bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Learning Frameworks for Histopathological Image Processing in Colorectal Cancer Diagnostics
Authors: Frasca Maria , Cutica Ilaria , Pravettoni Gabriella , Torre Davide La 
Published: November 2024

Abstract

Artificial intelligence (AI) in the field of pathology and medical diagnostics has rapidly evolved, with applications focused on analyzing histopathological images. These images, obtained from biopsies or surgical procedures, are crucial for diagnosing diseases, particularly cancer, and provide essential insights into tissue structure. Traditionally, pathologists faced a challenging task in accurately analyzing the cellular features within these images. However, the introduction of deep learning, has significantly improved diagnostic reliability. In this study, two convolutional neural network models were implemented and compared. Both were trained on a multiclass dataset of histological images related to colorectal cancer. Among the two tested models, VGG-19 demonstrated the best performance, achieving a precision rate of 98%. Using a Python-based graphical interface, we employed the "Grad-CAM" technique to gain deeper insight into the model's classification process and identify key regions during training. The application of artificial intelligence to colon histopathological images also has the potential to improve patient outcomes and early cancer diagnosis. By combining AI with intuitive interfaces, we can enhance diagnostic accuracy and accelerate the analysis process.
Aberrant promoter methylation, expression and function of RASSF1A gene in a series of Italian parathyroid tumors
Authors: Verdelli Chiara , Fabrizio Federico Pio , Maroni Paola , Morotti Annamaria , Tavanti Giulia Stefania , Carrara Silvia , Guarnieri Vito , Cetani Filomena , Scillitani Alfredo , Maggiore Riccardo , Perticone Francesca , Vaira Valentina , Muscarella Lucia Anna , Corbetta Sabrina 
Published: November 2024

Abstract

Purpose: Aberrant epigenetic features are key events involved in parathyroid tumorigenesis, including DNA methylation, histone methylation, and non-coding RNAs. Ras Association Domain Family Protein1 Isoform A (RASSF1A) and Adenomatous Polyposis of Colon (APC) are frequently downregulated in human cancers. Here, we investigated their deregulated expression and the potential role in parathyroid neoplasms.
Methods: methylation of RASSF1A and APC promoters was analyzed in a series of parathyroid adenomas (PAds, n=80) and parathyroid carcinomas (PCas, n=9) from Italian patients with primary hyperparathyroidism,
Results: RASSF1A and APC promoter methylation occurred in about 90% of PAds samples. PCas displayed RASSF1A promoter methylation, while APC promoter was methylated only in 2 samples. Of note, RASSF1A promoter methylation negatively correlated with PAds tumor size. However, RASSF1Atranscript and protein levels were reduced in PAds and PCas compared with parathyroid normal glands. Investigating the potential mechanism involved in RASSF1A promoter methylation, we found that DNA methyltransferases (DNMTs) activity was variable in PAds and inversely correlated with RASSF1A protein levels. In addition, the RASSF1A promoter methylation negatively correlated with long-non-coding Antisense Intronic Noncoding RASSF1A (ANRASSF1A) mRNA levels, excluding the involvement of ANRASSF1 in RASSF1A regulation. In HEK293A cells transfected with the calcium sensing receptor (CASR), loss of RASSF1A increased basal phosphorylated Extracellular signal-regulated kinase (pERK/ERK) levels blunting the CASR-induced increases.
Conclusion: RASSF1A and APC promoter methylation is a hallmark of parathyroid tumors; deregulation of DNMTs activity contributes to modulation of RASSF1Aexpression. Loss of RASSF1A may be involved in the tuning of ERK pathway in parathyroid tumors.
3D Creatine Kinase Imaging (CKI) for In Vivo Whole-Brain Mapping of Creatine Kinase Reaction Rates with 31P-Magnetization Transfer MR Fingerprinting
Authors: Widmaier Mark Stephan , Kaiser Antonia , Lim Song-I , Pandurevic Pontus , Döring Andre , Huang Zhiwei , Wenz Daniel , Xiao Ying , Jiang Yun , Xin Lijing 
Published: November 2024

Abstract

The creatine kinase (CK) is a key enzyme involved in brain bioenergetics, but imaging its activity noninvasively in the human brain remains a significant challenge. This study aims to advance the magnetization transfer (MT)-31P magnetic resonance fingerprinting (MRF) framework for 3D Creatine Kinase Imaging (CKI), delivering the first whole-brain CK reaction rate maps. The method was implemented and validated on a clinical 7 Tesla MRI scanner with a 49:30-minute acquisition time and the within-session reproducibility was assessed. The CKI method successfully enables the whole-brain mapping of CK reaction rates, showing robust reproducibility with coefficients of variation (CV) below 11% for 25-minute scan sessions. Furthurmore, CKI acquisition provided simultaneous mapping of adenosine triphosphate (ATP) and phosphocreatine (PCr) concentrationratios, PCr longitudinal relaxation time (T1PCr), and phosphorus-based B0 maps at a 7.2 × 7.2 × 20 mm3 resolution. CKI provides, for the first time,3D whole-brain mapping of kCK rates in high resolution, using a user-friendly, push-button approach. A functional CKI (fCKI) study demonstrated the first CK activation cluster map in response to visual stimulation, revealing a mean 17% increase in CK rates in the visual cortex. The novel imaging modalities, CKI and fCKI, have the potential to offer new insights into brain bioenergetics both at rest and during activity.
Improve Life Satisfaction among Adolescent: The Role of Natural exposure, Mindfulness and Chemosensory Hedonic Capacity
Authors: Teng Shan , Chunxin Tan , Su Waxun , Zhang Jianqiang , Zhao Jiubo 
Published: November 2024

Abstract

Purpose This study explores the influence mechanism of
nature-deficit disorder on life satisfaction of adolescent，and the
possible mediating role of mindfulness and chemosensory hedonic
capacity between them. Methods A survey was conducted on 1417
adolescents using the Adolescent Nature-Deficit Scale（ANDS）, the
Mindful Attention Awareness Scale—Children(MAAS-C), The
Chemosensory Pleasure Scale for children (CPS-C), and the
Satisfaction with Life Scale (SWLS). Results Correlation analysis
showed that, nature-deficit disorder, mindfulness, chemosensory
hedonic capacity and life satisfaction significantly correlated
with each other. Path analysis indicated that nature-deficit
disorder can negatively impact on life satisfaction of adolescent;
Nature-deficit disorder affected life satisfaction indirectly not
only through the mediating effect of mindfulness and chemosensory
hedonic capacity respectively, but also through the chain mediating
effect of mindfulness and chemosensory hedonic capacity. Conclusion
nature-deficit disorder could exert effect on life satisfaction
among adolescent through the mediational chains of mindfulness and
chemosensory hedonic capacity. Keywords nature-deficit
disorder; life satisfaction; mindfulness; chemosensory hedonic
capacity; chained meditation
Influence of weather and climate variability on the incidence of groundnut thrips across five agro climatic zones of India: A decadal analysis
Authors: Prabhakar M , Vennila S. , Nisar Shabistana , Chandra Puran , Yadav Satish Kumar , Srinivasa M , Prasad YG , Thirupathi M , Kaplana M , Kumar Nallagatla Vinod , Singh VK 
Published: November 2024

Abstract

Population dynamics and damage levels of insects on crop is influenced by changing weather patterns and variability in climate over short and long scales of time. Temporal changes in abundance and infestation of thrips (Thripidae: Thysonoptera) over six seasons at five groundnut growing agro ecologies of India were related to changing weather and climatic variability in addition to deducing future status of thrips. The Onset of thrips abundance (nos/three leaves/plant) and infestation (%) over crop seasons varied spatially. Thrips abundance and infestation compared for crop seasons (2011-20) showed significant inter seasonal differences within locations for seasons. Lower abundance and infestation at Junagadh (Gujarat) and Virudhachalam (Tamil Nadu) over Dharwad (Karnataka), Jalgaon (Maharashtra) and Kadiri (Andhra Pradesh) were noted. Statistical comparisons of seasonal weather, climatic deviations and magnitude of temperature and rainfall indicated within and between seasonal as w ell as spatially differing variability. All significant associations of climatic deviations with thrips dynamics were positive and increased thrips infestation was predicted for 2050 and 2080 at Junagadh. At least one or more changing climatic variables had positive significance with either thrips abundance or infestation at each study location and it is needful to practice relevant thrips management studying at local levels. Projected increased thrips infestation at Junagadh for future periods sets the research agenda for development of resistant cultivars and adjustments in a local cropping system.
Effect of Photobiomodulation on Root Covering Associated with the Connective Tissue Grafting Technique - Randomized Controlled Clinical Study
Authors: Guimarães Camila Coelho , Ferreira Anderson Jara , Sperandio Marcelo 
Published: November 2024

Abstract

Introduction:Gingival recessions are very common periodontal defects that result in aesthetic impairment of the patient due to disharmony and asymmetry of the gingival contour, as well as complaints of dentin hypersensitivity. The aim of this study was to evaluate the effects of photobiomodulation (PBM) on root coverage of gingival recessions using the connective tissue graft technique in a prospective, randomized, double-blind clinical study.Materials and Methods:40 patients were selected and randomly divided into 2 groups with Miller Class I and II gingival recession on canines or premolars without the presence of cervical wear. The test group underwent tunneling with connective tissue grafting for root coverage and BMF application, while the control group underwent tunneling with connective tissue grafting for root coverage and placebo BMF application. The data was analyzed using the Friedman test (repeated measures) and the Wilcoxon test (baseline and final), with p<0.05.Results:Among the clinical parameters, there was no difference between the control group and the test group in any of the parameters investigated. Regarding patient-centered parameters, dentin hypersensitivity was significantly reduced after 6 months in both groups. There was also an improvement in aesthetics at the end of treatment in both groups and, with regard to post-operative discomfort, there was a significant difference in the group treated with MBF.Conclusion:Photobiomodulation reduced patients' post-operative discomfort without significantly affecting clinical parameters.
An Explainable machine learning model for predicting response to targeted therapy and immunotherapy in advanced hepatocellular carcinoma: a multicentric study
Authors: Zhang Jin-Xing , Yan Hai-Tao , Fan Wen-Long , Wei Juan , Liu Sheng , Shi Hai-Bin , Cheng Yuan , Feng Zun-lei , Zu Qing-Quan 
Published: November 2024

Abstract

Background and aims Combination therapy based on targeted therapy and immunotherapy is a first-line treatment for advanced hepatocellular carcinoma (HCC). However, accurately predicting tumor response to the combination therapy is challenging. We aimed to develop an explainable machine learning model to predict response to the combination therapy in advanced HCC.
Methods Patients with advanced HCC who received targeted therapy combined with immunotherapy at four tertiary hospitals were enrolled between January 2020 and January 2024. The extreme gradient boosting (XGBoost) model was constructed to predict whether patients would respond to the combination therapy. The area under the receiver operating characteristic curve (AUC) and F1 score were used to evaluate the predictive performance of the XGBoost model. The SHapley Additive exPlanations (SHAP) method was deployed to interpret the XGBoost model.
Results A total of 179 patients were enrolled in this study, and seventy-six patients (42.5%) showed a response to the combination therapy. The XGBoost model had an AUC of 0.795 (95% confidence interval: 0.716–0.873) and a F1 score of 0.704 for predicting the response to the combination therapy for advanced HCC in the training set. The importance of SHAP variables in the XGBoost model ranked from high to low, was: interventional therapy, portal vein tumor thrombus, extrahepatic metastasis, number of tumors, and age.
Conclusion The XGBoost machine learning model shows high performance in predicting response to targeted therapy combined with immunotherapy in advanced HCC. Additionally, the SHAP method facilitates a comprehensive interpretation of the results generated by the machine learning model.
Healthcare-Seeking Intentions of Middle-Aged and Elderly Individuals with Critical Diseases in Taiwan During the COVID-19
Authors: Lee Po-Chun , Huang Ching-Yuan , Hsu Meng-Jun 
Published: November 2024

Abstract

Background
The COVID-19 pandemic has posed a significant threat to global public health. Over the past decade, Taiwan has experienced an aging population, with mortality rates from illnesses rising each year. During the pandemic, middle-aged and elderly patients with critical diseases were often reluctant to seek medical care due to fear of infection, potentially impacting disease control, health monitoring, and quality of life. Understanding the healthcare-seeking behavior of middle-aged and elderly patients with critical diseases during the pandemic is crucial for improving healthcare accessibility and reducing mortality rates.
Methods
This study applied the Theory of Planned Behavior (TPB) as the foundational framework, incorporating three main constructs: “attitude,” “subjective norm,” and “perceived behavioral control.” Additionally, two more constructs, “perceived risk” and “trust,” were included to explore the healthcare decision-making “behavioral intentions” of critical disease patients during the COVID-19 pandemic. Using a cross-sectional study design and purposive sampling, a total of 526 valid questionnaires were collected, and the structural equation model was verified using Partial Least Squares (smart PLS).
Results
Among the five primary dimensions influencing patients’ healthcare decision-making "behavioral intentions," “trust” was found to have the most significant impact, followed by “attitude,” “perceived risk,” “perceived behavioral control,” and “subjective norm.” All secondary dimensions within the five primary dimensions were shown to significantly affect "behavioral intentions" through mediating effects. Additionally, the three common causes of critical diseases—hypertension, hyperglycemia, and hyperlipidemia—were found to have a positive and significant impact on "behavioral intentions."
Conclusion
The expanded Theory of Planned Behavior used in this study provides a theoretical framework for understanding health behavior decision-making processes, effectively explaining the "behavioral intentions" of middle-aged and elderly patients with critical diseases in seeking healthcare during the COVID-19 pandemic.
ACR combined with PPS to treat lumbar degenerative diseases: a retrospective study
Authors: Yan Xiaobing , Feng Dapeng , Chu Jin , Li Zhengwei 
Published: November 2024

Abstract

Study Design. Retrospective study to investigate the benefits of ACR for lumbar degenerative diseases (LDD).
Objective. Investigate the outcomes of anterior column realignment(ACR) combined with percutaneous pedicle screw fixation(PPS) and differ for transforaminal lumbar interbody fusion (TLIF) for LDD.
Methods.
From June 2018 to December 2021, 22 consecutive patients with LDD underwent ACR. At the same time while 22 patients underwent TLIF. Preoperative and intraoperative parameters of all the patients are collected. The influences of ACR on mechanical factors and indirect decompression were evaluated by radiological parameters. Function improvements are assessed by Oswestry Disability Index (ODI), Visual Analogue Score (VAS) and Japanese Orthopaedic Association (JOA) Scores during one year of follow-up.
Results.
Preoperatively, there was no significant difference of age, sex, body mass index (BMI), ODI, VAS and JOA scores in both groups . Compared with ACR group, TLIF group had increased hospital stay (6.77±3.25 days vs. 5.0±1.11 days, P<0.05), blood loss (645.45±571.95ml vs. 235.45±78.30ml, P<0.05) and postoperative drainage (391.82±364.84 ml vs. 0 ml, P<0.001). ACR could significantly improve the radiological parameters. The short-term scores of function and pain of ACR group were higher than TLIF group.
Conclusion.
Both of ACR and TLIF could effectively resolve the symptoms of LDD. Compared with TLIF, ACR had a better improvement of short-term outcomes. ACR could be performed and improved as optional treatment strategy for LDD.
Predicting pragmatic language abilities from brain structural MRI in preschool children with ASD by NBS-Predict
Authors: Qian Lu , Ding Ning , Fang Hui , Xiao Ting , Sun Bei , Gao HuiYun , Ke XiaoYan 
Published: November 2024

Abstract

Pragmatics, as it pertains to spoken language, plays a crucial role in effectively conveying messages across various social communication contexts. This aspect is frequently highlighted in the challenges experienced by children diagnosed with autism spectrum disorder (ASD). Notably, there remains a paucity of research investigating how the structural connectome (SC) predicts pragmatic language abilities within this population. Using diffusion tensor imaging (DTI) and deterministic tractography, we constructed the whole-brain white matter structural network (WMSN) in a cohort comprising 92 children with ASD and 52 typically developing (TD) preschoolers, matched for age and gender. Subsequent graph theoretical analyses were conducted to assess alterations in the global and node-based properties of the WMSN within both cohorts. To further elucidate these findings, we employed NBS-Predict, a novel methodology that integrates machine learning (ML) with network-based statistics (NBS), to identify dysconnected subnetworks associated with ASD. Our application of NBS-Predict allowed us to predict pragmatic language abilities based on the SC derived from the whole-brain WMSN in the ASD group. Initially, NBS-Predict identified a subnetwork characterized by 42 reduced connections across 37 brain regions (p = 0.01), achieving a highest classification accuracy of 79.4% (95% CI: 0.791–0.796). The dysconnected regions were predominantly localized within the brain’s frontotemporal and subcortical areas, with the right superior medial frontal gyrus (SFGmed.R) emerging as the region exhibiting the most extensive disconnection. Moreover, NBS-Predict demonstrated that the optimal correlation coefficient between the predicted pragmatic language scores and the actual measured scores was 0.204 (95% CI: 0.181–0.226). This analysis revealed a significant association between the pragmatic language abilities of the ASD cohort and the white matter connections linking the SFGmed.R with the bilateral anterior cingulate gyrus (ACC). In summary, our findings suggest that the subnetworks displaying the most significant abnormal connections were concentrated in the frontotemporal and subcortical regions among the ASD group. Furthermore, the observed abnormalities in the white matter connection pathways between the SFGmed.R and ACC may underlie the neurobiological basis for pragmatic language deficits in preschool children with ASD.
Evaluation of imputation strategies for multi-centre studies: Application to a large clinical pathology dataset
Authors: Grigoroff Lucy , Masuda Reika , Lindon John , Kadyrov Janonna , Nicholson Jeremy Kirk , Holmes Elaine , Wist Julien 
Published: November 2024

Abstract

As part of a strategy for accommodating missing data in large heterogeneous datasets, two Random Forest-based (RF) imputation methods, missForest and MICE were evaluated along with several strategies to help them handle the inherent structure of the dataset. Background: A total of 3817 complete cases of clinical chemistry variables from a large-scale, multi-site preclinical longitudinal pathology study were used as an evaluation dataset. Three types of ‘missingness’ in various proportions were artificially introduced to compare imputation performance for different strategies including variable inclusion and stratification. Results: MissForest was found to outperform MICE, being robust and capable of automatic variable selection. Stratification had minimal effect on missForest but severely deteriorated the performance of MICE. Conclusion: In general, storing and sharing datasets prior to any correction is a good practise, so that imputation can be performed on merged data if necessary.
Macular ganglion cell complex layer thickness measured with spectral-domain OCT in a large population-based cohort study
Authors: Lin Caixia , Wu Jian , Lv Aiguo , Liu Hongyi , Pan Qing , Cao Kai , Jia Xu , Fan Sujie , Wang Ning Li 
Published: November 2024

Abstract

Purpose: To establish the normal GCC thicknesses profile in the general population using SD-OCT in different macular sectors. To determine the systemic and ophthalmic factors associated with GCC thickness and further identify the potential risk factors were the secondary objective.
Methods: Participants in the population-based cohort study had to be at least thirty years old. Every participant had a routine ophthalmological examination. Using SD-OCT, the GCC thickness was determined. To assess the relationship between GCC thickness and systemic and ocular characteristics, mixed linear models were used. R V.4.1.1 was the statistical analysis program utilized.
Results: 2490 subjects average age of 56.60 ± 10.39 years were collected in this analysis. GCC average thickness measured was 95.57±7.47μm. GCC thickness of the superior(95.46±7.87μm) was the thinnest, and the inferior subfield(95.68±7.66μm) was thickest. In univariate and multivariate regression models，thinner GCC thickness was significantly associated with older age (P < 0.001), absence of smoking (P = 0.002), higher SBP (P < 0.001) and DBP (P < 0.001), more diabetes (P<0.001), higher HbA1c (P<0.001), lower HDL (P=0.001), higher LDL (P=0.011), coronary heart disease (P < 0.001), history of coronary heart disease (P = 0.007), lower IOP (P = 0.198), higher spherical equivalent (P = 0.009), and better BCVA (P < 0.001).
Conclusions: When diagnosing non-glaucoma patients, it is important to take into account the variation in GCC thickness throughout the Chinese community. In the meantime, the thickness of GCC is tightly associated to several ocular and systemic variables. Our results also highlighted the necessity of creating normative databases globally, as well as demonstrating ethnic disparities in GCC thickness and the uniqueness of related ocular and systemic variables.