bluuebunny/crossref_metadata_2025_split huggingface dataset:
External validation of the 2-year mortality prediction tool in hemodialysis patients developed using a Bayesian network
Authors: Granal Maelys , Brokhes-Le Calvez Sophie , Dimitrov Yves , Chantrel François , Borni-Duval Claire , Muller Clotilde , Délia May , Krummel Thierry , Hannedouche Thierry , Ducher Micher , Fauvel Jean-Pierre 
Published: April 2024

ABSTRACT

Background
In recent years, a number of predictive models have appeared to predict the risk of medium-term mortality in hemodialysis patients, but only one, limited to patients aged over 70 years, has undergone sufficiently powerful external validation. Recently, using a national learning database and an innovative approach based on Bayesian networks and 14 carefully selected predictors, we have developed a clinical prediction tool to predict all-cause mortality at 2 years in all incident hemodialysis patients. In order to generalize the results of this tool and propose its use in routine clinical practice, we carried out an external validation using an independent external validation database.

Methods
A regional, multicenter, observational, retrospective cohort study was conducted to externally validate the tool for predicting 2-year all-cause mortality in incident and prevalent hemodialysis patients. This study recruited a total of 142 incident and 697 prevalent adult hemodialysis patients followed up in one of the eight Association pour l'Utilisation du Rein Artificiel dans la région Lyonnaise (AURAL) Alsace dialysis centers.

Results
In incident patients, the 2-year all-cause mortality prediction tool had an area under the receiver curve (AUC-ROC) of 0.73, an accuracy of 65%, a sensitivity of 71% and a specificity of 63%. In prevalent patients, the performance for the external validation were similar in terms of AUC-ROC, accuracy and specificity, but was lower in term of sensitivity.

Conclusion
The tool for predicting all-cause mortality at 2 years, developed using a Bayesian network and 14 routinely available explanatory variables, obtained satisfactory external validation in incident patients, but sensitivity was insufficient in prevalent patients.
Thermal tolerance and survival are modulated by a natural gradient of infection in differentially acclimated hosts
Authors: De Bonville Jérémy , Côté Ariane , Binning Sandra A 
Published: April 2024

ABSTRACT
Wild ectotherms are exposed to multiple stressors, including parasites, that can affect their responses to environmental change. Simultaneously, unprecedented warm temperatures are being recorded worldwide, increasing both the average and maximum temperatures experienced in nature. Understanding how ectotherms, such as fishes, will react to the combined stress of parasites and higher average temperatures can help predict the impact of extreme events such as heat waves on populations. The critical thermal method (CTM), which assesses upper (CTmax) and lower (CTmin) thermal tolerance, is often used in acclimated ectotherms to help predict their tolerance to various temperature scenarios. Despite the widespread use of the CTM across taxa, few studies have characterized the response of naturally infected fish to extreme temperature events or how acute thermal stress affects subsequent survival. We acclimated naturally infected pumpkinseed sunfish (Lepomis gibbosus) to four ecologically relevant temperatures (10, 15, 20 and 25°C) and one future warming scenario (30°C) for 3 weeks before measuring CTmax and CTmin. We also assessed individual survival the week following CTmax. Parasites were counted and identified following trials to relate infection intensity to thermal tolerance and survival. Interestingly, trematode parasites causing black spot disease were negatively related to CTmax, suggesting that heavily infected fish are less tolerant to acute warming. Moreover, fish infected with yellow grub parasites showed decreased survival in the days following CTmax implying that the infection load has negative survival consequences on sunfish during extreme warming events. Our findings indicate that, when combined, parasite infection and high prolonged average temperatures can affect fish thermal tolerance and survival, emphasizing the need to better understand the concomitant effects of stressors on health outcomes in wild populations. This is especially true given that some parasite species are expected to thrive in warming waters making host fish species especially at risk.
Blood-based cardiometabolic phenotypes in atrial fibrillation and their associated risk: EAST-AFNET 4 biomolecule study
Authors: Fabritz Larissa , Chua Winnie , Cardoso Victor R , Al-Taie Christoph , Borof Katrin , Suling Anna , Krause Linda , Kany Shinwan , Magnussen Christina , Wegscheider Karl , Breithardt Guenter , Crijns Harry J G M , Camm A John , Gkoutos George , Ellinor Patrick T , Goette Andreas , Schotten Ulrich , Wienhues-Thelen Ursula-Henrike , Zeller Tanja , Schnabel Renate B , Zapf Antonia , Kirchhof Paulus 
Published: April 2024

Abstract

Aims
Atrial fibrillation (AF) and concomitant cardiometabolic disease processes interact and combine to lead to adverse events, such as stroke, heart failure, myocardial infarction, and cardiovascular death. Circulating biomolecules provide quantifiable proxies for cardiometabolic disease processes. The aim of this study was to test whether biomolecule combinations can define phenotypes in patients with AF.

Methods and results
This pre-specified analysis of the EAST-AFNET 4 biomolecule study assigned patients to clusters using polytomous variable latent-class analysis based on baseline concentrations of 13 precisely quantified biomolecules potentially reflecting ageing, cardiac fibrosis, metabolic dysfunction, oxidative stress, cardiac load, endothelial dysfunction, and inflammation. In each cluster, rates of cardiovascular death, stroke, or hospitalization for heart failure or acute coronary syndrome, the primary outcome of EAST-AFNET 4, were calculated and compared between clusters over median 5.1 years follow-up. Findings were independently validated in a prospective cohort of 748 patients with AF (BBC-AF; median follow-up 2.9 years).
Unsupervised biomolecule analysis assigned 1586 patients (71 years old, 46% women) into four clusters. The highest risk cluster was dominated by elevated bone morphogenetic protein 10, insulin-like growth factor–binding protein 7, N-terminal pro-B-type natriuretic peptide, angiopoietin 2, and growth differentiation factor 15. Patients in the lowest risk cluster showed low concentrations of these biomolecules. Two intermediate-risk clusters differed by high or low concentrations of C-reactive protein, interleukin-6, and D-dimer. Patients in the highest risk cluster had a five-fold higher cardiovascular event rate than patients in the low-risk cluster. Early rhythm control was effective across clusters (Pinteraction = 0.63). Sensitivity analyses and external validation in BBC-AF replicated clusters and risk gradients.

Conclusion
Biomolecule concentrations identify cardiometabolic subphenotypes in patients with AF at high and low cardiovascular risk.
Hypertrophic cardiomyopathy detection with artificial intelligence electrocardiography in international cohorts: an external validation study
Authors: Siontis Konstantinos C , Wieczorek Mikolaj A , Maanja Maren , Hodge David O , Kim Hyung-Kwan , Lee Hyun-Jung , Lee Heesun , Lim Jaehyun , Park Chan Soon , Ariga Rina , Raman Betty , Mahmod Masliza , Watkins Hugh , Neubauer Stefan , Windecker Stephan , Siontis George C M , Gersh Bernard J , Ackerman Michael J , Attia Zachi I , Friedman Paul A , Noseworthy Peter A 
Published: April 2024

Abstract

Aims
Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts.

Methods and results
A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm’s ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P &lt; 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910–0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case–control ratio 1:2), the AUC was 0.921 (95% CI 0.909–0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%.

Conclusion
The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.
Durable left ventricular assist device explantation following recovery in paediatric patients: Determinants and outcome after explantation
Authors: Rohde Sofie , Miera Oliver , Sliwka Joanna , Sandica Eugen , Amodeo Antonio , Veen Kevin , de By Theo M M H , Bogers Ad J J C , Schweiger Martin 
Published: April 2024

Abstract

OBJECTIVES
Myocardial recovery in children supported by a durable left ventricular assist device is a rare, but highly desirable outcome because it could potentially eliminate the need for a cardiac transplant and the lifelong need for immunosuppressant therapy and the risk of complications. However, experience with this specific outcome is extremely limited.

METHODS
All patients &lt; 19 years old supported by a durable left ventricular assist device from the European Registry for Patients with Mechanical Circulatory Support database were included. Participating centres were approached for additional follow-up data after explantation. Associated factors for explantation due to myocardial recovery were explored using Cox proportional hazard models.

RESULTS
The incidence of recovery in children supported by a durable left ventricular assist device was 11.7% (52/445; median duration of support, 122.0 days). Multivariable analyses showed body surface area (hazard ratio 0.229; confidence interval 0.093–0.565; P = 0.001) and a primary diagnosis of myocarditis (hazard ratio 4.597; confidence interval 2.545–8.303; P &lt; 0.001) to be associated with recovery. Left ventricular end-diastolic diameter in children with myocarditis was not associated with recovery. Follow-up after recovery was obtained for 46 patients (88.5%). Sustained myocardial recovery was reported in 33/46 (71.7%) at the end of the follow-up period (28/33; &gt;2 year). Transplants were performed in 6/46 (11.4%) (in 5 after a ventricular assist device was reimplanted). Death occurred in 7/46 (15.2%).

CONCLUSIONS
Myocardial recovery occurs in a substantial portion of paediatric patients supported with durable left ventricular assist devices, and sustainable recovery is seen in around three-quarters of them. Even children with severely dilated ventricles due to myocarditis can show recovery. Clinicians should be attentive to (developing) myocardial recovery. These results can be used to develop internationally approved paediatric weaning guidelines.
Evidence-based potential of generative artificial intelligence large language models in orthodontics: a comparative study of ChatGPT, Google Bard, and Microsoft Bing
Authors: Makrygiannakis Miltiadis A , Giannakopoulos Kostis , Kaklamanos Eleftherios G 
Published: April 2024

Summary

Background
The increasing utilization of large language models (LLMs) in Generative Artificial Intelligence across various medical and dental fields, and specifically orthodontics, raises questions about their accuracy.

Objective
This study aimed to assess and compare the answers offered by four LLMs: Google’s Bard, OpenAI’s ChatGPT-3.5, and ChatGPT-4, and Microsoft’s Bing, in response to clinically relevant questions within the field of orthodontics.

Materials and methods
Ten open-type clinical orthodontics-related questions were posed to the LLMs. The responses provided by the LLMs were assessed on a scale ranging from 0 (minimum) to 10 (maximum) points, benchmarked against robust scientific evidence, including consensus statements and systematic reviews, using a predefined rubric. After a 4-week interval from the initial evaluation, the answers were reevaluated to gauge intra-evaluator reliability. Statistical comparisons were conducted on the scores using Friedman’s and Wilcoxon’s tests to identify the model providing the answers with the most comprehensiveness, scientific accuracy, clarity, and relevance.

Results
Overall, no statistically significant differences between the scores given by the two evaluators, on both scoring occasions, were detected, so an average score for every LLM was computed. The LLM answers scoring the highest, were those of Microsoft Bing Chat (average score = 7.1), followed by ChatGPT 4 (average score = 4.7), Google Bard (average score = 4.6), and finally ChatGPT 3.5 (average score 3.8). While Microsoft Bing Chat statistically outperformed ChatGPT-3.5 (P-value = 0.017) and Google Bard (P-value = 0.029), as well, and Chat GPT-4 outperformed Chat GPT-3.5 (P-value = 0.011), all models occasionally produced answers with a lack of comprehensiveness, scientific accuracy, clarity, and relevance.

Limitations
The questions asked were indicative and did not cover the entire field of orthodontics.

Conclusions
Language models (LLMs) show great potential in supporting evidence-based orthodontics. However, their current limitations pose a potential risk of making incorrect healthcare decisions if utilized without careful consideration. Consequently, these tools cannot serve as a substitute for the orthodontist’s essential critical thinking and comprehensive subject knowledge. For effective integration into practice, further research, clinical validation, and enhancements to the models are essential. Clinicians must be mindful of the limitations of LLMs, as their imprudent utilization could have adverse effects on patient care.
A long and winding road: culture change on data sharing in exposomics
Authors: Wright Robert O , Makris Konstantinos C , Natsiavas Pantelis , Fennell Timothy , Rushing Blake R , Wilson Ander ,   Members of the Exposomics Consortium, Adamu Yau , Adar Sara D , Adebamowo Clement , Akhtari Farida , Akhtari Farida , Argos Maria , Arunachalam Saravanan , Baumert Brittney , Beglarian Emily , Berger Kimberly , Bhutani Jessie , Cai Lu , Calafat Antonia , Chao Mu-Rong , Chatziioannou Anastasia Chrysovalantou , Cheng Qiwen , Chung Ming Kei , Chung Ming Kei , Chung Ming Kei , Clark Robert , Hubal Elaine Cohen , Cooke Marcus , Costello Elizabeth , Cui Yuxia , Dierickx Erin , Dolinoy Dana , Du Xiuxia , Folle Aline Duarte , Gao Peng , Gaulke Christopher , Giebelhaus Ryland T , Goodrich Jesse , Grafanaki Katerina , Gullapalli Rama , Habre Rima , Hanson Heidi , Harari Homero , Hart Jaime , He Jingxuan , Holmes Philip , Hood Darryl B , House John , Hu Hui , Hu Chiung-Wen , James Peter , Jankowska Marta , Ji Hong , Kannan Srimathik , Konstantinou Corina , Lai Yunjia , Langston Mike , Lasalle Janine , Liang Donghai , Liao Jiawen , Luo Jiajun , Makris Konstantinos C , Manz Katherine , Miller Gary , Motsinger-Reif Alison , Ouidir Marion , Page Grier , Pan Shudi , Parker Graham , Paul Kimberly , Peluso Alina , Penning Trevor , Pierce Brandon , Prajapati Nirmala , Quintana Penelope J E , Rajasekar Arcot (Raja) , Ramesh Aramandla , Ruden Douglas , Rushing Blake , Schmitt Charles , Schüssler-Fiorenza Rose Sophia Miryam , Shah Ruchir , Shahriar Mohammad , Soares Lissa , Soliman Ghada , Stanek Lindsay , States J Christopher , Stingone Jeanette , Irizarry Savannah Sturla , Sun Yangbo , Teitelbaum Susan , Tong Ai Phuong , Vijayakumar Nisha , Walker Ryan , Wang Yi , Whyte Kathryn , Wu Lang , Wu K Lily , Yuan Xin/Jean , Zhang Qiong , Zhang Xinyue , Zhang Kai , Zhao Neil 
Published: April 2024

Abstract
Data sharing requires cooperation from data generators (eg, epidemiologists, lab investigators) and data users (eg, epidemiologists, biostatisticians, computer scientists). Data generation and data use in human exposome studies require significant but different skill sets and are separated temporally in many cases. Sharing will require maintaining a history of data generation and a system to address the concerns of data generators around credit for conducting rigorous work (eg, authorship). Sharing also requires addressing the needs of data users to facilitate harmonization, searchability and QA/QC of data. We present these issues from the perspectives of data generators and data users and include the special case of real-world data (eg, electronic health records). We conclude with recommendations to address how to better promote data sharing in exposomics through authorship, cost recovery and addressing ethical issues.
Volatiles profiles and factors affecting absorption of key odorants in Osmanthus black tea
Authors: Dai Binwei , Chen Weixuan , Huang Weihong , Liu Junsheng , Li Bo , He Puming , Grierson Donald , Tu Youying , Wu Yuanyuan 
Published: April 2024

Abstract

Objectives
Osmanthus black tea (OBT) is produced by reprocessing black tea while it absorbs the fragrance of Osmanthus fragrans and this scenting process is crucial for forming the unique aroma of OBT. This work intended to reveal the effects of scenting parameters, the types of base tea, and scenting technologies on the aroma quality of OBT.

Materials and Methods
In this study, volatile compounds of OBTs with different scenting parameters, types of base tea, and scenting technologies were analyzed by solid-phase microextraction and gas chromatography–mass spectrometry. Weighted gene co-expression network analysis and orthogonal partial least squares discriminant analysis were used to identify the key volatile compounds of OBT.

Results
More than 80 volatile compounds of OBT were found, and six compounds, α-ionone, β-ionone, γ-decalactone, dihydro-β-ionone, dihydro-β-ionol, and 6-pentyl-2-pyrone, were identified as the key volatiles of OBT. As scenting time (ST) increased, the key volatile compounds in OBT showed an upward trend or increased initially and then decreased. Meanwhile, the contents of key volatile compounds increased as the ratio of flowers to tea (RFT) increased. In addition, base teas with a high proportion of pekoes produced higher-quality OBT by absorbing more key volatile compounds from O. fragrans. Comparing OBTs made from the fast-scenting process and the traditional scenting process (TS), showed that higher aroma quality was obtained through repeated scenting rounds of TS.

Conclusions
Appropriate long ST and high RFT, as well as base tea with a high proportion of pekoes and TS with repeated scenting rounds are beneficial for the accumulation of odorants and the improvement of aroma quality in OBT.
Current advances and future directions in combined hepatocellular and cholangiocarcinoma
Authors: Zhang Yu-Zhu , Liu Yu-Chen , Su Tong , Shi Jiang-Nan , Huang Yi , Liang Bo 
Published: April 2024

Abstract
The low incidence of combined hepatocellular cholangiocarcinoma (cHCC-CCA) is an important factor limiting research progression. Our study extensively included nearly three decades of relevant literature and assembled the most comprehensive database comprising 5,742 patients with cHCC-CCA. We summarized the characteristics, tumor markers, and clinical features of these patients. Additionally, we present the evolution of cHCC-CCA classification and explain the underlying rationale for these classification standards. We reviewed cHCC-CCA diagnostic advances using imaging features, tumor markers, and postoperative pathology, as well as treatment options such as surgical, adjuvant, and immune-targeted therapies. In addition, recent advances in more effective chemotherapeutic regimens and immune-targeted therapies were explored. Furthermore, we described the molecular mutation features and potential specific markers of cHCC-CCA. The prognostic value of Nestin has been proven, and we speculate that Nestin will also play a role in classification and diagnosis. However, further research is needed. Moreover, we believe that the possibility of using machine learning liquid biopsy for preoperative diagnosis and establishing a scoring system are directions for future research.
Enhancing tomato fruit antioxidant potential through hydrogen nanobubble irrigation
Authors: He Jing , Zhou Yunpeng , Geilfus Christoph-Martin , Cao Jiankang , Fu Daqi , Baram Shahar , Liu Yanzheng , Li Yunkai 
Published: April 2024

Abstract
Eating fruits and vegetables loaded with natural antioxidants can boost human health considerably and help fight off diseases linked to oxidative stress. Hydrogen has unique antioxidant effects. However, its low-solubility and fast-diffusion has limited its applications in agriculture. Integration of hydrogen with nanobubble technology could address such problems. However, the physiological adaptation and response mechanism of crops to hydrogen nanobubbles is still poorly understood. Antioxidant concentrations of lycopene, ascorbic acid, flavonoids, and resveratrol in hydrogen nanobubble water drip-irrigated tomato fruits increased by 16.3–264.8% and 2.2–19.8%, respectively, compared to underground water and oxygen nanobubble water. Transcriptomic and metabolomic analyses were combined to investigate the regulatory mechanisms that differed from the controls. Comprehensive multi-omics analysis revealed differences in the abundances of genes responsible for hormonal control, hydrogenase genes, and necessary synthetic metabolites of antioxidants, which helped to clarify the observed improvements in antioxidants. This is the first case of hydrogen nanobubble water irrigation increasing numerous natural antioxidant parts in fruits. Considering the characteristics of hydrogen and the application of the nanobubble technology in agriculture, the findings of the present study could facilitate the understanding of the potential effects of hydrogen on biological processes and the mechanisms of action on plant growth and development.