bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early Cognitive and Language Development Characteristics of Children with Williams Syndrome in China
Authors: Yao Dan , Zeng Yan , Li Fang-fang , Shen Ji-yang , Ji Chai 
Published: September 2024

Abstract

Background: Williams syndrome (WS) is an inherited multisystem disorder characterized by cognitive and linguistic dissonance with distinct strengths and weaknesses. The aim of this studywas to investigate the characteristics of early cognitive and language development in WS children of different ages.
Methofs:106 children, aged 1-5 years, diagnosed with WS in the outpatient department of child healthcare in our hospital from September 2018 to June 2023 were included in this study. All children underwent cognitive development assessment to observe and analyze the developmental characteristics of WS children at different ages.
Results: The developmental levels of gross motor and fine motor functional areas of WS children were significantly lower than those of Global developmental delay (GDD) children, while the developmental level of language functional area of WS children was significantly higher than that of GDD children. While the language ability of WS children showed significant advantages from the age of two and remained so until the age of five. At the same time, WS children in the group basically maintained a relatively stable level in each functional area with age, and there was no difference between verbal and nonverbal intelligence quotient (IQ) in all ages.
Conclusions: The results of the present study identify a new feature that the relative prominence of language ability in early childhood of WS children is not a matter of their superiority over nonverbal ability, but rather a relative manifestation of language superiority as the language ability of WS children has remained stable relative to the developmental characteristics of other children with developmental delays whose language ability declines slowly with age. This finding can help us explore interventions that may help WS children reach their full potential, while emphasizing the need for individualized assessment and management of WS children to guide educational and rehabilitative strategies for WS children.
Developed Impact Load test to Measuring the Cohesion Energy of the Asphalt Binder
Authors: Abdali Abdulhaq Hadi 
Published: September 2024

Abstract

The cohesion of the asphalt binder plays a pivotal and effective role in evaluating the performance efficiency of the asphalt mixture under different loading and environmental conditions. This cohesion can be represented by the forces that bind the asphalt particles to each other (the structural form of asphalt particle bonding). The amount of force that causes the displacement of these particles to the point of fracture is equal to the ability of the cohesive asphalt binder to prevent this fracture, and it is usually an instantaneous force. An asphalt binder sandwich model is prepared by cutting the rocks into slices of regular thickness and then cutting them into prisms of regular shape and dimensions to suit the dimensions of the manufactured device. The asphalt bond that connects these prisms is of a known thickness. To calculate the strength of the thin asphalt binder confined between the rock prisms, a simple device was manufactured to calculate the amount of energy resulting from the collision of a specific block with the asphalt binder region, which reflects the amount of cohesion or bonding between the asphalt particles. The proposed device consists of an iron base to stabilize the asphalt bond sandwich model with a circular column to raise the hammer holder with a known and variable weight. The resistance of the asphalt binder, which depends on the cohesive forces of the particles of the material itself, increases with the increase in the thickness of the binder and also with an increase in the percentage of added additive up to 5% for both types SBS and crumb rubber.
Exploring the Self-Perceived Causes of Eating Disorders among Chinese Social Media Users with Self-Reported Eating Disorders
Authors: He Jinbo , Zhang Yucheng , Liu Zhiyuan , Barnhart Wesley , Cui Shuqi , Chen Shiting , Fu Yuru , Ji Feng , Nagata Jason , Sun Shaojing 
Published: September 2024

Abstract

Background
Even though robust evidence suggests the high prevalence of Eating disorders (EDs) in China, EDs in China are characterized by low diagnosis rates, delayed treatment-seeking, and ineffective treatments. Given that listening to patients’ perspectives and lived experiences is crucial to improving our understanding of EDs in the Chinese context, an investigation of the perceived causes of EDs in Chinese individuals with EDs represents a key step in improving the prevention and treatment of EDs in China.
Aims
To explore the perceived causes of eating disorders (EDs) based on the data from the users of a popular Chinese social media platform, Zhihu.
Methods
We extracted and analyzed the data using a content analysis. Eight specific causes that could be classified into two groups were coded, including individual factors (e.g., “body image and eating”) and sociocultural factors (e.g., “media and cultural ideals”).
Results
A total of 2079 entries regarding self-reported EDs were retained for content analysis (14.7% were anorexia nervosa, 37.6% were bulimia nervosa, and 47.7% were binge-eating disorder). More than 90% of users with self-reported EDs claimed causes belonging to individual factors, while 35–51% of users claimed sociocultural factors. “Body image and eating” (68–87%) and “psychological and emotional problems” (65–67%) were the most commonly claimed specific causes, while “traumatic life events” (13–14%), “genetics and biology” (7–13%), and “sports and health” (9–12%) were the least claimed. Chi-square independent tests showed that users with different self-reported EDs disproportionately claimed certain causes.
Conclusions
Using large-scale social media data, findings enhanced our understanding of the perceived etiology of EDs in the Chinese context from individuals with lived experiences of EDs and highlighted the variations in perceived causes across different self-reported ED types.
Clinicians’ experience of barriers and facilitators to care delivery in an ECPR service for out-of-hospital cardiac arrest: a qualitative study
Authors: Eddison Jasper , Millerchip Oscar , Rosenberg Alex , Lewinsohn Asher , Raitt James 
Published: September 2024

Abstract

Background:Out-of-hospital cardiac arrest (OHCA) survival in the UK remains overall poor with fewer than 10% of patients surviving to hospital discharge. Extracorporeal cardiopulmonary resuscitation (ECPR) is a developing therapy option that can improve the outcomes in select patients if treatment begins within an hour. Clinicians' perspectives are a pivotal consideration to development of effective systems for OHCA ECPR, but they have been infrequently explored. This study investigates clinicians' views on the barriers and facilitators to establishing effective systems to facilitate transport of OHCA patients for in-hospital ECPR.
Methods:In January 2023, Thames Valley Air Ambulance (TVAA) and Harefield Hospital (HH) developed an ECPR partnership pathway for conveyance of OHCA patients for in-hospital ECPR. The authors of this study conducted a survey of clinicians across both services looking to identify clear barriers and positive contributors to the effective implementation of the programme. The survey included questions about technical and non-technical barriers and facilitators, with free-text responses analysed thematically.
Results:Responses were received from 14 pre-hospital and 9 in-hospital clinicians’ representative of various roles and experiences. Data analysis revealed 10 key themes and 19 subthemes. The interconnected themes, identified by pre-hospital clinicians as important barriers or facilitators in this ECPR system included educational programmes; collectiveness in effort and culture; teamwork; inter-service communication; concurrent activity; and clarity of procedures. Themes from in-hospital clinicians’ responses were distilled into key considerations focusing on learning and marginal gains, standardising and simplifying protocols, training and simulation; and nurturing effective teams.
Conclusion:This study identified several clear themes and subthemes from lived clinical experience that should be considered when developing and modelling an ECPR system for OHCA. These insights may inform future development of ECPR programmes for OHCA in other centres. Key recommendations identified include prioritising education and training (including regular simulations), standardising a ‘pitstop style’ handover process, establishing clear roles during the cannulation process to including and developing standardised protocols and selection criteria. This study also provides insight into the feasibility of using pre-hospital critical care teams for intra-arrest patient retrieval in the pre-hospital arena.
Kinetic modeling and multi-objective optimization of ibuprofen synthesis using the SAO-CatBoost framework
Authors: Xiang Lang , Qu Pengfei 
Published: September 2024

Abstract

This study proposes the SAO-CatBoost framework, utilizing the Snow Ablation Optimizer (SAO) to enhance a CatBoost-based meta-model for modeling and optimizing the ibuprofen synthesis process. Initially, a database of 39,460 input combinations is created using chemical reaction theory. The enhanced meta-model, built with CatBoost, outperforms traditional optimization algorithms (Random Search, Bayesian Optimization, and Particle Swarm Optimization) in pre- dicting reaction time (RT) and conversion rate (CR). Importance analyses through SHAP values identify critical input variables impacting RT and CR, notably the concentration of the catalyst precursor (L2PdCl2), hydrogen ions (H+ ), and water (H2O). Partial dependence and interaction effects are explored to understand the interactions between input variables and their effects on reaction time and conversion rate. To optimize reaction efficiency and product selectivity, ini- tial concentrations and reaction rate constants are treated as decision variables, and NSGA-II is employed for multi-objective optimization, aiming to simultaneously minimize RT and maximize CR. Within this framework, uncertainty analysis of the meta-model is conducted under various levels using Monte Carlo simulation and Prediction Interval analysis, demonstrating a significant increase in prediction uncertainty with greater input perturbations. This study demonstrates the SAO-CatBoost framework’s effectiveness in optimizing ibuprofen synthesis, highlighting its reli- ability in achieving optimal reaction conditions in chemical engineering.
Clinical significance of a new early diagnostic model for bladder cancer based on genome-wide microarray profiling of serum exosomal lncRNAs
Authors: Zhao Liming , Tian Guang , Wang Xiaohua , Li Luning , Gao Yongli , Gao Yisheng , Wang Jinfeng 
Published: September 2024

Abstract

Purpose
The aim of our report was to recognize bladder cancer (BC)-specific serum exosome-derived long noncoding RNAs (lncRNAs) profile for early diagnosis of BC.
Methods
Potential BC-specific exosomal lncRNA indicators were discerned by genome-wide microarray profiling analysis of serum exosomes from 10 healthy participants and 10 early-stage BC patients (Ta and T1), followed by multi-stage validation through quantitative real-time PCR (qRT-PCR) in BC cells, culture solution as well as 200 serum specimens and 50 tissue specimens from non-muscle-invasive bladder cancer (NMIBC) patients. The diagnostic panel was established using logistic regression and evaluated by receiver-operating characteristic (ROC) curve.
Results
In the training stage, a diagnostic panel was constructed based on three up-regulated exosomal lncRNAs (G023016, RP11-553N19.1 and LINC0087) in NMIBC patients compared with healthy controls, yielding an area under ROC curve (AUC) of 0.827. We verified tumor-derived origin of these three lncRNAs which existed steadily in serum because of being enclosed in exosomes. The three-lncRNA panel was demonstrated to perform well in terms of NMIBC diagnosis, revealing AUC values of 0.809 and 0.812 respectively in the following expanded validation stage and double-blind stage which was demonstrated to be significantly superior to that of urine cytology in double-blind stage (AUC = 0.630) (P < 0.0001). Moreover, serum exosome-derived G023016 significantly associated with tumor grade and TNM stage (P = 0.006 and P < 0.001, respectively), and LINC0087 significantly associated with TNM stage (P = 0.023).
Conclusion
The three-exosomal lncRNA signature could function as qualified blood-based non-invasive indicator for early diagnosis of BC.
Prostate cancer-derived exosomal PSM-E inhibits macrophage M2 polarization to suppress tumor invasion and metastasis through the RACK1/FAK/ERK pathway
Authors: Qin Xingliang , Niu Rouxi , Tan Yongyao , Huang Yuxin , Ren Weishu , Zhou Weiwei , Wu Huiquan , Zhang Junlong , Xu Mingze , Zhou Xiang , Guan Hongyu , Zhu Xun , Chen Yu , Cao Kaiyuan 
Published: September 2024

Abstract

Background
It is well-established that understanding the mechanism of prostate cancer (PCa)-associated metastasis is paramount for improving its prognosis. Metastasis is known to involve the communication between tumor-associated macrophages (TAMs) and tumor cells. Exosomes are crucial in mediating this intercellular communication within the tumor microenvironment. Nonetheless, the role of exosomal proteins in PCa metastasis is not yet fully understood. Here, we investigated the mechanisms of prostate cancer-derived exosomal PSM-E on regulating macrophage M2 polarization to suppress tumor invasion and metastasis.
Methods
PSM-E levels in exosomes were detected by transmission electron microscopy and Western blotting analysis. The diagnostic value of urine-derived exosomal PSM-E in PCa were evaluated by LC-MS/MS, correlation analysis, and ROC curves analysis. The mechanisms underlying the inhibitory effect of exosomal PSM-E on the M2 polarization of macrophages was investigated by co-IP, IHC staining, and PCa tumorigenesis model.
Results
We revealed that exosomal PSM-E is upregulated in exosomes derived from the serum and urine of PCa patients. Clinically, an elevated exosomal PSME expression in urine is significantly correlated with an advanced pathological tumor stage and a high Gleason score. Our research also revealed that exosomal PSM-E inhibits prostate cancer cell proliferation, invasion, and metastasis by suppressing macrophage polarization in vitro and in vivo. Furthermore, we provided compelling evidence that exosomal PSM-E inhibits M2 polarization of macrophages by recruiting RACK1 and suppressing the ERK and FAK signaling pathways, consequently suppressing PCa invasion and metastasis. Furthermore, we found that the protease-associated domain of PSM-E and the fourth tryptophan-aspartate repeat of RACK1 are crucial for the interaction between PSM-E and RACK1.
Conclusions
Notably, exosomes carrying PSM-E from PCa urine could potentially serve as a biomarker for PCa, and targeting exosomal PSM-E may represent a strategy for preventing tumor progression in this patient population.
Edge-Guided Multi-Scale Adaptive Feature Fusion Network for Liver Tumor Segmentation
Authors: Zhang Tiange , Liu Yuefeng , Zhao Qiyan , Xue Guoyue , Shen Hongyu 
Published: September 2024

Abstract

Automated segmentation of liver tumors on CT scans is essential for aiding diagnosis and assessing treatment. Computer-aided diagnosis can reduce the costs and errors associated with manual processes and ensure the provision of accurate and reliable clinical assessments. However, liver tumors in CT images vary significantly in size and have fuzzy boundaries, making it difficult for existing methods to achieve accurate segmentation. Therefore, this paper proposes MAEG-Net, a multi-scale adaptive feature fusion liver tumor segmentation network based on edge guidance. Specifically, we design a multi-scale adaptive feature fusion module incorporating multi-scale information better to guide the segmentation of tumors of different sizes. Additionally, to address the problem of blurred tumor boundaries in images, we introduce an edge-aware guidance module to improve the model's feature learning ability under these conditions. Evaluation results on the liver tumor dataset (LiTS2017) show that our method achieves a Dice coefficient of 71.84% and a VOE of 38.64%, demonstrating the best performance for liver tumor segmentation in CT images.
Cognivue Clarity ® Characterizes Mild Cognitive Impairment and Alzheimer’s Disease in Biomarker Confirmed Cohorts in the Bio-Hermes Study
Authors: Galvin James , Kleiman Michael J. , Estes Paul W. , Harris Heather M. , Fung Ernest 
Published: September 2024

Abstract

The Bio-Hermes Study was a cross-sectional observational study designed to develop a database of blood-based and digital biomarkers to improve detection of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). We examined the ability of Cognivue Clarity® to (a) detect MCI and AD in clinical diagnostics groups, (b) determine the presence of amyloid, and (c) distinguish between biomarker-confirmed groups. Bio-Hermes enrolled 887 participants who completed both Cognivue Clarity and amyloid PET scans (388 Cognitively Normal, 282 MCI, 217 Probable AD). Cognivue Clarity differentiated between Cognitively Normal, MCI, and probable AD in clinical cohorts, amyloid positive from amyloid negative individuals, and True Controls from MCI due to AD and AD in biomarker-confirmed cohorts (all p<.001) with large effect sizes. Cognivue Clarity correlated with amyloid PET and plasma amyloid and pTau (all p<.001). In biomarker confirmed groups, Cognivue Clarity had a positive likelihood ratio of 2.17, a negative likelihood ratio of 0.29, and a diagnostic odds ratio of 7.48. Cognivue Clarity detected cognitive impairment and differentiated between both clinically and biomarker defined MCI and AD groups. The use of Cognivue Clarity could assist with identification of MCI-AD or AD for inclusion into current treatment protocols or for enriching recruitment into clinical trials.
Trial Registration: ClinicalTrials.gov (NCT04733989).
Electrostatic Assembly of Graphene@SiO2 Composite for Enhanced Dispersive Solid-Phase Extraction: Targeting Eight Pesticide Residues
Authors: Liu Sheng , Li Bo , Xu Jian , Yu Yang , Zhu He , Li Zhen , Zhang Zhaoxue , Lv Mei , Wang Litao 
Published: September 2024

Abstract

As a new carbon nanomaterial, Graphene (Gr) has attracted wide attention in the field of separation and analysis because of its large specific surface area and strong hydrophobicity. A highly efficient and selective graphene/SiO2 (Gr/SiO2) dispersive solid-phase extraction (d-SPE) material was prepared through electrostatic assembly. This process involved the combination of negatively-charged poly (sodium 4-styrenesulfonate) (PSS) mediated GS (denoted as PSS-GS) and positively-charged SiO2, modified with triethoxy silane amino. The precursor material was characterized using FESEM. We evaluated the extraction performance of this new sorbent with eight pesticide residues, using the HPLC-MS method. The sorbent demonstrated excellent recovery rates for the pesticide residues under various frequency of use conditions and pH levels. It showed that the SiO2 and Gr have synergistic extraction effect, and the composite material has good stability and reusable, Ultimately, this newly developed d-SPE material was successfully applied in the analysis of fruit juice samples, yielding good recovery rates in the range of 82.18 to 117.49%.
Combining Medical Images and Biomechanical Data in Sports Injury Prediction Models
Authors: Cai Weixia , Zhu Jintao , Zhuang Xueqin 
Published: September 2024

Abstract

This article combined medical images and biomechanical data to construct a sports injury prediction model, solving the issues of incomplete data acquisition and analysis, lack of comprehensive prediction models, insufficient consideration of individual differences, lack of real-time monitoring and preventive measures, and limited technical means in traditional aerobics sports injury research. It studied the collection of a large number of MRI and CT images, using median filtering and Gaussian filtering for denoising processing, and image enhancement through histogram equalization. Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) can be used to extract and fuse features from preprocessed images and biomechanical data. The motion capture system and force platform collect joint angles, muscle strength, motion trajectory and other data, and integrate medical images and biomechanical data through multimodal fusion methods. The constructed prediction model is based on the extraction and integration of key features, combined with individual differences to provide personalized injury prevention recommendations. The system has developed a real-time monitoring function, which collects data in real time through sensors and wearable devices, conducts response time testing using the performance testing tool Apache JMeter, and evaluates the accuracy of warnings through a confusion matrix. The experimental results show that the constructed model achieves an accuracy of 85%, a precision of 82%, a recall rate of 90%, and an F1 value of 86%, all of which are superior to traditional methods in various indicators. The system designed in this article improves the accuracy and real-time performance of predicting injuries in aerobics, providing reliable prevention and monitoring methods for athletes.
Emotional overload in bulimia nervosa: an ERP study of emotion processing and regulation
Authors: Vuillier Laura , Wang Ziyi , Hassan Sanjidha , Harrison Amy , Somerville Matthew P. , He Xun 
Published: September 2024

Abstract

Objective
People with bulimia nervosa (BN) self-report difficulties processing and regulating emotions. However, self-reports have been shown to be biased, particularly with people with BN who have difficulties describing their emotions. Self-reports also cannot easily disentangle between early processing and later regulatory stages, so it is not clear whether people with BN really do process their emotions more intensely or whether this is due to the aftermath of regulatory difficulties. This study aimed to use an objective way to measure (1) whether people with BN process their emotions with higher intensity compared to healthy controls (HC) and (2) whether they can successfully implement an emotion regulation strategy called cognitive reappraisal.
Methods
We developed a neuroimaging task using electroencephalography to answer these questions, using the Late Positive Potential (LPP) as an objective measure of emotional arousal at the processing and regulatory stages. We tested the task in females with BN (N = 32) and matched HC (N = 35).
Results
We found that our BN group showed higher LPP compared to our HC group when viewing emotional pictures, demonstrating increased emotional intensity at the processing stage. We also found that our BN group had difficulties successfully implementing cognitive reappraisal to reduce emotional arousal.
Discussion
This suggests that people with BN process their emotions with higher intensity and struggle to implement subsequent cognitive reappraisal strategies. This has direct implications for clinicians who should be aware that when evoking affect in treatment, people with BN may need greater support in understanding and managing their emotions.