Browse Articles
Discover research articles across all indexed journals
Invitation appeals and STEM academic scientists research participation: Findings from six survey experiments
Survey research is a primary method used to investigate the opinions, perceptions and behaviors of academic scientists. However, little is known about the most successful appeal strategies for eliciting survey participation from these busy, highly educated professionals. Drawing on leverage-salience theory, this study examines the impacts of two sets of invitation appeals—information and representation appeals—on survey response rates among academic scientists in four STEM fields employed at U.S. R1 universities. Findings from six randomized experiments show that the effectiveness of both sets of invitation appeals is mixed and context-dependent, varying based on the polarization and relevance of survey topics, STEM academic scientists’ career stage, and their prior interactions with survey administrators. Specifically, self-representation appeals are most effective for polarized topics when recipients have low community affiliation. Less detailed information appeals are more successful when asking about low relevance topics, particularly for recipients with greater demands on their time, while more detailed information is effective for highly relevant and polarized topics. Additionally, invitations containing more detailed information are effective for first-time recipients in survey panels. This complexity reinforces the importance of designing effective outreach strategies to account for survey topics and recipient characteristics.
An understanding of the motivations that influence the beef cattle production systems adopted by farmers in central Mozambique
The analysis of factors that affect livestock production, from the farmers’ perspective, is essential for improving efficiency in animal production. The objectives of this study were to analyse: i) the historical and current motivations for beef cattle production and ii) the situation of communal pasture areas. For data collection, semi-structured interviews were held with one hundred and one farmers in the districts of Angónia, Changara and Manica, in Mozambique. The results show that in Angónia and Changara districts, the primary motivation for starting beef cattle production was to keep cattle as a saving asset, whereas the primary motivation of Manica’s farmers was to use cattle as draught animal power to expand crop production. These motivations remain the same over the years of the farmers’ experience. Grazing areas have decreased over the years, mainly due to their occupation for crop production, and this perception was associated with the studied district (p = 0.004). The studied districts, particularly Angónia and Manica, have similar characteristics, suggesting that similar intervention models may be designed. The results raise the question of how to increase the productivity of beef cattle systems, primarily motivated by savings and animal traction while maintaining their characteristics, which are essential for the socio-economic conditions of the farmers. Overall, the study suggests that motivations for beef cattle production and the establishment of grazing areas should be considered when developing strategies and policies to improve these systems.
Economic impact of the Elecsys anti-Müllerian hormone Plus immunoassay for anti-Müllerian hormone testing as part of polycystic ovary syndrome assessment in the United Kingdom
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women. Current international PCOS assessment and management guidelines recommend anti-Müllerian hormone (AMH) as an alternative to transvaginal ultrasound for assessing polycystic ovarian morphology, which is one of three criteria for diagnosing PCOS. This study assessed the economic impact of using the Elecsys® AMH Plus immunoassay (Roche Diagnostics International Ltd, Rotkreuz, Switzerland) for AMH testing in the United Kingdom health system to assess women with signs and symptoms of PCOS. A decision tree model estimated the costs and health outcomes of using the Elecsys AMH Plus immunoassay to determine polycystic ovarian morphology as part of PCOS assessment in a simulated cohort of women aged 25–45 years who were exposed to different diagnosis pathways. The comparator scenario was the standard of care, where transvaginal ultrasound was used for assessment. Base-case results indicated that the Elecsys AMH Plus immunoassay could lead to cost savings of £284,029 per year on the total cost of PCOS diagnosis (1.4% reduction vs. transvaginal ultrasound), in addition to savings on managing secondary comorbidities, such as type 2 diabetes and stroke care. Cost savings with the Elecsys AMH Plus immunoassay were observed in all scenarios versus using transvaginal ultrasound, including scenarios with various referral rates to specialists and dropout rates from the diagnosis pathway, and low adherence to lifestyle recommendations. With the known current delays in the United Kingdom for diagnosis of PCOS, implementing the Elecsys AMH Plus immunoassay for AMH testing may not only provide cost benefits, but also reduce waiting times for diagnosis and treatment, improving patient health outcomes.
Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system
Objective This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adolescents, thoroughly exploring the correlation between retinal vascular parameters and axial length (AL), and ultimately revealing the changing patterns of retinal vascular characteristics in children with different refractive errors. The findings aim to provide a scientific basis for the prevention, early screening, and formulation of personalized treatment strategies for myopia. Methods The study selected 124 students from Jiandong Primary School in Changzhi City who underwent myopia prevention and control screening. Their axial length data were recorded, and fundus photographs were taken using the Topcon TNF506 non-mydriatic fundus camera. Subsequently, these fundus images were meticulously analyzed using the EVision AI fundus image analysis system, which is a commercial software that employs pre-trained algorithms to automatically extract retinal vascular parameters.Pearson and Spearman correlation coefficients were used to analyze the correlation between retinal vascular parameters and axial length, and multiple linear regression analysis was further conducted to explore their intrinsic associations. Results The study found that in the low myopia group, axial length was significantly negatively correlated with various retinal vascular parameters, including the average diameters of arteries and veins, average vascular tortuosity, atrophy arc area, and leopard spot density. In the moderate to high myopia group, axial length also showed significant negative correlations with the average diameter of arteries, some average venous tortuosity, and average vascular diameter. However, fractal dimension of vessels and average branch angle did not show significant changes across all myopia groups. Conclusion This study clearly demonstrates a significant correlation between axial length and retinal vascular parameters, with notable differences in this correlation among children with different refractive errors. These findings not only provide a new perspective for understanding the pathological mechanisms of myopia but also offer important scientific evidence for the development of more precise and personalized myopia prevention and control strategies in the future. They have potential guiding significance for clinical practice and policy formulation.
Arrhythmia classification based on multi-input convolutional neural network with attention mechanism
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variability, data imbalance, and feature representation limitations. In this work, we propose a novel arrhythmia classification algorithm based on a multi-input convolutional neural network (CNN) enhanced with a Squeeze-and-Excitation (SE) attention mechanism. Distinct from previous methods that rely on single-resolution features or unimodal inputs, our model integrates multi-scale time-frequency representations derived from Short-Time Fourier Transform (STFT) applied to ECG signals segmented into two temporal resolutions. The dual-branch CNN architecture enables complementary feature learning from both short and long segments, while SE blocks enhance inter-channel dependencies to prioritize critical features. The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. Evaluated on MIT-BIH and SPH arrhythmia databases, the proposed model achieves high accuracy (99.13% and 95.84%, respectively) and Macro-F1 scores (94.46% and 95.91%), outperforming several state-of-the-art approaches. These results highlight the model’s potential for robust and interpretable arrhythmia classification in clinical practice.
Correction for Izdebski et al., Unbalanced social–ecological acceleration led to state formation failure in early medieval Poland
Space-time analysis of head and neck cancer in Asia and its 34 countries and territories (1990–2021): Implications from the Global Burden of Disease Study 2021
Background Asia bears a disproportionate burden of head and neck cancer (HNC). This study aimed to analyze its spatial distribution and temporal trends in Asia from 1990 to 2021, projecting trends to 2030. Methods We performed a secondary analysis of data from the Global Burden of Disease Study (GBD) 2021, examining disability-adjusted life years (DALYs) for HNC and its five major subtypes: nasopharyngeal cancer (NPC), thyroid cancer (TC), laryngeal cancer (LC), lip and oral cavity cancer (LOC), and other pharyngeal cancer (OPC), across five Asian subregions and 34 countries/territories from 1990 to 2021. Temporal trends were evaluated using Joinpoint regression, and projections to 2030 were generated through Bayesian Age-Period-Cohort model. Results From 1990 to 2021, DALYs for HNC increased in five subregions. In contrast, age-standardized DALY rates (ASDR) declined across all subregions except South Asia, with East Asia experiencing the most rapid decrease. In 2021, South Asia recorded the highest DALYs (6,412,639) and ASDR (405.82 per 100,000) for HNC. LOC was the main HNC type in most regions (32.41% − 46.23%), except East Asia, where NPC was most common (38.96%). South Asia also exhibited the highest ASDRs for LC (67.29), LOC (182.29), and OPC (93.00) per 100,000, while Southeast Asia demonstrated the highest ASDRs for NPC (50.77) and TC (18.22) per 100,000. Significant disparities in ASDR trends for HNC subtypes were observed across Asia. By 2030, South Asia is projected to maintain the highest ASDRs for HNC (394.59), LC (62.98), LOC (185.31), and OPC (95.50). East and Southeast Asia are expected to show comparable ASDRs for NPC (approximately 50.00), with Southeast Asia leading in TC ASDR (23.90). Conclusions HNC remains a significant public health challenge in Asia, with substantial heterogeneity in its subtypes across the five subregions. Implementing targeted, region-specific strategies is crucial to mitigating the disease burden.
The state value
This paper considers the state value using the future contract pricing approach. Our model allows adding an unlimited number of factors that affect the state value. We think this model may be useful to evaluate the performance of the government and the decision-making process by knowing the optimal value and the optimal time for the decision. This dynamic model differs from the traditional pricing model for evaluating the nation’s wealth using the discounted cash flow model (DCF), which does not allow considering the market condition via the risk-neutral approach. The state value determinants are divided into two classes, determinants and sub-determinants. We presented a model to determine the optimal value of the marginal return on assets for making a governmental decision. Traditional DCF issues including pricing intangible components, cash flow uncertainty, and asset marginal yield jumps were taken into account.
Measuring historical pollution: Natural history collections as tools for public health and environmental justice research
Through the industrial era, pollutants have been unevenly distributed in the environment, disproportionately impacting disenfranchised communities. Redressing the unequal distribution of environmental pollution is thus a question of environmental justice and public health that requires policy solutions. However, data on pollutants for many locations and time periods are limited because environmental monitoring is largely reactive—i.e., pollutants are monitored only after they are recognized as harmful and are circulating in the environment at elevated levels. Without comprehensive historical pollution data, it is difficult to understand the full, intergenerational consequences of pollutants on environmental and human health. We assert that biological specimens in natural history collections are an underutilized source of quantitative pollution data for tracking environmental pollutants over two centuries to inform justice-centered policy solutions. Specifically, we: 1) discuss the need for quantitative pollution data in environmental research and its implications for public health and policy, 2) examine the capacity of biological specimens as tools for tracking environmental pollutants through space and time, 3) present a framework for integrating pollution datasets from specimens with spatially and temporally matched human health datasets to inform and evaluate policy, and 4) identify challenges and research directions associated with the use of quantitative pollution datasets. Biological specimens present a unique opportunity to fill critical gaps that address environmental challenges relevant to public health and policy. This work demands interdisciplinary partnerships and inclusive practices to connect data generated from specimens with urgent questions about environmental health and justice.
Evaluation of optimal strategies for breast cancer screening in Ghana: A simulation study based on a continuous tumor growth model
Mammographic breast cancer screening plays a crucial role in detecting small tumors, which can prevent the progression of the disease and reduce the risk of breast cancer mortality. This study aimed to evaluate optimal strategies for a breast cancer screening program in Ghana. A continuous growth model was employed to evaluate the natural history of breast cancer in Ghana, from its onset to detection. We estimated tumor growth rates and the age at which symptomatic detection occurs using the maximum likelihood estimation method based on clinical data from the National Center of Radiotherapy and Nuclear Medicine at Korle Bu Teaching Hospital. Our results revealed that biennial screening provided a better trade-off between interval cancers and overdiagnosis than annual or triennial intervals. The simulation results for early screening under biennial intervals showed an average detection age of 47 years for unscreened individuals (control group) and 46 years for those screened (intervention group). While the screening approach (50–69 years) with biennial screening proved more reliable than other strategies, the early screening approach (30-65 years with biennial screenings) provided certain advantages in detection for the Ghanaian population. Our findings highlight the importance of early detection and advocate for the systematic adoption of mammography in Ghana and other low- and middle-income countries, contributing to enhanced breast cancer screening and patient treatment plans, as well as informing policy development.
Reply to Larsen and Riisgård: Fluid dynamics of choanocyte chambers
EPHX1 and ERCC2 polymorphisms are associated with cisplatin-induced nephrotoxicity and prognosis in Thai cancer patients
Cisplatin is a widely used chemotherapeutic drug for various cancers. One of the common adverse effects of cisplatin is nephrotoxicity including acute kidney injury (AKI) and acute kidney disease (AKD). Single Nucleotide Polymorphisms (SNPs) can be used to identify cancer patients who are susceptible to developing cisplatin-induced nephrotoxicity (CIN). In this study, we validated the association between 6 SNPs in the drug metabolizing enzyme genes, SLC22A2 (rs316019) & EPHX1 (rs1051740), and the DNA repair genes, ERCC1 (rs11615 & rs3212986) & ERCC2 (rs13181 & rs1799793), and CIN in the 169 Thai patients with head and neck, lung, or esophageal cancer. Effect of these SNPs on cumulative incidence of AKD, progression-free survival (PFS), and overall survival (OS) was also assessed. EPHX1 rs1051740 TC genotype was significantly associated with AKD in co-dominant [OR 2.894, 95% CI 1.091–7.680; P = 0.033] and over-dominant [OR 2.793, 95% CI 1.333–5.851; P = 0.006] models, and with an increased cumulative incidence of AKD (P = 0.021). Additionally, ERCC2 rs13181 and rs1799793 were significantly associated with OS (P = 0.002 and 0.004). Our results reveal an association between EPHX1 rs1051740 and AKD, and confirms the previously reported associations between ERCC2 SNPs and OS. These findings may help in predicting CIN in Thai cancer patients.
Characterization and prediction of non-melanoma skin cancer incidence in China: Joinpoint regression and age-period-cohort model
Objective Understanding the non-melanoma skin cancer (NMSC) incidence and its trends in China is an important prerequisite for effective prevention and control of NMSC. Methods NMSC incidence data was collected from the Annual Report of China Cancer Registry from 2005 to 2018. The Joinpoint regression model was used to estimate the average annual percent change (AAPC) and annual percent change (APC) to reflect the time trend. Age-period-cohort model with the intrinsic estimator algorithm was used to analyze age, period, and cohort effects. Bayesian age-period-cohort (BAPC) model with integrated nested laplace approximation was used for prediction. Results The age-standardized incidence rate (ASIR) of NMSC increased from 1.02/ 100,000 to 1.63/100,000 from 2005 to 2018, showing an increasing trend with AAPC of 3.7% (95% CI: 2.5%, 4.9%). The ASIR was higher in men than in women, while the increase rate was reversed, and it was lower in rural than in urban areas, while AAPC was 1.15 times higher. The risk of NMSC incidence increased with age. The cohort effect was first to increase and then to decrease and the inflection point appeared in 1930-1934. The ASIR of NMSC in China will continue to rise during 2019-2035. Conclusion The ASIR of NMSC in China from 2005 to 2018 showed an increasing trend with age, gender, and regional differences, and will continue to increase in the future. NMSC remains a public health problem and requires continuous attention.
A hybrid approach to enhance HbA1c prediction accuracy while minimizing the number of associated predictors: A case-control study in Saudi Arabia
Type 2 diabetes (T2D) is considered a significant global health concern. Hemoglobin A1c level (HbA1c) is recognized as the most reliable indicator for its diagnosis. Genetic, family, environmental, and health behaviors are the factors associated with the disease. T2D is linked to substantial economic costs and human suffering, making it a primary concern for health planners, physicians, and those living with the disease. Saudi Arabia currently ranks seventh worldwide in terms of prevalence rate. Despite this high rate, the country lacks focused research on T2D. This study aims to develop hybrid prediction models that integrate the strengths of multiple algorithms to enhance HbA1c prediction accuracy while minimising the number of significant Key Performance Indicators (KPIs). The proposed model can help healthcare practitioners diagnose T2D at an early stage. Analyses were conducted in a case-control study in Saudi Arabia involving cases (patients with HbA1c levels ≥ 6.5) and controls with normal HbA1c levels (< 6.5). Medical records from 3,000 King Abdulaziz University Hospital patients containing demographic, lifestyle, and lipid profile data were used to develop the models. For the first time, we utilized recommended machine learning algorithms to develop hybrid prediction models to reduce the number of significant KPIs while enhancing HbA1c prediction accuracy. The hybrid model combining Random Forest (RF) and Logistic Regression (LR) with only 4 out of 10 KPIs outperformed other models with an accuracy of 0.93, precision of 0.95, recall of 0.90, F-score of 0.92, an AUC of 0.88, and Gini index of 0.76. The significant variables identified by the model through backward elimination are age, body mass index (BMI), triglycerides (TG), and high-density lipoprotein (HDL). The proposed model helps healthcare providers identify patients at risk of T2D by monitoring fewer key predictors of HbA1c levels, enhancing early intervention strategies for managing diabetes in Saudi Arabia.
The pumping function of sponge choanocyte chambers
Global genetic diversity of Infectious Salmon Anemia Virus (ISAV) a scoping review protocol
Background Infectious salmon anemia virus is one of the most important pathogens responsible for causing infectious salmon anemia in Atlantic salmon (Salmo salar). Following its first emergence in 1980s in Norway, it has been reported in several salmon producing countries worldwide, with new variants frequently reported. These variants mostly exhibit differences in segments 5 and 6 of the genome, which contribute to the genetic diversity and variability in virulence. Despite the considerable economic losses associated with ISA, there remains a critical gap in available information on genetic diversity and classification. This study aims to provide a comprehensive and up-to-date synopsis of all known ISAV variants worldwide. Methods The Population, Concept, Context approach was used to formulate the research primary question. The primary research question of this review is “What variants of ISAV with respect to segment 5 and 6 has been identified globally in Atlantic salmon?” To address this question, four databases: PubMed, CAB Abstracts via (EBSCO host), Scopus, and the Earth, Atmospheric & Aquatic Science Collection via ProQuest will be used for primary literature search with no language and geographical area restrictions. Studies will be screened using predefined inclusion and exclusion criteria and will be imported in COVIDENCE. Two co-authors will independently screen, extract data, and assess the selected studies. Any discrepancies between the authors will be resolved with the assistance of two other co-authors in each stage of the protocol. Discussion To the best of our knowledge, this protocol outlines the first scoping review which will provide insights into the genetic diversity of ISAV, offering a comprehensive overview of the reported variants and their distribution globally. These findings could enhance our understanding of the genetic diversity of the virus, help customize mitigation strategies based on variants involved and provide foundation to develop a universally accepted nomenclature system.
Correction for Yuan et al., Molecular mechanism and functional significance of Wapl interaction with the Cohesin complex
Continuous self-repair protects vimentin intermediate filaments from fragmentation
Intermediate filaments are key regulators of cell mechanics. Vimentin, a type of intermediate filament expressed in mesenchymal cells and involved in migration, forms a dense network in the cytoplasm that is constantly remodeling through filament transport, elongation/shortening, and subunit exchange. While it is known that filament elongation involves end-to-end annealing, the reverse process of filament shortening by fragmentation remains unclear. Here, we use a combination of in vitro reconstitution, probed by fluorescence imaging and atomic force microscopy, with theoretical modeling to uncover the molecular mechanism involved in filament breakage. We first show that vimentin filaments are composed of two populations of subunits, half of which are exchangeable and half immobile. We also show that the exchangeable subunits are tetramers. Furthermore, we reveal a mechanism of continuous filament self-repair, where a soluble pool of vimentin tetramers in equilibrium with the filaments is essential to maintain filament integrity. Filaments break due to local fluctuations in the number of tetramers per cross-section, induced by the constant subunit exchange. We determine that a filament tends to break if approximately four tetramers are removed from the same filament cross-section. Finally, we analyze the dynamics of association/dissociation and fragmentation to estimate the binding energy of a tetramer to a complete versus a partially disassembled filament. Our results provide a comprehensive description of vimentin turnover and reveal the link between subunit exchange and fragmentation.
Co-opted SUMO machinery promotes condensate formation associated with membranous replication organelles of a positive-strand RNA virus
Positive-strand RNA viruses are important pathogens of humans and plants. These viruses built viral replication organelles (VROs) with the help of co-opted host proteins and intracellular membranes to support robust virus replication in infected cells. Tomato bushy stunt virus (TBSV), a model (+)RNA virus, assembles membranous VROs, which are associated with vir-condensate substructures driven by TBSV p33 replication-associated protein. In this work, we provide evidence that the peroxisome-associated TBSV and the mitochondria-associated carnation Italian ringspot virus hijack the host small ubiquitin-like modifier (SUMO) machinery in yeast model host and plants. Based on knockdown of components of the SUMO pathway, we show that SUMO machinery acts as a cellular proviral dependency factor during TBSV replication. The sumoylation machinery was found to be partially retargeted from the nucleus into vir-condensate associated with membranous VROs through direct interactions with TBSV p33. We developed a yeast-based sumoylation assay that demonstrated p33 sumoylation. Absence of sumoylation or mutations in SIM SUMO-interacting motif in p33 replication protein reduced the ability of p33 to form droplets in vitro via phase separation. We demonstrate that p33 sumoylation and its intrinsically disordered region play noncomplementary roles in droplet formation. Mutations in p33 sumoylation sites and p33-SIM sequence resulted in reduced-sized VROs, which showed diminished protection of TBSV p33 and the viral RNA from degradation and also reduced viral RNA recombination. Altogether, the co-opted host sumoylation machinery promotes viral replication and RNA recombination. This finding could provide opportunities for antiviral interventions via targeting protein posttranslational modifications.