new method for patients with contraindications in enhanced CT.
The value of NGS-based multi-gene testing for differentiation of benign from malignant and risk stratification of thyroid nodules
Authors: Fei Mingjian , Ding Dongdong , Ouyang Xuanyi , Shen Wenyan , Zhang Fenglan , Zhang Bo , Qin Lan 
Published: November 2024

BackgroundFine-needle aspiration (FNA) biopsy is typically used in conjunction with cytopathologic evaluation to differentiate between benign and malignant thyroid nodules. Even so, the cytology results for 20-30% of thyroid nodules are indeterminate. This study sought to evaluate the usefulness of next-generation sequencing (NGS)-based multi-gene panel testing for risk stratification and the differentiation of benign from malignant thyroid nodules.MethodsThyroid nodule samples were obtained from a cohort of 359 patients who underwent FNA. An NGS-based multi-gene panel testing was conducted for these samples, in which single-nucleotide variants (SNVs) and small insertion/deletions (InDels) can be detected in 11 genes and fusion events can be identified in 5 genes. Surgical resection was conducted for 113 patients (113/359), and then histopathology results were obtained.ResultsIn comparison to cytology alone, the diagnostic sensitivity of NGS combination cytology increased from 0.7245 (95% CI: 0.6289-0.8032) to 0.898 (95% CI: 0.8223-0.9437); the associated AUC was 0.8303 (vs. Cytology AUC: 0.7622, P &lt; 0.001). BRAFV600E was identified in 136 patients, of whom 79 underwent surgery and were diagnosed with papillary thyroid carcinoma (PTC) pathologically. TERT promoter mutations or BRAF/RAS co-mutations with other genes were identified in 5 patients, while 4 patients were diagnosed with malignant thyroid cancer using the pathological method. RAS mutations were identified in 27 patients, while 10 patients underwent surgery, which showed that 3 patients were classified as PTC and 7 cases were benign. In addition, 4 RET fusions, 1 RET activation mutation, and 3 TP53 inactivation mutations were identified in the remaining 8 patients who have not undergone surgery. Negative genetic test results or variants with uncertain significance were identified in 183 patients. Among these patients, 12 malignant thyroid tumors, including 11 PTC and 1 MTC, were diagnosed in 20 patients who received surgery.ConclusionThyroid nodules coupled with BRAFV600E, TERT promoter variants, BRAF/RAS co-mutations with other genes, RET fusions, and RET activating mutations were classified as high-risk. Nodules with RAS mutations (NRAS, KRAS, HRAS) and TP53 inactivating mutations were considered to be in the intermediate-risk group, while those with non-pathogenic mutations (negative and variants of uncertain significance) were placed in the low-risk group. When combined with cytopathology, NGS increases the sensitivity of diagnosing benign and malignant thyroid nodules, and the reference is useful for patient risk stratification.
Development of ultrasound-based clinical, radiomics and deep learning fusion models for the diagnosis of benign and malignant soft tissue tumors
Authors: Dai Xinpeng , Lu Haiyong , Wang Xinying , Zhao Bingxin , Liu Zongjie , Sun Tao , Gao Feng , Xie Peng , Yu Hong , Sui Xin 
Published: November 2024

ObjectivesThe aim of this study is to develop an ultrasound-based fusion model of clinical, radiomics and deep learning (CRDL) for accurate diagnosis of benign and malignant soft tissue tumors (STTs)MethodsIn this retrospective study, ultrasound images and clinical data of patients with STTs from two hospitals were collected between January 2021 and December 2023. Radiomics features and deep learning features were extracted from the ultrasound images, and the optimal features were selected to construct fusion models using support vector machines. The predictive performance of the model was evaluated based on three aspects: discrimination, calibration and clinical usefulness. The DeLong test was used to compare whether there was a significant difference in AUC between the models. Finally, two radiologists who were unaware of the clinical information performed an independent diagnosis and a model-assisted diagnosis of the tumor to compare the performance of the two diagnoses.ResultsA training cohort of 516 patients from Hospital-1 and an external validation cohort of 78 patients from Hospital-2 were included in the study. The Pre-FM CRDL showed the best performance in predicting STTs, with area under the curve (AUC) of 0.911 (95%CI: 0.894-0.928) and 0.948 (95%CI: 0.906-0.990) for training cohort and external validation cohort, respectively. The DeLong test showed that the Pre-FM CRDL significantly outperformed the clinical models (P&lt; 0.05). In addition, the Pre-FM CRDL can improve the diagnostic accuracy of radiologists.ConclusionThis study demonstrates the high clinical applicability of the fusion model in the differential diagnosis of STTs.