bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bioinformatics analysis of predictive value of EZH2 in early breast cancer
Authors: Mao Enwen , Sun Lei 
Published: September 2024

Abstract

Background
The breast cancer is still considered the second leading cause of cancer death in women, although in high-risk individuals through breast ultrasound, mammography and breast magnetic resonance tomography (such as the MRT) imaging screening in the early diagnosis of cancer, but still urgently needed for the diagnosis and treatment of early breast cancer, especially breast cancer to discover new biomarkers.
Methods
The gene chip data were retrieved from GEO database to screen the differentially expressed genes (DEG) in breast cancer.The expression of DEG was verified and the prognostic value was evaluated using GEPIA databases.The protein-protein interaction (PPI) network was plotted with STRING, and Cytoscape was used for cell map visualization. Timer database was used to analyze the correlation between DEGs and immune infiltration level in breast cancer, and Kaplan-Meier plotter was used to analyze the overall survival of the screened target gene in breast cancer patients.
Results
The functions of target genes were mainly in cell division, cell proliferation and signal transduction. These highly expressed genes are associated with poor prognosis in breast cancer patients, among which we found that EZH2 is of great significance for the diagnosis and prognosis of early breast cancer. The enrichment analysis of its functions and pathways includes PI3K-AKT signaling pathway, MAPK signaling pathway, protein binding, cell cycle, etc.EZH2 was positively correlated with immune infiltration cells in patients with breast cancer.
Conclusion
EZH2 in breast cancer may be a useful target for diagnosis and treatment of early breast cancer.
Comparison of different iterative reconstruction algorithms with contrast-enhancement boost technique on the image quality of CT pulmonary angiography for obese patients
Authors: Ye Mei , Wang Li , Xing Yan , Li Yuxiang , Zhao Zicheng , Xu Min , Liu Wenya 
Published: September 2024

Abstract

Objective
To evaluate the effect of contrast-enhancement-boost (CE-boost) postprocessing technique on improving the image quality of obese patients in computed tomography pulmonary angiography (CTPA) compared to hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR) algorithms.
Methods
This prospective study was conducted on 100 patients who underwent CTPA for suspected pulmonary embolism. Non-obese patients with a body mass index (BMI) under 25 were designated as group 1, while obese patients (group 2) had a BMI exceeding 25. The CE-boost images were generated by subtracting non-contrast HIR images from contrast-enhanced HIR images to further improve the visibility of pulmonary arteries. The CT value, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively assessed. Two chest radiologists independently reviewed the CT images (5, best; 1, worst) across three subjective characteristics including diagnostic confidence, subjective image noise, and vascular contrast.
Results
CE-boost had significantly higher CT values than HIR and MBIR in both groups (all p < 0.001). MBIR yielded the lowest image noise compared with HIR and CE-boost (all p < 0.001). The SNR and CNR of the MPA were significantly higher in CE-boost than that in MBIR (all p < 0.05), with HIR showing the lowest values (all p < 0.001). Group 2 MBIR received significantly better subjective image noise scores, while the diagnostic confidence and vascular contrast scored highest with the group 2 CE-boost (all p < 0.05).
Conclusion
Compared to the HIR algorithm, both CE-boost technique and MBIR algorithm can improve the image quality of CTPA in obese patients. CE-boost had the greatest potential in increasing the visualization of pulmonary artery and its branches.
A Finger on the Pulse of Cardiovascular Health: Estimating Blood Pressure with Smartphone Photoplethysmography-Based Pulse Waveform Analysis
Authors: Liu Ivan , Liu Fangyuan , Zhong Qi , Ni Shiguang 
Published: September 2024

Abstract

Utilizing mobile phone cameras for continuous blood pressure (BP) monitoring presents a cost-effective and accessible approach, yet it is challenged by limitations in accuracy and interpretability. This study introduces four innovative strategies to enhance smartphone-based photoplethysmography for BP estimation (SPW-BP), addressing the interpretability-accuracy dilemma. First, we employ often-neglected data-quality improvement techniques, such as height normalization, corrupt data removal, and boundary signal reconstruction. Second, we conduct a comprehensive analysis of thirty waveform indicators across three categories to identify the most predictive features. Third, we use SHapley Additive exPlanations (SHAP) analysis to ensure the transparency and explainability of machine learning outcomes. Fourth, we utilize Bland-Altman analysis alongside AAMI and BHS standards for comparative evaluation. Data from 127 participants demonstrated a significant correlation between smartphone-captured waveform features and those from standard BP monitoring devices. Employing multiple linear regression within a cross-validation framework, waveform variables predicted systolic blood pressure (SBP) with a mean absolute error (MAE) of 9.86 ± 6.78 mmHg and diastolic blood pressure (DBP) with an MAE of 8.01 ± 5.15 mmHg. Further application of Random Forest models significantly improved the prediction MAE for SBP to 8.91 ± 6.30 mmHg and for DBP to 6.68 ± 4.54 mmHg, indicating enhanced predictive accuracy. Correlation and SHAP analysis identified key features for improving BP estimation. However, Bland-Altman analysis revealed systematic biases, and MAE analysis showed that the results did not meet AAMI and BHS accuracy standards. Our findings highlight the potential of SPW-BP, yet suggest that smartphone PPG technology is not yet a viable alternative to traditional medical devices for BP measurement.
Relationships between Empathy, Executive Functions, and Internalizing and Externalizing Symptoms in Early Adolescents
Authors: Yetim Onat , Çakır Resul , Tamam Lut 
Published: September 2024

Abstract

Background
Previous studies have shown associations between internalizing and externalizing symptoms, executive functions, and empathy. However, the mechanisms that affect this relationship remain unclear. This study employed regression analysis to explore the predictive effect of internalizing and externalizing symptoms and executive functions on empathy.
Method
Our study consisted of three consecutive stages. In the first stage, we assessed 2150 adolescents’ parents of 2150 adolescents aged 10–12 years using the Strengths and Difficulties Questionnaire to determine which participants should be included in the subsequent stages. In the second stage, we conducted a pilot study with 50 participants to assess the validity of the assessment system and the six film scenes to be used in the following stage. Finally, in the third stage, we obtained the participants' state empathy, trait empathy, and executive functioning.
Results
The regression analysis showed that working memory performance (β = 0.261) and externalizing symptoms (β = -0.157) predicted cognitive empathy, but only externalizing symptoms predicted affective empathy (β = -0.193).
Conclusion
This study highlights the effect of externalization on both cognitive and affective empathy and the effect of working memory on cognitive empathy. These findings may serve to inform psychological interventions to improve empathic abilities in early adolescence.
The involvement of 5-HT was necessary for EA-mediated improvement of post-stroke depression
Authors: Yao Lulu , Deng Bing , Di Wenhui , Long Haoxi , He Qian , Jiang Zhiyuan , Nan Taiyu , Gu Jun , Huang Keni , Li Hongtao , Xu Nenggui 
Published: September 2024

Abstract

The prevalence of depression is as high as about 30% within five years after stroke, while there is still no breakthrough of the Western medical treatments for post-stroke depression (PSD) in clinical practice. The traditional acupuncture treatment is practiced to be effective for the therapy of PSD, but its mechanism still needs to be elucidated. With a combination of methods, including behavioral testing, in vivo electrophysiological recording, mRNA sequencing, immunofluorescence, in vivo fiber recording, and genetic modulation, this study showed that electroacupuncture (EA) at Baihui (GV20) and Shenting (GV24) acupoints improved the depressive-like behaviors and neuronal electrophysiological activities in PSD model mice, which was established by bilateral injection of collagenase IV into the medial prefrontal cortex (mPFC). Moreover, it was found that the EA-mediated improvement was comparable to that of fluoxetine. The mRNA sequence analysis indicated that the 5-hydroxytryptamine (5-HT) system was involved in the pathogenesis of PSD. Meanwhile, the number of 5-HT positive neurons in the dorsal raphe nucleus (DRN) and 5-HT transmitter in the mPFC was significantly decreased, and ablation of neurons in the DRN could prevent the efficacy of EA. Together, our results have provided the insight of the biological mechanism underlying acupuncture in the treatment of PSD and revealed the scientific connotation of acupuncture in both clinical and scientific value.
Investigating the Impact of Land Transfer on Household Livelihood Vulnerability: An Empirical Study across Five Provinces in China
Authors: Liu Bo , LI LIANJUN , LIAO Cairong 
Published: September 2024

Abstract

In the context of global agricultural transformation and rural development, land transfer, as an essential means to optimize land resource allocation, has received increasing attention regarding its influence on the vulnerability of rural households' livelihoods. Based on the questionnaire survey data of 1848 farmers from five provinces in China, this paper uses the AHP entropy weighting method to conduct empirical analysis by constructing an analytical framework that integrates the Sustainable Livelihood framework and the Risk Exposure-Sensitivity and Adaptive Capacity framework to conduct an in-depth analysis of the impact of land transfer on farmers in China. It also examines the impact of land transfer on the livelihood vulnerability of different households and suggests strategies to mitigate vulnerability. The results show that land transfer significantly affects rural households' livelihood vulnerability while increasing agricultural production efficiency. It has the most significant impact on the livelihood vulnerability of purely agricultural households and the most negligible impact on non-agricultural households. Different types of households face different risks and sensitivities, but pure agricultural households have the most significant adaptive capacity and resilience. A higher share of agricultural income corresponds to a greater vulnerability of the household's livelihood. On this basis, the following policy recommendations are made: Constructing and perfecting the land circulation mechanism is imperative to ensure farmers' rights and optimize resource allocation. Furthermore, strengthening the land circulation information service system is crucial for enhancing farmers' awareness and facilitating policy implementation. Promoting income diversification and agricultural skill upgrading for farmers is essential to enhance the resilience of rural households' livelihoods. Addressing farmers' psychological changes in land circulation by establishing support systems is vital to coping with uncertainty and risk.
Effects of CPAP treatment on arterial stiffness and inflammatory factors in patients with coronary heart disease complicated with OSA
Authors: Wang Liang , Wang Yuanqi , Jiao Tiantian , Xu Linghao , Ji Endong , Tapu Sakibur Rahman , Liu Yehong , Li Jiming 
Published: September 2024

Abstract

Background Continuous Positive Airway Pressure (CPAP) treatment brings more benefits than risks to most coronary heart disease (CHD) patients with obstructive sleep apnea (OSA). However, the pathophysiological mechanism by which CPAP treatment improves the prognosis of patients with CHD and OSA remains unclear. The purpose of this study was to clarify whether CPAP can improve arterial stiffness and inflammatory factor levels in CHD patients with OSA, and to further improve prognosis.
Method 59 patients with coronary heart disease complicated by moderate to severe sleep apnea were divided into a CPAP treatment group (CPAP+coronary heart disease standard treatment) and a control group (only coronary heart disease standard treatment). Peripheral blood test reports were collected and pulse wave velocity (PWV) measurements were performed for each patient at the beginning, 3 months, and 6 months of treatment.
Results After 6 months of treatment, the CPAP group showed more significant improvement in the levels of inflammatory factors such as WBC, N, CRP, IL-6, PCT, and PWV than the control group.
Conclusion After active treatment with CPAP, arterial stiffness and inflammatory cytokine levels in patients with coronary heart disease and OSA improved. This association should be given more attention in clinical practice, and sleep apnea should be actively treated. The early initiation of CPAP treatment can improve patient prognosis.
Medium-term outcomes of High-Intensity Focused Ultrasound (HIFU) focal treatment for primary localized prostate cancer: Single-center study
Authors: Deleuze Claire , Suartz Caio Vinícius , Rozet François , Rodriguez-Sanchez Lara , Lanz Camille , Macek Petr , Mombet Annick , Cathala Nathalie , Cathelineau Xavier , Barret Eric 
Published: September 2024

Abstract

Background
Focal therapy maintains local control of prostate cancer (PCa) while preserving part of the healthy prostate parenchyma in order to limit the functional impact. This study has evaluated the medium-term oncological and functional outcomes of primary focal HIFU therapy in patients with localized prostate cancer.
Methods
From 2009 to 2019, 256 patients with low- or intermediate-risk PCa (unilateral positive biopsy ISUP grade 1 to 3, ≤cT2b and PSA ≤15ng/ml) were included. Follow-up with regular and MRI was performed. All patients had systematic follow-up biopsies at 1 year and in case of suspected recurrence. Failure was defined by any positive biopsy in the treated area. Univariate and multivariate analyses were performed to identify failure-predictive factors. Urinary continence and erectile function were analyzed.
Results
The median age was 68.1 years (IQR: 62.3-72.2), and the median follow-up was 5.2 years (IQR: 3.0-7.1). 118 (46.1%) patients were considered in HIFU failure because of positive control biopsy in a treated area, and 66 had clinically significant cancer. 138 patients (53.9%) had local control of PCa after primary HIFU (95 had negative biopsies, and 43 had positive biopsies in non-treated areas).
Failure-free survival at 2 and 4 years were 67.3% (95% CI 57.5-76.1) and 53.8% (95% CI 44.8-63.3). No death from PCa was reported. PSA density (PSA-D) (OR: 0.55, 95% CI 0.31-0.97) was found to be an independent predictive factor of focal HIFU failure (p=0.041). The rates of erectile dysfunction and urinary incontinence were 7% and 1.6%.
Conclusion
Focal HIFU treatment provides satisfactory medium-term disease control in more than half of the patients with limited morbidity. Preoperative PSA density was significantly associated with failure. in the future, patient selection will have to take into account additional parameters if we want to further improve treatment results.
Patient summary: We analyzed the medium-term oncological and functional outcomes of primary focal HIFU therapy in patients with localized prostate cancer. The treatment provides a mid-term disease control in more than half of the patients with limited morbidity. More rigorous patient selection, including PSA density, should lead to improved oncologic outcomes of focal HIFU.
A simple predictive model for sarcopenia based on the calf muscle maximum circumference
Authors: Wei An , Zou Yan , Tang Zhen-Hua , Guo Feng , Zhou Yan 
Published: September 2024

Abstract

Background: The correlation between calf circumference and sarcopenia has been demonstrated, but the correlation between the calf muscle maximum circumference and sarcopenia has not been studied. This study aimed to explore the relationship between the two and to construct a simple model to predict sarcopenia in hospitalized elderly patients.
Methods: This was a retrospective controlled study of patients >60 years of age hospitalized in the geriatric department of Hunan Provincial People's Hospital. The patients were thoroughly evaluated by questionnaires, laboratory, and ultrasound examinations, including measuring muscle thickness and calf muscle maximum circumference using ultrasound. Patients were categorized into sarcopenia and non-sarcopenia groups according to the consensus for diagnosis of sarcopenia recommended by the Asian Working Group on Sarcopenia 2019 (AWGS2). Independent predictors of sarcopenia were identified by univariate and multivariate logistic regression analyses, and a predictive model was developed and simplified. The prediction performance of the models was assessed using sensitivity, specificity, and area under the curve (AUC) and compared with independent predictors.
Results: We found that patient age, albumin level(ALB), brachioradialis muscle thickness (BRMT), gastrocnemius lateral head muscle thickness(Glh MT), and calf muscle maximal circumference(CMMC) were independent predictors of sarcopenia in hospitalized elderly patients. A predictive model was developed and simplified as Logistic P = - 4.5 + 1.4 × Age + 1.3 × ALB + 1.6 × BR MT + 3.7 × CMMC + 1.8 × Glh MT, and the diagnostic optimal cutoff value of the equation was 0.485. The sensitivity, specificity, and AUC of the model were 0.884(0.807-0.962), 0.837(0.762-0.911), and 0.927(0.890-0.963), respectively, which were significantly higher than those of the independent predictors.
Conclusion: We constructed a simple predictive model for sarcopenia including five variables: age, ABL level, BR MT, Glh MT, and CMMC. The AUC of the model is 0.927, which can help clinicians predict less muscle disease in patients with senile inpatients quickly.
Noninvasive brain stimulation during EEG improves machine learning classification in chronic stroke
Authors: Suresh Rishishankar E. , Zobaer M. S. , Triano Matthew J. , Saway Brian F. , Rowland Nathan C. 
Published: September 2024

Abstract

Background:
In individuals with chronic stroke and hemiparesis, noninvasive brain stimulation (NIBS) may be used as an adjunct to therapy for improving motor recovery. Specific states of movement during motor recovery are more responsive to brain stimulation than others, thus a system that could auto-detect movement state would be useful in correctly identifying the most effective stimulation periods. The aim of this study was to compare the performance of different machine learning models in classifying movement periods during EEG recordings of hemiparetic individuals receiving noninvasive brain stimulation. We hypothesized that transcranial direct current stimulation, a form of NIBS, would modulate brain recordings correlating with movement state and improve classification accuracies above those receiving sham stimulation.
Methods:
Electroencephalogram data were obtained from 10 participants with chronic stroke and 11 healthy individuals performing a motor task while undergoing transcranial direct current stimulation. Eight traditional machine learning algorithms and five ensemble methods were used to classify two movement states (a hold posture and an arm reaching movement) before, during and after stimulation. To minimize compute times, preprocessing and feature extraction were limited to z-score normalization and power binning into five frequency bands (delta through gamma).
Results:
Classification of disease state produced significantly higher accuracies in the stimulation (versus sham) group at 78.9% (versus 55.6%, p < 0.000002). We observed significantly higher accuracies when classifying stimulation state in the chronic stroke group (77.6%) relative to healthy controls (64.1%, p < 0.0095). In the chronic stroke cohort, classification of hold versus reach was highest during the stimulation period (75.2%) as opposed to the pre- and post-stimulation periods. Linear discriminant analysis, logistic regression, and decision tree algorithms classified movement state most accurately in participants with chronic stroke during the stimulation period (76.1%). For the ensemble methods, the highest classification accuracy for hold versus reach was achieved using low gamma frequency (30–50 Hz) as a feature (74.5%), although this result did not achieve statistical significance.
Conclusions:
Machine learning algorithms demonstrated sufficiently high movement state classification accuracy in participants with chronic stroke performing functional tasks during noninvasive brain stimulation. tDCS improved disease state and movement state classification in participants with chronic stroke.
Differential Prognostic Value of Residual Nodal Burden in Breast Cancer Subtypes
Authors: Thai Christine Hong Ngoc Che , An Selena J. , Haase Conner R. , Selfridge Julia M , Agala Chris B. , Gallagher Kristalyn K. , Spanheimer Philip M. 
Published: September 2024

Abstract

Purpose
Residual cancer burden (RCB) index after neoadjuvant chemotherapy (NAC) is highly prognostic in patients with breast cancer (BC) but does not account for subtype or the precise impact of residual nodal burden (RNB). We aimed to precisely define the effect of RNB on survival by subtypes.
Methods
Adult women with non-metastatic BC diagnosed from 2006–2021 in the National Cancer Database (NCDB) who received NAC followed by surgery within 8 months were included. RNB was also evaluated as a predictor of mortality with multivariable logistic regression. Kaplan-Meier analyses were performed to compare overall survival.
Results
51,917 patients were included. After adjustment, ypN stage was the strongest predictor of mortality, with an odds ratio (OR) of 2.24 (95% CI 2.08–2.41) for ypN1 vs ypN0 and increased with increasing nodal burden - ypN2 vs ypN0 OR 5.03, 95% CI 4.60–5.51 and ypN3 vs ypN0 OR 8.85, 95% CI 7.88–9.93. Stratification of survival curves with higher RNB is most pronounced for triple-negative breast cancer (TNBC) with an absolute difference of 64% in 5-year overall survival between ypN0 and ypN3 patients, and lowest for the ER+/HER2- subtype with a 25% absolute difference in 5-year OS between ypN0 and ypN3 patients. On interaction analysis, ypN status was a stronger predictor of mortality for the TNBC subtype compared to other subtypes.
Conclusion
RNB has a significantly different impact on survival by BC subtypes. Future study of optimal therapeutic strategies for patients with residual nodal disease after NAC should account for subtype specific differences in prognosis.