bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing Breastfeeding Initiation and Duration in Women With a Body Mass Index ≥30KG/M2: Developing an Intervention From Theory to Acceptability
Authors: Lyons Stephanie , Currie Sinead , Peters Sarah , Lavender Dame Tina , Turnbull Emilie , Bhatia Ria , Khan Zaynab , Smith Debbie 
Published: November 2024

Abstract

Background
Breastfeeding has many health benefits for both mother and child, but rates of initiation and duration amongst women with a BMI ≥ 30kg/m2 are low. Few interventions aiming to increase breastfeeding in this group have been successful; likely because existing interventions do not target psychological factors. Therefore, this study aimed to design and explore the acceptability of a newly developed psychological intervention to increase breastfeeding initiation and duration in women with a BMI ≥ 30kg/m2.
Methods
The Medical Research Council’s Complex Intervention Development Framework was followed to design the intervention. A ‘breastfeeding workbook’ was developed, based on literature and psychological theory, and filled with tailored information and activities. A Patient and Public Involvement group of women with a BMI ≥ 30kg/m2 who had breastfed, health professionals and researchers were consulted throughout the process, selecting the intervention content, format and delivery methods. Thirteen women with a BMI ≥ 30kg/m2 then reviewed the workbook and took part in in-depth qualitative interviews to assess its acceptability. Thematic analysis was conducted, informed by the Theoretical Framework of Acceptability version 2 (TFAv2).
Results
The findings reveal the intervention is acceptable to the target population; women believe the intervention shows promise for increasing breastfeeding initiation and duration, is representative of their experiences, is accessible, and aligns with their belief system. They valued that the intervention provided realistic expectations of breastfeeding, options to overcome the challenges of breastfeeding in the real-world and supported them to breastfeed without inducing stigma or shame regarding their weight or infant feeding practices. Suggestions for improvement are also included, such as incorporating audio and video content as alternatives to written text and translation options.
Conclusions
An acceptable, psychological intervention was developed to increase breastfeeding initiation and duration in women with BMIs ≥ 30kg/m2. These findings can inform maternity and breastfeeding care, future research directions and intervention development.
Effect of Porosity on Microstructure, Mechanical Properties and In Vivo Test of TiNbSn Alloy Produced via Powder Metallurgy Route
Authors: Çakmak Ömer , Kaya Mehmet , Karakurt Eyyüp Murat , Annaç Ebru Elibol , Köm Mustafa 
Published: November 2024

Abstract

Ti6Al4V alloy are widely utilized as load-bearing implant due to its acceptable strength properties and good corrosion resistance, including a relatively low young modulus. However, concerns about its use in certain clinical applications arise from the known toxicity of aluminium nickel and vanadium. To address this issue, a new type of porous Ti16Nb4Sn (at. %) alloys, which possess a relatively low Young's modulus and good cytotoxicity properties, was developed by using a powder metallurgy process combined with a spacer. Microstructure examination of test alloys was done via scanning electron microscopy, optical microscopy, energy dispersive spectroscopy, and X-ray spectra. A uniaxial compression test was conducted for assessing the biomechanical performances of the alloys. Lastly, in vivo test was analysed by using rats. Summarizing all the results, randomly distributed micro and macropores with sharp corner were observed in the microstructures, which led to a significant reduction in Young's modulus from 91 GPa to 20 GPa. In addition, no toxic or allergic interaction between the alloys and bone tissue was observed, which revealed that Ti16Nb4Sn alloys achieved in this work may be considered as a promising load-bearing implant.
Comprehensive bioinformatics analysis identifies biomarkers for cardiovascular risk in end-stage renal diseases
Authors: Lu Fangfang 
Published: November 2024

Abstract

Objective
End-stage renal disease (ESRD) can increase the risk of cardiovascular disease (CV). We aimed to investigate the pathways and mechanisms associated with potential protective genes linked to CV (CVP).
Methods
We conducted a systematic bioinformatics analysis using publicly available datasets from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified in patients with ESRD with and without arrhythmia using stringent statistical criteria. Functional enrichment analyses were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to elucidate the biological roles of these DEGs. Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the identified biomarkers for CV risk prediction.
Results
Our analysis revealed a distinct set of DEGs in ESRD patients with arrhythmia compared to those without arrhythmia. GO and KEGG pathway analyses indicated that these DEGs were involved in key biological processes and pathways relevant to cardiovascular disorders and renal function, including wound healing, platelet activation, and fluid-level regulation. Moreover, this study identified four downregulated genes (ABLIM3, TREML1, VCL, and AVPR1A) and two upregulated genes (BHLHA15 and FZD8), which exhibited significant alterations in expression levels, with some showing robust discriminatory power, as evidenced by high Area Under the Curve (AUC) values in ROC analysis for predicting patients without CV risks.
Conclusion
This study identified a panel of genes (including a miRNA and an unknown gene) in the plasma that may serve as promising biomarkers for predicting arrhythmia risk in ESRD patients. These findings provide a foundation for future validation studies aimed at integrating plasma biomarkers into clinical practice to improve risk stratification and management of CV in patients with ESRD.
Stachys tibetica derived silver nanoparticles: A robust multifunctional material for enhanced biological activity and photocatalytic properties
Authors: Dar Naseer Ahmad , Dar Parvaiz A , Qadir Mahpara , Shah Wajaht Amin 
Published: November 2024

Abstract

Stachys tibetica, a significant medicinal plant was collected from Ladakh (India) and subjected to extraction. The extract was titrated with AgNO3 at 50ºC to obtain silver nanoparticles with plant extract acts as a reducing and capping agent. The eco-friendly synthetic procedure utilizes the phytochemicals in Stachys tibetica, ensuring a sustainable and non-toxic approach to nanoparticle production. The characterization of the silver nanoparticles was conducted using various techniques, including Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and dynamic light scattering (DLS). Field emission scanning electron microscopy (FE-SEM) was utilized to examine the surface morphology, revealing the irregular and rugged spherical shape of the synthesized nanoparticles. Stachys tibetica-derived silver nanoparticles (AgNPs) act as a versatile and robust multifunctional material with proficient bioactivity and catalytic properties. The synthesized silver nanoparticles displayed effective antioxidant and antimicrobial properties against Bacillus Cereus, Pseudomonas, Escherichia coli, and S.Aeureus. Additionally, the green nanoparticles degraded Rhodamine-B under sunlight irradiation within 1 hour at a rate constant of 0.066 min− 1.
Development and validation of an in-hospital mortality prediction scoring system for patients with intra-abdominal sepsis: data from two large cohorts
Authors: Zhang Jianjun , Chen Yuhong , Zhao Congcong , Wang Jinrong , Hu Zhenjie 
Published: November 2024

Abstract

Object:
Intra-abdominal infection is often the first or second source of sepsis. This study aims to develop and validate a practical predictive tool to assess the risk of in-hospital mortality in patients with intra-abdominal sepsis.
Methods
This study used structured query language to extract clinical data of patients with abdominal sepsis from the MIMIC-IV (Intensive Care Medicine Information Marketplace IV) and the eICU Collaborative Research Database, which served as the development cohort and external validation cohort. Model screening was performed using least absolute shrinkage and selection operator (LASSO) regression, and a prediction model was constructed by logistic regression. Internal and external validation were used to evaluate the model.
Results
The prediction model based on six predictors (lactate, age, partial thromboplastin time, urea nitrogen, total bilirubin, platelets) showed good predictive performance, such as a C-index of 0.795 in the development cohort, a C-index of 0.767 in the internal validation cohort,,and a C-index of 0.846 in the external validation cohort.
Conclusions
We built a predictive model and developed a nomogram of in-hospital deaths from abdominal sepsis based on baseline characteristics. The predictive model shows good performance and can be used by clinicians as a tool to predict patient outcomes.
Design, Synthesis and Biological Evaluation of a Novel [18F]AlF-H3RESCA-FAPI Radiotracer Targeting Fibroblast Activation Protein.
Authors: Zhang Qingyu , Hu Zhoumi , Zhao Haitao , Du Fuqiang , Lv Chun , Peng Tukang , Zhang Yukai , Zhang Bowu , Liu Jianjun , Wang Cheng 
Published: November 2024

Abstract

Background
Cancer-associated fibroblasts (CAFs), critical in tumor progression, overexpress fibroblast activation protein (FAP), presenting it as a promising target for tumor imaging and therapy. Our objective was to develop a novel radiotracer, [18F]AlF-H3RESCA-FAPI, that achieves high labeling efficiency at room temperature for PET imaging of FAP-expressing tumors.
Results
The structure's feasibility was confirmed through molecular docking and ADMET prediction. H3RESCA-FAPI was synthesized and radiolabeled with [18F]AlF2+. Optimal labeling conditions were identified as pH 5.0, a molar ratio of aluminum chloride to precursor of 0.58, and a precursor mass of 50 µg. The radiotracer demonstrated high binding affinity to FAP (KD < 10.09 pM), favorable radiochemical yield (52.0 ± 3.0%), and radiochemical purity exceeding 95%. In vitro and in vivo studies revealed good stability and rapid clearance from non-target tissues. PET imaging in U87MG tumor-bearing mice showed substantial tumor uptake, which was specifically blocked by co-injection with unlabeled DOTA-FAPI-04, confirming tumor-specific uptake.
Conclusions
[18F]AlF-H3RESCA-FAPI is a promising radiotracer for PET imaging of FAP-expressing tumors, exhibiting high tumor-specific uptake. With further structural modifications to enhance pharmacokinetic properties, it could become a potential candidate for clinical translation, providing a readily accessible new tool for future non-invasive tumor imaging research.
Early Detection and Prevention of Occupational Diseases Related to 'Excessive Workload': Analyzing of Scientific Researchers' Data in Universities Utilizing Deep Learning Models
Authors: Yang Xinyi , Yu Lu , Wei Hengjian , Xue Le , Shen Wenjing , Wei Huanping , Fang Yiping 
Published: November 2024

Abstract

As a typical representative of a high-stress occupational group, university researchers are exposed to significant risks associated with ‘excessive workload’. Continuous engagement in intense mental labor leads to the accumulation of physical and mental fatigue, which ultimately increases the susceptibility to cardiovascular and heart diseases. Identifying and monitoring sensitive physiological indicators associated with ‘excessive workload’ is considered an effective strategy to reduce the risks. In this study, an experiment was conducted to build a dataset for researchers using a selection of physiologically sensitive indicators. The dataset including photoplethysmography (PPG) signals, facial behavioral attributes and head posture feature parameters. Six deep learning models and three machine learning models were used in this study for analysis. The results show that all constructed models exhibit excellent performance. Notably, the PSO-CNN-LSTM and MFO-CNN-BiLSTM models show unrivalled accuracy and robustness in the classification task, with prediction accuracies of 99.62% and 99.76%. Respectively, along with a stable AUC value of over 0.99. This highlights their ability to accurately predict the risk of ‘excessive workload’ related diseases in humans. This study provides new insights into the prevention and management of occupational diseases, enhancing occupational health management.
Microclimate and dry years interfere with landscape structure effects on intraspecific trait variation
Authors: Jacome Santiago Fernando Ordonez , Deák Balázs , Valkó Orsolya , Szász Vivien , Neumann Krisztina Verbényiné , Csergő Anna Mária 
Published: November 2024

Abstract

Predicting how changes in weather patterns and land use jointly impact populations is a pressing task in ecology. Microclimate may play a key role in species’ local persistence by modulating regional weather effects. We lack sufficient empirical evidence to understand the relative effects of landscape structure and habitat conditions on intraspecific trait variation.
Using a spatially and temporally replicated demographic dataset, we tested the relative effect of landscape structure (area and connectivity of remnant habitat fragments), microclimate (heat load), and fluctuation in weather conditions (study year) on intraspecific plant trait variation, and we investigated whether the local heat load modulated the weather effects on the studied traits.
We performed repeated measurements of stem height, leaf area, number of stems, main inflorescence length and number of primary side inflorescencesof 569 permanently marked individuals of the grassland specialist Salvia nemorosa L. We sampled 13 populations encompassing microhabitats exposed to different heat load levels, over three consecutive years.
Mature individuals had fewer stems in isolated, and taller stems in small habitat fragments. High levels of heat load and dry years affected negatively all measured traits, and the negative effects of exposure to high heat load were generally exacerbated in dry years.
Exposure to strong environmental stressors could ultimately obscure the real effect of human impact on plant populations. Landscape planning for conservation of dry grassland species should ensure not only improved habitat connectivity but also high-quality habitats with heterogeneous microclimates able to buffer weather extremes.
Mini-scale Traffic Flow Optimization: An Iterative QUBOs Approach Converting from Hybrid Solver to Pure Quantum Processing Unit
Authors: Salloum Hadi , Zhanalin Sanzhar , Badr Amer Al , Kholodov Yaroslav 
Published: November 2024

Abstract

Traffic congestion continues to pose a significant challenge in urban environments, necessitating innovative approaches to traffic management. This paper explores the application of Quantum Annealing (QA) for real-world traffic optimization, expanding on the pioneering work of Volkswagen and D-Wave. In 2017, a collaborative team demonstrated the potential of QA to optimize traffic flow by solving a complex Quadratic Unconstrained Binary Optimization (QUBO) problem involving 418 cars, which required 1,254 qubits. Later, this research culminated in a pilot project at the Web Summit conference in Lisbon, one of Europe’s largest technology events, showcasing quantum computing-based traffic optimization. Since the QPU alone could not directly handle the full problem size, the team employed a hybrid classical-quantum approach, leading to significant improvements in traffic distribution. This paper builds on that foundation by investigating potential speedups using a purely quantum approach, particularly by utilizing the QPU for smaller QUBO problems. The proposed method (MTF) enhances traffic management by decomposing the overall optimization problem into smaller, more manageable subproblems. This decomposition enables us to harness the advantages of the QPU while tackling more complex traffic scenarios that previous approaches struggled to manage. By breaking the problem into smaller parts, we mitigate the challenges associated with embedding large-scale problems into the QPU, which often presents computational difficulties. To evaluate our approach, we conducted experiments involving 100, 200, 300, 400, and 500 cars on a complex traffic map featuring multiple start and end points. We successfully embedded the problem into the D-Wave Advantage Quantum Processing Unit, utilizing the "Pegasus" topology, which resulted in a significant acceleration of the solution process. The experiment results show improved speed and effectiveness in real-world scenarios by leveraging the QPU for better traffic optimization.
Efficacy of Arthroscopic Assisted Lower Trapezius Tendon Transfer versus Reverse Shoulder Arthroplasty in Patients with Posterosuperior Irreparable Rotator Cuff Tear without Arthritis: Propensity score Matching Study
Authors: Baek Chang Hee , Lim Chaemoon , Kim Jung Gon , Kim Bo Taek , Kim Seung Jin 
Published: November 2024

Abstract

Introduction: Shoulder dysfunction, including loss of active forward elevation (FE) and external rotation (ER), is challenging in posterosuperior irreparable rotator cuff tears (PSIRCTs). We compared the clinical outcomes of reverse shoulder arthroplasty (RSA) and arthroscopy-assisted lower trapezius tendon transfer (aLTT) in PSIRCTs patients without arthritis.
Material and Methods: Approximately 29 patients were included in each group(RSA group and aLTT group), using propensity score matching based on demographic variables with a minimum 2-year follow-up period. Clinical results were compared with the visual analogue scale score, Constant shoulder score, American Shoulder and Elbow Surgeons score, University of California Los Angeles shoulder score, and activities of daily living requiring active external rotation (ADLER) score, active range of motion and rotational strength between the two groups. Subsequently, the arthritic change of shoulder joint was evaluated using the acromiohumeral distance (AHD) and Hamada grade.
Results: The clinical outcomes were significantly improved in both groups. However, ADLER score (20.6 ± 4.0 vs. 27.3 ± 3.7, p <.001), ER at 0˚ of abduction (34.2 ± 13.2 vs. 47.5 ± 11.1, p < .001), ER at 90˚ of abduction (49.6 ± 15.4 vs. 66.5 ± 19.5, p <.001) and ER strength (16.4 ± 4.0 vs. 24.1 ± 9.1, p < .001) of aLTT group were significantly better than that of RSA group. No significant increase of AHD and no significant progression of arthritis change were observed in aLTT group.
Conclusions: Although both RSA and aLLT improved overall patient outcomes postoperatively, aLTT was superior inclinical scores, notably the ADLER score, active ER, and ER strength in PSIRCTs patients without arthritis. These findings suggest that aLTT could be a first-line joint-preserving treatment option for PSIRCTs patients without arthritis, given the longevity and related complications associated with arthroplasty.
Enhanced YOLOv8 with Lightweight and Efficient Detection Head for for Detecting Rice Leaf Diseases
Authors: Gan Bo , Pu Guolin , Xing Weiyin , Wang Lianfang , Liang Shu 
Published: November 2024

Abstract

Detecting rice leaf diseases is essential for agricultural stability and crop health. However, the diversity of these diseases, their uneven distribution, and complex field environments create challenges for precise, multi-scale detection. While YOLO object detection algorithms show strong performance in automated detection, further optimization is needed. This paper presents G-YOLO, a novel architecture that combines a Lightweight and Efficient Detection Head (LEDH) with Multi-scale Spatial Pyramid Pooling Fast (MSPPF). The LEDH enhances detection speed by simplifying the network structure while maintaining accuracy, reducing computational demands. The MSPPF improves the model’s ability to capture intricate details of rice leaf diseases at various scales by fusing multi-level feature maps. On the RiceDisease dataset, G-YOLO surpasses YOLOv8n with 4.4% higher mAP@0.5, 3.9% higher mAP@0.75, and a 13.1% increase in FPS, making it well-suited for resource-constrained devices due to its efficient design.
Unravelling the Tumourigenesis Mechanisms of Oncocytic Cell Tumours: Discoveries from a Comparative Omics Study
Authors: CANBERK SULE , FERREIRA MARTA , Paula Arnaud Da Cruz , PEREIRA LUÍSA , OLIVEIRA CARLA , OSÓRIO HUGO , SOARES PAULA , MÁXIMO VALDEMAR 
Published: November 2024

Abstract

Oncocytic cell tumours (OCTs), formerly known as Hürthle cell tumours in thyroid, are a subset of thyroid and other endocrine neoplasms that present diagnostic and therapeutic challenges due to their variable clinical behaviour. Considering the limited exploration of transcriptomic and proteomic profiles of OCTs compared to MRNs in the literature, we conducted RNA and protein sequencing on 12 OCTs (5 oncocytic adenomas and 7 oncocytic carcinomas) and 6 MRNs, based on the fact that oncocytic morphology alone does not determine biological behavior. RNA sequencing data analysis revealed the presence of 47 downregulated and 38 upregulated differentially expressed genes (DEGs) in OCTs when compared to MRNs. Significant signalling pathways affecting OCTs were associated with the heme metabolism. Protein sequencing data analysis showed the presence of 20 underexpressed and 64 overexpressed differentially expressed proteins (DEPs) in OCTs than in MRNs, and all of the OCAs were found to cluster together, constituting a distinct cluster than the one comprising the MRNs. The majority of DEPs affected three major cellular pathways in OCTs, including epigenetic modifications, tumor microenvironment, and protein biogenesis, that may shape the behavior and morphology of these tumors. Hence, further research into these mechanisms and their impact on tumour phenotype and behaviour may lead to better diagnostic and therapeutic strategies for patients with OCTs.
Efficacy and Safety of Ultra-Pulsed CO2 Fractional Laser (UP) for the Treatment of Periorbital Static Wrinkles
Authors: Gao Ni , Gao Lin , Wang Yuanli , Wang Li , Song Pu , Lu Meiheng , Gao Lin 
Published: November 2024

Abstract

Objective: To evaluate the effectiveness and safety of Ultra-Pulsed CO2 Fractional Laser (UP) for the treatment of periorbital static wrinkles.
Methods: Thirty patients with periorbital static wrinkles were selected and given one session of ultra-pulsed CO2 fractional laser treatment. Patients were photographed and assessed using Think View skin testing and Antera3D skin analysis before treatment, immediately after treatment, and at 2 weeks, 1 month, 2 months, and 3 months post-treatment. Patients were scored for pain during surgery and followed up by telephone on postoperative days 1, 3, and 5 to record adverse reactions. Data such as overall periorbital wrinkle score, average wrinkle depth, average wrinkle width, and maximum wrinkle depth were used for outcome evaluation using Antera3D analysis.
Results: All 30 patients could tolerate the intraoperative treatment, with a VAS pain score of 5.67±1.15. 93.33% of the subjects expressed satisfaction with the treatment effect. The Fitzpatrick wrinkle scale scores of all subjects decreased after treatment compared to before. 3D detection showed that the overall wrinkle score decreased after treatment compared to before. Specifically, the average wrinkle depth was significantly reduced at 3 months postoperatively (p<0.001), and the maximum wrinkle depth improved at 1 month (p<0.05) and decreased significantly at 2 and 3 months postoperatively (p<0.001). There were no significant adverse reactions after the surgery.
Conclusion: The Ultra-Pulsed CO2 Fractional Laser (UP) is safe and effective in the treatment of periorbital static wrinkles.