bluuebunny/crossref_metadata_2025_split huggingface dataset:
Access to colorectal cancer screening in populations in China, 2020: A coverage‐focused synthesis analysis
Authors: Li Yan‐Jie , Wang Xin , Wu Yu‐Jie , Zhou Xin‐Yi , Li Jibin , Qin Jiangmei , Xu Wanghong , Lew Jie‐Bin , Chen Wanqing , Shi Ju‐Fang 
Published: March 2024

AbstractIn populations in China, colorectal cancer (CRC) screening can be mainly accessed through organized screening, opportunistic screening, and physical examination. This screening intervention is found to be effective but the exact coverage rate is difficult to measure. Based on data from published articles, official websites, and available program reports, the screening coverage rate and related indicators were quantified. A rapid review was then conducted to estimate the overall and the breakdown coverage rates of the sub‐type screening services, by leveraging the numbers of articles and the by‐type median sample sizes. Up to 2020, two central government‐funded and four provincial/municipal‐level organized CRC screening programs have been initiated and included in this analysis. For populations aged 40–74, the estimated coverage rate of organized programs in China was 2.7% in 2020, and the 2‐year cumulative coverage rate in 2019–2020 was 5.3% and the 3‐year cumulative coverage rate in 2018–2020 was 7.7%. The corresponding coverage rates of 50–74‐year‐olds were estimated to be 3.4%, 7.1%, and 10.3%, respectively. Based on the rapid review approach, the overall screening coverage rate for 40–74 years, considering organized screening programs, opportunistic screening, and physical examinations, was then estimated to be 3.0% in China in 2020. However, comparing the findings of this study with the number of health check‐ups reported in the local national health statistics yearbooks suggests that the number of CRC physical examinations may be underestimated in this study. The findings suggest that further efforts are needed to improve population access to CRC screening in China. Furthermore, evidence for access to opportunistic CRC screening and physical examination is limited, and more quantitative investigation is needed.
Comparative analysis of cone‐beam breast computed tomography and digital breast tomosynthesis for breast cancer diagnosis: A comprehensive study on reconstruction algorithms
Authors: Komolafe Temitope Emmanuel , Tian Yuchi , Awoniya Olanrewaju James , Chen Shuang‐Qing , Yang Xiaodong 
Published: March 2024

AbstractBreast cancer (BC) is the most commonly diagnosed non‐skin cancer in women. To achieve early and accurate diagnosis, three‐dimensional (3D) cone‐beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) modalities are used. Importantly, the comparison of reconstruction accuracy of both CBBCT and DBT has rarely been investigated, thus constituting a research gap. This study systematically investigated the performances of the CBBCT and DBT for different reconstruction algorithms using both BR3D breast phantom and breast images. We acquired clinical breast images and scanned the BR3D phantom for additional breast images. These acquired images were used to simulate projection data using predefined CBBCT and DBT geometries. The simulated projections were reconstructed using five different reconstruction algorithms. To evaluate the reconstruction accuracy, we calculated average image quality assessment (IQA) indices, including peak signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), root mean square error (RMSE), and others, across different algorithms and modalities. The pooled PSNR, SSIM, and RMSE for DBT and CBBCT images are (31.6265 ± 0.8725), (0.9353 ± 0.0077), and (0.0270 ± 0.0025) and (29.7007 ± 0.9249), (0.9136 ± 0.0130), and (0.0342 ± 0.0040), which implies that the overall IQA indices of DBT are superior to CBBCT; therefore, DBT tends to reveal more BC detectability as the diagnosis outcome would largely depend on good quality images. The results show that DBT gives an improved result for all algorithms compared to CBBCT, although further experimental trials may be needed to establish the findings fully. The findings suggest that using DBT may enhance the accuracy of BC diagnosis compared to CBBCT due to its superior image quality in clinical practice, emphasizing the importance of selecting optimal reconstruction algorithms for improved diagnostic outcomes.
Efficient feature extraction and hybrid deep learning for early identification of uterine fibroids in ultrasound images
Authors: Lekshmanan Chinna Meena , Pathrose Mary Joe Prathap 
Published: March 2024

AbstractNon‐cancerous growths called uterine fibroids develop in the uterus. They can vary in size, location, and number, and can produce symptoms including excessive menstrual flow, pelvic discomfort, and reproductive problems. Early detection of uterine fibroids is important because it allows for timely intervention and appropriate management strategies. Extracting meaningful features from ultrasound (US) images requires robust and effective techniques. However, different feature extraction methods may yield varying results, and the choice of technique can influence the accuracy of fibroid detection. This paper presents an efficient approach for early detection of uterine fibroids in US images. Our proposed technique combines efficient feature extraction methods and a hybrid deep learning approach. Firstly, we employ the well‐known canny edge detection algorithm to accurately identify the edges of the fibroid region in the US images. This step helps in segmenting the target edge portion for further analysis. Additionally, we introduce an improved bird swarm optimization (IBSO) algorithm to extract a comprehensive set of features, utilizing both known features and newly obtained features. This approach enhances the accuracy of fibroid detection in uterine images. The proposed method uses a convolutional recurrent neural network (CRNN) to accurately detect and treat uterine fibroids, ensuring timely diagnosis and treatment. Our proposed IBSO‐CRNN model produces accuracy rates of 99.897% and 97.568% on the augmented and original datasets, respectively.
Unraveling interindividual variation of trimethylamine N‐oxide and its precursors at the population level
Authors: Andreu‐Sánchez Sergio , Ahmad Shahzad , Kurilshikov Alexander , Beekman Marian , Ghanbari Mohsen , van Faassen Martijn , van den Munckhof Inge C. L. , Steur Marinka , Harms Amy , Hankemeier Thomas , Ikram M. Arfan , Kavousi Maryam , Voortman Trudy , Kraaij Robert , Netea Mihai G. , Rutten Joost H. W. , Riksen Niels P. , Zhernakova Alexandra , Kuipers Folkert , Slagboom P. Eline , van Duijn Cornelia M. , Fu Jingyuan , Vojinovic Dina 
Published: March 2024

AbstractTrimethylamine N‐oxide (TMAO) is a circulating microbiome‐derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels of TMAO, its precursors (betaine, carnitine, deoxycarnitine, choline), and TMAO‐to‐precursor ratios are associated with clinical outcomes, including CVD and mortality. This was followed by an in‐depth analysis of their genetic, gut microbial, and dietary determinants. The analyses were conducted in five Dutch prospective cohort studies including 7834 individuals. To further investigate association results, Mendelian Randomization (MR) was also explored. We found only plasma choline levels (hazard ratio [HR] 1.17, [95% CI 1.07; 1.28]) and not TMAO to be associated with CVD risk. Our association analyses uncovered 10 genome‐wide significant loci, including novel genomic regions for betaine (6p21.1, 6q25.3), choline (2q34, 5q31.1), and deoxycarnitine (10q21.2, 11p14.2) comprising several metabolic gene associations, for example, CPS1 or PEMT. Furthermore, our analyses uncovered 68 gut microbiota associations, mainly related to TMAO‐to‐precursors ratios and the Ruminococcaceae family, and 16 associations of food groups and metabolites including fish‐TMAO, meat‐carnitine, and plant‐based food‐betaine associations. No significant association was identified by the MR approach. Our analyses provide novel insights into the TMAO pathway, its determinants, and pathophysiological impact on the general population.
Photocrosslinkable triple helical protein with enhanced higher‐order formation for biomaterial applications
Authors: Akilandeswari Gopalan , Varshashankari Vijayakumar , Muthusamy Shalini , Aarthy Mayilvahanan , Thamizhvani Karthigeyan , Mercyjayapriya Jebakumar , Ashokraj Sundarapandian , Mohandass Pachaiyappan , Prem Suresh , Ayyadurai Niraikulam 
Published: March 2024

AbstractBacterial collagen, produced via recombinant DNA methods, offers advantages including consistent purity, customizable properties, and reduced allergy potential compared to animal‐derived collagen. Its controlled production environment enables tailored features, making it more sustainable, non‐pathogenic, and compatible with diverse applications in medicine, cosmetics, and other industries. Research has focused on the engineering of collagen‐like proteins to improve their structure and function. The study explores the impact of introducing tyrosine, an amino acid known for its role in fibril formation across diverse proteins, into a newly designed bacterial collagen‐like protein (Scl2), specifically examining its effect on self‐assembly and fibril formation. Biophysical analyses reveal that the introduction of tyrosine residues didn't compromise the protein's structural stability but rather promoted self‐assembly, resulting in the creation of nanofibrils—a phenomenon absent in the native Scl2 protein. Additionally, stable hydrogels are formed when the engineered protein undergoes di‐tyrosine crosslinking under light exposure. The hydrogels, shown to support cell viability, also facilitate accelerated wound healing in mouse fibroblast (NIH/3T3) cells. These outcomes demonstrate that the targeted inclusion of functional residues in collagen‐like proteins enhances fibril formation and facilitates the generation of robust hydrogels using riboflavin chemistry, presenting promising paths for research in tissue engineering and regenerative medicine.
Machine‐learning descriptor search on the density of states profile of bimetallic alloy systems and comparison with the d‐band center theory
Authors: Ishikawa Atsushi 
Published: March 2024

AbstractIn this study, the electronic density of states (DOSs) calculated with density functional theory (DFT) were analyzed by the machine‐learning techniques. More than 400 pure metal and bimetallic alloy systems were calculated with DFT, and obtained the surface DOSs and the CH3 adsorption energy (Ead). By fitting the Gaussian functions to the DOS, multiple descriptors, such as the Gaussian peak positions, heights, and widths were extracted. Several regression methods, such as the least absolute shrinkage of selection operator (LASSO), random‐forest, gradient‐boosting, and extra‐tree were used to find the relationship between these descriptors and the Ead. The results show that the energy position of the peaks in the d‐projected DOS is the most important descriptor, in agreement with the previously known d‐band center theory. It was also shown that the peak position in d‐projected DOS improves the regression model in addition to the d‐band center, since it reduces the regression error.
The effect of low birth weight as an intrauterine exposure on the early onset of sarcopenia through possible molecular pathways
Authors: Celik Dilek , Campisi Manuela , Cannella Luana , Pavanello Sofia 
Published: March 2024

AbstractSarcopenia, a musculoskeletal disease characterized by the progressive loss of skeletal muscle mass, strength, and physical performance, presents significant challenges to global public health due to its adverse effects on mobility, morbidity, mortality, and healthcare costs. This comprehensive review explores the intricate connections between sarcopenia and low birth weight (LBW), emphasizing the developmental origins of health and disease (DOHaD) hypothesis, inflammatory processes (inflammaging), mitochondrial dysfunction, circadian rhythm disruptions, epigenetic mechanisms, and genetic variations revealed through genome‐wide studies (GWAS). A systematic search strategy was developed using PubMed to identify relevant English‐language publications on sarcopenia, LBW, DOHaD, inflammaging, mitochondrial dysfunction, circadian disruption, epigenetic mechanisms, and GWAS. The publications consist of 46.2% reviews, 21.2% cohort studies, 4.8% systematic reviews, 1.9% cross‐sectional studies, 13.4% animal studies, 4.8% genome‐wide studies, 5.8% epigenome‐wide studies, and 1.9% book chapters. The review identified key factors contributing to sarcopenia development, including the DOHaD hypothesis, LBW impact on muscle mass, inflammaging, mitochondrial dysfunction, the influence of clock genes, the role of epigenetic mechanisms, and genetic variations revealed through GWAS. The DOHaD theory suggests that LBW induces epigenetic alterations during foetal development, impacting long‐term health outcomes, including the early onset of sarcopenia. LBW correlates with reduced muscle mass, grip strength, and lean body mass in adulthood, increasing the risk of sarcopenia. Chronic inflammation (inflammaging) and mitochondrial dysfunction contribute to sarcopenia, with LBW linked to increased oxidative stress and dysfunction. Disrupted circadian rhythms, regulated by genes such as BMAL1 and CLOCK, are associated with both LBW and sarcopenia, impacting lipid metabolism, muscle mass, and the ageing process. Early‐life exposures, including LBW, induce epigenetic modifications like DNA methylation (DNAm) and histone changes, playing a pivotal role in sarcopenia development. Genome‐wide studies have identified candidate genes and variants associated with lean body mass, muscle weakness, and sarcopenia, providing insights into genetic factors contributing to the disorder. LBW emerges as a potential early predictor of sarcopenia development, reflecting the impact of intrauterine exposures on long‐term health outcomes. Understanding the complex interplay between LBW with inflammaging, mitochondrial dysfunction, circadian disruption, and epigenetic factors is essential for elucidating the pathogenesis of sarcopenia and developing targeted interventions. Future research on GWAS and the underlying mechanisms of LBW‐associated sarcopenia is warranted to inform preventive strategies and improve public health outcomes.
Advanced feature learning and classification of microscopic breast abnormalities using a robust deep transfer learning technique
Authors: Rehman Amjad , Mahmood Tariq , Alamri Faten S. , Saba Tanzila , Naseem Shahid 
Published: March 2024

AbstractBreast cancer is a major health threat, with early detection crucial for improving cure and survival rates. Current systems rely on imaging technology, but digital pathology and computerized analysis can enhance accuracy, reduce false predictions, and improve medical care for breast cancer patients. The study explores the challenges in identifying benign and malignant breast cancer lesions using microscopic image datasets. It introduces a low‐dimensional multiple‐channel feature‐based method for breast cancer microscopic image recognition, overcoming limitations in feature utilization and computational complexity. The method uses RGB channels for image processing and extracts features using level co‐occurrence matrix, wavelet, Gabor, and histogram of oriented gradient. This approach aims to improve diagnostic efficiency and accuracy in breast cancer treatment. The core of our method is the SqE‐DDConvNet algorithm, which utilizes a 3 × 1 convolution kernel, SqE‐DenseNet module, bilinear interpolation, and global average pooling to enhance recognition accuracy and training efficiency. Additionally, we incorporate transfer learning with pre‐trained models, including mVVGNet16, EfficientNetV2B3, ResNet101V2, and CN2XNet, preserving spatial information and achieving higher accuracy under varying magnification conditions. The method achieves higher accuracy compared to baseline models, including texture and deep semantic features. This deep learning‐based methodology contributes to more accurate image classification and unique image recognition in breast cancer microscopic images.Research Highlights
Introduces a low‐dimensional multiple‐channel feature‐based method for breast cancer microscopic image recognition.
Uses RGB channels for image processing and extracts features using level co‐occurrence matrix, wavelet, Gabor, and histogram of oriented gradient.
Employs the SqE‐DDConvNet algorithm for enhanced recognition accuracy and training efficiency.
Transfer learning with pre‐trained models preserves spatial information and achieves higher accuracy under varying magnification conditions.
Evaluates predictive efficacy of transfer learning paradigms within microscopic analysis.
Utilizes CNN‐based pre‐trained algorithms to enhance network performance.
Prenatal treatment with corticosterone via maternal injection induces learning and memory impairments via delaying postsynaptic development in hippocampal CA1 neurons of rats
Authors: Kim Hye‐Ji , Ko Eun‐A , Kwon Oh‐Bin , Jung Sung‐Cherl 
Published: March 2024

AbstractPreviously, we reported that prenatal exposure to high corticosterone induced attention‐deficit hyperactivity disorder (ADHD)‐like behaviors with cognitive deficits after weaning. In the present study, cellular mechanisms underlying cortisol‐induced cognitive dysfunction were investigated using rat pups (Corti.Pups) born from rat mothers that were repetitively injected with corticosterone during pregnancy. In results, Corti.Pups exhibited the failure of behavioral memory formation in the Morris water maze (MWM) test and the incomplete long‐term potentiation (LTP) of hippocampal CA1 neurons. Additionally, glutamatergic excitatory postsynaptic currents (EPSCs) were remarkably suppressed in Corti.Pups compared to normal rat pups. Incomplete LTP and weaker EPSCs in Corti.Pups were attributed to the delayed postsynaptic development of CA1 neurons, showing a higher expression of NR2B subunits and lower expression of PSD‐95 and BDNF. These results indicated that the prenatal treatment with corticosterone to elevate cortisol level might potently downregulate the BDNF‐mediated signaling critical for the synaptic development of hippocampal CA1 neurons during brain development, and subsequently, induce learning and memory impairment. Our findings suggest a possibility that the prenatal dysregulation of cortisol triggers the epigenetic pathogenesis of neurodevelopmental psychiatric disorders, such as ADHD and autism.
A hybrid statistical downscaling prediction model with timescale decomposition for summer precipitation over Hainan Island, China
Authors: Zhao Junhu , Wu Hui , Xiong Kaiguo , Qiao Shaobo , Yang Jie , Feng Guolin , Li Yingfa , Xing Caiying , Zhu Jingjing 
Published: March 2024

AbstractBy observing well‐known sea surface temperature (SST) indices and outputs from Climate Forecast System version 2 (CFSv2) hindcasts and predictions, in this study, we developed a hybrid statistical downscaling prediction model (HSDPM) based on a timescale decomposition approach, which effectively improved the forecasting ability of summer (June–August) precipitation over Hainan Island (HNSP) in China; this precipitation presented multiple obvious timescale variabilities. We found that the interannual variability of the HNSP is closely related to the observed North Atlantic tripole SST anomalies in the preceding winter and the summer sea level pressure over the South China Sea by CFSv2 predicted in March. On the other hand, the interdecadal variability in the HNSP is linked to the prewinter Pacific Interdecadal Oscillation (PDO) according to the observations, the CFSv2 predictions of the summer surface air temperature over the tropical central‐east Pacific. On this basis, both the interannual and interdecadal components of the HNSP are effectively predicted using the corresponding predictors via multiple regression; thus, the HSDPM is ultimately established by combining the above two components. Compared with the original CFSv2 model, the HSDPM model achieves a considerable improvement in performance in predicting the HNSP. Specifically, the temporal correlation coefficient, ratio of root‐mean‐square error and anomaly sign consistency rate between the observed and HSDPM‐predicted HNSPs are 0.70, 17.4% and 80.5%, respectively, which are significantly greater than the above three forecasting index values of 0.23, 38.3% and 48.8%, respectively, obtained from the original CFSv2 predictions. The application of the HSDPM may be beneficial for drought and flood prevention and mitigation in Hainan Island.
Enteral nutrition in children and adolescents who receive extracorporeal membrane oxygenation and its impact on complications and mortality: A systematic review and meta‐analysis
Authors: Li Xiuhong , Fan Liping , Pan Xiaolan , Kwok Chun Shing 
Published: March 2024

AbstractEnteral nutrition (EN) is one method of nutrition support for children and adolescents receiving extracorporeal membrane oxygenation (ECMO) therapy, and there are no guidelines for its use in this population. We conducted a systematic review to determine whether EN is effective and safe in children supported by ECMO. We searched the Cochrane Library database, MEDLINE, and Embase on Ovid in March 2023 to identify studies that evaluated children and adolescents who received ECMO and were treated with EN. Random effects meta‐analysis was used to estimate the odds of mortality with EN compared with parenteral nutrition (PN). A total of 14 studies were included in this review with 1650 patients (796 received EN). The median duration of ECMO was 5–10 days, and the median EN initiation time ranged from 23 h to 7 days. The pooled results suggest no significant difference in mortality with EN compared with PN (odds ratio [OR] = 0.77; 95% CI, 0.56–1.05; I2 = 26%). Exclusion of the only study that reported an increase in mortality resulted in a borderline significant reduction in mortality with EN (OR = 0.71; 95% CI, 0.51–1.00; I2 = 26%). The predictors of EN were male sex, older age, heavier weight, greater height, cardiac diagnosis, longer duration of ECMO, and use of venovenous ECMO. Most studies suggest no correlation between EN and complications. EN use in children and adolescents who receive ECMO does not appear to be associated with increased mortality compared with PN and was safe in terms of intestinal complications and feeding intolerance.