bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel deep learning framework for detection of epileptic seizures using EEG signals
Authors: Mallick Sayani , Baths Veeky 
Published: March 2024

IntroductionEpilepsy is a chronic neurological disorder characterized by abnormal electrical activity in the brain, often leading to recurrent seizures. With 50 million people worldwide affected by epilepsy, there is a pressing need for efficient and accurate methods to detect and diagnose seizures. Electroencephalogram (EEG) signals have emerged as a valuable tool in detecting epilepsy and other neurological disorders. Traditionally, the process of analyzing EEG signals for seizure detection has relied on manual inspection by experts, which is time-consuming, labor-intensive, and susceptible to human error. To address these limitations, researchers have turned to machine learning and deep learning techniques to automate the seizure detection process.MethodsIn this work, we propose a novel method for epileptic seizure detection, leveraging the power of 1-D Convolutional layers in combination with Bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) and Average pooling Layer as a single unit. This unit is repeatedly used in the proposed model to extract the features. The features are then passed to the Dense layers to predict the class of the EEG waveform. The performance of the proposed model is verified on the Bonn dataset. To assess the robustness and generalizability of our proposed architecture, we employ five-fold cross-validation. By dividing the dataset into five subsets and iteratively training and testing the model on different combinations of these subsets, we obtain robust performance measures, including accuracy, sensitivity, and specificity.ResultsOur proposed model achieves an accuracy of 99–100% for binary classifications into seizure and normal waveforms, 97.2%–99.2% accuracy for classifications into normal-interictal-seizure waveforms, 96.2%–98.4% accuracy for four class classification and accuracy of 95.81%–98% for five class classification.DiscussionOur proposed models have achieved significant improvements in the performance metrics for the binary classifications and multiclass classifications. We demonstrate the effectiveness of the proposed architecture in accurately detecting epileptic seizures from EEG signals by using EEG signals of varying lengths. The results indicate its potential as a reliable and efficient tool for automated seizure detection, paving the way for improved diagnosis and management of epilepsy.
Neural correlates of breath work, mental imagery of yoga postures, and meditation in yoga practitioners: a functional near-infrared spectroscopy study
Authors: Li Xiawen , Zhou Yu , Zhang Chenping , Wang Hongbiao , Wang Xiaochun 
Published: March 2024

ObjectivePrevious research has shown numerous health benefits of yoga, a multicomponent physical and mental activity. The three important aspects of both traditional and modern yoga are breath work, postures, and meditation. However, the neural mechanisms associated with these three aspects of yoga remain largely unknown. The present study investigated the neural underpinnings associated with each of these three yoga components in long- and short-term yoga practitioners to clarify the neural advantages of yoga experience, aiming to provide a more comprehensive understanding of yoga’s health-promoting effects.MethodsParticipants were 40 Chinese women, 20 with a long-term yoga practice and 20 with a short-term yoga practice. Functional near-infrared spectroscopy was conducted while participants performed abdominal breathing, mental imagery of yoga postures, and mindfulness meditation. The oxygenated hemoglobin concentrations activated in the brain during these three tasks were used to assess the neural responses to the different aspects of yoga practice. The self-reported mastery of each yoga posture was used to assess the advantages of practicing yoga postures.ResultsBlood oxygen levels in the dorsolateral prefrontal cortex during breath work were significantly higher in long-term yoga practitioners than in short-term yoga practitioners. In the mental imagery of yoga postures task, self-reported data showed that long-term yoga practitioners had better mastery than short-term practitioners. Long-term yoga practitioners demonstrated lower activation in the ventrolateral prefrontal cortex, with lower blood oxygen levels associated with performing this task, than short-term yoga practitioners. In the mindfulness meditation task, blood oxygen levels in the orbitofrontal cortex and the ventrolateral prefrontal cortex were significantly higher in long-term yoga practitioners than in short-term yoga practitioners.ConclusionThe three core yoga components, namely, yogic breathing, postures, and meditation, showed differences and similarities in the activation levels of the prefrontal cortex. Long-term practice of each component led to the neural benefits of efficient activation in the prefrontal cortex, especially in the dorsolateral prefrontal cortex, orbitofrontal cortex, and ventrolateral prefrontal cortex.
Caregiver perceptions of a pediatric produce prescription program during the COVID-19 pandemic
Authors: Li Zhongyu , Zhang Fang Fang , Cash Sean B. , Hager Kurt , Trevino Leo , Folta Sara C. 
Published: March 2024

IntroductionProduce prescription programs are rapidly expanding as a type of Food is Medicine intervention with prospects for mitigating food insecurity and reducing diet-related health disparities. Gaining insight into participant perspectives on program logistics and perceived impacts is crucial to program success and improvements.MethodsBetween May and June 2021, we conducted individual and small group interviews with 23 caregivers with children aged 1–5 years who participated in a produce prescription program from 2020 to 2021 in Texas, U.S. They were provided with a gift card to a major national grocery retailer to purchase fresh produce. The card was reloaded $60 monthly for 8 months with automatic roll-over of unused funds to the next month. Participants also received nutrition education in the form of two videos. A deductive analysis approach was employed, and NVivo qualitative data analysis software was used to perform coding and to assist with subsequent analyses.ResultsAll 23 participants were female, with an average age of 37.5 years, and the majority identified as Hispanic/Latino (83%). About 43% of the families had three or more children. Six themes were generated from interviews. Three of these themes were related to program logistics: (1) ease of program use; (2) participant satisfaction with the incentive; and (3) desire for additional store options. The remaining main themes pertained to program impact: (1) the enhanced ability to purchase produce; (2) the usefulness of the nutrition education; and (3) persistent challenges encountered when preparing the produce for picky eaters and young children.ConclusionA pediatric produce prescription program was perceived as logistically easy and a helpful source of financial support for accessing fresh produce. Program features such as card-based incentive system and partnership with major grocery retailer were favored by participants. For future program design, it may be beneficial to consider collaborating with multiple grocery outlets and enhancing the intensity and targeting of nutrition education.
CD7-positive leukemic blasts with DNMT3A mutations predict poor prognosis in patients with acute myeloid leukemia
Authors: Bai Yanliang , Sun Xiaobai , Li Mengyi , Niu Xiaona , Cao Weijie , Niu Junwei , Xiao Xingjun , Chen Yuqing , Sun Kai 
Published: March 2024

BackgroundDNMT3A mutations can be detected in premalignant hematopoietic stem cells and are primarily associated with clonal hematopoiesis of indeterminate potential; however, current evidence does not support assigning them to a distinct European Leukemia Net (ELN) prognostic risk stratification. CD7 is a lymphoid antigen expressed on blasts in approximately 30% of acute myeloid leukemia (AML), and its role in AML remains unclear and depends on subgroup evaluation. This study investigated the prognostic value of DNMT3A mutation combined with CD7 expression in AML.MethodsWe retrospectively analyzed the clinical data of 297 newly diagnosed non-M3 AML patients. According to the DNMT3A mutation and CD7 expression in AML cells, patients were divided into the DNMT3A-mutated/CD7-positive (CD7+), DNMT3A-mutated/CD7-negative (CD7-), DNMT3A-wild-type/CD7+, and DNMT3A-wild-type/CD7- groups.ResultsThe DNMT3A-mutated/CD7+ group had lower complete remission rates and higher relapse rates. Importantly, these patients had significantly shorter overall survival (OS) and relapse-free survival (RFS). Furthermore, multivariate analysis showed that CD7+ with DNMT3A mutation was an independent risk factor for OS and RFS.ConclusionCD7+ with DNMT3A mutation predicts a poor prognosis in AML patients, and the immunophenotype combined with molecular genetic markers can help to further refine the current risk stratification of AML.
Evaluation of the neoadjuvant chemotherapy response in osteosarcoma using the MRI DWI-based machine learning radiomics nomogram
Authors: Zhang Lu , Gao Qiuru , Dou Yincong , Cheng Tianming , Xia Yuwei , Li Hailiang , Gao Song 
Published: March 2024

ObjectiveTo evaluate the value of a nomogram combined MRI Diffusion Weighted Imaging (DWI) and clinical features to predict the treatment response of Neoadjuvant Chemotherapy (NAC) in patients with osteosarcoma.MethodsA retrospective analysis was conducted on 209 osteosarcoma patients admitted into two bone cancer treatment centers (133 males, 76females; mean age 16.31 ± 11.42 years) from January 2016 to January 2022. Patients were classified as pathological good responders (pGRs) if postoperative histopathological examination revealed ≥90% tumor necrosis, and non-pGRs if &lt;90%. Their clinical features were subjected to univariate and multivariate analysis, and features with statistically significance were utilized to construct a clinical signature using machine learning algorithms. Apparent diffusion coefficient (ADC) values pre-NAC (ADC 0) and post two chemotherapy cycles (ADC 1) were recorded. Regions of interest (ROIs) were delineated from pre-treatment DWI images (b=1000 s/mm²) for radiomic features extraction. Variance thresholding, SelectKBest, and LASSO regression were used to select features with strong relevance, and three machine learning models (Logistic Regression, RandomForest and XGBoost) were used to construct radiomics signatures for predicting treatment response. Finally, the clinical and radiomics signatures were integrated to establish a comprehensive nomogram model. Predictive performance was assessed using ROC curve analysis, with model clinical utility appraised through AUC and decision curve analysis (DCA).ResultsOf the 209patients, 51 (24.4%) were pGRs, while 158 (75.6%) were non-pGRs. No significant ADC1 difference was observed between groups (P&gt;0.05), but pGRs had a higher ADC 0 (P&lt;0.01). ROC analysis indicated an AUC of 0.681 (95% CI: 0.482-0.862) for ADC 0 at the threshold of ≥1.37×10-3 mm²/s, achieving 74.7% sensitivity and 75.7% specificity. The clinical and radiomics models reached AUCs of 0.669 (95% CI: 0.401-0.826) and 0.768 (95% CI: 0.681-0.922) respectively in the test set. The combined nomogram displayed superior discrimination with an AUC of 0.848 (95% CI: 0.668-0.951) and 75.8% accuracy. The DCA suggested the clinical utility of the nomogram.ConclusionThe nomogram based on combined radiomics and clinical features outperformed standalone clinical or radiomics model, offering enhanced accuracy in evaluating NAC response in osteosarcoma. It held significant promise for clinical applications.
Case report and literature review of rezvilutamide in the treatment of hormone-sensitive prostate cancer
Authors: Zhang Chunlei , Ren Jie , Kang Yindong , Chang Dehui 
Published: March 2024

BackgroundProstate cancer represents a major health concern worldwide, with the treatment of metastatic hormone-sensitive prostate cancer (mHSPC) and locally advanced prostate cancer posing a particular challenge. Rezvilutamide, a new androgen receptor antagonist from China, has shown early promise; however, its real-world effectiveness and safety profile require further evidence. This case series evaluates the preliminary clinical outcomes of rezvilutamide in combination with androgen deprivation therapy (ADT), focusing on PSA response and radiological findings across various stages of prostate cancer in four patients.Case descriptionCase 1 details a 68-year-old male with low-volume mHSPC who exhibited a positive therapeutic response, demonstrated by decreasing PSA levels and improved radiographic results, despite experiencing mild side effects related to the drug. Case 2 describes a 71-year-old male with high-volume mHSPC who had a favorable outcome, with no significant changes in tumor size or metastatic spread and no negative reactions to the drug. Case 3 involves a 55-year-old male with locally advanced prostate cancer, who saw a reduction in PSA levels and a small decrease in tumor volume, yet with ongoing bladder involvement. Genetic testing showed no significant mutations. Case 4 presents a 74-year-old male with extensive metastatic disease who initially responded to the treatment but later exhibited disease advancement and an ATM gene mutation, signaling a shift to metastatic castration-resistant prostate cancer (mCRPC). This finding underscores the crucial role of genetic testing in directing future treatment, with therapies such as olaparib or chemotherapy being advised.ConclusionsRezvilutamide has shown a potential benefit in the management of mHSPC and locally advanced prostate cancer, generally with a mild safety profile. Initial positive responses, particularly in PSA decline and radiographic progression, are promising. Nevertheless, the varying responses, notably concerning genetic mutations, highlight the necessity for tailored treatment approaches. Due to the small cohort and brief follow-up period, more extensive research with larger populations and prolonged monitoring is essential to conclusively determine the benefits and safety of rezvilutamide. The utilization of genetic insights is key to refining treatment decisions and enhancing outcomes for patients with advanced prostate cancer.
Pulse shape discrimination in an organic scintillation phoswich detector using machine learning techniques
Authors: Lee Yujin , Kim Jinyoung , Koh Byoung-cheol , Yoon Young Soo , Ha Chang Hyon 
Published: March 2024

We developed machine learning algorithms for distinguishing scintillation signals from a plastic-liquid coupled detector known as a phoswich. The challenge lies in discriminating signals from organic scintillators with similar shapes and short decay times. Using a single-readout phoswich detector, we successfully identified γ radiation signals from two scintillating components. Our Boosted Decision Tree algorithm demonstrated a maximum discrimination power of 3.02 ± 0.85 standard deviation in the 950 keV region, providing an efficient solution for self-shielding and enhancing radiation detection capabilities.
Families’ experiences of the Low Arousal Approach: a qualitative study
Authors: McDonnell Andrew Austin , Page Andrea , Bews-Pugh Stephanie , Morgalla Karolina Anna , Kaur-Johal Tarendeep , Maher Mary 
Published: March 2024

BackgroundParents and carers supporting a family member presenting with behaviors of concern experience heightened stress. The Low Arousal Approach is a crisis management strategy which recognizes that stress, or physiological arousal, can be expressed through behaviors of concern. This approach aims to equip parents and carers to manage behaviors in a person-centered and non-confrontational way. There is a paucity of published research exploring the experiences of families applying this approach.MethodsSeventeen parents who had received training in the Low Arousal Approach were interviewed to gain their perspectives on supporting their family members using this approach.ResultsThematic analysis revealed themes relating to parental stress, which was related to external pressures, isolation, family stress, and challenges in their caring role. They described encountering negative narratives relating to self-criticism and negative judgments from others. Training in the Low Arousal Approach was related to being empowered through access to evidence, increased confidence, and increased ability to advocate for their family member’s needs. Low Arousal was described as a “lifestyle” that enabled increased coping for the family unit as a whole.Discussion/conclusionFindings indicate that it is vitally important to recognize the views of parents and carers, and these are equally as important as the views of professionals. We must understand parents’ and carers’ needs in order to provide adequate support.
Eye-movement reveals word order effects on comparative sentences in older adults using a verb-final language
Authors: Hwang Jihyun , Lee Seunghun J. , Sung Jee Eun 
Published: March 2024

ObjectivesThis study aimed to examine age-related differences in the comprehension of Korean comparative sentences with varying word orders by employing both offline and online measures, and to investigate how variations in word order affect sentence processing across different age groups.MethodsA total of 52 monolingual native Korean speakers, 26 young adults, and 26 older adults, completed a sentence-picture-matching task under two word order conditions: comparative-first and nominative-first. Offline measures included accuracy and response time, while an online method involved eye-tracking within the Visual World Paradigm. Data analyses were performed using linear and generalized linear mixed-effects models.ResultsOlder adults demonstrated lower accuracy and longer response times compared to younger individuals. Distinctive fixation patterns were observed, particularly in the sentential-final phrase, across different age groups. Specifically, nominative-first sentences elicited greater target advantage scores among younger adults, whereas older adults showed higher scores in comparative-first sentences.ConclusionThe study highlights the potential of comparative sentences in elucidating age-related changes in sentence comprehension. These differences were evident not only in offline tasks but also in real-time processing, as evidenced by eye-tracking data. The findings suggest distinct processing strategies employed by young and older adults and underscore the importance of considering both syntactic and semantic cues in sentence comprehension.
Systematic review and meta-analysis of neurofeedback and its effect on posttraumatic stress disorder
Authors: Voigt Jeffrey D. , Mosier Michael , Tendler Aron 
Published: March 2024

BackgroundTo date, only one systematic review and meta-analysis of randomized controlled trials (RCTs) has evaluated the effect of neurofeedback in PTSD, which included only four studies and found an uncertainty of the effect of EEG-NF on PTSD symptoms. This meta-analysis is an update considering that numerous studies have since been published. Additionally, more recent studies have included fMRI-NF as well as fMRI-guided or -inspired EEG NFMethodsSystematic literature searches for RCTs were conducted in three online databases. Additional hand searches of each study identified and of systematic reviews and meta-analyses published were also undertaken. Outcomes evaluated the effect of neurofeedback vs. a control (active, sham, and waiting list) on their effects in reducing PTSD symptoms using various health instruments. Meta-analytical methods used were inverse variance random-effects models measuring both mean and standardized mean differences. Quality and certainty of the evidence were assessed using GRADE. Adverse events were also evaluated.ResultsA total of 17 studies were identified evaluating a total of 628 patients. There were 10 studies used in the meta-analysis. Results from all studies identified favored neurofeedback’s effect on reducing PTSD symptoms including BDI pretest–posttest [mean difference (MD): 8.30 (95% CI: 3.09 to 13.52; P = 0.002; I2 = 0%)]; BDI pretest–follow-up (MD: 8.75 (95% CI: 3.53 to 13.97; P &lt; 0.00001; I2 = 0%); CAPS-5 pretest–posttest [MD: 7.01 (95% CI: 1.36 to 12.66; P = 0.02; I2 = 86%)]; CAPS-5 pretest–follow-up (MD: 10 (95% CI: 1.29 to 21.29; P = 0.006; I2 = 77%); PCL-5 pretest–posttest (MD: 7.14 (95% CI: 3.08 to 11.2; P = 0.0006; I2 = 0%); PCL-5 pretest–follow-up (MD: 14.95 (95% CI: 7.95 to 21.96; P &lt; 0.0001; I2 = 0%). Other studies reported improvements using various other instruments. GRADE assessments of CAPS, PCL, and BDI demonstrated a moderate/high level in the quality of the evidence that NF has a positive clinical effect.ConclusionBased on newer published studies and the outcomes measured, NF has demonstrated a clinically meaningful effect size, with an increased effect size at follow-up. This clinically meaningful effect appears to be driven by newer fMRI-guided NF and deeper brain derivates of it.
Socioeconomic inequalities in healthcare system efficiency in Japan during COVID-19 pandemic: an analysis of the moderating role of vaccination
Authors: Tang Yin 
Published: March 2024

BackgroundIn the context of the COVID-19 pandemic, limited research has focused on socioeconomic disparities in Local Healthcare System Efficiency (LHSE) among Japanese prefectures. This study seeks to investigate the moderating impact of vaccination on the relationship between LHSE and socioeconomic characteristics and endowmentsMethodsTo explore these relationships, we first utilized the Data Envelopment Analysis with Slack-Based Measure to measure the LHSE, based on data from Japanese prefectures during waves 2 to 5 of the pandemic. Then estimating the impact of socioeconomic variables on LHSE. Finally, we assessed the changes in the way socioeconomic variables affect LHSE before and after vaccine deployment using the Seemingly Unrelated Estimation t-test methodology.ResultsThe research findings suggest an overall reduction in LHSE disparities across various regions due to the utilization of vaccines. Particularly in areas with relatively nsufficient bed resources, a significant improvement in LHSE was observed in most regions. However, there was no evidence supporting the role of vaccine deployment in mitigating socioeconomic inequalities in LHSE. Conversely, the utilization of vaccines showed a positive correlation between the improvement in LHSE and the proportion of older adult population in regions with sufficient bed resources. In regions facing bed shortages, the enhancement of LHSE became more reliant on reducing the occupancy rate of secured beds for severe cases after the introduction of vaccination.DiscussionIn regions facing bed shortages, the enhancement of LHSE became more reliant on reducing the occupancy rate of secured beds for severe cases. This underscores the importance for policymakers and implementers to prioritize the treatment of severe cases and ensure an effective supply of medical resources, particularly secured beds for severe cases, in their efforts to improve LHSE, in the post-COVID-19 era with rising vaccine coverage.