bluuebunny/crossref_metadata_2025_split huggingface dataset:
Families’ importance in nursing care–families’ opinions: a cross-sectional survey study in the homecare setting
Authors: Woldring Josien M. , Paans Wolter , Gans Reinold , Dorland Laura , Luttik Marie Louise 
Published: June 2024

Abstract
Background
Informal care is an essential part of support provided in the homecare setting. To ensure effective healthcare provision, good communication and collaboration between informal and formal care providers are crucial. To achieve this aim, it is necessary to have a clear understanding of the perspectives of all stakeholders. In the scientific literature, limited knowledge is available regarding family members’ opinions about their involvement in care. To date, no instruments have been developed that accurately measure these opinions. This study aims to elucidate the opinions of family members about their involvement in nursing care.

Methods
A cross-sectional survey approach was employed. The methodological steps in this study were (1) convert the Families’ Importance in Nursing Care–Nurses’ Attitudes (FINC-NA) from a nurses’ perspective to a family perspective and thus develop the Families’ Importance in Nursing Care–Families’ Opinions (FINC-FO) and (2) measure families’ opinions regarding their involvement in home nursing care. The questionnaire was sent to 3,800 patients with activated patient portals, which accounts for about 17% of the total patient base. Responses were received from 1,339 family members, a response rate of 35%.

Results
The developed FINC-FO questionnaire showed homogeneity and internal consistency. The results of the questionnaire indicate that family members consider it important to be involved in care and that they wish to be acknowledged as participants in discussions about care (planning) but are less inclined to actively participate in the provision of care by nurses. Family members expressed less explicit opinions about their own support needs. Factors such as level of education, type of partnership, and amount of care provided are seemingly associated with these opinions.

Conclusions
Family members in the homecare setting wish to be involved in discussions about care (planning). The transition in care from primarily formal to more informal care necessitates an awareness and clear definition—on part of both healthcare professionals and families—of their respective roles in the provision of care. Communication about wishes, expectations, and the need for support in care is essential to ensure quality of care and that the family can sustain caregiving.
Hemostatic effects of tranexamic acid in cardiac surgical patients with antiplatelet therapy: a systematic review and meta-analysis
Authors: Tian Lijuan , Li Xiaotao , He Lixian , Ji Hongwen , Yao Yuntai ,   the Evidence in Cardiovascular Anesthesia (EICA) Group
Published: June 2024

Abstract
Background
The purpose of the current study was to assess the efficacy of tranexamic acid (TXA) on reducing bleeding in cardiac surgical patients with preoperative antiplatelet therapy (APT).

Methods
Five electronic databases were searched systematically for randomized-controlled trials (RCTs) assessing the impact of intravenous TXA on post-operative bleeding on cardiac surgical patients with preoperative APT until May 2024. Primary outcome of interest was post-operative blood loss. Secondary outcomes of interest included the incidence of reoperation due to post-operative bleeding, post-operative transfusion requirements of red blood cells (RBC), fresh-frozen plasma (FFP), and platelet concentrates. Mean difference (MD) with 95% confidence interval (CI) or odds ratios (OR) with 95% CI was employed to analyze the data. Subgroup and meta-regression analyses were performed to assess the possible influence of TXA administration on reducing bleeding and transfusion requirements.

Results
A total of 12 RCTs with 3018 adult cardiac surgical patients (TXA group, 1510 patients; Control group, 1508 patients) were included. The current study demonstrated that TXA significantly reduced post-operative blood loss (MD =  − 0.38 L, 95% CI: − 0.73 to − 0.03, P = 0.03; MD =  − 0.26 L, 95% CI: − 0.28 to − 0.24, P < 0.00001; MD =  − 0.37 L, 95% CI: − 0.63 to − 0.10, P = 0.007) in patients receiving dual antiplatelet therapy (DAPT), aspirin, or clopidogrel, respectively. Patients in TXA group had significantly lower incidence of reoperation for bleeding as compared to those in Control group. The post-operative transfusion of RBC and FFP requirements was significantly lower in TXA group than Control group. Subgroup analyses showed that studies with DAPT discontinued on the day of surgery significantly increased the risk of post-operative blood loss [(MD: − 1.23 L; 95% CI: − 1.42 to − 1.04) vs. (MD: − 0.16 L; 95% CI: − 0.27 to − 0.05); P < 0.00001 for subgroup difference] and RBC transfusion [(MD: − 3.90 units; 95% CI: − 4.75 to − 3.05) vs. (MD: − 1.03 units; 95% CI: − 1.96 to − 0.10); P < 0.00001 for subgroup difference] than those with DAPT discontinued less than 5–7 days preoperatively.

Conclusions
This meta-analysis demonstrated that TXA significantly reduced post-operative blood loss and transfusion requirements for cardiac surgical patients with preoperative APT. These potential clinical benefits may be greater in patients with aspirin and clopidogrel continued closer to the day of surgery.

Trial registration number
CRD42022309427.
Measurement invariance of the Pandemic Anxiety Inventory in different demographic groups
Authors: Schonfeld Irvin Sam , Prytherch Tasmyn , Cropley Mark , Verkuilen Jay , Bianchi Renzo 
Published: June 2024

Abstract
Background
The Pandemic Anxiety Inventory (PAI) was developed in the context of the COVID-19 pandemic. Its content allows it to assess anxiety in connection to any pandemic. Previous research has demonstrated the instrument’s reliability and validity. An important question for clinicians and researchers, however, remains open: Does the PAI have similar meaning for members of different demographic groups? The finding of measurement invariance would allow clinicians and researchers to comparatively assess pandemic-related anxiety across demographic groups, including favored and disfavored groups.

Methods
We conducted a multi-group confirmatory factor analysis to assess the measurement invariance of the PAI using data obtained from a sample of 379 residents of the United Kingdom.

Results
The PAI demonstrated invariance across genders, age groups, individuals who are married or in a relationship and those who are not, as well as individuals with higher and lower incomes. In an ancillary analysis, we found invariance across subsamples of Whites and Nonwhites, although we note that the Nonwhite group was small (n = 60) and heterogeneous. The findings of a supplemental MIMIC analysis were consistent with the above.

Conclusions
The PAI shows measurement invariance across a variety of demographic groups. Our findings suggest that the instrument can be meaningfully employed to compare pandemic-related anxiety across these groups.
Original or post-war paintings? The fixed wooden scenery of the Teatro Olimpico in Vicenza: a guided multidisciplinary approach based on scientific analyses and HBIM
Authors: Antonelli Fabrizio , Piovesan Rebecca , Tesser Elena , Tosato Marco , Sorbo Emanuela 
Published: June 2024

Abstract
Archival resources, a photogrammetric survey, analysis of materials and techniques, and evaluation of the state of conservation were interconnected phases in the interdisciplinary research on the perspective scenery of the Teatro Olimpico in Vicenza. To fill existing gaps related to the history of this unique artefact and to the undocumented retouching of paint layers on the scenery during post-war reconstruction work, a broad analytical approach (optical microscopy, XRPD, SEM–EDX, μFTIR and μRaman) was applied to micro-samples, the selection of which was guided by consolidated geometrical and archival data. The aims were to obtain a characterisation of the pigments and binders and to evaluate the microstratigraphic sequence, the state of conservation of the scenery flats, and the deterioration processes involved. The findings unveiled a discernible variability in the production techniques of the finishes, frequently lacking the classic microstratigraphic sequence associated with the traditional method for painting on wooden panels from the sixteenth century. Moreover, by identifying many pigments that could be used as temporal markers we were able unequivocally to establish, for the first time, that a significant part of the scenery designed by the architect Vincenzo Scamozzi was heavily repainted in the post-WWII period. These analytical results and all the data collected on the artefacts over time were related through an HBIM model, enabling the historical and technical-analytical information to be linked to the geometrical survey and thus to provide guidance for actions based on current and future knowledge for the maintenance and monitoring of the Teatro Olimpico.
Data oversampling and imbalanced datasets: an investigation of performance for machine learning and feature engineering
Authors: Mujahid Muhammad , Kına EROL , Rustam Furqan , Villar Monica Gracia , Alvarado Eduardo Silva , De La Torre Diez Isabel , Ashraf Imran 
Published: June 2024

AbstractThe classification of imbalanced datasets is a prominent task in text mining and machine learning. The number of samples in each class is not uniformly distributed; one class contains a large number of samples while the other has a small number. Overfitting of the model occurs as a result of imbalanced datasets, resulting in poor performance. In this study, we compare different oversampling techniques like synthetic minority oversampling technique (SMOTE), support vector machine SMOTE (SVM-SMOTE), Border-line SMOTE, K-means SMOTE, and adaptive synthetic (ADASYN) oversampling to address the issue of imbalanced datasets and enhance the performance of machine learning models. Preprocessing significantly enhances the quality of input data by reducing noise, redundant data, and unnecessary data. This enables the machines to identify crucial patterns that facilitate the extraction of significant and pertinent information from the preprocessed data. This study preprocesses the data using various top-level preprocessing steps. Furthermore, two imbalanced Twitter datasets are used to compare the performance of oversampling techniques with six machine learning models including random forest (RF), SVM, K-nearest neighbor (KNN), AdaBoost (ADA), logistic regression (LR), and decision tree (DT). In addition, the bag of words (BoW) and term frequency and inverse document frequency (TF-IDF) features extraction approaches are used to extract features from the tweets. The experiments indicate that SMOTE and ADASYN perform much better than other techniques thus providing higher accuracy. Additionally, overall results show that SVM with ’linear’ kernel tends to attain the highest accuracy and recall score of 99.67% and 1.00% on ADASYN oversampled datasets and 99.57% accuracy on SMOTE oversampled dataset with TF-IDF features. The SVM model using 10-fold cross-validation experiments achieved 97.40 mean accuracy with a 0.008 standard deviation. Our approach achieved 2.62% greater accuracy as compared to other current methods.
Green biosynthesis of bimetallic ZnO@AuNPs with its formulation into cellulose derivative: biological and environmental applications
Authors: Al Abboud Mohamed A. , Mashraqi Abdullah , Qanash Husam , Gattan Hattan S. , Felemban Hashim R. , Alkorbi Faeza , Alawlaqi Mohamed M. , Abdelghany Tarek M. , Moawad Hanan 
Published: June 2024

AbstractNanoparticles (NPs) formulation in biopolymers is an attractive process for the researcher to decrease the disadvantages of NPs application alone. Bimetallic NPs are a promising formula of two NPs that usually act as synergetic phenomena. Zinc oxide and gold NPs (ZnO@AuNPs) biosynthesis as a bimetallic was prepared via the eco-friendly manner currently. Carboxymethylcellulose (CMC) was employed for the formulation of ZnO@AuNPs as a nanocomposite via a green method. Physicochemical and topographical characterization was assigned to ZnO@AuNPs and nanocomposite features. The nanostructure of bimetallic NPs and nanocomposite were affirmed with sizes around 15 and 25 nm, respectively. Indeed, the DLS measurements affirmed the more reasonable size and stability of the prepared samples as 27 and 93 nm for bimetallic NPs and nanocomposite, respectively. The inhibitory potential of nanocomposite was more than ZnO@AuNPs against Staphylococcus aureus, Escherichia coli, Salmonella typhi, Enterococcus faecalis, Mucor albicans, Aspergillus flavus, and Mucor circinelloid. ZnO@AuNPs and nanocomposite exhibited antioxidant activity via DPPH with IC50 of 71.38 and 32.4 µg/mL, correspondingly. Excellent anti-diabetic potential of nanocomposite with IC50 of 7.4 µg/mL, and ZnO@AuNPs with IC50 of 9.7 µg/mL was reported compared with the standard acarbose with the IC50 of 50.93 µg/mL for amylase inhibition (%). Photocatalytic degradation of RR195 and RB dyes was performed by ZnO@AuNPs and nanocomposite, where maximum degradation was 85.7 ± 1.53 and 88.7 ± 0.58%, respectively using ZnO@AuNPs, 90.3 ± 0.28 and 91.8 ± 0.27%, respectively using nanocomposite at 100 min.
Graphical Abstract
Self-selection or situational stratification? A quasiexperimental study on social class differences in health behaviors in China
Authors: Hong Yanbi , Zeng Diyang , Shen Ji 
Published: June 2024

AbstractFundamental cause theory suggests that differences in social status lead to health inequalities, with lifestyle serving as the intermediary mechanism. This study uses multiple waves of data from the China Family Panel Studies (CFPS) to first explore differences in drinking, smoking, and physical exercise across different social classes and finds that managers have significantly greater tendencies toward risky health behaviors such as drinking and smoking. Subsequently, the study examines changes in class differences in drinking behavior with respect to the anticorruption policy. The results show that neither lifestyle transition theory nor the self-selection mechanism can fully explain the phenomenon of managers drinking more. Health stratification is not a simple reflection of the socioeconomic status gradient, and there is an urgent need to rethink the theoretical framework of social stratification that emphasizes microlevel individual practices as a direct reflection of macrostructural positions.
Determining the footprint of breeding in the seed microbiome of a perennial cereal
Authors: Michl Kristina , David Christophe , Dumont Benjamin , Mårtensson Linda-Maria Dimitrova , Rasche Frank , Berg Gabriele , Cernava Tomislav 
Published: June 2024

Abstract
Background
Seed endophytes have a significant impact on plant health and fitness. They can be inherited and passed on to the next plant generation. However, the impact of breeding on their composition in seeds is less understood. Here, we studied the indigenous seed microbiome of a recently domesticated perennial grain crop (Intermediate wheatgrass, Thinopyrum intermedium L.) that promises great potential for harnessing microorganisms to enhance crop performance by a multiphasic approach, including amplicon and strain libraries, as well as molecular and physiological assays.

Results
Intermediate wheatgrass seeds harvested from four field sites in Europe over three consecutive years were dominated by Proteobacteria (88%), followed by Firmicutes (10%). Pantoea was the most abundant genus and Pantoea agglomerans was identified as the only core taxon present in all samples. While bacterial diversity and species richness were similar across all accessions, the relative abundance varied especially in terms of low abundant and rare taxa. Seeds from four different breeding cycles (TLI C3, C5, C704, C801) showed significant differences in bacterial community composition and abundance. We found a decrease in the relative abundance of the functional genes nirK and nifH as well as a drop in bacterial diversity and richness. This was associated with a loss of amplicon sequence variants (ASVs) in Actinobacteria, Alphaproteobacteria, and Bacilli, which could be partially compensated in offspring seeds, which have been cultivated at a new site. Interestingly, only a subset assigned to potentially beneficial bacteria, e.g. Pantoea, Kosakonia, and Pseudomonas, was transmitted to the next plant generation or shared with offspring seeds.

Conclusion
Overall, this study advances our understanding of the assembly and transmission of endophytic seed microorganisms in perennial intermediate wheatgrass and highlights the importance of considering the plant microbiome in future breeding programs.
CT and MRI radiomic features of lung cancer (NSCLC): comparison and software consistency
Authors: Bortolotto Chandra , Pinto Alessandra , Brero Francesca , Messana Gaia , Cabini Raffaella Fiamma , Postuma Ian , Robustelli Test Agnese , Stella Giulia Maria , Galli Giulia , Mariani Manuel , Figini Silvia , Lascialfari Alessandro , Filippi Andrea Riccardo , Bottinelli Olivia Maria , Preda Lorenzo 
Published: June 2024

Abstract
Background
Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques.

Methods
Contrast-enhanced CT and MRI images of 35 patients affected with non-small cell lung cancer (NSCLC) were manually segmented and preprocessed using three different methods. Sixty-six Image Biomarker Standardisation Initiative-compliant features common to the considered platforms, PyRadiomics and LIFEx, were extracted. The correlation among features with the same mathematical definition was analyzed by comparing PyRadiomics and LIFEx (at fixed imaging technique), and MRI with CT results (for the same software).

Results
When assessing the agreement between LIFEx and PyRadiomics across the considered resampling, the maximum statistically significant correlations were observed to be 94% for CT features and 95% for MRI ones. When examining the correlation between features extracted from contrast-enhanced CT and MRI using the same software, higher significant correspondences were identified in 11% of features for both software.

Conclusions
Considering NSCLC, (i) for both imaging techniques, LIFEx and PyRadiomics agreed on average for 90% of features, with MRI being more affected by resampling and (ii) CT and MRI contained mostly non-redundant information, but there are shape features and, more importantly, texture features that can be singled out by both techniques.

Relevance statement
Identifying and selecting features that are stable cross-modalities may be one of the strategies to pave the way for radiomics clinical translation.

Key points
• More than 90% of LIFEx and PyRadiomics features contain the same information.
• Ten percent of features (shape, texture) are stable among contrast-enhanced CT and MRI.
• Software compliance and cross-modalities stability features are impacted by the resampling method.

Graphical Abstract
Two-step hierarchical binary classification of cancerous skin lesions using transfer learning and the random forest algorithm
Authors: Suleiman Taofik Ahmed , Anyimadu Daniel Tweneboah , Permana Andrew Dwi , Ngim Hsham Abdalgny Abdalwhab , Scotto di Freca Alessandra 
Published: June 2024

AbstractSkin lesion classification plays a crucial role in the early detection and diagnosis of various skin conditions. Recent advances in computer-aided diagnostic techniques have been instrumental in timely intervention, thereby improving patient outcomes, particularly in rural communities lacking specialized expertise. Despite the widespread adoption of convolutional neural networks (CNNs) in skin disease detection, their effectiveness has been hindered by the limited size and data imbalance of publicly accessible skin lesion datasets. In this context, a two-step hierarchical binary classification approach is proposed utilizing hybrid machine and deep learning (DL) techniques. Experiments conducted on the International Skin Imaging Collaboration (ISIC 2017) dataset demonstrate the effectiveness of the hierarchical approach in handling large class imbalances. Specifically, employing DenseNet121 (DNET) as a feature extractor and random forest (RF) as a classifier yielded the most promising results, achieving a balanced multiclass accuracy (BMA) of 91.07% compared to the pure deep-learning model (end-to-end DNET) with a BMA of 88.66%. The RF ensemble exhibited significantly greater efficiency than other machine-learning classifiers in aiding DL to address the challenge of learning with limited data. Furthermore, the implemented predictive hybrid hierarchical model demonstrated enhanced performance while significantly reducing computational time, indicating its potential efficiency in real-world applications for the classification of skin lesions.
Evaluating circulating cell-free DNA and DNA integrity index as biomarkers in non-small cell lung cancer
Authors: Ezzeldin Nada , El-Lebedy Dalia , Hassan Mirhane , Shalaby Alaa Omar , Hussein Sabah Ahmed Mohamed , Gharib Ahmed Mohamed , Hamdy Gehan , Mohammed Asmaa Mahmoud , Ramadan Abeer , Sobeih Mohamed Emam 
Published: June 2024

Abstract
Background
Analysis of free DNA molecules shed from tumour cells in plasma of patients referred as circulating tumour DNA (ctDNA) with reference to physiological circulating cell-free DNA (cfDNA) is nowadays exploited as liquid biopsy and is considered a new emerging promising biomarker for diagnosis, selection of proper treatment, and prognosis of cancer. DNA integrity index (DII) is assessed by calculating the ratio between the concentration of long cfDNA strands released from tumour cells (ALU247) and the short strands released from normal cells (ALU115). The aim of the current study was to evaluate DII as a potential diagnostic and prognostic biomarker of NSCLC.

Methods
Our study included 48 NSCLC patients diagnosed as primary NSCLC before starting treatment, 30 COPD patients diagnosed clinically, radiologically, and subjected to chest high-resolution computerized tomography, and 40 healthy controls. cfDNA concentration and DII were measured by quantitative real-time polymerase chain reaction (qPCR).

Results
ALU115, ALU247, and DII were significantly higher in NSCLC compared to COPD patients (p < 0.0001) and controls (p < 0.0001) and in COPD patients compared to control subjects (p < 0.0001). DII positively correlated with the stage of tumour (p = 0.01), tumour metastasis (p = 0.004), and with adenocarcinoma compared to other histopathological types (p = 0.02). To evaluate clinical utility of DII in NSCLC, ROC curve analysis demonstrated an AUC of 0.91 at a cut-off value of 0.44 with total accuracy = 85.6%, sensitivity = 90%, specificity = 83%, PPV = 78.1%, and NPV = 92.1%.

Conclusion
cfDNA and DII represent a promising diagnostic and prognostic tool in NSCLC. This type of noninvasive liquid biopsy revealed its chance in the screening, early diagnosis, and monitoring of NSCLC.