bluuebunny/crossref_metadata_2025_split huggingface dataset:
PDFF‐CNN: An attention‐guided dynamic multi‐orientation feature fusion method for gestational age prediction on imbalanced fetal brain MRI dataset
Authors: Feng Ziteng , Zhou Ran , Xia Wei , Wang Siru , Liu Yang , Huang Zhongwei , Gan Haitao 
Published: December 2023

AbstractBackgroundFetal brain magnetic resonance imaging (MRI)‐based gestational age prediction has been widely used to characterize normal fetal brain development and diagnose congenital brain malformations.PurposeThe uncertainty of fetal position and external interference leads to variable localization and direction of the fetal brain. In addition, pregnant women typically concentrate on receiving MRI scans during the fetal anomaly scanning week, leading to an imbalanced distribution of fetal brain MRI data. The above‐mentioned problems pose great challenges for deep learning‐based fetal brain MRI gestational age prediction.MethodsIn this study, a pyramid squeeze attention (PSA)‐guided dynamic feature fusion CNN (PDFF‐CNN) is proposed to robustly predict gestational ages from fetal brain MRI images on an imbalanced dataset. PDFF‐CNN contains four components: transformation module, feature extraction module, dynamic feature fusion module, and balanced mean square error (MSE) loss. The transformation and feature extraction modules are employed by using the PSA to learn multiscale and multi‐orientation feature representations in a parallel weight‐sharing Siamese network. The dynamic feature fusion module automatically learns the weights of feature vectors generated in the feature extraction module to dynamically fuse multiscale and multi‐orientation brain sulci and gyri features. Considering the fact of the imbalanced dataset, the balanced MSE loss is used to mitigate the negative impact of imbalanced data distribution on gestational age prediction performance.ResultsEvaluated on an imbalanced fetal brain MRI dataset of 1327 routine clinical T2‐weighted MRI images from 157 subjects, PDFF‐CNN achieved promising gestational age prediction performance with an overall mean absolute error of 0.848 weeks and an of 0.904. Furthermore, the attention activation maps of PDFF‐CNN were derived, which revealed regional features that contributed to gestational age prediction at each gestational stage.ConclusionsThese results suggest that the proposed PDFF‐CNN might have broad clinical applicability in guiding treatment interventions and delivery planning, which has the potential to be helpful with prenatal diagnosis.
Kinetic modeling and parametric imaging of 18F‐PSMA‐11: An evaluation based on total‐body dynamic positron emission tomography scans
Authors: Yuan Hui , Zhang Guojin , Sun Taotao , Ren Jingyun , Zhang Qing , Xiang Zeyin , Liu Entao , Jiang Lei 
Published: December 2023

AbstractBackgroundThe prostate‐specific membrane antigen (PSMA) targeted positron‐emitting tomography (PET) tracers are increasingly used in clinical practice, with novel tracers constantly being developed. Recently, 18F‐PSMA‐11 has been gaining growing interest for several merits; however, direct in vivo visualization of its kinetic features in humans remains lacking.PurposeTo visualize the kinetic features of 18F‐PSMA‐11 in healthy subjects and patients with prostate cancer derived from the total‐body dynamic PET scans.MethodsA total of 8 healthy volunteers (7 males; 1 female) and 3 patients with prostate cancer underwent total‐body PET/CT imaging at 1 and 2 h post injection (p.i.) of 18F‐PSMA‐11, of which 7 healthy subjects and 3 patients underwent total‐body dynamic PET scans lasting 30 min. Reversible two‐tissue compartments (2TC) and Patlak models were fitted based on the voxel‐based time activity curves (TACs), with the parametric images generated subsequently. Additionally, semi‐automated segmentation of multiple organs was performed in the dynamic images to measure the SUVmean at different time points and in the parametric images to estimate the mean value of the kinetic parameters of these organs.Results18F‐PSMA‐11 showed quick accumulation within prostate cancer, as early as 45 s after tracer injection. It was rapidly cleared from blood circulation and predominantly excreted through the urinary system. High and rapid radiotracer accumulation was observed in the liver, spleen, lacrimal glands, and salivary glands, whereas gradual accumulation was observed in the skeleton. Prostate cancer tissue is visualized in all parametric images, and best seen in DV and Patlak Ki images. Patlak Ki showed a good correlation with 2TC Ki values (r = 0.858, p < 0.05) but less noise than 2TC images. A scanning time point of 30–35 min p.i. was then suggested for satisfactory tumor to background ratio.ConclusionProstate cancer tissue is visible in most parametric images, and is better shown by Patlak Ki and 2TC DV images. Patlak Ki is consistent with, and thus is preferred over, 2TC Ki images for substantially quicker calculation. Based on the dynamic imaging analysis, a shorter uptake time (30–35 min) might be preferred for a better balance of tumor to background ratio.
Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification
Authors: Klein Tobias , Gladytz Thomas , Millward Jason M. , Cantow Kathleen , Hummel Luis , Seeliger Erdmann , Waiczies Sonia , Lippert Christoph , Niendorf Thoralf 
Published: December 2023

AbstractRenal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data‐driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease. To explore this potential, we employed dynamic parametric T2 mapping of the kidney in rats in conjunction with a custom‐tailored deep dilated U‐Net (DDU‐Net) architecture. The architecture was trained, validated, and tested on manually segmented ground truth kidney data, with benchmarking against an analytical segmentation model and a self‐configuring no new U‐Net. Subsequently, we applied our approach to in vivo longitudinal MRI data, incorporating interventions that emulate clinically relevant scenarios in rats. Our approach achieved high performance metrics, including a Dice coefficient of 0.98, coefficient of determination of 0.92, and a mean absolute percentage error of 1.1% compared with ground truth. The DDU‐Net enabled automated and accurate quantification of acute changes in kidney size, such as aortic occlusion (−8% ± 1%), venous occlusion (5% ± 1%), furosemide administration (2% ± 1%), hypoxemia (−2% ± 1%), and contrast agent‐induced acute kidney injury (11% ± 1%). This approach can potentially be instrumental for the development of dynamic parametric MRI‐based tools for kidney disorders, offering unparalleled insights into renal pathophysiology.
Interest in and barriers to online ESOL instruction for adults during and beyond COVID‐19: Exploring relationships with sociodemographics and English proficiency
Authors: Cox Jessica G. , Chen Lauren Y. , Okatch Harriet 
Published: December 2023

AbstractDigital divides mean that marginalized groups such as adults who speak English as a second or other language (ESOL) are less likely to have access to online instruction. Higher levels of English proficiency are associated with better health and employment; therefore, access to ESOL classes is essential. We investigated how sociodemographics and English proficiency relate to adult learners' preferences for, and barriers to, online instruction of ESOL during and beyond the COVID‐19 pandemic. Sixty‐one adults completed a survey on their pandemic experiences, demographics, and ESOL classes. Analyses showed nonsignificant relationships between interest in online instruction and internet access, education, income, and age. Respondents reported expecting more nondigital than digital barriers to online instruction overall. Expecting to encounter digital barriers did not constrain respondents' interest in future online instruction; however, beginner‐proficiency individuals had higher interest than those with intermediate or no proficiency. Of the five specific types of remote instruction included in the survey, learning to use new technologies interested most respondents the most. Results will inform ESOL practitioners and administrations as they continue to develop online or digital literacies components for their classes.
PLS3 Mutations in X-Linked Osteoporosis: Clinical and Genetic Features in Five New Families
Authors: Costa Adriana , Martins Andreia , Machado Catarina , Lundberg Elena , Nilsson Ola , Wang Fan , Costantini Alice , Tournis Symeon , Höppner Jakob , Grasemann Corinna , Mäkitie Outi 
Published: December 2023

AbstractChildhood-onset osteoporosis is a rare but clinically significant condition. Studies have shown pathogenic variants in more than 20 different genes as causative for childhood-onset primary osteoporosis. The X-chromosomal PLS3, encoding Plastin-3, is one of the more recently identified genes. In this study, we describe five new families from four different European countries with PLS3-related skeletal fragility. The index cases were all hemizygous males presenting with long bone and vertebral body compression fractures. All patients had low lumbar spine bone mineral density (BMD). The age at the first clinical fracture ranged from 1.5 to 13&nbsp;years old. Three of the identified PLS3 variants were stop-gain variants and two were deletions involving either a part or all exons of the gene. In four families the variant was inherited from the mother. All heterozygous women reported here had normal BMD and no bone fractures. Four patients received bisphosphonate treatment with good results, showing a lumbar spine BMD increment and vertebral body reshaping after 10 months to 2 years of treatment. Our findings expand the genetic spectrum of PLS3-related osteoporosis. Our report also shows that early treatment with bisphosphonates may influence the disease course and reduce the progression of osteoporosis, highlighting the importance of early diagnosis for prompt intervention and appropriate genetic counseling.
Monetary policy frameworks since Bretton Woods, across the world and its regions
Authors: Cobham David 
Published: December 2023

AbstractThe Comprehensive Monetary Policy Framework (CMPF) project, which considers de jure and de facto, domestic (money, inflation) and external (exchange rate), monetary policy targets, has now classified 186 countries/currency areas from 1974 to 2017. This means that it is now possible to track the evolution of monetary policy frameworks across the world and its regions. This paper outlines the methodology of the classification and analyses the trends at global, regional and sub-regional levels.
Ammonium Perchlorate-Based Energetic Molecular Perovskite DAP-4 Deposited on CNTs: Catalytic Decomposition Behavior, Mechanisms, and Kinetics
Authors: Ismael Shukri , Yehia M. , Elbasuney Sherif 
Published: December 2023

AbstractEnergetic molecular perovskite with superior decomposition enthalpy and high oxidizing ability is the out coming potential oxidizer in advanced highly energetic systems. In this study, perovskite DAP-4 was fabricated by molecular assembly stagey; multi wall carbon nanotubes (MWCNTs) were employed as a potential catalyst for thermal decomposition of DAP-4. Encapsulation method was adopted to develop DAP-4@MWCNTs nanocomposite. MWCNTs experienced superior catalytic effect on DAP-4 decomposition. MWCNTs offered an increase in DAP-4 decomposition enthalpy by 37.5%, with decrease in its main decomposition temperature by 6 °C. Decomposition kinetics were investigated via isoconversional (model free) and model fitting including Kissinger, Kissinger–Akahira–Sunose (KAS), and integral isoconversional method of Ozawa, Flyn and Wall (FWO). DAP-4@MWCNTs demonstrated apparent activation energy of 135.3 ± 3.9 kJ/mol compared with 142.3 ± 4.15 kJ/mol for pure DAP-4 via KAS model. While DAP-4 demonstrated decomposition reaction of first order reaction model (F1); DAP-4@MWCNTs demonstrated decomposition reaction of third order model (F3). Moreover, a possible catalytic mechanism of MWCNTs via induced holes and electrons to enhance electron transfer ability. This work could promote the application of DAP-4 in the field of solid rocket propellant.
Resection margins, lymph node harvest and 3 year survival in open and laparoscopic colorectal cancer surgery; a prospective cohort study
Authors: De Zoysa M. I. M. , Lokuhetty M. D. S. , Seneviratne S. L. 
Published: December 2023

Abstract
Introduction
Laparoscopic colorectal cancer surgery has been gaining popularity in the last decade. However, there are concerns about adequate lymph node dissection and safe resection margins in laparoscopic colorectal cancer surgery. This study was aimed at comparing the lymph node (LN) clearance and surgical resection margins and 3-year survival for open and laparoscopic colorectal cancer surgery.

Method
A pre-tested interviewer administered questionnaire was used to assess the adoption of the laparoscopic approach by Sri Lankan surgeons. Data was collected prospectively from patients who underwent open or laparoscopic colorectal cancer surgery at the University Surgical Unit of the National Hospital of Sri Lanka from April 2016 to May 2019. The histopathology records were analysed to determine the longitudinal and circumferential resection margins(CRM) and the number of lymph nodes harvested. The resection margins were classified as positive or negative. The total number of LN examined was evaluated. Presence of local recurrence and liver metastasis was determined by contrast enhanced CT scan during 3-years of follow up. Chi square, T test and z test for proportions were used to compare CRM, LN harvest and survival rates between the groups.

Results
Of the surgeons interviewed only 11 (18.4%) performed laparoscopic colorectal cancer surgery. A total of 137 patients (83 males and 54 females) were studied. Eighty-one procedures were laparoscopic and 56 procedures were open. All patients had clear longitudinal resection margins. Seventy-eight patients in the laparoscopic group (96%) and 51 patients (91%) in the open group had clear CRM (p > 0.05). A total of 2188 LNs (mean 15.9) were resected in all procedures. Six-hundred-eighty-nine lymph nodes were removed during open procedures (mean 12.3, SD 0.4) and 1499 (mean 18.5, SD 0.6) were removed during laparoscopy (p < 0.05). At 3 years follow-up the disease-free survival in the laparoscopic and open colon cancer patients was 27/41 (65.8%) and 16/29 (55.1%) respectively (p = 0.35). Disease free survival in the laparoscopic and open rectal cancer patients was 23/38 (60.5%) and 13/25 (52.0%) respectively (p = 0.40). Four patients were lost during follow-up.

Discussion and conclusion
CRM was comparable in the two groups. Laparoscopic group had a significantly higher LN harvest. Three-year survival rates were similar in the two groups. Acceptable results can be obtained with laparoscopic colorectal cancer surgery.
Structural characterization of newly-developed Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5 alloys with amorphous matrixes
Authors: Młynarek-Żak Katarzyna , Dhiman Indu , Matus Krzysztof , Kądziołka-Gaweł Mariola , Łoński Wojciech , Radoń Adrian , Czeppe Tomasz , Babilas Rafał 
Published: December 2023

AbstractThe low glass-forming ability of aluminium-based metallic glasses significantly limits their development and preparation. This paper updates the current state of knowledge by presenting the results of structural studies of two newly-developed Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5 alloys with a reduced aluminium content (< 80 at.%). The alloys were produced by conventional casting (ingots) and melt-spinning (ribbons). Structural characterization was carried out for bulk ingots first, and then for the melt-spun ribbons. The ingots possessed a multiphase crystalline structure, as confirmed by X-ray diffraction and scanning electron microscopy observations. The amorphous structure of the melt-spun ribbons was determined by X-ray diffraction and transmission electron microscopy. SEM observations and EDX element maps of the cross-section of melt-spun ribbons indicated a homogeneous elemental composition. Neutron diffraction revealed the presence of nanocrystals in the amorphous matrix of the melt-spun ribbons. DSC data of the melt-spun ribbons showed exothermic events corresponding to the first crystallization at temperatures of 408 °C and 387 °C for Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5, respectively.
Tumor infiltrating lymphocytes (TILs) are a prognosis biomarker in Colombian patients with triple negative breast cancer
Authors: Huertas-Caro Carlos A. , Ramírez Mayra A. , Rey-Vargas Laura , Bejarano-Rivera Lina María , Ballen Diego Felipe , Nuñez Marcela , Mejía Juan Carlos , Sua-Villegas Luz Fernanda , Cock-Rada Alicia , Zabaleta Jovanny , Fejerman Laura , Sanabria-Salas María Carolina , Serrano-Gomez Silvia J. 
Published: December 2023

AbstractTriple negative breast cancer (TNBC) is highly immunogenic and high levels of tumor infiltrating lymphocytes (TILs) have been associated with a better prognosis and higher probability to achieve pathological complete response. Here, we explore the potential role of stromal TILs level and composition as a prognostic and predictive biomarker in TNBC. 195 Tumor biospecimens from patients diagnosed with TNBC were included. Stromal TILs (sTILs), positive CD4/CD8 cells were evaluated. Differences in clinic-pathological characteristics according to immune infiltration were assessed. The predictive and prognostic value of immune infiltration was analyzed by multivariate models. Higher immune infiltration was observed in patients with favorable clinical–pathological features. Survival analysis showed that longer overall survival times were observed in patients with a higher infiltration of sTILs (p = 0.00043), CD4 + (p = 0.0074) and CD8 + (p = 0.008). In the multivariate analysis, low levels of sTILs were found to be associated with a higher mortality hazard (HR: 1.59, 95% CI 1.01–2.48). CD4 and CD8 immune infiltration were associated with higher odds for pathological complete response (OR: 1.20, 95% CI 1.00–1.46, OR: 1.28, 1.02–1.65, respectively). Our results suggest that immune infiltration could be used as a prognostic marker for overall survival in TNBC patients.
Identification of CXCL16 as a diagnostic biomarker for obesity and intervertebral disc degeneration based on machine learning
Authors: Liu Jiahao , Zhang Jian , Zhao Xiaokun , Pan Chongzhi , Liu Yuchi , Luo Shengzhong , Miao Xinxin , Wu Tianlong , Cheng Xigao 
Published: December 2023

AbstractIntervertebral disc degeneration (IDD) is the primary cause of neck and back pain. Obesity has been established as a significant risk factor for IDD. The objective of this study was to explore the molecular mechanisms affecting obesity and IDD by identifying the overlapping crosstalk genes associated with both conditions. The identification of specific diagnostic biomarkers for obesity and IDD would have crucial clinical implications. We obtained gene expression profiles of GSE70362 and GSE152991 from the Gene Expression Omnibus, followed by their analysis using two machine learning algorithms, least absolute shrinkage and selection operator and support vector machine-recursive feature elimination, which enabled the identification of C-X-C motif chemokine ligand 16 (CXCL16) as a shared diagnostic biomarker for obesity and IDD. Additionally, gene set variant analysis was used to explore the potential mechanism of CXCL16 in these diseases, and CXCL16 was found to affect IDD through its effect on fatty acid metabolism. Furthermore, correlation analysis between CXCL16 and immune cells demonstrated that CXCL16 negatively regulated T helper 17 cells to promote IDD. Finally, independent external datasets (GSE124272 and GSE59034) were used to verify the diagnostic efficacy of CXCL16. In conclusion, a common diagnostic biomarker for obesity and IDD, CXCL16, was identified using a machine learning algorithm. This study provides a new perspective for exploring the possible mechanisms by which obesity impacts the development of IDD.
Warming inhibits increases in vegetation net primary productivity despite greening in India
Authors: Das Ripan , Chaturvedi Rajiv Kumar , Roy Adrija , Karmakar Subhankar , Ghosh Subimal 
Published: December 2023

AbstractIndia is the second-highest contributor to the post-2000 global greening. However, with satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001–2019 fails to translate into increased carbon uptake due to warming constraints. Our analysis further shows 6.19% decrease in Net Primary Productivity (NPP) during 2001–2019 over the temporally consistent forests in India despite 6.75% increase in LAI. We identify hotspots of statistically significant decreasing trends in NPP over the key forested regions of Northeast India, Peninsular India, and the Western Ghats. Together, these areas contribute to more than 31% of the NPP of India (1274.8 TgC.year−1). These three regions are also the warming hotspots in India. Granger Causality analysis confirms that temperature causes the changes in net-photosynthesis of vegetation. Decreasing photosynthesis and stable respiration, above a threshold temperature, over these regions, as seen in observations, are the key reasons behind the declining NPP. Our analysis shows that warming has already started affecting carbon uptake in Indian forests and calls for improved climate resilient forest management practices in a warming world.
Sea level variability and modeling in the Gulf of Guinea using supervised machine learning
Authors: Ayinde Akeem Shola , Yu Huaming , Wu Kejian 
Published: December 2023

AbstractThe rising sea levels due to climate change are a significant concern, particularly for vulnerable, low-lying coastal regions like the Gulf of Guinea (GoG). To effectively address this issue, it is crucial to gain a comprehensive understanding of historical sea level variability, and the influencing factors, and develop a reliable modeling system for future projections. This knowledge is essential for informed planning and mitigation strategies aimed at protecting coastal communities and ecosystems. This study presents a comprehensive analysis of mean sea level anomaly (MSLA) trends in the GoG between 1993 and 2020, covering three distinct periods (1993–2002, 2003–2012, and 2013–2020). It investigates the connections between interannual sea level variability and large-scale oceanic and atmospheric forcings. Furthermore, the study evaluates the performance of supervised machine learning techniques to optimize sea level modeling. The findings reveal a consistent rise in MSLA linear trends across the basin, particularly pronounced in the northern region, with a total linear trend of 88 mm over the entire period. The highest decadal trend (38.7 mm) emerged during 2013–2020, with the most substantial percentage increment (100%) occurring in 2003–2012. Spatial variation in decadal sea-level trends was influenced by subbasin physical forcings. Strong interannual signals in the spatial sea level distribution were identified, linked to large-scale oceanic and atmospheric phenomena. Seasonal variations in sea level trends are attributed to seasonal changes in the forcing factors. The evaluation of supervised learning modeling methods indicates that Random Forest Regression and Gradient Boosting Machines are the most accurate, reproducing interannual sea level patterns in the GoG with 97% and 96% accuracy. These models could be used to derive regional sea level projections via downscaling of climate models. These findings provide essential insights for effective coastal management and climate adaptation strategies in the GoG.