bluuebunny/crossref_metadata_2025_split huggingface dataset:
A two-tier feature selection method for predicting mortality risk in ICU patients with acute kidney injury
Authors: Liu Mengqing , Fan Zhiping , Gao Yu , Mubonanyikuzo Vivens , Wu Ruiqian , Li Wenjin , Xu Naiyue , Liu Kun , Zhou Liang 
Published: July 2024

AbstractAcute kidney injury (AKI) is one of the most important lethal factors for patients admitted to intensive care units (ICUs), and timely high-risk prognostic assessment and intervention are essential to improving patient prognosis. In this study, a stacking model using the MIMIC-III dataset with a two-tier feature selection approach was developed to predict the risk of in-hospital mortality in ICU patients admitted for AKI. External validation was performed using separate MIMIC-IV and eICU-CRD. The area under the curve (AUC) was calculated using the stacking model, and features were selected using the Boruta and XGBoost feature selection methods. This study compares the performance of a stacking model using two-tier feature selection with a model using single-tier feature selection (XGBoost: 85; Boruta: 83; two-tier: 0.91). The predictive effectiveness of the stacking model was further validated by using different datasets (Validation 1: 0.83; Validation 2: 0.85) and comparing it with a simpler model and traditional clinical scores (SOFA: 0.65; APACH IV: 0.61). In addition, this study combined interpretable techniques and causal inference to analyze the causal relationship between features and predicted outcomes.
Prospective multicenter study to identify optimal target population for motorized spiral enteroscopy
Authors: Giordano Antonio , Compañy Luis , Alajarin-Cervera Miriam , Ruiz-Gómez Francisco Antonio , Fernández-Gil Pedro Luis , Alonso-Lázaro Noelia , Sola-Vera Javier , Urpi-Ferreruela Miguel , Aicart-Ramos Marta , Parejo-Carbonell Sofía , Dedeu-Cuscó Josep Maria , Prieto-Frías César , Bógalo-Romero Cintia , Egea-Valenzuela Juan , Carretero Cristina , Pons-Beltrán Vicente , González-Suárez Begoña 
Published: July 2024

AbstractMotorized spiral enteroscopy (MSE) enhances small bowel exploration, but the optimal target population for this technique is unknown. We aimed to identify the target population for MSE by evaluating its efficacy and safety, as well as detecting predictors of efficacy. A prospective multicenter observational study was conducted at 9 tertiary hospitals in Spain, enrolling patients between June 2020–2022. Analyzed data included demographics, indications for the procedure, exploration time, depth of maximum insertion (DMI), technical success, diagnostic yield, interventional yield, and adverse events (AE) up to 14 days from enteroscopy. Patients with prior gastrointestinal surgery, unsuccessful balloon enteroscopy and small bowel strictures were analyzed. A total of 326 enteroscopies (66.6% oral route) were performed in 294 patients (55.1% males, 65 years ± 21). Prior abdominal surgery was present in 50% of procedures (13.5% gastrointestinal surgery). Lower DMI (162 vs 275 cm, p = 0.037) and diagnostic yield (47.7 vs 67.5%, p = 0.016) were observed in patients with prior gastrointestinal surgery. MSE showed 92.2% technical success and 56.9% diagnostic yield after unsuccessful balloon enteroscopy (n = 51). In suspected small bowel strictures (n = 49), the finding was confirmed in 23 procedures (46.9%). The total AE rate was 10.7% (1.8% classified as major events) with no differences related to prior gastrointestinal/abdominal surgery, unsuccessful enteroscopy, or suspected small bowel strictures. The study demonstrates that MSE has a lower diagnostic yield and DMI in patients with prior gastrointestinal surgery but is feasible after unsuccessful balloon-enteroscopy and in suspected small bowel strictures without safety concerns.
Accounting for deep soil carbon in tropical forest conservation payments
Authors: Sundqvist Maja K. , Hasselquist Niles J. , Jensen Joel , Runesson Josefin , Goodman Rosa C. , Axelsson E. Petter , Alloysius David , Lindh Arvid , Ilstedt Ulrik , Aguilar Francisco X. 
Published: July 2024

AbstractSecondary tropical forests are at the forefront of deforestation pressures. They store large amounts of carbon, which, if compensated for to avoid net emissions associated with conversion to non-forest uses, may help advance tropical forest conservation. We measured above- and below-ground carbon stocks down to 1 m soil depth across a secondary forest and in oil palm plantations in Malaysia. We calculated net carbon losses when converting secondary forests to oil palm plantations and estimated payments to avoid net emissions arising from land conversion to a 22-year oil palm rotation, based on land opportunity costs per hectare. We explored how estimates would vary between forests by also extracting carbon stock data for primary forest from the literature. When tree and soil carbon was accounted for, payments of US$18–51 tCO2–1 for secondary forests and US$14–40 tCO2–1 for primary forest would equal opportunity costs associated with oil palm plantations per hectare. If detailed assessments of soil carbon were not accounted for, payments to offset opportunity costs would need to be considerably higher for secondary forests (US$28–80 tCO2–1). These results show that assessment of carbon stocks down to 1 m soil depth in tropical forests can substantially influence the estimated value of avoided-emission payments.
A novel high-throughput qPCR chip for solving co-infections in RAS farmed rainbow trout
Authors: Sørensen Juliane , Cuenca Argelia , Schmidt Jacob Günther , Madsen Simon Brøndgaard , Iburg Tine Moesgaard , Madsen Lone , Vendramin Niccoló 
Published: July 2024

AbstractRecirculating aquaculture systems (RAS) have become more attractive due to reduced water consumption and effluent discharge. However, intensification of production increases the risk of introducing pathogens at farming sites. The emergence of uncultivable pathogens and RAS pathobiome diversity shifts the traditional disease paradigm from “one pathogen, one disease” to complex multiple-pathogen disease cases. Piscine orthoreovirus genotype 3 (PRV-3) is an excellent example, as it is capable of inducing anemia and heart pathology resembling heart and skeletal muscle inflammation under experimental conditions, and is associated with increased mortality in association with other pathogens in the field. The aim of this study was to develop a method for detection of multiple pathogens and putative pathogens, as co-infections are common in aquaculture. To do this, in the pilot study, we mapped the pathobiome of RAS-farmed rainbow trout (Oncorhynchus mykiss) (commercial RAS, farm A) using both standard diagnostic methods and metabarcording (16S rRNA) to investigate the gill microbiome. During this study, we observed infections with multiple pathogens, and detected two putative gill pathogens Candidatus Branchiomonas cysticola and Candidatus Piscichlamydia salmonis, both of which have been linked with complex gill disease in Atlantic salmon (Salmo salar). Based on the pilot study, we developed and tested a high throughput qPCR (HT-qPCR) chip targeting 22 viral and bacterial pathogens and putative pathogens, followed by a surveillance of a fish cohort in a commercial RAS farm during production (farm B). Co-infection with PRV-3 and Ca. B. cysticola combined with stress inducing management practices may explain the severe disease outbreak observed (37% mortality). The time course study sets the base for a future screening scheme for disease prediction and addresses limitations of the method when testing environmental DNA/RNA.
Classification of LAMOST spectra of B-type and hot subdwarf stars using kernel support vector machine
Authors: Tahir Muhammad , Yude Bu , Mehmood Tahir , Bashir Saima , Zhenping Yi , Awais Muhammad 
Published: July 2024

AbstractMachine learning has emerged as a leading field in artificial intelligence, demonstrating expert-level performance in various domains. Astronomy has benefited from machine learning techniques, particularly in classifying and identifying stars based on their features. This study focuses on the spectra-based classification of 11,408 B-type and 2422 hot subdwarf stars. The study employs baseline correction using Asymmetric Least Squares (ALS) to enhance classification accuracy. It applies the Pan-Core concept to identify 500 unique patterns or ranges for both types of stars. These patterns are the foundation for creating Support Vector Machine (SVM) models, including the linear (L-SVM), polynomial (P-SVM), and radial basis (R-SVM) kernels. Parameter tuning for the SVM models is achieved through cross-validation. Evaluation of the SVM models on test data reveals that the linear kernel SVM achieves the highest accuracy (87.0%), surpassing the polynomial kernel SVM (84.1%) and radial kernel SVM (80.1%). The average calibrated accuracy falls within the range of 90–95%. These results demonstrate the potential of using spectrum-based classification to aid astronomers in improving and expanding their understanding of stars, with a specific focus on the identification of hot subdwarf stars. This study presents a valuable investigation for astronomers, as it enables the classification of stars based on their spectra, leveraging machine learning techniques to enhance their knowledge and insights in astronomy.
Network resonance and the auditory steady state response
Authors: Johnson Teryn D. , Gallagher Austin J. , Coulson Seana , Rangel Lara M. 
Published: July 2024

AbstractThe auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.
Solving the resource constrained project scheduling problem with quantum annealing
Authors: Pérez Armas Luis Fernando , Creemers Stefan , Deleplanque Samuel 
Published: July 2024

AbstractQuantum annealing emerges as a promising approach for tackling complex scheduling problems such as the resource-constrained project scheduling problem (RCPSP). This study represents the first application of quantum annealing to solve the RCPSP, analyzing 12 well-known mixed integer linear programming (MILP) formulations and converting the most qubit-efficient one into a quadratic unconstrained binary optimization (QUBO) model. We then solve this model using the D-wave advantage 6.3 quantum annealer, comparing its performance against classical computer solvers. Our results indicate significant potential, particularly for small to medium-sized instances. Further, we introduce time-to-target and Atos Q-score metrics to evaluate the effectiveness of quantum annealing and reverse quantum annealing. The paper also explores advanced quantum optimization techniques, such as customized anneal schedules, enhancing our understanding and application of quantum computing in operations research.
Combined effects of micropollutants and their degradation on prokaryotic communities at the sediment–water interface
Authors: Borreca Adrien , Vuilleumier Stéphane , Imfeld Gwenaël 
Published: July 2024

AbstractPesticides and pharmaceuticals enter aquatic ecosystems as complex mixtures. Various processes govern their dissipation and effect on the sediment and surface waters. These micropollutants often show persistence and can adversely affect microorganisms even at low concentrations. We investigated the dissipation and effects on procaryotic communities of metformin (antidiabetic drug), metolachlor (agricultural herbicide), and terbutryn (herbicide in building materials). These contaminants were introduced individually or as a mixture (17.6 µM per micropollutant) into laboratory microcosms mimicking the sediment–water interface. Metformin and metolachlor completely dissipated within 70 days, whereas terbutryn persisted. Dissipation did not differ whether the micropollutants were introduced individually or as part of a mixture. Sequence analysis of 16S rRNA gene amplicons evidenced distinct responses of prokaryotic communities in both sediment and water. Prokaryotic community variations were mainly driven by matrix composition and incubation time. Micropollutant exposure played a secondary but influential role, with pronounced effects of recalcitrant metolachlor and terbutryn within the micropollutant mixture. Antagonistic and synergistic non-additive effects were identified for specific taxa across taxonomic levels in response to the micropollutant mixture. This study underscores the importance of considering the diversity of interactions between micropollutants, prokaryotic communities, and their respective environments when examining sediment–water interfaces affected by multiple contaminants.
Drug exposure and risk factors of maculopathy in tamoxifen users
Authors: Kwon Hyeon Yoon , Kim Jiyeong , Ahn Seong Joon 
Published: July 2024

AbstractTamoxifen, a pivotal therapy for hormone receptor-positive breast cancer, is known for its efficacy in reducing breast cancer recurrence and mortality. However, concerns about potential ocular complications, particularly maculopathy, have emerged. This study aims to investigate the risk and associated factors of diverse macular conditions in tamoxifen users, considering drug exposure, demographics, and systemic diseases. A nationwide cohort of tamoxifen users, comprised of 14,267 tamoxifen users, was analyzed using the health insurance review and assessment database in South Korea. Demographic and clinical characteristics were examined, and the cumulative incidence of macular diseases was stratified by age and cumulative tamoxifen dosage. We conducted logistic regression analysis to identify potential risk factors among clinical variables such as age, sex, indications for tamoxifen use, and systemic diseases associated with various macular conditions. Additionally, Cox proportional hazard models were used to determine the baseline clinical characteristics predictive of these macular conditions, with subsequent calculation of hazard ratios. Cumulative incidences of overall macular diseases, other maculopathy excluding common macular diseases, and macular edema were 26.4, 11.4, and 6.5%, respectively. The incidence of various macular conditions increased with age and the cumulative tamoxifen dose. Age, cumulative dose group, and liver diseases demonstrated significant associations with overall macular diseases and maculopathy excluding common macular diseases in multivariate logistic regression analyses (all P < 0.05). Furthermore, age emerged as significant predictive factors of maculopathy in Cox proportional hazard models. Tamoxifen-induced maculopathy poses a concern for prescribing physicians and ophthalmologists, and this study provides valuable insights into its risk and risk factors. This study may contribute to evidence-based guidelines for tamoxifen maculopathy screening, emphasizing the importance of considering age, cumulative dose, and liver diseases for recommendation on screening timing and frequency.
Enhancing handwritten text recognition accuracy with gated mechanisms
Authors: Chinthaginjala Ravikumar , Dhanamjayulu C. , Kim Tai-hoon , Ahmed Suhaib , Kim Si-Yeong , Kumar A. S. , Annepu Visalakshi , Ahmad Shafiq 
Published: July 2024

AbstractHandwritten Text Recognition (HTR) is a challenging task due to the complex structures and variations present in handwritten text. In recent years, the application of gated mechanisms, such as Long Short-Term Memory (LSTM) networks, has brought significant advancements to HTR systems. This paper presents an overview of HTR using a gated mechanism and highlights its novelty and advantages. The gated mechanism enables the model to capture long-term dependencies, retain relevant context, handle variable length sequences, mitigate error propagation, and adapt to contextual variations. The pipeline involves preprocessing the handwritten text images, extracting features, modeling the sequential dependencies using the gated mechanism, and decoding the output into readable text. The training process utilizes annotated datasets and optimization techniques to minimize transcription discrepancies. HTR using a gated mechanism has found applications in digitizing historical documents, automatic form processing, and real-time transcription. The results show improved accuracy and robustness compared to traditional HTR approaches. The advancements in HTR using a gated mechanism open up new possibilities for effectively recognizing and transcribing handwritten text in various domains. This research does a better job than the most recent iteration of the HTR system when compared to five different handwritten datasets (Washington, Saint Gall, RIMES, Bentham and IAM). Smartphones and robots are examples of low-cost computing devices that can benefit from this research.
Salinity gradient induced blue energy generation using two-dimensional membranes
Authors: Manikandan D. , Karishma S. , Kumar Mukesh , Nayak Pramoda K. 
Published: July 2024

AbstractSalinity gradient energy (SGE), known as blue energy is harvested from mixing seawater with river water in a controlled way using ion exchange membranes (IEMs). Using 2D materials as IEMs improves the output power density from a few Wm−2 to a few thousands of Wm−2 over conventional membranes. In this review, we survey the efforts taken to employ the different 2D materials as nanoporous or lamellar membranes for SGE and provide a comprehensive analysis of the fundamental principles behind the SGE. Overall, this review is anticipated to explain how the 2D materials can make SGE a viable source of energy.
Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging
Authors: Pahud de Mortanges Aurélie , Luo Haozhe , Shu Shelley Zixin , Kamath Amith , Suter Yannick , Shelan Mohamed , Pöllinger Alexander , Reyes Mauricio 
Published: July 2024

AbstractExplainable artificial intelligence (XAI) has experienced a vast increase in recognition over the last few years. While the technical developments are manifold, less focus has been placed on the clinical applicability and usability of systems. Moreover, not much attention has been given to XAI systems that can handle multimodal and longitudinal data, which we postulate are important features in many clinical workflows. In this study, we review, from a clinical perspective, the current state of XAI for multimodal and longitudinal datasets and highlight the challenges thereof. Additionally, we propose the XAI orchestrator, an instance that aims to help clinicians with the synopsis of multimodal and longitudinal data, the resulting AI predictions, and the corresponding explainability output. We propose several desirable properties of the XAI orchestrator, such as being adaptive, hierarchical, interactive, and uncertainty-aware.
Longitudinal associations of an exposome score with serum metabolites from childhood to adolescence
Authors: Healy Darren R. , Zarei Iman , Mikkonen Santtu , Soininen Sonja , Viitasalo Anna , Haapala Eero A. , Auriola Seppo , Hanhineva Kati , Kolehmainen Marjukka , Lakka Timo A. 
Published: July 2024

AbstractEnvironmental and lifestyle factors, including air pollution, impaired diet, and low physical activity, have been associated with cardiometabolic risk factors in childhood and adolescence. However, environmental and lifestyle exposures do not exert their physiological effects in isolation. This study investigated associations between an exposome score to measure the impact of multiple exposures, including diet, physical activity, sleep duration, air pollution, and socioeconomic status, and serum metabolites measured using LC-MS and NMR, compared to the individual components of the score. A general population of 504 children aged 6–9 years at baseline was followed up for eight years. Data were analysed with linear mixed-effects models using the R software. The exposome score was associated with 31 metabolites, of which 12 metabolites were not associated with any individual exposure category. These findings highlight the value of a composite score to predict metabolic changes associated with multiple environmental and lifestyle exposures since childhood.
Hybridization between Aedes aegypti and Aedes mascarensis mosquitoes leads to disruption of male sex determination
Authors: Liang Jiangtao , Kang Lin , Michalak Pawel , Sharakhov Igor V. 
Published: July 2024

AbstractUnderstanding the sex determination pathway and its disruptions in mosquitoes is critical for the effective control of disease vectors through genetic manipulations based on sex separation. When male hybrids of Aedes aegypti females and Ae. mascarensis males are backcrossed to Ae. aegypti females, a portion of the backcross progeny manifests as males with abnormal sexual differentiation. We discovered a significant correlation between pupal abnormalities and the feminization of subsequent adults exemplified by the relative abundance of ovarian and testicular tissues. All intersex individuals were genetic males as they expressed a male determining factor, Nix. Further, our analysis of the sex-specific splicing of doublesex and fruitless transcripts demonstrated the presence of both male and female splice variants indicating that sex determination is disrupted. A comparative transcriptomic analysis revealed similar expression levels of most female-associated genes in reproductive organs and carcasses between intersexual males and normal females. Moreover, intersexes had largely normal gene expression in testes but significant gene downregulation in male accessory glands when compared with normal males. We conclude that evolving hybrid incompatibilities between Ae. aegypti and Ae. mascarensis involve disruption of sex determination and are accompanied by changes in gene expression associated with sexual differentiation.