bluuebunny/crossref_metadata_2025_split huggingface dataset:
The correlation between intracranial atherosclerosis and white matter hyperintensities in cerebral small vessel disease: a high-resolution magnetic resonance imaging study
Authors: Zhang Gui-Song , Bu Wei , Meng Ling-Hui , Li Wen-Jun , Dong Yu-Juan , Cao Xiao-Yun , Gao Qi , Zhang Xuan-Ye , Ren Hui-Ling 
Published: January 2025

ObjectiveRecent studies have indicated a close relationship between intracranial arterial stenosis and white matter hyperintensities (WMHs), but few have reported on the correlation between the characteristics of intracranial arterial wall plaques and WMHs. The aim of this study was to comprehensively assess the correlation between intracranial atherosclerosis plaques and WMHs using 3.0T high-resolution magnetic resonance imaging (HR-MRI).Patients and methodsNinety-two ischemic stroke patients with middle cerebral artery (MCA) stenosis &lt;50% on cranial magnetic resonance angiography (MRA) underwent conventional MRI and HR-MRI examinations. T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images were processed using 2D VBNeT automatic segmentation technology to segment WMH volume. HR-MRI images were analyzed using ImageJ software to evaluate the luminal area, outer wall area, plaque distribution, luminal stenosis rate, remodeling patterns, and other plaque parameters at the stenosis site and reference points of the MCA M1 segment. The correlation between the presence of plaques, plaque distribution, luminal stenosis rate, T1 hyperintensity, remodeling patterns, remodeling ratio (RR), eccentric plaques, and plaque burden with the volume of cerebral WMHs was analyzed.ResultsCompared with the no-plaque group, the plaque group had significantly higher age, male ratio, total WMH volume, periventricular WMH (PVWMH) volume, deep WMH (DWMH) volume, and juxtacortical WMH (JCWMH) volume (all p &lt; 0.05). The Kruskal-Wallis H test showed that patients with plaques on the superior and dorsal sides of the MCA M1 segment had higher levels of total WMH volume, PVWMH volume, DWMH volume, and JCWMH volume than patients with plaques on the inferior and ventral sides (all p &lt; 0.05). Age, diabetes, previous stroke events, plaque distribution, positive remodeling, eccentric plaques, and RR were positively correlated with total WMH volume, PVWMH volume, and JCWMH volume (all p &lt; 0.05). The presence of plaques, plaque distribution, and positive remodeling were independent risk factors for total WMH volume (all p &lt; 0.05).ConclusionThe presence of intracranial atherosclerotic plaques, plaque distribution, and positive remodeling are closely associated with increased cerebral WMHs burden in patients with ischemic stroke, which further supports the relationship between large artery atherosclerosis and CSVD.
Effects of physiotherapy on degenerative cerebellar ataxia: a systematic review and meta-analysis
Authors: Matsugi Akiyoshi , Bando Kyota , Kondo Yuki , Kikuchi Yutaka , Miyata Kazuhiro , Hiramatsu Yuichi , Yamanaka Yuya , Tanaka Hiroaki , Okuda Yuta , Haruyama Koshiro , Yamasaki Yuichiro 
Published: January 2025

BackgroundEvidence of the effectiveness of physiotherapy, including muscle strength training, coordination training, aerobic exercise, cycling regimen, balance training, gait training, and activity of daily living training, in patients with degenerative cerebellar ataxia (DCA) was insufficient for clinical decision making. We aimed to explore clinical outcomes and examine the parameters associated with physical impairment and activity in people with DCA based on preregistration (PROSPERO: CRD42024493883).MethodsThe PubMed, Cochrane Library, CHINAL, and PEDro databases were searched for relevant randomized controlled trials (RCTs). Data extraction, quality assessment, and heterogeneity analyses were conducted. The Grading of Recommendations Assessment, Development, and Evaluation framework (GRADE) was used to assess the quality of evidence, and a meta-analysis was performed.ResultsEighteen RCTs, which included 398 participants, showed a serious risk of bias (RoB) and low certainty of evidence for this primary outcome. For meta-analysis, 315 patients assessed based on the Scale for Assessment and Rating of Ataxia (SARA) were included. Overall, physiotherapy significantly reduced SARA scores (MD = −1.41, [95% CI: −2.16, −0.66]); the subgroup analysis showed that the following interventions exerted significant effects: multi-aspect training program (5 studies, MD = −1.59, [95% CI: −5.15, −0.03]), balance training (3 studies, MD = −1.58, [95% CI: −2.55, −0.62]), and aerobic training (3 studies, MD = −1.65, [95% CI: −2.53, −0.77]). By contrast, vibration (2 studies, MD = −0.56, [95% CI: −2.05, 0.93]) and dual-task training (1 study, MD = 0.24, [95% CI: −6.4, 6.88]) exhibited no significant effects.ConclusionPhysical therapy, especially multi-aspect physical therapy such as muscle strengthening, coordination training, gait training, and ADL training, may reduce DCA symptoms. Further, balance and aerobic training can be added to the program. However, the estimated effect size may change in future studies because of the serious RoB, very low certainty of evidence, and high heterogeneity with SARA as the primary outcome. High-quality RCTs are required to establish evidence for the effectiveness of physical therapy in patients with DCA.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=493883, identifier: CRD42024493883.
An ictogenic marker in the mesial temporal epilepsy and its temporal evolutionary features
Authors: Lu Hongjuan , Yang Haoran , Zhang Wei , Liu Xingzhou , Sun Wei 
Published: January 2025

ObjectiveTo observe and measure the morphological and temporal evolutionary features of the hypersynchronous (HYP) pattern in the mesial temporal seizure.MethodsThe HYP patterns during preictal and interictal states of 16 mesial temporal epileptic patients were analyzed. The wave components of the HYP transients were firstly observed and measured. The dynamic deformations and parameter changes of the components were further analyzed along the preictal-ictal axis. The difference of emergence rate of HYP transients and typical interictal spike during interictal periods was also compared.ResultsThe HYP transients were invariably composed of slow-wave proper, sharp wave and post-slow component among studied patients for all the 93 seizures. During preictal epoch, all of the seizures incorporated present evolutionary manner of type 1 characterized by smooth modification of HYP transients in morphology, including gradual shortening of the inter-transient interval, increase of amplitude and time duration of slow-wave proper and sharp wave, amplitude decrease of the post-slow component, as well as amplitude increases of ripple and fast ripple, and 2/3 seizures showed some more sophisticated transitional manners (type 2) following type 1, including reduction in amplitude with decrease of inter-transient intervals, superimposed or followed by the emergent low amplitude rhythmic activities, or both of them. The HYP transients and typical interictal spikes were found to mutually “repelling” each other in interictal period.ConclusionThe HYP transients showed a combinational feature and temporal evolution manners during preictal state. The emergence of HYP transients in cluster reflects the transitional trend from interictal to ictal state.SignificanceHYP should be viewed as an index of ictogenesis in the mesial temporal seizure.
A novel muscle network approach for objective assessment and profiling of bulbar involvement in ALS
Authors: Rong Panying , Heidrick Lindsey , Pattee Gary 
Published: January 2025

IntroductionAs a hallmark feature of amyotrophic lateral sclerosis (ALS), bulbar involvement significantly impacts psychosocial, emotional, and physical health. A validated objective marker is however lacking to characterize and phenotype bulbar involvement, positing a major barrier to early detection, progress monitoring, and tailored care. This study aimed to bridge this gap by constructing a multiplex functional mandibular muscle network to provide a novel objective measurement tool of bulbar involvement.MethodsA noninvasive electrophysiological technique—surface electromyography—was combined with graph network analysis to extract 48 features measuring the regulatory mechanisms, connectivity, integration, segregation, assortativity, and lateralization of the functional muscle network during a speech task. These features were clustered into 10 interpretable latent factors. To evaluate the utility of the muscle network as a bulbar measurement tool, a heterogenous ALS cohort, consisting of eight individuals with overt clinical bulbar symptoms and seven without, along with 10 neurologically healthy controls, was employed to train and validate statistical and machine learning algorithms to assess the disease effects on the network features and the relation of the network performance to the current clinical diagnostic standard and behavioral patterns of bulbar involvement.ResultsSignificant disease effects were found on most network features. The most robust effects were manifested by reduced and more variable myoelectric activities, and reduced functional connectivity and integration of the muscle network. The 10 latent factors (1) demonstrated acceptably high efficacy for detecting bulbar neuromuscular changes across all clinically confirmed symptomatic cases and clinically silent prodromal cases (area under the curve = 0.89–0.91; F1 score = 0.85–0.87; precision = 0.84–0.86; recall = 0.87–0.88); and (2) selectively correlated with clinically meaningful behavioral patterns (conditional R2 = 0.45–0.81).ConclusionThe functional muscle network shows promise for an objective quantifiable measurement tool to improve early detection and profiling of bulbar involvement across the prodromal and symptomatic stages. This tool has various strengths, including the use of a clinically readily available noninvasive instrument, fully automated data processing and analytics, and generation of interpretable objective outcome measures (i.e., latent factors), together rendering it highly scalable in routine clinical practice for assessing and monitoring of bulbar involvement.
Noise reduction in brain magnetic resonance imaging using adaptive wavelet thresholding based on linear prediction factor
Authors: Pereira Neto Ananias , Barros Fabrício J. B. 
Published: January 2025

IntroductionWavelet thresholding techniques are crucial in mitigating noise in data communication and storage systems. In image processing, particularly in medical imaging like MRI, noise reduction is vital for improving visual quality and accurate analysis. While existing methods offer noise reduction, they often suffer from limitations like edge and texture loss, poor smoothness, and the need for manual parameter tuning.MethodsThis study introduces a novel adaptive wavelet thresholding technique for noise reduction in brain MRI. The proposed method utilizes a linear prediction factor to adjust the threshold adaptively. This factor leverages temporal information and features from both the original and noisy images to determine a weighted threshold. This dynamic thresholding approach aims to selectively reduce or eliminate noise coefficients while preserving essential image features.ResultsThe proposed method was rigorously evaluated against existing state-of-the-art noise reduction techniques. Experimental results demonstrate significant improvements in key performance metrics, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM).DiscussionThe proposed adaptive thresholding technique effectively addresses the limitations of existing methods by providing a more efficient and accurate noise reduction approach. By dynamically adjusting the threshold based on image-specific characteristics, this method effectively preserves image details while effectively suppressing noise. These findings highlight the potential of the proposed method for enhancing the quality and interpretability of brain MRI images.
Altered static and dynamic spontaneous brain activity in patients with dysthyroid optic neuropathy: a resting-state fMRI study
Authors: Lu Jinling , Hu Hao , Zhou Jiang , Jiang Wenhao , Pu Xiongying , Chen Huanhuan , Xu Xiaoquan , Wu Feiyun 
Published: January 2025

PurposeTo investigate static and dynamic brain functional alterations in dysthyroid optic neuropathy (DON) using resting-state functional MRI (rs-fMRI) with the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo).Materials and methodsFifty-seven thyroid-associated ophthalmopathy (TAO) patients (23 DON and 34 non-DON) and 27 healthy controls (HCs) underwent rs-fMRI scans. Static and dynamic ALFF (sALFF and dALFF) and ReHo (sReHo and dReHo) values were compared between groups. The support-vector machine (SVM) classification method was used to examine the diagnostic performance of the identified models.ResultsCompared to non-DON patients, DON patients showed decreased sALFF in the bilateral lingual gyrus (LING) and right cuneus (CUN), alongside increased sALFF in the bilateral medial part of the superior frontal gyrus, right dorsolateral part of the superior frontal gyrus (SFGdor), and right precentral gyrus. DON patients also exhibited decreased dALFF in the left LING and right CUN, together with increased dALFF in the right orbital part of the middle frontal gyrus and right SFGdor in comparison to non-DON patients. Meanwhile, DON patients had lower sReHo in the right LING, and higher sReHo and dReHo in the right supramarginal gyrus compared to non-DON patients. When detecting DON, the dALFF model showed optimal diagnostic performance (AUC 0.9987).ConclusionDysthyroid optic neuropathy patients exhibited both static and dynamic brain functional alterations in visual, cognitive, and emotion-related brain regions, deepening our current understanding of the underlying neural mechanisms of this disease. Rs-fMRI-based metrics, especially dALFF, may serve as relevant neuroimaging markers for diagnosing DON.
Association between lipid accumulation product and chronic obstructive pulmonary disease: a cross-sectional study based on U.S. adults
Authors: Hua Xingshi , Liu Ying , Xiao Xiaoyu 
Published: January 2025

BackgroundLipid Accumulation Product (LAP), which is derived from measurements of waist circumference and triglyceride (TG) levels, serves as a comprehensive indicator of lipid accumulation. Emerging research indicates that lipid accumulation dysfunction might significantly contribute to the pathogenesis of Chronic Obstructive Pulmonary Disease (COPD). Nevertheless, the investigation into the association between LAP and COPD risk is still insufficient, particularly in population-based research. This research intends to examine the possible correlation between LAP and the likelihood of developing COPD.MethodsThis study, designed as a cross-sectional analysis, made use of data gathered from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2017 to 2020, encompassing a total of 7,113 eligible participants. LAP, the exposure variable, was calculated using waist circumference and triglyceride concentration. COPD diagnosis was determined using participants’ self-reported information. To explore the association between LAP and COPD, multivariate logistic regression models were applied, and smoothing curve fitting was employed to examine any potential nonlinear patterns. Further analysis included stratified subgroup evaluations to assess how variables such as sex, smoking habits, and alcohol intake might impact the relationship between LAP and COPD.ResultsThe findings indicated a significant increase in COPD risk with each one-unit rise in ln LAP, as evidenced by an Odds Ratio (OR) of 1.16 [95% Confidence Interval (CI): 1.04–1.30, p &lt; 0.01]. Furthermore, a quartile-based analysis revealed that individuals in the highest ln LAP category had a considerably higher likelihood of developing COPD compared to those in the lowest category, with an OR of 1.35 (95% CI: 1.04–1.75, P for trend &lt;0.01). Furthermore, the smoothing curve fitting identified a nonlinear and positive association between ln LAP and COPD, suggesting a steeper increase in risk as ln LAP values rise. Subgroup analysis suggested that this association remained fairly consistent across various demographic groups.ConclusionThis study found a significant link between higher LAP levels and an elevated risk of COPD, with the association displaying a nonlinear pattern. As a marker of lipid accumulation abnormalities, LAP may serve as a valuable tool for assessing COPD risk and could inform strategies for early identification and targeted clinical management.
Salt use patterns and heavy metal urinary excretion
Authors: Zhang Shuai , Tang Hanhan , Zhou Minglian , Pan Linqing 
Published: January 2025

BackgroundSalt usage patterns have been associated with a risk of multiple diseases; however, their relationship with heavy metal exposure has not been extensively studied.MethodsThis study analyzed survey data from 11,574 NHANES participants. Weighted linear regression models were used to examine the relationship between the type of salt used by participants, the frequency of adding salt at the table, and the frequency of adding regular or seasoned salt to cooking or food preparation, and urinary concentrations of 10 heavy metals. Multiple sensitivity analyses were also performed.ResultsThe weighted regression analysis indicated that participants’ salt usage patterns were associated with an increased urinary excretion of certain heavy metals. Specifically, regarding the type of salt used, compared to regular salt, the use of salt substitutes was significantly positively correlated with urinary molybdenum (Mo) levels, while not using salt or substitutes at the table was significantly positively correlated with urinary levels of both Mo and arsenic (As). In terms of the frequency of adding regular salt at the table, frequent addition compared to rarely adding salt was significantly positively correlated with urinary levels of cadmium (Cd), and antimony (Sb), while showing a significant negative correlation with urinary Mo levels. Additionally, when examining the frequency of using regular salt during cooking or food preparation, those who occasionally or very often added regular salt had significantly higher urinary levels of barium (Ba), cesium (Cs), and thallium (Tl) compared to those who never added regular salt during cooking. These associations remained stable in sensitivity analyses.ConclusionOur analysis revealed that participants’ salt usage patterns are associated with increased excretion of certain heavy metals, suggesting possible increased exposures to these metals. While these findings are concerning, they require validation in other populations and should be confirmed through prospective studies designed based on this hypothesis.
A stacking ensemble system for identifying the presence of histological variants in bladder carcinoma: a multicenter study
Authors: Peng Canjie , He Quanhao , Lv Fajin , Jiang Qing , Chen Yong , Wei Zongjie , Xv Yingjie , Liao Fangtong , Xiao Mingzhao 
Published: January 2025

PurposeTo create a system to enable the identification of histological variants of bladder cancer in a simple, efficient, and noninvasive manner.Material and methodsIn this multicenter diagnostic study, we retrospectively collected basic information and CT images about the patients concerned from three hospitals. An interactive deep learning-based bladder cancer image segmentation framework was constructed using the Swin UNETR algorithm for further features extraction. Radiomic features and deep learning features were extracted for further stacking ensemble system construction. The segmentation model’ performance was assessed by using Dice Similarity (Dice) metrics, Intersection Over Union (IOU), Sensitivity (SEN) and Specificity (SPE). To evaluate the system’s performance, we used the Receiver Operating Characteristics (ROC) curve, the Accuracy Score (ACC) and Decision Curve Analysis (DCA).Results410 patients from one hospital were included in the training set, while 60 patients from two other hospitals were included in the test set. A total of 50 features comprising 46 radiomic features and 4 deep learning features were finally retained for further stacking ensemble model building. The interactive segmentation model and system exhibited excellent performance in both training (Dice = 0.78, IOU = 0.65, SEN = 0.83, SPE = 1.00, AUC = 0.940, ACC = 0.868) and testing datasets (Dice = 0.80, IOU = 0.67, SEN = 0.89, SPE = 1.00, AUC = 0.905, ACC = 0.900).ConclusionWe successfully constructed a stacking ensemble machine learning model for early, non-invasive identification of histological variants in bladder cancer which will help urologists make clinical decisions.
Intraoperative circulation predict prolonged length of stay after head and neck free flap reconstruction: a retrospective study based on machine learning
Authors: Liu Zhongqi , Wen Jinbei , Chen Yingzhen , Zhou Bin , Cao Minghui , Guo Mingyan 
Published: January 2025

BackgroundHead and neck free flap reconstruction presents challenges in managing intraoperative circulation, potentially leading to prolonged length of stay (PLOS). Limited research exists on the associations between intraoperative circulation and PLOS given the difficulty of manual quantification of intraoperative circulation time-series data. Therefore, this study aimed to quantify intraoperative circulation data and investigate its association with PLOS after free flap reconstruction utilizing machine learning algorithms.Methods804 patients who underwent head and neck free flap reconstruction between September 2019 and February 2021 were included. Machine learning tools (Fourier transform, et al.) were utilized to extract features to quantify intraoperative circulation data. To compare the accuracy of quantified intraoperative circulation and manual intraoperative circulation assessments in the PLOS prediction, predictive models based on these 2 assessment methods were developed and validated.ResultsIntraoperative circulation was quantified and a total of 114 features were extracted from intraoperative circulation data. Quantified intraoperative circulation models with a real-time predictive manner were constructed. A higher area under the receiver operating characteristic curve (AUROC) was observed in quantified intraoperative circulation data models (0.801 [95% CI, 0.733–0.869]) compared to manual intraoperative circulation assessment models (0.719 [95% CI, 0.641–0.797]) in PLOS prediction.ConclusionMachine learning algorithms facilitated quantification of intraoperative circulation data. The developed real-time quantified intraoperative circulation prediction models based on this quantification offer a potential strategy to optimize intraoperative circulation management and mitigate PLOS following head and neck free flap reconstruction.