bluuebunny/crossref_metadata_2025 huggingface dataset:
The use of δ
13C in CO to determine removal of CH4 by Cl radicals in the atmosphere
*
Authors: Röckmann Thomas , van Herpen Maarten , Brashear Chloe , van der Veen Carina , Gromov Sergey , Li Qinyi , Saiz-Lopez Alfonso , Meidan Daphne , Barreto Africa , Prats Natalia , Mármol Ignacio , Ramos Ramón , Baños Isabel , Arrieta Jesús M , Zaehnle Sönke , Jordan Armin , Moossen Heiko , Timas Helder , Young Dickon , Sperlich Peter , Moss Rowena , Johnson Matthew S
Published: April 2024

The reaction of CH4 with chlorine (Cl) radicals in the atmosphere is associated with an extraordinarily strong isotopic fractionation, where 12CH4 reacts about 70 ‰ faster with Cl than 13CH4. Therefore, although the Cl-based sink of CH4 constitutes only a small contribution to its total removal rate, the uncertainty in this small sink has been identified as one of the two largest uncertainties of isotope-based CH4 source apportionment at the global scale. The uncertainty arises from the fact that Cl levels in the atmosphere are so low that they cannot be detected directly. One very sensitive indirect method to identify and quantify the CH4 + Cl reaction in the atmosphere is the detection of the extremely 13C-depleted reaction product carbon monoxide (CO) from this reaction. This article reviews the concept of this approach, its successful application in the atmosphere, its challenges and opportunities for identifying and quantifying Cl-based removal of CH4 at the regional and global scale and its potential to detect and evaluate possible attempts to enhance CH4 removal from the atmosphere.
Cost modeling of photocatalytic decomposition of atmospheric methane and nitrous oxide
Authors: Randall Richard , Jackson Robert B , Majumdar Arun
Published: April 2024

Abstract

The photocatalytic decomposition of atmospheric methane (CH4) and nitrous oxide (N2O) could be valuable tools for mitigating climate change; however, to date, few photocatalyst deployment strategies have had their costs modeled. Here, we construct basic cost models of three photocatalytic CH4 and N2O decomposition systems: (1) a ground-based solar system with natural airflow over photocatalyst-painted rooftops, (2) a ground-based LED-lit system with fan-driven airflow, and (3) an aerosol-based solar system on solid particles dispersed in the atmosphere. Each model takes as inputs the photocatalyst’s apparent quantum yield (AQY; a measure of how efficiently photons drive a desired chemical reaction) and the local CH4 or N2O concentration. Each model calculates an overall rate of greenhouse gas (GHG) drawdown and returns a levelized cost of GHG removal per equivalent ton of carbon dioxide (tCO2e). Based on prior studies of atmospheric carbon dioxide removal, we adopt $100/tCO2e as a target cost. We estimate that painting rooftops with photocatalysts might meet the target cost for decomposition of >10 ppm CH4 with catalyst AQYs >4%. If painting and cleaning costs were reduced by a factor of ∼3 from our scenario, removal of ambient CH4 could meet the cost target with AQYs >1% and removal of ambient N2O could do so with AQYs >0.1%. Fan-driven systems with LED illumination appear to be very challenging, achieving removal costs <$100/tCO2e only for AQYs of >10% for CH4 and >1% for N2O. Dispersing photocatalytic aerosols in the troposphere could be cost-effective with AQYs of >0.4% for ambient CH4 or >0.04% for ambient N2O. However, the mass of aerosols required is large and their side effects and social acceptability are uncertain. We note that, for any system, AQYs on the order of 1% will likely be extremely challenging to achieve with such dilute reagents.
Linking physical climate risk with mandatory business risk disclosure requirements
Authors: Pitman A J , Saribatir E , Greenhill C , Green S , Pitman S J , Fiedler T
Published: April 2024

Mandatory disclosure of physical climate risks to businesses is planned or being implemented in many countries. This raises the question, how viable is it to link increasing physical climate risk, expressed as extreme events, to an individual business. We demonstrate how the characteristics of increasing frequency, magnitude and duration of extreme events impact a hypothetical business supply chain using the analogy of a spider’s web, where an extreme event impacting a strand of the web (supply/market line) impacts the efficiency of the web (supply chain). We demonstrate that our hypothetical business, located in the centre of the web, can be unaffected by a very large number of extreme events, or be severely impacted by a small number of events, depending on exactly where the event occurs and the properties of the event. This implies that a business cannot assess physical climate risk based on a change in the frequency of events; the business needs to know the precise location of the events, as well as the magnitude and duration of each event. This information is not available and is unlikely to ever be available from climate model projections. Therefore, individual businesses required to disclose future physical climate risk are very unlikely to be able to provide useful quantitative assessments. We recommend that a business-specific storyline approach to future risk is used where multiple lines of evidence are woven into a risk assessment, including climate projections. Generic top–down prescriptions of future scenarios are very likely to lead to misrepresentation of risk and very poor outcomes for business, investors or financial regulators seeking to build resilience to future climate change.
Unravelling the origin of isoprene in the human body—a forty year Odyssey
Authors: Mochalski P , King J , Unterkofler K , Mayhew C A
Published: April 2024

In the breath research community’s search for volatile organic compounds that can act as non-invasive biomarkers for various diseases, hundreds of endogenous volatiles have been discovered. Whilst these systemic chemicals result from normal and abnormal metabolic activities or pathological disorders, to date very few are of any use for the development of clinical breath tests that could be used for disease diagnosis or to monitor therapeutic treatments. The reasons for this lack of application are manifold and complex, and these complications either limit or ultimately inhibit the analytical application of endogenous volatiles for use in the medical sciences. One such complication is a lack of knowledge on the biological origins of the endogenous volatiles. A major exception to this is isoprene. Since 1984, i.e. for 40 years, it has been generally accepted that the pathway to the production of human isoprene, and hence the origin of isoprene in exhaled breath, is through cholesterol biosynthesis via the mevalonate (MVA) pathway within the liver. However, various studies between 2001 and 2012 provide compelling evidence that human isoprene is produced in skeletal muscle tissue. A recent multi-omic investigation of genes and metabolites has revealed that this proposal is correct by showing that human isoprene predominantly results from muscular lipolytic cholesterol metabolism. Despite the overwhelming proof for a muscular pathway to isoprene production in the human body, breath research papers still reference the hepatic MVA pathway. The major aim of this perspective is to review the evidence that leads to a correct interpretation for the origins of human isoprene, so that the major pathway to human isoprene production is understood and appropriately disseminated. This is important, because an accurate attribution to the endogenous origins of isoprene is needed if exhaled isoprene levels are to be correctly interpreted and for assessing isoprene as a clinical biomarker.
Fe3O4/CoFe2O4 core-shell nanoparticles with enhanced magnetic properties for hyperthermia application
Authors: Oanh V T K , Nguyen L H , Phong L T H , Trang M T T , Thu H P , Truong N X , Ca N X , Nam P H , Manh D H
Published: April 2024

Fe3O4/CoFe2O4 core/shell nanoparticles with varying shell thickness were fabricated by seed-mediated growth via thermal decomposition method. Ligand exchange process using poly(maleic anhydride-alt-1-octadecene) (PMAO) was performed to prepare the aqueous magnetic fluids from the as-synthesised nanoparticles. X-ray diffraction (XRD), transmission electron microscopy (TEM) and Quantum Design PPMS VersaLab were utilised to characterise morphological and magnetic properties of the sample. XRD results showed that all the particles were single phase with spinel structure and the average crystallite size in the range of 11–17 nm. All particles were spherical in TEM images with similar size compared to results calculated from XRD. Magnetic measurements were performed at different temperatures (50 − 300 K) at 30 kOe. The result showed that the saturation magnetisation (M
s) and coercivity (H
C) were significantly increased with the formation of hard magnetic shell with varying thickness. The dynamic light scattering (DLS) analysis presented a narrow distribution and zeta potential of −16 to −35 mV, indicating a good stability of the ferrofluids. The cytotoxicity of the FOC3/PMAO ferrofluid, which has the highest SAR value of 372.02 W g−1, was tested on Hep-G2 cell line at different concentrations from 10 to 100 μg ml−1. Less than 30% of the cell was inhibited, indicating that the FOC3/PMAO particles have low toxicity at these tested concentrations. Thus, these as-synthesised core/shell nanoparticles with uniform particle size, high saturation magnetisation, good stability and five-time increased specific absorption rate (SAR) compared to the Fe3O4 core nanoparticles are very promising in hyperthermia and magnetic resonance imaging (MRI) applications.
Characterization of banana powder-based film reinforced with CNF and Bio-mediated ZnO nanoparticles for potential food applications
Authors: Leta Tshiamo B , Adeyemi Jerry O , Fawole Olaniyi A
Published: April 2024

The formulation of a multifunctional nanocomposite packaging material with potential against agents of food deterioration, such as free radicals and microorganisms, has emerged as a solution for shelf-life extension and food security. This study developed banana powder (BP) film infused with cellulose nanofiber (CNF) and ZnO-PPW and ZnO-PSW nanoparticles (NPs) at different concentrations for food applications. The BP/CNF/ZnO films were characterized using UV–vis spectroscopy, XRD, FT-IR, and SEM techniques. The analyses confirmed the successful infusion of ZnO NPs into the BP/CNF matrix, leading to significant changes (p < 0.05) in color and appearance, enhanced UV–vis barrier properties, and increased thickness and flexibility of the films. Furthermore, the presence of ZnO in the base matrix influenced the moisture content (19%–29%), film solubility (68%–74%), and oil permeability significantly more than the control BP/CNF film. Adding ZnO significantly improved the UV barrier properties compared to the control. The nanocomposite BP/CNF/ZnO films demonstrated concentration-based antioxidant and good antimicrobial activity against five selected food pathogens (Escherichia coli, Enterococcus faecalis, Listeria monocytogenes and Staphylococcus aureus). Similarly, good antioxidant properties were reported in different assays, proving superior to the control BP/CNF. These key findings, especially those of the BP/CNF/ + 0.6% ZnO NPs films, showed that these films possess great potential for application as food packaging materials with antioxidant and antimicrobial properties.
From electronic structure to magnetism and skyrmions
Authors: Borisov Vladislav
Published: April 2024

Solid state theory, density functional theory and its generalizations for correlated systems together with numerical simulations on supercomputers allow nowadays to model magnetic systems realistically and in detail and can be even used to predict new materials, paving the way for more rapid material development for applications in energy storage and conversion, information technologies, sensors, actuators etc. Modeling magnets on different length scales (between a few

Å

ngström and several micrometers) requires, however, approaches with very different mathematical formulations. Parameters defining the material in each formulation can be determined either by fitting experimental data or from theoretical calculations and there exists a well-established approach for obtaining model parameters for each length scale using the information from the smaller length scale. In this review, this approach will be explained step-by-step in textbook style with examples of successful scale-bridging modeling of different classes of magnetic materials from the research literature as well as based on results newly obtained for this review.
Compact pixelated scintillator detector investigation for gamma ray detection
Authors: Wang Jin-Long , Wu Xiao-Guang , He Zi-Yang , Yang Li-Wang , Zheng Yun , Li Cong-Bo , Li Tian-Xiao , Zhao Zi-Hao
Published: April 2024

Objective. A scintillator is a luminescent material that converts high-energy photons into visible light and is widely used in medical imaging. Different scintillators are applied to gamma imaging in proton therapy and boron neutron capture therapy (BNCT). A pixelated scintillator is suitable for position measurement. The energy resolution, detection efficiency and position measurement of pixelated scintillators coupled to a SiPM were investigated via two kinds of detectors. The goal of this manuscript was to accurately measure the gamma source position through spectrum analysis in selection of energy windows for characteristic gamma lines. Approach. Scintillators were effectively manufactured and encapsulated before testing, especially for the easily deliquescent LaBr3. The compact front-end electronic prototype modules with 2 × 2 array SiPMs in stacked form and 1 × 10 array SiPMs in parallel form were developed for gamma ray energy resolution and efficiency measurements with a radioactive source of 22Na, which had two energy gamma lines at 511 keV and 1274 keV. Energy calibration was used for accurate energy window selection when measuring the position of the gamma source. Main results. Evident inconsistencies were present between different pixels of the same type of scintillator. Thus, an energy calibration method was needed. LaBr3 was the first candidate scintillator for the gamma ray spectrum measurement since it exhibited the best performance with an energy resolution of ∼5%. The recommended size of LaBr3 was 5 × 5 mm2, which had a higher efficiency than the 3 × 3 mm2 size. The gamma count of the multiple mode of the 2 × 2 array was much higher than that of the single mode, while the energy resolution was poorer. Thus, multiple mode was not suitable for gamma ray detection. The 1 × 10 array detector had the potential to measure the gamma ray source position and could be used for proton therapy and BNCT. A small deviation of 0.22 cm was observed in the measurement of the source center position with Energy Window 1 for 511 keV and Energy Window 2 for 1274 keV before the energy calibration. No deviation was observed after energy calibration. Thus, to achieve a higher accuracy position measurement, automatic energy calibration algorithm was coded into data acquisition software. Significance. The characteristic gamma lines produced by particle therapy are abundant and useful for imaging technology. Our developed compact pixelated scintillator detector coupled with SiPMs could measure the gamma spectrum with high resolution. The energy calibration and window selection method could measure the position of the source with high accuracy. Therefore, an advanced imaging device based on the energy spectrum for particle therapy could be potentially attainable.
Pozzolanic potential of sustainable precursors for engineered geopolymer composites (EGC)
Authors: Subramanian Saravanan , Davis Robin , Thomas Blessen Skariah
Published: April 2024

Confirming the pozzolanic activity is crucial to ensure their compatibility and performance in geopolymer composite (GC) applications, as it improves the geopolymerization process and optimizes the strength characteristics of GCs. This work evaluates the pozzolanic properties of Fly ash (FA), Basic Oxygen Furnace (BOF) slag, and Iron Ore Tailings (IOT) for their potential use in the development of Engineered Geopolymer Composites (EGC). IOT partially substitutes fine aggregate, while FA and BOF slag are the major precursors. Pozzolanic properties of the aforementioned materials were assessed through the Frattini, saturated lime test (SLT), and strength activity index (SAI). The Frattini test values recorded were 90, 47, and 30% of CaO removal, denoting their degree of pozzolanicity respectively for BOF Slag, FA, and IOT. In the SLT, the formation of stable calcium silicate hydrates and aluminates are verified by the reaction of the test pozzolans with lime, thereby conforming their pozzolanicity. The results from the Frattini and SAI tests showed a significant correlation, indicating an effective pozzolanicity measure of the test materials. However, the results from the SLT did not align with the outcomes from the Frattini and SAI tests. This contradiction suggests that the SLT is ineffective compared to the other two test methods in measuring the pozzolanic activity of the test materials. The research findings provide valuable insights into the potential usage of these materials (pozzolans) as sustainable building materials in the construction industry.
Multi-head CNN-based activity recognition and its application on chest-mounted sensor-belt
Authors: Verma Updesh , Tyagi Pratibha , Aneja Manpreet Kaur
Published: April 2024

In recent years, a great deal of research has been done on the identification, monitoring, and classification of human activities. Human activity recognition (HAR) is a term commonly used to describe the automatic identification of physical activities. For activity recognition, there are primarily vision-based and sensor-based methods available. The computer vision-based method is generally effective in lab settings, but because of clutter, fluctuating light levels, and contrast, it may not perform well in real-world scenarios. Continuous monitoring and analysis of physiological signals obtained from heterogeneous sensors attached to an individual’s body is required to realise sensor-based HAR systems. Most of the previous research in human activity recognition (HAR) is biased along with feature engineering and pre-processing which requires a good amount of domain knowledge. Application-specific modelling and time-taking methods are involved in these approaches. In this work, the multi-head convolutional neural network-based human activity recognition framework is proposed where automatic feature extraction and classification are involved in the form of an end-to-end classification approach. Experiments of this approach are performed by taking raw wearable sensor data with few pre-processing steps and without the involvement of a handcrafted feature extraction technique. 99.23% and 93.55% accuracy are obtained on the WISDM and UCI-HAR datasets which denoted the much improvement in the assessment of HAR over other similar approaches. The model is also tested on locally collected data from a chest mounted belt with fabric sensors and an accuracy of 87.14% has been achieved on that data.
Viscoelastic behaviour of yttrium oxide and reduced graphene oxide embedded epoxy nanocomposite
Authors: Singh Pooja , Sharma Swati , Kumar Kaushal , Iyer Ganesh , Lal Sohan , Kumar Arun
Published: April 2024

In this work, two different types of nanofillers yttrium oxide (Y2O3) or yttria and reduced graphene oxide (RGO) are used to reinforce with epoxy polymer for the synthesis of epoxy nanocomposites by using the ultrasonication dual mixing approach. Raman spectroscopy has been done to analyze the microstructure of yttria and conformation of the formed RGO from Graphene oxide. The viscoelastic behavior of epoxy nanocomposites is evaluated with the help of the dynamic mechanical analyzer. Further Storage modulus is used to determine the cross-link density ‘νe’, coefficient of effectiveness ‘C factor’, and reinforcement efficiency factor ‘r factor’. The damping coefficient (Tan δ) helps in determining the glass transition temperature of the epoxy and its nanocomposites. The results demonstrate that at 1.6 wt% Y2O3 & 0.8 wt% RGO reinforcement in pure epoxy matrix showed maximum enhancement in terms of storage modulus, loss modulus, and glass transition temperature. The semi-circular shape that resulted from the study of the Cole-Cole plot of all the nanocomposites demonstrated the homogenous dispersion of nanoparticles and efficient bonding between epoxy and nanoparticles. Field Emission Scanning Electron Microscopy (FESEM) has been used to identify the interfacial interaction between nanoparticle and epoxy matrix through tensile fracture surfaces.
A methodological integration of fisher score technique with intelligent machine learning methods for ball bearing fault investigation
Authors: Kumar Rajeev , Anand R S
Published: April 2024

This paper presents an efficient approach to detect, diagnose and estimate the severity of failures in various components of bearings in induction motors using vibration signature analysis. This automated method integrates the Fisher Score feature selection method and an efficient hyperparameter tuning model with machine learning models, including Support Vector Machine (SVM), k-Nearest Neighbor (k-NN) and Decision Tree (DT), to accurately classify defects in bearings. This approach ensures accurate classification of bearing defects within less computation time. This work is carried out with vibration signals, recorded from a laboratory experimental setup on Machine Fault Simulator (MFS), focusing on ball bearing with defects in inner race, outer race and ball itself. Time and Frequency domain analysis are employed to compute the features for fault investigation in ball bearings using machine learning models. The computed results demonstrate that the proposed feature selection method with hyperparameter tuning achieved remarkable maximum accuracy among X, Y and XY combinations of datasets, with 97% in DT, 94% in SVM and 95.23% in k-NN models during the frequency domain analysis. Notably, these model accuracies improved to 99.04% in DT, 98% in SVM and 98% in k-NN during further analysis with Fisher Score technique. Consequently, the testing loss using this hyperparameter tuning function remains very low. Overall, this paper compares the results of time and frequency domain analysis and introduces a promising approach for both efficient and accurate fault detection and severity estimation in bearings of induction motors, potentially reducing the need for extensive manpower and sensor usage.
Optimal coordination of directional overcurrent protection relays using hybrid optimizer
Authors: Habib Kashif , Wadood Abdul , Wei Tang , Khan Shahbaz , Xing Xu
Published: April 2024

In order to minimize or maximize an objective function, electrical engineering problems might benefit from optimization methodologies inspired by nature. This study employs a hybrid particle swarm optimizer (HPSO) to get rid of local optimum solutions and find the best global one for directional overcurrent protection relays (DOPR) protection. DOPR coordination is a highly constrained, mixed-integral nonlinear optimization problem. An adaptive defense method has been created to counteract the intentionally challenging design. Therefore, design variables such as time multiplier setting (TMS) and plug setting (PS) are utilized for each relay in the circuit. The goal function is to reduce the amount of time spent to trace the fault by all the relays. Reducing the time required for each relay to trace the fault is the aim of function. After analyzing and comparing two test studies of the IEEE benchmark using various optimization strategies, we found that the results for the IEEE 15-bus system has minimum time of 8.9 s, which is improved by 22.92% to 82.89%, and those for the IEEE 30-bus system minimum time of 22.45 s that is improved by 4.41% to 39.6%. In terms of overall DOPR operation and computational time needed to get the global optimum solution, the acquired results are demonstrably superior to those obtained using conventional and state-of-the-art methods.
A multiscale and multicriteria generative adversarial network to synthesize 1-dimensional turbulent fields
Authors: Granero Belinchon Carlos , Cabeza Gallucci Manuel
Published: April 2024

This article introduces a new neural network stochastic model to generate a 1-dimensional stochastic field with turbulent velocity statistics. Both the model architecture and training procedure ground on the Kolmogorov and Obukhov statistical theories of fully developed turbulence, so guaranteeing descriptions of (1) energy distribution, (2) energy cascade and (3) intermittency across scales in agreement with experimental observations. The model is a generative adversarial network (GAN) with multiple multiscale optimization criteria. First, we use three physics-based criteria: the variance, skewness and flatness of the increments of the generated field, that retrieve respectively the turbulent energy distribution, energy cascade and intermittency across scales. Second, the GAN criterion, based on reproducing statistical distributions, is used on segments of different length of the generated field. Furthermore, to mimic multiscale decompositions frequently used in turbulence’s studies, the model architecture is fully convolutional with kernel sizes varying along the multiple layers of the model. To train our model, we use turbulent velocity signals from grid turbulence at Modane wind tunnel.
Approaches to medication history taking in different hospital settings: A scoping review
Authors: Terstegen Theresa , Niestroj Christina , Stangl Julia , Scherkl Camilo , Morath Benedict , Haefeli Walter E , Seidling Hanna M
Published: April 2024

Purpose

A comprehensive medication history can contribute to safe therapy. Many approaches aiming to improve medication history taking require significant human resources. To design an efficient process that delivers high-quality medication histories, the individual requirements and resources of a given setting need to be considered. We aimed to provide an overview of existing approaches to medication history taking and their performance in different settings to potentially support the selection of an appropriate procedure.

Methods

We searched 3 literature databases (PubMed/MEDLINE, CINAHL, PsycINFO) for publications on approaches to medication history taking and analyzed them with regard to their key components as well as the setting, patient population, assessed outcomes, and efficacy.

Results

In total, 65 publications were included and analyzed. The majority of the reported approaches relied on involvement of dedicated staff (n = 43), followed by process-oriented interventions (eg, checklists; n = 15) and information technology (IT)–guided interventions (n = 11). A mean (SD) of 6 (2.9) outcomes were described in each study. Medication discrepancies were reported in 89% of all studies, yet about 75 different descriptions of this outcome were used, making it difficult to compare study results. Only 11 studies applied a sample size calculation and statistical tests. Of those, 10 reported a positive effect of their respective intervention on the quality of medication histories.

Conclusion

Most approaches focused on pharmacy staff, which are associated with considerable cost and resources. Therefore, IT-based approaches and patient engagement should be investigated as cost-effective alternatives and tested for superiority in the same setting. Reporting guidelines and standardized methodology are needed to improve the comparability of such studies.
BTR: a bioinformatics tool recommendation system
Authors: Green Ryan , Qu Xufeng , Liu Jinze , Yu Tingting
Published: April 2024

Motivation

The rapid expansion of Bioinformatics research has led to a proliferation of computational tools for scientific analysis pipelines. However, constructing these pipelines is a demanding task, requiring extensive domain knowledge and careful consideration. As the Bioinformatics landscape evolves, researchers, both novice and expert, may feel overwhelmed in unfamiliar fields, potentially leading to the selection of unsuitable tools during workflow development.

Results

In this article, we introduce the Bioinformatics Tool Recommendation system (BTR), a deep learning model designed to recommend suitable tools for a given workflow-in-progress. BTR leverages recent advances in graph neural network technology, representing the workflow as a graph to capture essential context. Natural language processing techniques enhance tool recommendations by analyzing associated tool descriptions. Experiments demonstrate that BTR outperforms the existing Galaxy tool recommendation system, showcasing its potential to streamline scientific workflow construction.

Availability and implementation

The Python source code is available at https://github.com/ryangreenj/bioinformatics_tool_recommendation.
How Does Treatment Coverage and Proportion Never Treated Influence the Success of Schistosoma mansoni Elimination as a Public Health Problem by 2030?
Authors: Kura Klodeta , Mutono Nyamai , Basáñez Maria-Gloria , Collyer Benjamin S , Coffeng Luc E , Thumbi S M , Anderson Roy M
Published: April 2024

Background

The 2030 target for schistosomiasis is elimination as a public health problem (EPHP), achieved when the prevalence of heavy-intensity infection among school-aged children (SAC) reduces to <1%. To achieve this, the new World Health Organization guidelines recommend a broader target of population to include pre-SAC and adults. However, the probability of achieving EPHP should be expected to depend on patterns in repeated uptake of mass drug administration by individuals.

Methods

We employed 2 individual-based stochastic models to evaluate the impact of school-based and community-wide treatment and calculated the number of rounds required to achieve EPHP for Schistosoma mansoni by considering various levels of the population never treated (NT). We also considered 2 age-intensity profiles, corresponding to a low and high burden of infection in adults.

Results

The number of rounds needed to achieve this target depends on the baseline prevalence and the coverage used. For low- and moderate-transmission areas, EPHP can be achieved within 7 years if NT ≤10% and NT <5%, respectively. In high-transmission areas, community-wide treatment with NT <1% is required to achieve EPHP.

Conclusions

The higher the intensity of transmission, and the lower the treatment coverage, the lower the acceptable value of NT becomes. Using more efficacious treatment regimens would permit NT values to be marginally higher. A balance between target treatment coverage and NT values may be an adequate treatment strategy depending on the epidemiological setting, but striving to increase coverage and/or minimize NT can shorten program duration.
Safety and efficacy of EsoFLIP dilation in patients with esophageal dysmotility: a systematic review
Authors: Iqbal Umair , Yodice Michael , Ahmed Zohaib , Anwar Hafsa , Arif Syeda Faiza , Lee-Smith Wade M , Diehl David L
Published: April 2024

Esophageal manometry is utilized for the evaluation and classification of esophageal motility disorders. EndoFlip has been introduced as an adjunctive test to evaluate esophagogastric junction (EGJ) distensibility. Treatment options for achalasia and EGJ outflow obstruction (EGJOO) include pneumatic dilation, myotomy, and botulinum toxin. Recently, a therapeutic 30 mm hydrostatic balloon dilator (EsoFLIP, Medtronic, Minneapolis, MN, USA) has been introduced, which uses impedance planimetry technology like EndoFlip. We performed a systematic review to evaluate the safety and efficacy of EsoFLIP in the management of esophageal motility disorders. A systematic literature search was performed with Medline, Embase, Web of science, and Cochrane library databases from inception to November 2022 to identify studies utilizing EsoFLIP for management of esophageal motility disorders. Our primary outcome was clinical success, and secondary outcomes were adverse events. Eight observational studies including 222 patients met inclusion criteria. Diagnoses included achalasia (158), EGJOO (48), post-reflux surgery dysphagia (8), and achalasia-like disorder (8). All studies used 30 mm maximum balloon dilation except one which used 25 mm. The clinical success rate was 68.7%. Follow-up duration ranged from 1 week to a mean of 5.7 months. Perforation or tear occurred in four patients. EsoFLIP is a new therapeutic option for the management of achalasia and EGJOO and appears to be effective and safe. Future comparative studies with other therapeutic modalities are needed to understand its role in the management of esophageal motility disorders.
Aortic aneurysms in a general population cohort: prevalence and risk factors in men and women
Authors: Pham Michael Huy Cuong , Sigvardsen Per Ejlstrup , Fuchs Andreas , Kühl Jørgen Tobias , Sillesen Henrik , Afzal Shoaib , Nordestgaard Børge Grønne , Køber Lars Valeur , Kofoed Klaus Fuglsang
Published: April 2024

Aims

The prevalence and difference in risk factors for having thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) in men compared with women in the general population is not well described. This study aimed to test the hypotheses that (i) cardiovascular risk factors for TAA and AAA differ and (ii) the prevalence of TAA and AAA is sex specific.

Methods and results

Aortic examination using computed tomography angiography was performed in 11 294 individuals (56% women), with a mean age of 62 (range 40–95) years participating in the Copenhagen General Population Study. TAAs were defined as an ascending aortic diameter ≥45 mm and a descending aortic diameter ≥35 mm, while AAAs were defined as an abdominal aortic diameter ≥30 mm. Demographic data were obtained from questionnaires. Overall prevalence of aortic aneurysms (AAs) in the study population included: total population 2.1%, men 4.0% and women 0.7% (P-value men vs. women P < 0.001). AAs were independently associated with male sex, increasing age, and body surface area (BSA). While TAAs were associated with hypertension, odds ratio (OR) = 2.0 [95% confidence interval (CI): 1.5–2.8], AAAs were associated with hypercholesterolaemia and smoking, OR = 2.4 (95% CI: 1.6–3.6) and 3.2 (95% CI: 1.9–5.4).

Conclusion

Subclinical AAs are four times more prevalent in men than in women. In both sexes, increasing age and BSA are risk factors for AAs of any anatomical location. Whereas arterial hypertension is a risk factor for TAAs, hypercholesterolaemia and smoking are risk factors for AAAs.
Simple models vs. deep learning in detecting low ejection fraction from the electrocardiogram
Authors: Hughes John Weston , Somani Sulaiman , Elias Pierre , Tooley James , Rogers Albert J , Poterucha Timothy , Haggerty Christopher M , Salerno Michael , Ouyang David , Ashley Euan , Zou James , Perez Marco V
Published: April 2024

Aims

Deep learning methods have recently gained success in detecting left ventricular systolic dysfunction (LVSD) from electrocardiogram (ECG) waveforms. Despite their high level of accuracy, they are difficult to interpret and deploy broadly in the clinical setting. In this study, we set out to determine whether simpler models based on standard ECG measurements could detect LVSD with similar accuracy to that of deep learning models.

Methods and results

Using an observational data set of 40 994 matched 12-lead ECGs and transthoracic echocardiograms, we trained a range of models with increasing complexity to detect LVSD based on ECG waveforms and derived measurements. The training data were acquired from the Stanford University Medical Center. External validation data were acquired from the Columbia Medical Center and the UK Biobank. The Stanford data set consisted of 40 994 matched ECGs and echocardiograms, of which 9.72% had LVSD. A random forest model using 555 discrete, automated measurements achieved an area under the receiver operator characteristic curve (AUC) of 0.92 (0.91–0.93), similar to a deep learning waveform model with an AUC of 0.94 (0.93–0.94). A logistic regression model based on five measurements achieved high performance [AUC of 0.86 (0.85–0.87)], close to a deep learning model and better than N-terminal prohormone brain natriuretic peptide (NT-proBNP). Finally, we found that simpler models were more portable across sites, with experiments at two independent, external sites.

Conclusion

Our study demonstrates the value of simple electrocardiographic models that perform nearly as well as deep learning models, while being much easier to implement and interpret.
Digest: Sexual selection may shape species’ range limits
Authors: Sinclair Olivia R , Taberer Tabitha R
Published: April 2024

In a recent study, Tschol et al. (2024) present a model that investigates how 2 different forms of sexual selection, selection for traits that increase mate encounters and selection for traits that enhance one’s ability to compete for mates, affect geographical range limits. The model demonstrates that range limits expand in response to selection on mate-encountering traits and contract when selection acts on reproductive competitiveness. When traits coevolve, range limits depend on the mating system. This study demonstrates the importance of accounting for sexual selection and intraspecific interactions when investigating eco-evolutionary dynamics of geographic range limits.
Multi-omics analysis reveals improvement of tomato quality by grafting on goji rootstock
Authors: Wang Ruiting , Yang Yang , Xu Kexin , Wang Tingjin , A. Elsadek Mohamed , Yuan Lu , Hu Zhongyuan , Lv Yongping , Yuan Xin , Chen Xiangfu , Wang Yiting , Chen Liping
Published: April 2024

Background

Tomato quality is a complex trait influenced by multiple genes involved in various complicated metabolic pathways.

Materials and Methods

This study sought to improve tomato taste and quality by grafting on goji rootstock. We integrated physiological and biochemical indicators, as well as metabolic and transcriptomic analysis, to evaluate tomato quality.

Results

The grafted tomatoes showed significant increases in soluble solids (51.48%), vitamin C (16.86%), soluble protein (16.19%), titratable acid (11.73%), anthocyanin (11.43%), and polysaccharide (9.43%) content compared to those of the control. Metabolomics analysis identified 234 differentially accumulated metabolites and transcriptome analysis identified 4213 differentially expressed genes between grafted and control tomatoes at three ripening stages (mature green, turning, and fully red). A total of 93 phenolic compounds, including flavonoids and phenolic acids, showed differential accumulation patterns between grafted and control tomatoes at the fully red stage. These changes were attributed to the upregulation of key genes (F3ʹH, F3ʹ5ʹH, DFR, and ANS) associated with flavonoids and anthocyanin synthesis in the goji rootstock compared to those of the control. The expression of genes involved in sucrose hydrolysis and starch synthesis, including invertase (INV), sucrase synthase (SUS), and beta-amylase (BAM) genes, were suppressed by goji grafting, resulting in increased levels of sugars. In addition, the consistency between the transcriptomic and metabolomic data provided a robust validation of the observed quality changes.

Conclusions

Taken together, our results demonstrate that grafting onto goji rootstock improves tomato quality by modulating multiple genes involved in phenylpropanoid, sucrose, and starch pathways during fruit development, providing valuable insights for improving the quality and taste of tomato.
Disparities in Stress Exposure and Later-Life Disability
Authors: Sauerteig-Rolston Madison R , Ferraro Kenneth F
Published: April 2024

Background and Objectives

Drawing from cumulative inequality theory and the weathering hypothesis, this study examined the relationship between life-course stress exposure (measured cumulatively and by domains) and the onset of disability in later life among White, Black, U.S.-born Hispanic, and foreign-born Hispanic older adults.

Research Design and Methods

Cross-sectional and longitudinal models were estimated using nationally representative data from the Health and Retirement Study (N = 11,483). We used logistic regression models to examine associations between stress exposure and Wave 1 disability (i.e., occurrence), and Weibull-accelerated failure-time models to examine the relationship between stress exposure and age of onset of disability 12–14 years later (i.e., incidence). We tested for moderation between stress and disability by race, ethnicity, and Hispanic nativity.

Results

At Wave 1, higher odds of disability occurrence were associated with cumulative stress burden (CSB; odds ratio [OR] = 4.93, 95% confidence interval [CI]: 2.95–8.23). In a model specifying domains of stressors, disability occurrence was associated with childhood financial strain (OR = 1.22, CI: 1.01–1.46), lifetime traumatic events (OR = 1.92, CI: 1.41–2.62), neighborhood disadvantage (OR = 1.32, CI: 1.01–1.73), and major lifetime discrimination (OR = 1.64, CI: 1.12–2.41). Over time, earlier onset of disability was associated with CSB (β = −0.39), childhood traumatic events (β = −0.16), adult financial strain (β = −0.17), everyday discrimination (β = −0.15), and major lifetime discrimination (β = −0.13). The effect of childhood traumatic events on the transition to disability was stronger for U.S.-born Hispanic adults than White adults (occurring 33% earlier).

Discussion and Implications

To reduce racial, ethnic, and nativity disparities in disability, it is important to consider the historical and structural disadvantages associated with stress exposure across the life course. It is also important to acknowledge that nativity influences stratification processes associated with disparities in racial and ethnic health trajectories.
The Benefits of Technology for Engaging Aging Adults: Findings From the PRISM 2.0 Trial
Authors: Czaja Sara J , Charness Neil , Rogers Wendy A , Sharit Joseph , Moxley Jerad H , Boot Walter R
Published: April 2024

Background and Objectives

Technology has potential for providing support for aging adults. This study evaluated the Personal Reminder Information and Social Management 2.0 (PRISM 2.0) software, in terms of enhancing social engagement and quality of life, and decreasing loneliness among older adults.

Research Design and Methods

The randomized field trial conducted in diverse living contexts (rural locations, senior housing, and assisted living communities [ALC]). Two hundred and forty-five adults, aged 64 to 99 years, were randomly assigned to the PRISM 2.0 (integrated software system designed for aging through an iterative design process) or a Standard Tablet (without PRISM) Control condition, where participants received the same amount of contact and training as those in the PRISM 2.0 condition. Primary outcomes included measures of loneliness, social support, social connectedness, and quality of life. Secondary outcomes included measures of social isolation, mobile device proficiency, and technology readiness. Data were collected at baseline and 6 and 9 months postrandomization. This article focuses on the 6-month outcomes due to coronavirus disease 2019-related data challenges at 9 months.

Results

Contrary to our hypothesis, participants in rural locations and senior housing in both conditions reported less loneliness and social isolation, and greater social support and quality of life at 6 months, and an increase in mobile device proficiency. Participants in the ALCs in both conditions also evidenced an increase in mobile device proficiency. Improvements in quality of life and health-related quality of life were associated with decreases in loneliness.

Discussion and Implications

This study provides compelling evidence about the benefits of technology for older adults in terms of enhancing social outcomes and quality of life. However, the findings also underscore that for technology applications to be successful, they need to be adapted to the abilities and needs of the user group and instructional support needs to be provided.

Clinical Trials Registration #

NCT03116399
Strategies to Improve Emergency Transitions From Long-Term Care Facilities: A Scoping Review
Authors: Tate Kaitlyn , Cummings Greta , Jacobsen Frode , Halas Gayle , Van den Bergh Graziella , Devkota Rashmi , Shrestha Shovana , Doupe Malcolm
Published: April 2024

Background and Objectives

Older adults residing in residential aged care facilities (RACFs) often experience substandard transitions to emergency departments (EDs) through rationed and delayed ED care. We aimed to identify research describing interventions to improve transitions from RACFs to EDs.

Research Design and Methods

In our scoping review, we included English language articles that (a) examined an intervention to improve transitions from RACF to EDs; and (b) focused on older adults (≥65 years). We employed content analysis. Dy et al.’s Care Transitions Framework was used to assess the contextualization of interventions and measurement of implementation success.

Results

Interventions in 28 studies included geriatric assessment or outreach services (n = 7), standardized documentation forms (n = 6), models of care to improve transitions from RACFs to EDs (n = 6), telehealth services (n = 3), nurse-led care coordination programs (n = 2), acute-care geriatric departments (n = 2), an extended paramedicine program (n = 1), and a web-based referral system (n = 1). Many studies (n = 17) did not define what “improvement” entailed and instead assessed documentation strategies and distal outcomes (e.g., hospital admission rates, length of stay). Few authors reported how they contextualized interventions to align with care environments and/or evaluated implementation success. Few studies included clinician perspectives and no study examined resident- or family/friend caregiver-reported outcomes.

Discussion and Implications

Mixed or nonsignificant results prevent us from recommending (or discouraging) any interventions. Given the complexity of these transitions and the need to create sustainable improvement strategies, future research should describe strategies used to embed innovations in care contexts and to measure both implementation and intervention success.