bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment
Authors: Bruder Jonas Christian , Wagner Kathrin , Lachner-Piza Daniel , Klotz Kerstin Alexandra , Schulze-Bonhage Andreas , Jacobs Julia 
Published: June 2022

RationaleHigh frequency oscillations (HFO; ripples = 80–200, fast ripples 200–500 Hz) are promising epileptic biomarkers in patients with epilepsy. However, especially in temporal epilepsies differentiation of epileptic and physiological HFO activity still remains a challenge. Physiological sleep-spindle-ripple formations are known to play a role in slow-wave-sleep memory consolidation. This study aimed to find out if higher rates of mesial-temporal spindle-ripples correlate with good memory performance in epilepsy patients and if surgical removal of spindle-ripple-generating brain tissue correlates with a decline in memory performance. In contrast, we hypothesized that higher rates of overall ripples or ripples associated with interictal epileptic spikes correlate with poor memory performance.MethodsPatients with epilepsy implanted with electrodes in mesial-temporal structures, neuropsychological memory testing and subsequent epilepsy surgery were included. Ripples and epileptic spikes were automatically detected in intracranial EEG and sleep-spindles in scalp EEG. The coupling of ripples to spindles was automatically analyzed. Mesial-temporal spindle-ripple rates in the speech-dominant-hemisphere (left in all patients) were correlated with verbal memory test results, whereas ripple rates in the non-speech-dominant hemisphere were correlated with non-verbal memory test performance, using Spearman correlation).ResultsIntracranial EEG and memory test results from 25 patients could be included. All ripple rates were significantly higher in seizure onset zone channels (p &lt; 0.001). Patients with pre-surgical verbal memory impairment had significantly higher overall ripple rates in left mesial-temporal channels than patients with intact verbal memory (Mann–Whitney-U-Test: p = 0.039). Spearman correlations showed highly significant negative correlations of the pre-surgical verbal memory performance with left mesial-temporal spike associated ripples (rs = −0.458; p = 0.007) and overall ripples (rs = −0.475; p = 0.006). All three ripple types in right-sided mesial-temporal channels did not correlate with pre-surgical nonverbal memory. No correlation for the difference between post- and pre-surgical memory and pre-surgical spindle-ripple rates was seen in patients with left-sided temporal or mesial-temporal surgery.DiscussionThis study fails to establish a clear link between memory performance and spindle ripples. This highly suggests that spindle-ripples are only a small portion of physiological ripples contributing to memory performance. More importantly, this study indicates that spindle-ripples do not necessarily compromise the predictive value of ripples in patients with temporal epilepsy. The majority of ripples were clearly linked to areas with poor memory function.
Comatose Patients After Cardiopulmonary Resuscitation: An Analysis Based on Quantitative Methods of EEG Reactivity
Authors: Huang Huijin , Su Yingying , Niu Zikang , Liu Gang , Li Xiaoli , Jiang Mengdi 
Published: June 2022

ObjectiveEvery year, approximately 50–110/1,00,000 people worldwide suffer from cardiac arrest, followed by hypoxic-ischemic encephalopathy after cardiopulmonary resuscitation (CPR), and approximately 40–66% of patients do not recover. The purpose of this study was to identify the brain network parameters and key brain regions associated with awakening by comparing the reactivity characteristics of the brain networks between the awakening and unawakening groups of CPR patients after coma, thereby providing a basis for further awakening interventions.MethodThis study involved a prospective cohort study. Using a 64-electrode electroencephalography (EEG) wireless 64A system, EEG signals were recorded from 16 comatose patients after CPR in the acute phase (&lt;1 month) from 2019 to 2020. MATLAB (2017b) was used to quantitatively analyze the reactivity (power spectrum and entropy) and brain network characteristics (coherence and phase lag index) after pain stimulation. The patients were divided into an awakening group and an unawakening group based on their ability to execute commands or engage in repeated and continuous purposeful behavior after 3 months. The above parameters were compared to determine whether there were differences between the two groups.Results(1) Power spectrum: the awakening group had higher gamma, beta and alpha spectral power after pain stimulation in the frontal and parietal lobes, and lower delta and theta spectral power in the bilateral temporal and occipital lobes than the unawakening group. (2) Entropy: after pain stimulation, the awakening group had higher entropy in the frontal and parietal lobes and lower entropy in the temporal occipital lobes than the unawakening group. (3) Connectivity: after pain stimulation, the awakening group had stronger gamma and beta connectivity in nearly the whole brain, but weaker theta and delta connectivity in some brain regions (e.g., the frontal-occipital lobe and parietal-occipital lobe) than the unawakening group.ConclusionAfter CPR, comatose patients were more likely to awaken if there was a higher stimulation of fast-frequency band spectral power, higher entropy, stronger whole-brain connectivity and better retention of frontal-parietal lobe function after pain stimulation.
Impact of Body Temperature in Patients With Acute Basilar Artery Occlusion: Analysis of the BASILAR Database
Authors: Zhang Wenbin , Li Fengli , Zhang Cai , Lei Bo , Deng Wei , Zeng Hongliang , Yu Yang , Wu Junxiong , Peng Daizhou , Tian Zhenxuan , Zhu Xiurong , Hu Zhizhou , Hong Yifan , Li Wenbo , Ge Hanming , Xu Xinwei , Ju Dongsheng , Yang Shunyu , Pan Chengde , Zi Wenjie , Wang Shouchun 
Published: June 2022

BackgroundA link between body temperature and stroke outcomes has been established but not for acute basilar artery occlusion. We aimed to determine the association between body temperature and clinical outcomes in patients with acute basilar artery occlusion and temperature management range.MethodsWe included patients from the Endovascular Treatment for Acute Basilar Artery Occlusion Study (BASILAR) database with records of both admission body temperature (ABT) and peak body temperature (PBT). ABT was defined as the body temperature first measured at the hospital visit, PBT was defined as the highest temperature within 24 h of treatment, and minus body temperature (MBT) was defined as PBT-ABT. The primary clinical outcome was favorable functional outcome, defined as the proportion of patients with a modified Rankin Scale score of 0–3 at 3 months. Secondary outcomes included 3-month mortality, in-hospital mortality, and symptomatic cerebral hemorrhage.ResultsA total of 664 patients were enrolled in the study; 74.7% were men, with a median age of 65 (interquartile range, 57.25–74) years. In all patients, multivariate analysis indicated that PBT and MBT were independent predictors of favorable functional outcome [odds ratio (OR), 0.57 (95% CI, 0.43–0.77); OR, 0.68 (95% CI, 0.52–0.88), respectively], and higher ABT, PBT, and MBT were associated with an increased 3-month mortality [OR, 1.47 (95% CI, 1.03–2.10), OR, 1.58 (95% CI, 1.28–1.96), OR, 1.35 (95% CI, 1.11–1.65), respectively]. Proportional odds models demonstrated that when ABT, PBT, MBT were in the range of &lt;37.5, &lt;38.9, and −0.6–2.7°C, respectively, the benefit of the endovascular treatment is clearly greater than that of standard medical treatment in terms of favorable functional outcome.ConclusionsBody temperature is an independent predictor of clinical outcome in patients with acute basilar artery occlusion. It is necessary to control the patient body temperature within the appropriate range in clinical settings.Trial RegistrationChinese Clinical Trial Registry ChiCTR1800014759. Registered 03 February 2018. Retrospectively registered.
Causal Effects of Motor Control on Gait Kinematics After Orthopedic Surgery in Cerebral Palsy: A Machine-Learning Approach
Authors: Steele Katherine M. , Schwartz Michael H. 
Published: June 2022

BackgroundAltered motor control is common in cerebral palsy (CP). Understanding how altered motor control affects movement and treatment outcomes is important but challenging due to complex interactions with other neuromuscular impairments. While regression can be used to examine associations between impairments and movement, causal modeling provides a mathematical framework to specify assumed causal relationships, identify covariates that may introduce bias, and test model plausibility. The goal of this research was to quantify the causal effects of altered motor control and other impairments on gait, before and after single-event multi-level orthopedic surgery (SEMLS).MethodsWe evaluated the impact of SEMLS on change in Gait Deviation Index (ΔGDI) between gait analyses. We constructed our causal model with a Directed Acyclic Graph that included the assumed causal relationships between SEMLS, ΔGDI, baseline GDI (GDIpre), baseline neurologic and orthopedic impairments (Imppre), age, and surgical history. We identified the adjustment set to evaluate the causal effect of SEMLS on ΔGDI and the impact of Imppre on ΔGDI and GDIpre. We used Bayesian Additive Regression Trees (BART) and accumulated local effects to assess relative effects.ResultsWe prospectively recruited a cohort of children with bilateral CP undergoing SEMLS (N = 55, 35 males, age: 10.5 ± 3.1 years) and identified a control cohort with bilateral CP who did not undergo SEMLS (N = 55, 30 males, age: 10.0 ± 3.4 years). There was a small positive causal effect of SEMLS on ΔGDI (1.70 GDI points). Altered motor control (i.e., dynamic and static motor control) and strength had strong effects on GDIpre, but minimal effects on ΔGDI. Spasticity and orthopedic impairments had minimal effects on GDIpre or ΔGDI.ConclusionAltered motor control did have a strong effect on GDIpre, indicating that these impairments do have a causal effect on a child’s gait pattern, but minimal effect on expected changes in GDI after SEMLS. Heterogeneity in outcomes suggests there are other factors contributing to changes in gait. Identifying these factors and employing causal methods to examine the complex relationships between impairments and movement will be required to advance our understanding and care of children with CP.
Identification of Auxiliary Biomarkers and Description of the Immune Microenvironmental Characteristics in Duchenne Muscular Dystrophy by Bioinformatical Analysis and Experiment
Authors: Han Xu , Han Jingzhe , Wang Ning , Ji Guang , Guo Ruoyi , Li Jing , Wu Hongran , Ma Shaojuan , Fang Pingping , Song Xueqin 
Published: June 2022

BackgroundDuchenne muscular dystrophy (DMD) is a genetic muscle disorder characterized by progressive muscle wasting associated with persistent inflammation. In this study, we aimed to identify auxiliary biomarkers and further characterize the immune microenvironment in DMD.MethodsDifferentially expressed genes (DEGs) were identified between DMD and normal muscle tissues based on Gene Expression Omnibus (GEO) datasets. Bioinformatical analysis was used to screen and identify potential diagnostic signatures of DMD which were further validated by real-time quantitative reverse transcription PCR (RT-qPCR). We also performed single-sample gene-set enrichment analysis (ssGSEA) to characterize the proportion of tissue-infiltrating immune cells to determine the inflammatory state of DMD.ResultsIn total, 182 downregulated genes and 263 upregulated genes were identified in DMD. C3, SPP1, TMSB10, TYROBP were regarded as adjunct biomarkers and successfully validated by RT-qPCR. The infiltration of macrophages, CD4+, and CD8+ T cells was significantly higher (p &lt; 0.05) in DMD compared with normal muscle tissues, while the infiltration of activated B cells, CD56dim natural killer cells, and type 17 T helper (Th17) cells was lower. In addition, the four biomarkers (C3, SPP1, TMSB10, TYROBP) were strongly associated with immune cells and immune-related pathways in DMD muscle tissues.ConclusionAnalyses demonstrated C3, SPP1, TMSB10, and TYROBP may serve as biomarkers and enhance our understanding of immune responses in DMD. The infiltration of immune cells into the muscle microenvironment might exert a critical impact on the development and occurrence of DMD.
Association Between Nap Duration and Cognitive Functions Among Saudi Older Adults
Authors: Alqurashi Yousef D. , AlHarkan Khalid , Aldhawyan Adam , Bahamdan Ahmed , Alabdulkader Assim , Alotaibi Raed , Alduailej Saleh , Alqahtani Mohammed , Ghamdi Kholoud Al 
Published: June 2022

PurposeCurrent evidence of whether napping promotes or declines cognitive functions among older adults is contradictory. The aim of this study was to determine the association between nap duration and cognitive functions among Saudi older adults.MethodsOld adults (&gt; 60 years) were identified from the Covid-19 vaccine center at Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia between May and August 2021. Face-to-face interviews were conducted by a geriatrician or family physicians. Data collected for each participant included sociodemographic, sleep patterns, health status and cognitive functions. St. Louis University mental status (SLUMS) was used to assess the cognitive functions. A multi-Linear regression model was used to determine the association between cognitive functions and nap duration.ResultsTwo-hundred participants (58 females) aged 66 ± 5 years were recruited. Participants were categorized according to their nap duration into non-nappers (0 min), short nappers (&gt; 0- ≤ 30 min), moderate nappers (&gt; 30–≤ 90 min), and extended nappers (&gt; 90 min). The mean duration of the nap was 49.1 ± 58.4 min. The mean SLUMS score was 24.1 ± 4.7 units. Using the multi-linear regression model, the mean total SLUMS score for extended nappers was, on average, significantly lower than non-nappers [−2.16 units; 95% CI (−3.66, −0.66), p = &lt; 0.01] after controlling for the covariates (age, sex, education level, sleep hours, diabetes mellitus, hypertension, pain).ConclusionsExtended napping was associated with deterioration in cognitive function among Saudi older adults.
A New Online Dynamic Nomogram: Construction and Validation of an Assistant Decision-Making Model for Laryngeal Squamous Cell Carcinoma
Authors: Liu Yuchen , Han Yanxun , Chen Bangjie , Zhang Jian , Yin Siyue , Li Dapeng , Wu Yu , Jiang Yuan , Wang Xinyi , Wang Jianpeng , Fu Ziyue , Shen Hailong , Ding Zhao , Yao Kun , Tao Ye , Wu Jing , Liu Yehai 
Published: June 2022

BackgroundLaryngeal squamous cell carcinoma (LSCC) is the most common type of head and neck squamous cell carcinoma. However, there are currently no reliable biomarkers for the diagnosis and prognosis of LSCC. Thus, this study aimed to identify the independent risk factors and develop and validate a new dynamic web-based nomogram that can predict auxiliary laryngeal carcinogenesis.MethodsData on the medical history of 221 patients who were recently diagnosed with LSCC and 359 who were recently diagnosed with benign laryngeal lesions (BLLs) at the First Affiliated Hospital of Anhui Medical University were retrospectively reviewed. Using the bootstrap method, 580 patients were divided in a 7:3 ratio into a training cohort (LSCC, 158 patients; BLL, 250 patients) and an internal validation cohort (LSCC, 63 patients; BLL, 109 patients). In addition, a retrospective analysis of 31 patients with LSCC and 54 patients with BLL from Fuyang Hospital affiliated with Anhui Medical University was performed as an external validation cohort. In the training cohort, the relevant indices were initially screened using univariate analysis. Then, least absolute shrinkage and selection operator logistic analysis was used to evaluate the significant potential independent risk factors (P&lt;0.05); a dynamic online diagnostic nomogram, whose discrimination was evaluated using the area under the ROC curve (AUC), was constructed, while the consistency was evaluated using calibration plots. Its clinical application was evaluated by performing a decision curve analysis (DCA) and validated by internal validation of the training set and external validation of the validation set.ResultsFive independent risk factors, sex (odds ratio [OR]: 6.779, P&lt;0.001), age (OR: 9.257, P&lt;0.001), smoking (OR: 2.321, P=0.005), red blood cell width distribution (OR: 2.698, P=0.001), albumin (OR: 0.487, P=0.012), were screened from the results of the multivariate logistic analysis of the training cohort and included in the LSCC diagnostic nomogram. The nomogram predicted LSCC with AUC values of 0.894 in the training cohort, 0.907 in the internal testing cohort, and 0.966 in the external validation cohort. The calibration curve also proved that the nomogram predicted outcomes were close to the ideal curve, the predicted outcomes were consistent with the real outcomes, and the DCA curve showed that all patients could benefit. This finding was also confirmed in the validation cohort.ConclusionAn online nomogram for LSCC was constructed with good predictive performance, which can be used as a practical approach for the personalized early screening and auxiliary diagnosis of the potential risk factors and assist physicians in making a personalized diagnosis and treatment for patients.
Application of Multi-Scale Fusion Attention U-Net to Segment the Thyroid Gland on Localized Computed Tomography Images for Radiotherapy
Authors: Wen Xiaobo , Zhao Biao , Yuan Meifang , Li Jinzhi , Sun Mengzhen , Ma Lishuang , Sun Chaoxi , Yang Yi 
Published: June 2022

ObjectiveTo explore the performance of Multi-scale Fusion Attention U-Net (MSFA-U-Net) in thyroid gland segmentation on localized computed tomography (CT) images for radiotherapy.MethodsWe selected localized radiotherapeutic CT images from 80 patients with breast cancer or head and neck tumors; label images were manually delineated by experienced radiologists. The data set was randomly divided into the training set (n = 60), the validation set (n = 10), and the test set (n = 10). We expanded the data in the training set and evaluated the performance of the MSFA-U-Net model using the evaluation indices Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), positive predictive value (PPV), sensitivity (SE), and Hausdorff distance (HD).ResultsFor the MSFA-U-Net model, the DSC, JSC, PPV, SE, and HD values of the segmented thyroid gland in the test set were 0.90 ± 0.09, 0.82± 0.11, 0.91 ± 0.09, 0.90 ± 0.11, and 2.39 ± 0.54, respectively. Compared with U-Net, HRNet, and Attention U-Net, MSFA-U-Net increased DSC by 0.04, 0.06, and 0.04, respectively; increased JSC by 0.05, 0.08, and 0.04, respectively; increased SE by 0.04, 0.11, and 0.09, respectively; and reduced HD by 0.21, 0.20, and 0.06, respectively. The test set image results showed that the thyroid edges segmented by the MSFA-U-Net model were closer to the standard thyroid edges delineated by the experts than were those segmented by the other three models. Moreover, the edges were smoother, over–anti-noise interference was stronger, and oversegmentation and undersegmentation were reduced.ConclusionThe MSFA-U-Net model could meet basic clinical requirements and improve the efficiency of physicians’ clinical work.
Using an Improved Residual Network to Identify PIK3CA Mutation Status in Breast Cancer on Ultrasound Image
Authors: Shen Wen-Qian , Guo Yanhui , Ru Wan-Er , Li Cheukfai , Zhang Guo-Chun , Liao Ning , Du Guo-Qing 
Published: June 2022

BackgroundThe detection of phosphatidylinositol-3 kinase catalytic alpha (PIK3CA) gene mutations in breast cancer is a key step to design personalizing an optimal treatment strategy. Traditional genetic testing methods are invasive and time-consuming. It is urgent to find a non-invasive method to estimate the PIK3CA mutation status. Ultrasound (US), one of the most common methods for breast cancer screening, has the advantages of being non-invasive, fast imaging, and inexpensive. In this study, we propose to develop a deep convolutional neural network (DCNN) to identify PIK3CA mutations in breast cancer based on US images.Materials and MethodsWe retrospectively collected 312 patients with pathologically confirmed breast cancer who underwent genetic testing. All US images (n=800) of breast cancer patients were collected and divided into the training set (n=600) and test set (n=200). A DCNN-Improved Residual Network (ImResNet) was designed to identify the PIK3CA mutations. We also compared the ImResNet model with the original ResNet50 model, classical machine learning models, and other deep learning models.ResultsThe proposed ImResNet model has the ability to identify PIK3CA mutations in breast cancer based on US images. Notably, our ImResNet model outperforms the original ResNet50, DenseNet201, Xception, MobileNetv2, and two machine learning models (SVM and KNN), with an average area under the curve (AUC) of 0.775. Moreover, the overall accuracy, average precision, recall rate, and F1-score of the ImResNet model achieved 74.50%, 74.17%, 73.35%, and 73.76%, respectively. All of these measures were significantly higher than other models.ConclusionThe ImResNet model gives an encouraging performance in predicting PIK3CA mutations based on breast US images, providing a new method for noninvasive gene prediction. In addition, this model could provide the basis for clinical adjustments and precision treatment.
Biological Characterization and Clinical Value of OAS Gene Family in Pancreatic Cancer
Authors: Gao Li-Juan , Li Jia-Lei , Yang Rui-Rui , He Zhong-Mei , Yan Min , Cao Xia , Cao Ji-Min 
Published: June 2022

BackgroundOAS gene family plays an important role in antiviral process, but its role in pancreatic cancer has not yet been studied.MethodsWe analyzed the expression, prognostic value and biological function of the OAS gene family in human pancreatic cancer through comprehensive bioinformatic analysis and cellular level validation.ResultsOAS family was highly expressed in pancreatic cancer, and this high expression significantly affected the clinical stage and prognosis of the tumor. OAS gene family was closely related to the immune infiltration of pancreatic cancer, especially neutrophils and dendritic cells, and many immune-related factors and pathways are enriched in the tumor, such as type I interferon signaling pathway and NOD-like receptor signaling pathway.ConclusionTaken together, high expression of OAS family is closely related to poor prognosis of pancreatic cancer. OAS gene family may serve as the biomarker and even therapeutic target of pancreatic cancer.