bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal real world correlation study of blood pressure and novel features of cerebral magnetic resonance angiography by artificial intelligence analysis on elderly cognitive impairment
Authors: Sun Shasha , Liu Dongyue , Zhou Yanfeng , Yang Ge , Cui Long-Biao , Xu Xian , Guo Yuanhao , Sun Ting , Jiang Jiacheng , Li Na , Wang Yabin , Li Sulei , Wang Xinjiang , Fan Li , Cao Feng 
Published: February 2023

ObjectiveThis study aims to investigate novel clinical risk factors for cognitive impairment (CI) in elderly.MethodsA total of 3221 patients (259 patients with CI and 2,962 subjects without CI) were recruited into this nested case-control study who underwent cerebral magnetic resonance angiography (MRA) from 2007 to 2021. All of the clinical data with MRA imaging were recorded followed by standardization processing blindly. The maximum stenosis score of the posterior circulatory artery, including the basilar artery, and bilateral posterior cerebral artery (PCA), was calculated by the cerebral MRA automatic quantitative analysis method. Logistic regression (LR) analysis was used to evaluate the relationship between risk factors and CI. Four machine learning approaches, including LR, decision tree (DT), random forest (RF), and support vector machine (SVM), employing 5-fold cross-validation were used to establish CI predictive models.ResultsAfter matching with age and gender, 208 CI patients and 208 control subjects were finalized the follow-up (3.46 ± 3.19 years) with mean age at 84.47 ± 6.50 years old. Pulse pressure (PP) in first tertile (&lt;58 mmHg) (OR 0.588, 95% confidence interval (CI): 0.362–0.955) was associated with a decreased risk for CI, and ≥50% stenosis of the left PCA (OR 2.854, 95% CI: 1.387–5.872) was associated with an increased risk for CI after adjusting for body mass index, myocardial infarction, and stroke history. Based on the means of various blood pressure (BP) parameters, the performance of the LR, DT, RF and SVM models accurately predicted CI (AUC 0.740, 0.786, 0.762, and 0.753, respectively) after adding the stenosis score of posterior circulatory artery.ConclusionElderly with low pulse differential pressure may have lower risk for cognitive impairment. The hybrid model combined with the stenosis score of posterior circulatory artery, clinical indicators, and the means of various BP parameters can effectively predict the risk of CI in elderly individuals.
Integration of structural MRI and epigenetic analyses hint at linked cellular defects of the subventricular zone and insular cortex in autism: Findings from a case study
Authors: Takahashi Emi , Allan Nina , Peres Rafael , Ortug Alpen , van der Kouwe Andre J. W. , Valli Briana , Ethier Elizabeth , Levman Jacob , Baumer Nicole , Tsujimura Keita , Vargas-Maya Nauru Idalia , McCracken Trevor A. , Lee Rosa , Maunakea Alika K. 
Published: February 2023

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction, communication and repetitive, restrictive behaviors, features supported by cortical activity. Given the importance of the subventricular zone (SVZ) of the lateral ventrical to cortical development, we compared molecular, cellular, and structural differences in the SVZ and linked cortical regions in specimens of ASD cases and sex and age-matched unaffected brain.MethodsWe used magnetic resonance imaging (MRI) and diffusion tractography on ex vivo postmortem brain samples, which we further analyzed by Whole Genome Bisulfite Sequencing (WGBS), Flow Cytometry, and RT qPCR.ResultsThrough MRI, we observed decreased tractography pathways from the dorsal SVZ, increased pathways from the posterior ventral SVZ to the insular cortex, and variable cortical thickness within the insular cortex in ASD diagnosed case relative to unaffected controls. Long-range tractography pathways from and to the insula were also reduced in the ASD case. FACS-based cell sorting revealed an increased population of proliferating cells in the SVZ of ASD case relative to the unaffected control. Targeted qPCR assays of SVZ tissue demonstrated significantly reduced expression levels of genes involved in differentiation and migration of neurons in ASD relative to the control counterpart. Finally, using genome-wide DNA methylation analyses, we identified 19 genes relevant to neurological development, function, and disease, 7 of which have not previously been described in ASD, that were significantly differentially methylated in autistic SVZ and insula specimens.ConclusionThese findings suggest a hypothesis that epigenetic changes during neurodevelopment alter the trajectory of proliferation, migration, and differentiation in the SVZ, impacting cortical structure and function and resulting in ASD phenotypes.
A prediction model of clinical outcomes in prolonged disorders of consciousness: A prospective cohort study
Authors: Xiong Qi , Le Kai , Wang Yong , Tang Yunliang , Dong Xiaoyang , Zhong Yuan , Zhou Yao , Feng Zhen 
Published: February 2023

ObjectiveThis study aimed to establish and validate a prediction model for clinical outcomes in patients with prolonged disorders of consciousness (pDOC).MethodsA total of 170 patients with pDOC enrolled in our rehabilitation unit were included and divided into training (n = 119) and validation sets (n = 51). Independent predictors for improved clinical outcomes were identified by univariate and multivariate logistic regression analyses, and a nomogram model was established. The nomogram performance was quantified using receiver operating curve (ROC) and calibration curves in the training and validated sets. A decision curve analysis (DCA) was performed to evaluate the clinical usefulness of this nomogram model.ResultsUnivariate and multivariate logistic regression analyses indicated that age, diagnosis at entry, serum albumin (g/L), and pupillary reflex were the independent prognostic factors that were used to construct the nomogram. The area under the curve in the training and validation sets was 0.845 and 0.801, respectively. This nomogram model showed good calibration with good consistency between the actual and predicted probabilities of improved outcomes. The DCA demonstrated a higher net benefit in clinical decision-making compared to treating all or none.ConclusionSeveral feasible, cost-effective prognostic variables that are widely available in hospitals can provide an efficient and accurate prediction model for improved clinical outcomes and support clinicians to offer suitable clinical care and decision-making to patients with pDOC and their family members.
The effect of prestimulus low-frequency neural oscillations on the temporal perception of audiovisual speech
Authors: Jiang Zeliang , An Xingwei , Liu Shuang , Wang Lu , Yin Erwei , Yan Ye , Ming Dong 
Published: February 2023

ObjectivePerceptual integration and segregation are modulated by the phase of ongoing neural oscillation whose frequency period is broader than the size of the temporal binding window (TBW). Studies have shown that the abstract beep-flash stimuli with about 100 ms TBW were modulated by the alpha band phase. Therefore, we hypothesize that the temporal perception of speech with about hundreds of milliseconds of TBW might be affected by the delta-theta phase.MethodsThus, we conducted a speech-stimuli-based audiovisual simultaneity judgment (SJ) experiment. Twenty human participants (12 females) attended this study, recording 62 channels of EEG.ResultsBehavioral results showed that the visual leading TBWs are broader than the auditory leading ones [273.37 ± 24.24 ms vs. 198.05 ± 19.28 ms, (mean ± sem)]. We used Phase Opposition Sum (POS) to quantify the differences in mean phase angles and phase concentrations between synchronous and asynchronous responses. The POS results indicated that the delta-theta phase was significantly different between synchronous and asynchronous responses in the A50V condition (50% synchronous responses in auditory leading SOA). However, in the V50A condition (50% synchronous responses in visual leading SOA), we only found the delta band effect. In the two conditions, we did not find a consistency of phases over subjects for both perceptual responses by the post hoc Rayleigh test (all ps &gt; 0.05). The Rayleigh test results suggested that the phase might not reflect the neuronal excitability which assumed that the phases within a perceptual response across subjects concentrated on the same angle but were not uniformly distributed. But V-test showed the phase difference between synchronous and asynchronous responses across subjects had a significant phase opposition (all ps &lt; 0.05) which is compatible with the POS result.ConclusionThese results indicate that the speech temporal perception depends on the alignment of stimulus onset with an optimal phase of the neural oscillation whose frequency period might be broader than the size of TBW. The role of the oscillatory phase might be encoding the temporal information which varies across subjects rather than neuronal excitability. Given the enriched temporal structures of spoken language stimuli, the conclusion that phase encodes temporal information is plausible and valuable for future research.
Purine signaling pathway dysfunction in autism spectrum disorders: Evidence from multiple omics data
Authors: Dai Si , Lin Jingjing , Hou Yanting , Luo Xuerong , Shen Yidong , Ou Jianjun 
Published: February 2023

IntroductionPrevious studies have suggested that the dysregulation of purine metabolism may be associated with autism spectrum disorder (ASD). Here, we adopted metabolomics and transcriptomics to verify and explore the underlying molecular mechanism of purine metabolism dysfunction in ASD and identify potential biomarkers within the purine metabolism pathway.MethodsUltra-high-performance liquid chromatography-mass spectrometry was used to obtain the plasma metabolic profiles of 12 patients with ASD and 12 typically developing (TD) children. RNA sequencing was used to screen differentially expressed genes related to the purine metabolic pathway and purine receptor-coding genes in 24 children with ASD and 21 healthy controls. Finally, serum uric acid levels were compared in 80 patients with ASD and 174 TD children to validate the omics results.ResultsA total of 66 identified metabolites showed significant between-group differences. Network analysis showed that purine metabolism was the most strongly enriched. Uric acid was one of the most highlighted nodes within the network. The transcriptomic study revealed significant differential expression of three purine metabolism-related genes (adenosine deaminase, adenylosuccinate lyase, and bifunctional enzyme neoformans 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) transformylase/inosine monophosphate (IMP) cyclohydrolase) (p &lt; 0.01) and five purinergic receptor genes (P2X7, P2Y2, P2Y6, P2Y8, and P2Y10) (p &lt; 0.05). In the validation sample, there was a significant difference in serum uric acid levels between the two groups (p &lt; 0.001), and the area under the curve for uric acid was 0.812 (sensitivity, 82.5%; specificity, 63.8%).DiscussionPatients with ASD had dysfunctional purine metabolic pathways, and blood uric acid may be a potential biomarker for ASD.
Development and validation of an inflammatory bowel disease nutrition self-screening tool (IBD-NST) for digital use
Authors: Wall Catherine L. , Wilson Bridgette , Lomer Miranda C. E. 
Published: February 2023

Background and aimThe identification of, and timely intervention for, patients with impaired nutritional status may reduce inflammatory bowel disease (IBD) complications. This study aimed to develop and validate an IBD-specific nutrition self-screening tool (IBD-NST) that identifies patients at nutrition risk.MethodsAn expert IBD panel was consulted to support development of an IBD-NST. The tool was assessed in different cohorts of patients attending IBD outpatient clinics for face, content and convergent validity and repeat reliability. The tool was compared with (i) the malnutrition universal screening tool to assess face validity and (ii) subjective global assessment (SGA), hand-grip strength (HGS) and mid-arm muscle circumference to assess convergent validity. Tool content was informed by agreement between assessment tools, sensitivity analysis and chi-squared tests. The IBD-NST was completed electronically twice, 1 week apart to assess repeat reliability using observed agreement and kappa statistic. Statistical significance assumed at p &lt; 0.05.ResultsIn total, 282 IBD patients (175 with Crohn’s disease) were recruited to validate the IBD-NST. The final validated IBD-NST includes body mass index (BMI), weight loss and IBD-specific nutrition-focussed questions which were acceptable to patients. It identified patients at risk of malnutrition, moderately or severely malnourished patients and patients at nutritional risk. The IBD-NST identified 54/179 (30%) patients at moderate or high nutrition risk and had excellent repeat reliability in 85 patients [r = 0.77 (95% CI 0.669 to 0.746)].ConclusionThe IBD-NST is a self-screening tool, validated for use as either a paper or e-health version, that identifies patients at nutrition risk who are likely to benefit from dietetic assessment and intervention. Furthermore, patients with IBD symptoms who are concerned about their dietary intake can potentially access dietetic care more easily therefore encouraging greater self-management of IBD-related symptoms. The routine use of the IBD-NST as a self-screening tool would enable patient-led care in the outpatient setting and may facilitate timely access to dietetic care.
Synthetic MRI, multiplexed sensitivity encoding, and BI-RADS for benign and malignant breast cancer discrimination
Authors: Liu Jinrui , Xu Mengying , Ren Jialiang , Li Zhihao , Xi Lu , Chen Bing 
Published: February 2023

ObjectiveTo assess the diagnostic value of predictive models based on synthetic magnetic resonance imaging (syMRI), multiplexed sensitivity encoding (MUSE) sequences, and Breast Imaging Reporting and Data System (BI-RADS) in the differentiation of benign and malignant breast lesions.MethodsClinical and MRI data of 158 patients with breast lesions who underwent dynamic contrast-enhanced MRI (DCE-MRI), syMRI, and MUSE sequences between September 2019 and December 2020 were retrospectively collected. The apparent diffusion coefficient (ADC) values of MUSE and quantitative relaxation parameters (longitudinal and transverse relaxation times [T1, T2], and proton density [PD] values) of syMRI were measured, and the parameter variation values and change in their ratios were calculated. The patients were randomly divided into training (n = 111) and validation (n = 47) groups at a ratio of 7:3. A nomogram was built based on univariate and multivariate logistic regression analyses in the training group and was verified in the validation group. The discriminatory and predictive capacities of the nomogram were assessed by the receiver operating characteristic curve and area under the curve (AUC). The AUC was compared by DeLong test.ResultsIn the training group, univariate analysis showed that age, lesion diameter, menopausal status, ADC, T2pre, PDpre, PDGd, T2Delta, and T2ratio were significantly different between benign and malignant breast lesions (P &lt; 0.05). Multivariate logistic regression analysis showed that ADC and T2pre were significant variables (all P &lt; 0.05) in breast cancer diagnosis. The quantitative model (model A: ADC, T2pre), BI-RADS model (model B), and multi-parameter model (model C: ADC, T2pre, BI-RADS) were established by combining the above independent variables, among which model C had the highest diagnostic performance, with AUC of 0.965 and 0.986 in the training and validation groups, respectively.ConclusionsThe prediction model established based on syMRI, MUSE sequence, and BI-RADS is helpful for clinical differentiation of breast tumors and provides more accurate information for individualized diagnosis.
Trefoil factor family proteins as potential diagnostic markers for mucinous invasive ovarian carcinoma
Authors: Werner Rönnerman Elisabeth , Pettersson Daniella , Nemes Szilárd , Dahm-Kähler Pernilla , Kovács Anikó , Karlsson Per , Parris Toshima Z. , Helou Khalil 
Published: February 2023

IntroductionOvarian cancer (OC) is the leading cause of gynecological cancer-related death. Of the main OC histologic subtypes, invasive mucinous carcinomas (MC) account for only 3% of OC cases and are frequently associated with favorable prognosis. Nevertheless, MCs differ greatly from the other OC histotypes in clinical, pathological, and biological behavior. However, the origin and molecular pathogenesis of MC are not yet fully understood. Therefore, identification of novel diagnostic markers could potentially facilitate early diagnosis of OC, particularly the MC histotype, thereby leading to the development of histotype-specific treatment regimens and improved survival rates.MethodsIn the present study, Trefoil factor gene family members (TFF1, TFF2 and TFF3) were identified as MC histotype-specific biomarkers using RNA sequencing (RNA-seq) data for 95 stage I-II OCs. The diagnostic value of TFF1, TFF2 and TFF3 was then evaluated by immunohistochemistry on 206 stage I-II OCs stratified by histotype (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], clear cell carcinoma [CCC], and MC).ResultsWe showed significantly elevated intracytoplasmic protein expression levels for TFF1, TFF2 and TFF3 in MC samples, thereby revealing an association between expression of Trefoil factor gene family members and the MC histotype. Taken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype.ConclusionTaken together, these findings suggest that the TFF proteins may play a pivotal role in tumor initiation and progression for the MC histotype. Moreover, these novel histotype-specific diagnostic biomarkers may not only improve patient stratification of early-stage ovarian carcinomas but may also be candidates for the development of molecular targeted therapies.
The value of enhanced CT features and texture-signatures in assessing the inflammatory infiltration of pancreatic ductal adenocarcinoma
Authors: Wang Fangqing , Guo Hang , Li Shunjia , Xu Jianwei , Yu Dexin 
Published: February 2023

PurposeTo explore the predictive value of computed tomography (CT) imaging features and CT-based texture analysis in assessing inflammatory infiltration in pancreatic ductal adenocarcinoma (PDAC).MethodsA total of 43 patients with PDAC confirmed by surgical pathology were included in the study. The clinical, radiological, surgical, and pathological features of the patients were analyzed retrospectively using the chi-square test or Spearman’s correlation. Receiver operating characteristic (ROC) curves were utilized to assess the overall predictive ability of the tumor enhancement degree on triphasic contrast-enhanced CT images for the inflammatory infiltration degree in PDAC. Furthermore, all CT data were uploaded to the RadCloud platform for region of interest (ROI) delineation and feature extraction. Then, the Variance Threshold and SelectKBest algorithms were used to find the optimal CT features. Binary logistic regression was employed to analyze the selected features in all three contrast-enhanced CT phases, and regression equations were formulated. ROC analysis was performed to evaluate the predictive effectiveness of each equation.ResultsThe analysis revealed a statistically significant correlation between the degree of differentiation and radiological findings such as necrosis and cystic degeneration, vascular invasion, and the presence of ascites (P &lt; 0.05). The enhancement degree of the tumor in both the arterial and venous phases was significantly correlated with the inflammatory infiltration degree (P &lt; 0.05); however, the areas under the ROC curve (AUCs) of arterial and venous enhancement were 0.570 and 0.542, respectively. Regression equations based on the texture features of triphasic contrast-enhanced tumors were formulated, and their AUCs were 0.982, 0.643, and 0.849.ConclusionConventional radiological features are not significantly correlated with the degree of inflammatory infiltration in PDAC. The enhancement degrees in both the arterial phase and venous phase were statistically correlated with the inflammatory infiltration level but had poor predictive value. The texture features of PDAC on contrast-enhanced CT may show a better assessment value, especially in the arterial phase.
An integrated solution of deep reinforcement learning for automatic IMRT treatment planning in non-small-cell lung cancer
Authors: Wang Hanlin , Bai Xue , Wang Yajuan , Lu Yanfei , Wang Binbing 
Published: February 2023

PurposeTo develop and evaluate an integrated solution for automatic intensity-modulated radiation therapy (IMRT) planning in non-small-cell lung cancer (NSCLC) cases.MethodsA novel algorithm named as multi-objectives adjustment policy network (MOAPN) was proposed and trained to learn how to adjust multiple optimization objectives in commercial Eclipse treatment planning system (TPS), based on the multi-agent deep reinforcement learning (DRL) scheme. Furthermore, a three-dimensional (3D) dose prediction module was developed to generate the patient-specific initial optimization objectives to reduce the overall exploration space during MOAPN training. 114 previously treated NSCLC cases suitable for stereotactic body radiotherapy (SBRT) were selected from the clinical database. 87 cases were used for the model training, and the remaining 27 cases for evaluating the feasibility and effectiveness of MOAPN in automatic treatment planning.ResultsFor all tested cases, the average number of adjustment steps was 21 ± 5.9 (mean ± 1 standard deviation). Compared with the MOAPN initial plans, the actual dose of chest wall, spinal cord, heart, lung (affected side), esophagus and bronchus in the MOAPN final plans reduced by 14.5%, 11.6%, 4.7%, 16.7%, 1.6% and 7.7%, respectively. The dose result of OARs in the MOAPN final plans was similar to those in the clinical plans. The complete automatic treatment plan for a new case was generated based on the integrated solution, with about 5-6 min.ConclusionWe successfully developed an integrated solution for automatic treatment planning. Using the 3D dose prediction module to obtain the patient-specific optimization objectives, MOAPN formed action-value policy can simultaneously adjust multiple objectives to obtain a high-quality plan in a shorter time. This integrated solution contributes to improving the efficiency of the overall planning workflow and reducing the variation of plan quality in different regions and treatment centers. Although improvement is warranted, this proof-of-concept study has demonstrated the feasibility of this integrated solution in automatic treatment planning based on the Eclipse TPS.