bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using multimodal ultrasound including full-time-series contrast-enhanced ultrasound cines for identifying the nature of thyroid nodules
Authors: He Hanlu , Zhu Junyan , Ye Zhengdu , Bao Haiwei , Shou Jinduo , Liu Ying , Chen Fen 
Published: August 2024

BackgroundBased on the conventional ultrasound images of thyroid nodules, contrast-enhanced ultrasound (CEUS) videos were analyzed to investigate whether CEUS improves the classification accuracy of benign and malignant thyroid nodules using machine learning (ML) radiomics and compared with radiologists.Materials and methodsThe B-mode ultrasound (B-US), real-time elastography (RTE), color doppler flow images (CDFI) and CEUS cines of patients from two centers were retrospectively gathered. Then, the region of interest (ROI) was delineated to extract the radiomics features. Seven ML algorithms combined with four kinds of radiomics data (B-US, B-US + CDFI + RTE, CEUS, and B-US + CDFI + RTE + CEUS) were applied to establish 28 models. The diagnostic performance of ML models was compared with interpretations from expert and nonexpert readers.ResultsA total of 181 thyroid nodules from 181 patients of 64 men (mean age, 42 years +/- 12) and 117 women (mean age, 46 years +/- 12) were included. Adaptive boosting (AdaBoost) achieved the highest area under the receiver operating characteristic curve (AUC) of 0.89 in the test set among 28 models when combined with B-US + CDFI + RTE + CEUS data and an AUC of 0.72 and 0.66 when combined with B-US and B-US + CDFI + RTE data. The AUC achieved by senior and junior radiologists was 0.78 versus (vs.) 0.69 (p &gt; 0.05), 0.79 vs. 0.64 (p &lt; 0.05), and 0.88 vs. 0.69 (p &lt; 0.05) combined with B-US, B-US+CDFI+RTE and B-US+CDFI+RTE+CEUS, respectively.ConclusionWith the addition of CEUS, the diagnostic performance was enhanced for all seven classifiers and senior radiologists based on conventional ultrasound images, while no enhancement was observed for junior radiologists. The diagnostic performance of ML models was similar to senior radiologists, but superior to those junior radiologists.
2.5D peritumoural radiomics predicts postoperative recurrence in stage I lung adenocarcinoma
Authors: Lan Haimei , Wei Chaosheng , Xu Fengming , Yang Eqing , Lu Dayu , Feng Qing , Li Tao 
Published: August 2024

ObjectiveRadiomics can non-invasively predict the prognosis of a tumour by applying advanced imaging feature algorithms.The aim of this study was to predict the chance of postoperative recurrence by modelling tumour radiomics and peritumour radiomics and clinical features in patients with stage I lung adenocarcinoma (LUAD).Materials and methodsRetrospective analysis of 190 patients with postoperative pathologically confirmed stage I LUAD from centre 1, who were divided into training cohort and internal validation cohort, with centre 2 added as external validation cohort. To develop a combined radiation-clinical omics model nomogram incorporating clinical features based on images from low-dose lung cancer screening CT plain for predicting postoperative recurrence and to evaluate the performance of the nomogram in the training cohort, internal validation cohort and external validation cohort.ResultsA total of 190 patients were included in the model in centre 1 and randomised into a training cohort of 133 and an internal validation cohort of 57 in a ratio of 7:3, and 39 were included in centre 2 as an external validation cohort. In the training cohort (AUC=0.865, 95% CI 0.824-0.906), internal validation cohort (AUC=0.902, 95% CI 0.851-0.953) and external validation cohort (AUC=0.830,95% CI 0.751-0.908), the combined radiation-clinical omics model had a good predictive ability. The combined model performed significantly better than the conventional single-modality models (clinical model, radiomic model), and the calibration curve and decision curve analysis (DCA) showed high accuracy and clinical utility of the nomogram.ConclusionThe combined preoperative radiation-clinical omics model provides good predictive value for postoperative recurrence in stage ILUAD and combines the model’s superiority in both internal and external validation cohorts, demonstrating its potential to aid in postoperative treatment strategies.
Neighborhood attention transformer multiple instance learning for whole slide image classification
Authors: Aftab Rukhma , Yan Qiang , Zhao Juanjuan , Yong Gao , Huajie Yue , Urrehman Zia , Mohammad Khalid Faizi 
Published: August 2024

IntroductionPathologists rely on whole slide images (WSIs) to diagnose cancer by identifying tumor cells and subtypes. Deep learning models, particularly weakly supervised ones, classify WSIs using image tiles but may overlook false positives and negatives due to the heterogeneous nature of tumors. Both cancerous and healthy cells can proliferate in patterns that extend beyond individual tiles, leading to errors at the tile level that result in inaccurate tumor-level classifications.MethodsTo address this limitation, we introduce NATMIL (Neighborhood Attention Transformer Multiple Instance Learning), which utilizes the Neighborhood Attention Transformer to incorporate contextual dependencies among WSI tiles. NATMIL enhances multiple instance learning by integrating a broader tissue context into the model. Our approach enhances the accuracy of tumor classification by considering the broader tissue context, thus reducing errors associated with isolated tile analysis.ResultsWe conducted a quantitative analysis to evaluate NATMIL’s performance against other weakly supervised algorithms. When applied to subtyping non-small cell lung cancer (NSCLC) and lymph node (LN) tumors, NATMIL demonstrated superior accuracy. Specifically, NATMIL achieved accuracy values of 89.6% on the Camelyon dataset and 88.1% on the TCGA-LUSC dataset, outperforming existing methods. These results underscore NATMIL’s potential as a robust tool for improving the precision of cancer diagnosis using WSIs.DiscussionOur findings demonstrate that NATMIL significantly improves tumor classification accuracy by reducing errors associated with isolated tile analysis. The integration of contextual dependencies enhances the precision of cancer diagnosis using WSIs, highlighting NATMILs´ potential as a robust tool in pathology.
The role of lymphocyte-C-reactive protein ratio in the prognosis of gastrointestinal cancer: a systematic review and meta-analysis
Authors: Liu XiaoMeng , Zhang JingChen , An HaoYu , Wang WanYao , Zheng YuKun , Wei FengJiang 
Published: August 2024

ObjectiveThe lymphocyte-to-C-reactive protein (LCR) ratio, an immune-inflammatory marker, shows prognostic potential in various cancers. However, its utility in gastrointestinal malignancies remains uncertain due to inconsistent findings. This systematic review and meta-analysis synthesizes recent evidence to elucidate the association between LCR and prognosis in gastrointestinal cancer patients, aiming to clarify LCR’s potential role as a prognostic biomarker.MethodsWe searched PubMed, Embase, Cochrane, and Web of Science databases up to May 2024 to evaluate the association between LCR and prognosis in gastrointestinal cancer patients. The main outcomes included overall survival (OS), recurrence-free survival (RFS), and disease-free survival (DFS). We also analyzed secondary parameters such as geographical region, study duration, sample size, LCR threshold, and patient characteristics (age, gender, tumor location, and TNM stage).ResultsThis meta-analysis of 21 cohort studies (n=9,131) finds a significant association between reduced LCR levels and poor prognosis in gastrointestinal cancer. Lower LCR levels were associated with worse overall survival (HR=2.01, 95% CI=1.75-2.31, P&lt;0.001), recurrence-free survival (HR=1.90, 95% CI=1.32-2.76, P&lt;0.001), and disease-free survival (HR=1.76, 95% CI=1.45-2.13, P&lt;0.001). Subgroup analyses by cancer type, timing, and LCR threshold consistently confirmed this relationship (P&lt;0.05).ConclusionLCR may serve as a prognostic marker in gastrointestinal cancer patients, with lower LCR levels associated with poorer prognosis. However, more high-quality studies are needed to validate these findings, considering the limitations of the current evidence.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023486858.
The prognostic value of preoperative peripheral blood inflammatory biomarkers in extrahepatic cholangiocarcinoma: a systematic review and meta-analysis
Authors: Zeng Di , Wang Yaoqun , Wen Ningyuan , Lu Jiong , Li Bei , Cheng Nansheng 
Published: August 2024

BackgroundRecent evidence indicates that inflammation plays a major role in the pathogenesis and progression of CCA. This meta-analysis seeks to evaluate the prognostic implications of preoperative inflammatory markers, specifically NLR, PLR, and LMR, in patients with eCCA. By focusing on these preoperative biomarkers, this study aims to provide valuable insights into their prognostic value and potential utility in clinical practice.MethodsFor this analysis, comprehensive searches were conducted in PubMed, Embase, and Web of Science databases from inception to May 2024. The primary outcomes of interest focused on the association between the levels of NLR, PLR, and LMR and the prognosis of eCCA patients. Statistical analyses were conducted using STATA 17.0 software.ResultsThe meta-analysis, involving 20 retrospective studies with 5553 participants, revealed significant correlations between preoperative biomarkers and the prognosis of eCCA patients. Elevated NLR, PLR, and decreased LMR levels were extensively studied regarding overall survival (OS) in eCCA patients. Elevated NLR was an independent predictor of poor OS (HR 1.86, p &lt; 0.001), similar to elevated PLR (HR 1.76, p &lt; 0.001), while decreased LMR predicted poor OS (HR 2.16, p &lt; 0.001). Subgroup analyses based on eCCA subtypes and curative surgery status showed consistent results.ConclusionsIn conclusion, our study emphasizes the clinical significance of assessing NLR, PLR, and LMR preoperatively to predict patient prognosis. Elevated NLR and PLR values, along with decreased LMR values, were linked to poorer overall survival (OS). Large-scale prospective cohort studies are required to confirm their independent prognostic value in eCCA.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024551031.
Skipping breakfast is associated to inadequate nutrient intakes among Tunisian children: a cross-sectional study
Authors: El Ati Jalila , Doggui Radhouene , Dogui Darine , El Ati-Hellal Myriam 
Published: August 2024

IntroductionBreakfast is widely acknowledged as a crucial meal of the day, particularly for children, owing to its role in supplying essential nutrients and energy necessary for optimal growth and cognitive function. This study aims to examine differences in nutrient intake between breakfast skippers and non-skippers among children.MethodsA representative sample of 1,200 Tunisian preschool and schoolchildren, aged 3–9 years, was randomly selected from kindergartens and primary schools in the Greater Tunis region which includes four governorates (Tunis, Ariana, Manouba and Ben Arous) using a two-stage cross-sectional design. Stratification was carried out depending on each of the selected governorates and urban/rural areas. Dietary intake was evaluated using the 24-hour recall method and a diet history covering the week preceding the survey. Nutritional food composition was derived from a specific Tunisian food composition database. Nutrient intake below age- and sex-specific reference values was considered inadequate.Results and DiscussionThe findings indicate that the daily intake of energy and nutrients was lower among breakfast skippers compared to regular breakfast eaters. After adjusting for energy, gender, age, BMI and household economic proxy, the daily consumption of total sugar, riboflavin, vitamin B-5, phosphorus and calcium was higher among breakfast consumers while saturated fatty acid intake was higher among skippers. A comparative analysis of daily mean food category intake between the two groups revealed a higher consumption of milk and dairy products among breakfast consumers. Regular breakfast consumption is an important part of maintaining a balanced diet and healthy weight.
Impact of religion and spirituality on the incidence of depression and mental health among young adults in the Czech Republic
Authors: Brečka Tibor A. , Ptáček Radek , Sebalo Ivan , Anders Martin , Sebalo Vňuková Martina 
Published: August 2024

IntroductionThe issue of the impact of religion and spirituality on mental health is a phenomenon which has recently become increasingly more accentuated. Despite the attention given to the topic, many questions still remain as to whether and how religion and spirituality affect a person’s mental wellbeing. In the text below, we have focused on examining the relationship between religion and spirituality and mental health among young adults in the Czech Republic. Research also explored the idea that forgiveness can be viewed as a component of religion or spirituality.Materials and methodsThe research project was executed in close cooperation with STEM/MARK, a renowned data collection agency. The methodological framework was constructed with a dual focus: leveraging standardized questionnaires to ensure data reliability and comparability while also incorporating tailored questions that delve into the participants’ socioeconomic status (SES) and background details. The study unfolded across four online sessions, a format chosen for its convenience and effectiveness in facilitating participant engagement while accommodating our respondents’ diverse schedules. The total sample approached comprised of 270 young adults that expressed certain form of religiosity.ResultsForgiveness and the depth of one’s personal religious or spiritual history emerged as the most influential factors. Forgiveness was significantly associated with an increase in self-blame (positively), and decrease in refocusing, planning (both negatively), and putting things into perspective (negatively) (Beta = 0.25, Beta = −0.06, and Beta = −0.16, respectively). In contrast, a deeper personal religious history was positively associated with self-blame, rumination, and refocusing (Beta = 0.22, Beta = 0.13, and Beta = 0.15, respectively).ConclusionThe finding that forgiveness may be a risk factor associated with regularly elevated depressive symptoms, stress, and maladaptive coping strategies such as self-blame and ruminating over problems, while negatively affecting physical, psychological, and environmental quality of life, clearly points to the need to examine the inner aspects of individual religions and spiritualities. These findings suggest that religious and spiritual beliefs may play a key role in how people experience and manage the emotional burdens and difficulties of life.
Effects of aripiprazole on prolactin levels and differences in effectiveness in patients with schizophrenia: a post-hoc analysis of the real-world data of a multicenter study
Authors: Li Qian , Su Yun-Ai , Liao Xuemei , Fang Maosheng , Gao Jianliang , Xu Jia , Duan Mingjun , Yu Haiying , Yang Yang , Chen Zhiyu , Liu Jintong , Yan Shaoxiao , Yao Peifen , Li Shuying , Wang Changhong , Wu Bin , Zhang Congpei , Si Tianmei 
Published: August 2024

ObjectivesTo investigate the effect of aripiprazole on prolactin levels in patients with schizophrenia and analyze whether varying baseline prolactin levels affect the effectiveness and safety of aripiprazole, in a real-life diagnostic and therapeutic setting in a post-hoc analysis.MethodsIn this post-hoc analysis, patients with schizophrenia in the acute phase were divided into an elevated-prolactin group and a normal-prolactin group. After 8 weeks of aripiprazole treatment, changes in the proportion of patients with an abnormal prolactin level were analyzed in both groups, and the efficacy and safety of aripiprazole were compared between the two groups.ResultsThe elevated-prolactin group had more women, a longer duration of disease, and lower Positive and Negative Syndrome Scale (PANSS) total and subscale scores at baseline compared with the normal-prolactin group (all P &lt; 0.05), and there was no significant difference in the proportion of patients with prior use of antipsychotic medication between the two groups. Regardless of previous antipsychotic use, patients in both groups developed hyperprolactinemia (23/168 [13.7%] in those who had taken antipsychotics vs. 43/375 [11.4%] in those who had not). After 8 weeks of aripiprazole treatment, the proportion of patients with abnormal prolactin in the elevated-prolactin group significantly decreased with prolonged treatment (P &lt; 0.001), and aripiprazole had no significant effect on the normal-prolactin group (P = 0.250). Normal-prolactin group showed better efficacy than the elevated-prolactin group, and the differences in efficacy between the two groups was observed from week 4 to the endpoint (all p&lt;0.05). In total, 87.2% (68/78) patients experienced mild to moderate adverse events in the elevated-prolactin group, which was significantly more frequent compared with the normal-prolactin group 71.0% (365/514).ConclusionsIn this real-world study, for patients with acute schizophrenia, aripiprazole was effective in lowering the proportion of patients with abnormal prolactin levels, while it had no significant effect on patients with normal baseline prolactin. After adjusting for factors such as sex, age, prior antipsychotic drugs use history and disease severity, effectiveness and safety of aripiprazole in patients with normal baseline prolactin was significantly better than that in patients with elevated baseline prolactin.
Inverted U-shaped relationship between serum 25-hydroxyvitamin D concentrations and Toxoplasma gondii infection: a cross-sectional study
Authors: Huang Lihua , Luo Xiaoyan , He Liuliu , You Xiaoyan , Chen Xiaobo 
Published: August 2024

BackgroundToxoplasma gondii (T. gondii) is a widespread zoonotic parasite transmitted through contaminated food or water. It poses a significant public health threat, especially to pregnant women and immunocompromised individuals. 25-Hydroxyvitamin D [25(OH)D] plays a critical role in regulating both innate and adaptive immune responses, particularly in its anti-infective capacity. However, the relationship between serum 25(OH)D concentrations and T. gondii infection remains uncertain.MethodsWe analyzed the data from the National Health and Nutrition Examination Survey (NHANES) spanning 2009–2014 to explore the association between serum 25(OH)D concentrations and T. gondii infection. Extensive demographic, comorbidity, and dietary data were collected. The status of T. gondii infection was determined using serum anti-IgG antibodies. Serum 25(OH)D levels were measured using ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). In addition, weighted logistic regression and restricted cubic spline analyses were performed.ResultsOur analysis included 10,157 participants (mean [SE] age, 45.38 [0.39] years; 49.73% female) who met the inclusion criteria. Serum 25(OH)D levels were categorized into quintiles, with the second quintile serving as the reference group. The final model, adjusted for age, sex, race, education level, poverty income ratio, body mass index, smoking status, hypertension, diabetes, chronic kidney disease, depression, physical activity, alcohol intake, seasonal testing, and dietary vitamin D, revealed the following adjusted odds ratios (ORs) for the quintiles: 0.75 (95% confidence interval [CI]: 0.60–0.93) for the first, 0.87 (95% CI: 0.69–1.10) for the third, 0.75 (95% CI: 0.58–0.95) for the fourth, and 0.66 (95% CI: 0.49–0.91) for the fifth. Additionally, a restricted cubic spline analysis revealed an inverted U-shaped relationship between serum 25(OH)D and T. gondii infection, with an inflection point at approximately 51.29 nmol/L. Odds ratios to the left and right of the inflection point were 1.17 (95% CI: 1.03–1.32) and 0.94 (95% CI, 0.90–0.98) per 10 nmol/L, respectively.ConclusionOur study uncovers an inverted U-shaped relationship between serum 25(OH)D concentrations and T. gondii infection, with an inflection point around 51.29 nmol/L.
Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks
Authors: Vashistha Rajat , Vegh Viktor , Moradi Hamed , Hammond Amanda , O’Brien Kieran , Reutens David 
Published: August 2024

IntroductionThe reconstruction of PET images involves converting sinograms, which represent the measured counts of radioactive emissions using detector rings encircling the patient, into meaningful images. However, the quality of PET data acquisition is impacted by physical factors, photon count statistics and detector characteristics, which affect the signal-to-noise ratio, resolution and quantitative accuracy of the resulting images. To address these influences, correction methods have been developed to mitigate each of these issues separately. Recently, generative adversarial networks (GANs) based on machine learning have shown promise in learning the complex mapping between acquired PET data and reconstructed tomographic images. This study aims to investigate the properties of training images that contribute to GAN performance when non-clinical images are used for training. Additionally, we describe a method to correct common PET imaging artefacts without relying on patient-specific anatomical images.MethodsThe modular GAN framework includes two GANs. Module 1, resembling Pix2pix architecture, is trained on non-clinical sinogram-image pairs. Training data are optimised by considering image properties defined by metrics. The second module utilises adaptive instance normalisation and style embedding to enhance the quality of images from Module 1. Additional perceptual and patch-based loss functions are employed in training both modules. The performance of the new framework was compared with that of existing methods, (filtered backprojection (FBP) and ordered subset expectation maximisation (OSEM) without and with point spread function (OSEM-PSF)) with respect to correction for attenuation, patient motion and noise in simulated, NEMA phantom and human imaging data. Evaluation metrics included structural similarity (SSIM), peak-signal-to-noise ratio (PSNR), relative root mean squared error (rRMSE) for simulated data, and contrast-to-noise ratio (CNR) for NEMA phantom and human data.ResultsFor simulated test data, the performance of the proposed framework was both qualitatively and quantitatively superior to that of FBP and OSEM. In the presence of noise, Module 1 generated images with a SSIM of 0.48 and higher. These images exhibited coarse structures that were subsequently refined by Module 2, yielding images with an SSIM higher than 0.71 (at least 22% higher than OSEM). The proposed method was robust against noise and motion. For NEMA phantoms, it achieved higher CNR values than OSEM. For human images, the CNR in brain regions was significantly higher than that of FBP and OSEM (p &lt; 0.05, paired t-test). The CNR of images reconstructed with OSEM-PSF was similar to those reconstructed using the proposed method.ConclusionThe proposed image reconstruction method can produce PET images with artefact correction.