bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a risk model for intracardiac thrombosis in patients with dilated cardiomyopathy: a retrospective study
Authors: Huang Yuan , Li Long-Chang , Li Yu-Xin , Gui Chun , Yang Li-Hua 
Published: January 2024

AbstractIntracardiac thrombosis is a severe complication in patients with non-ischemic dilated cardiomyopathy. This study aims to develop and validate an individualized nomogram to evaluate the risk of intracardiac thrombosis in patients with non-ischemic dilated cardiomyopathy. This retrospective study included patients diagnosed with dilated cardiomyopathy at first admission. Clinical baseline characteristics were acquired from electronic medical record systems. Multiple methods were applied to screen the key variables and generate multiple different variable combinations. Multivariable logistic regression was used to build the models, and the optimal model was chosen by comparing the discrimination. Then we checked the performance of the model in different thrombus subgroups. Finally, the model was presented using a nomogram and evaluated from the perspectives of discrimination, calibration, and clinical usefulness. Internal validation was performed by extracting different proportions of data for Bootstrapping. Ultimately, 564 eligible patients were enrolled, 67 of whom developed an intracardiac thrombosis. Risk factors included d-dimer, white blood cell count, high-sensitivity C-reactive protein, pulse pressure, history of stroke, hematocrit, and NT-proBNP in the optimal model. The model had good discrimination and calibration, and the area under the curve (AUC) was 0.833 (0.782–0.884), and the model’s performance in each subgroup was stable. Clinical decision curve analysis showed that the model had clinical application value when the high-risk threshold was between 2% and 78%. The AUC of interval validation (30% and 70% data resampling) was 0.844 (0.765–0.924) and 0.833 (0.775–0.891), respectively. This novel intracardiac thrombosis nomogram could be conveniently applied to facilitate the individual intracardiac thrombosis risk assessment in patients with non-ischemic dilated cardiomyopathy.
Investigation of the last two centuries sedimentation dynamics in high-altitude lakes of Southern Carpathians, Romania
Authors: Begy Robert-Cs. , Savin Codrin-F. , Korponai János , Magyari Enikő , Kovács Tibor 
Published: January 2024

AbstractThis study investigates the last two centuries sedimentation dynamics in four high-altitude lakes located in Southern Carpathians, Romania. Furthermore, a novel approach is proposed for identifying the anthropic or natural underlying causes, by comparison of the acceleration of the change in sedimentation rate with a baseline growth rate trend provided by an isolated peat bog. The high-resolution chronologies were developed using the 210Pb dating technique and the CRS model. 137Cs alternative time-marker validated the age-depth models and reassured the quality of the results. The results indicated several short-interval high sedimentation events within the lake cores, yielding up to five times the average rate for the investigated period. The cause of the high sedimentation episodes was generally attributed to anthropic activities (primarily road construction) and extreme natural events. A first-order derivative equation was employed to plot the acceleration in the sedimentation rate of the lakes with the peat bog baseline. The discrepancies between the acceleration trends highlighted significant deviations from the natural variation tendencies and provided preliminary data regarding the underlying causes of the intense sedimentation periods.
Superconducting and charge-ordered states in the anisotropic t–J–U model
Authors: Feng Yifan , Lou Jie , Chen Yan 
Published: January 2024

AbstractMotivated by the effect of symmetry breaking in cuprates superconductors YBa$$_2$$

2

Cu$$_3$$

3

O$$_{7-\delta }$$

7
-
δ

, we employ the renormalized mean-field theory to study the presence of uniform superconducting and charge-ordered states in two anisotropic t–J–U models, either with hopping strength anisotropy or antiferromagnetic interaction anisotropy. In the case of uniform superconducting state, compared with the isotropic t–J–U model with only $$d_{x^2-y^2}$$

d

x
2

-

y
2

-wave superconducting state, there is an additional s-wave superconducting state in the model with hopping strength anisotropy. Meanwhile, the hopping anisotropy may enhance the critical Coulomb interaction $$U_c$$

U
c

at the Mott insulator to the Gossamer superconductor transition point, and strong hopping anisotropy may weaken the superconducting state. In the case of a charge-ordered state, hopping anisotropy may suppress the amplitude of the charge density waves and pair density waves, which originate from local Coulomb interactions. These results indicate that the effects of hopping anisotropy and local Coulomb interactions are competitive. Moreover, the antiferromagnetic interaction anisotropy only weakly suppresses the superconducting gap and density wave amplitude. Our results show that the t–J–U model with hopping anisotropy is qualitatively consistent with experimental superconducting pair symmetry and charge density waves in the YBa$$_2$$

2

Cu$$_3$$

3

O$$_{7-\delta }$$

7
-
δ

system.
Improving tumor treatment through intratumoral injection of drug-loaded magnetic nanoparticles and low-intensity ultrasound
Authors: Hosseinpour Asma , Soltani Madjid , Souri Mohammad 
Published: January 2024

AbstractThe intratumoral injection of therapeutic agents responsive to external stimuli has gained considerable interest in treating accessible tumors due to its biocompatibility and capacity to reduce side effects. For the first time, a novel approach is explored to investigate the feasibility of utilizing low-intensity ultrasound in combination with intratumoral injection of drug-loaded magnetic nanoparticles (MNPs) to thermal necrosis and chemotherapy with the objective of maximizing tumor damage while avoiding harm to surrounding healthy tissue. In this study, a mathematical framework is proposed based on a multi-compartment model to evaluate the effects of ultrasound transducer’s specifications, MNPs size and distribution, and drug release in response to the tumor microenvironment characteristics. The results indicate that while a higher injection rate may increase interstitial fluid pressure, it also simultaneously enhances the concentration of the therapeutic agent. Moreover, by increasing the power and frequency of the transducer, the acoustic pressure and intensity can be enhanced. This, in turn, increases the impact on accumulated MNPs, resulting in a rise in temperature and localized heat generation. Results have demonstrated that smaller MNPs have a lower capacity to generate heat compared to larger MNPs, primarily due to the impact of sound waves on them. It is worth noting that smaller MNPs have been observed to have enhanced diffusion, allowing them to effectively spread within the tumor. However, their smaller size also leads to rapid elimination from the extracellular space into the bloodstream. To summarize, this study demonstrated that the local injection of MNPs carrying drugs not only enables localized chemotherapy but also enhances the effectiveness of low-intensity ultrasound in inducing tissue thermal necrosis. The findings of this study can serve as a valuable and reliable resource for future research in this field and contribute to the development of personalized medicine.
Reductions in sustained prescription opioid use within the US between 2017 and 2021
Authors: Schoenfeld Andrew J. , Munigala Satish , Gong Jonathan , Schoenfeld Roman J. , Banaag Amanda , Coles Christian , Koehlmoos Tracey P. 
Published: January 2024

AbstractOver the last decade, various efforts have been made to curtail the opioid crisis. The impact of these efforts, since the onset of the COVID-19 pandemic, has not been well characterized. We sought to develop national estimates of the prevalence of sustained prescription opioid use for a time period spanning the COVID-19 pandemic (2017–2021). We used TRICARE claims data (fiscal year 2017–2021) to identify patients who were prescription opioid non-users prior to receipt of a new opioid medication. We evaluated eligible patients for subsequent sustained prescription opioid use. The prevalence of sustained prescription opioid use during 2020–2021 was compared to 2017–2019. We performed multivariable logistic regression analyses to adjust for confounding. We performed secondary analyses that accounted for interactions between the time period and age, as well as a proxy for socioeconomic status. We determined there was a 68% reduction in the odds of sustained prescription opioid use (OR 0.32; 95% CI 0.27, 0.38; p < 0.001) in 2020–2021 as compared to 2017–2019. Significant reductions were identified across all US census divisions and all patient age groups. In both time periods, the plurality of encounters associated with initial receipt of an opioid that culminated in sustained prescription opioid use were associated with non-specific primary diagnoses. We found significant reductions in sustained prescription opioid use in 2020–2021 as compared to 2017–2019. The persistence of prescribing behaviors that result in issue of opioids for poorly characterized conditions remains an area of concern.
A novel smartphone application for early detection of habanero disease
Authors: Babatunde Ronke Seyi , Babatunde Akinbowale Nathaniel , Ogundokun Roseline Oluwaseun , Yusuf Obiwusi Kolawole , Sadiku Peter O. , Shah Mohd Asif 
Published: January 2024

AbstractHabanero plant diseases can significantly reduce crop yield and quality, making early detection and treatment crucial for farmers. In this study, we discuss the creation of a modified VGG16 (MVGG16) Deep Transfer Learning (DTL) model-based smartphone app for identifying habanero plant diseases. With the help of the smartphone application, growers can quickly diagnose the health of a habanero plant by taking a photo of one of its leaves. We trained the DTL model on a dataset of labelled images of healthy and infected habanero plants and evaluated its performance on a separate test dataset. The MVGG16 DTL algorithm had an accuracy, precision, f1-score, recall and AUC of 98.79%, 97.93%, 98.44%, 98.95 and 98.63%, respectively, on the testing dataset. The MVGG16 DTL model was then integrated into a smartphone app that enables users to upload photographs, get diagnosed, and explore a history of earlier diagnoses. We tested the software on a collection of photos of habanero plant leaves and discovered that it was highly accurate at spotting infected plants. The smartphone software can boost early identification and treatment of habanero plant diseases, resulting in higher crop output and higher-quality harvests.
Autistic traits and speech perception in social and non-social noises
Authors: Tsuji Yurika , Imaizumi Shu 
Published: January 2024

AbstractIndividuals with the autism spectrum disorder (ASD) experience difficulties in perceiving speech in background noises with temporal dips; they also lack social orienting. We tested two hypotheses: (1) the higher the autistic traits, the lower the performance in the speech-in-noise test, and (2) individuals with high autistic traits experience greater difficulty in perceiving speech, especially in the non-vocal noise, because of their attentional bias toward non-vocal sounds. Thirty-eight female Japanese university students participated in an experiment measuring their ability to perceive speech in the presence of noise. Participants were asked to detect Japanese words embedded in vocal and non-vocal background noises with temporal dips. We found a marginally significant effect of autistic traits on speech perception performance, suggesting a trend that favors the first hypothesis. However, caution is needed in this interpretation because the null hypothesis is not rejected. No significant interaction was found between the types of background noise and autistic traits, indicating that the second hypothesis was not supported. This might be because individuals with high autistic traits in the general population have a weaker attentional bias toward non-vocal sounds than those with ASD or to the explicit instruction given to attend to the target speech.
Assessment of aortic and peripheral arterial stiffness in patients with knee osteoarthritis by ultrasound Doppler derived pulse wave velocity
Authors: Yang Yong , Liang Xiao , Luo Hu , Cheng Yu-xin , Guo Yan , Wu Peng , Huang Yan-li , Zhang Jin-peng , Wang Zhen 
Published: January 2024

AbstractInformation regarding regional arterial stiffness assessment in osteoarthritis (OA) was scarce and sometimes contradictory. We aimed to investigate the aortic, lower limb peripheral arterial stiffness and their associations with knee OA. Patients with primary knee OA and matched non-OA controls were prospectively enrolled from two medical centers in China. The carotid-femoral pulse wave velocity (cfPWV) and femoral-ankle pulse wave velocity (faPWV) were measured using a novel ultrasound technique. A total of 238 participants (including 128 patients with knee OA and 110 controls) were included. In OA patients, cfPWV was significantly higher than that of non-OA controls (9.40 ± 1.92 vs 8.25 ± 1.26 m/s, P < 0.0001). However, faPWV measurements in OA patients (12.10 ± 2.09 m/s) showed no significant difference compared with that of the controls (11.67 ± 2.52 m/s, P = 0.130). Multiple regression analysis revealed that cfPWV was independently associated with knee OA (P < 0.0001) after adjusting for the confounding factors including age, gender, smoking, mean blood pressure, body mass index, heart rate, high-sensitivity C-reactive protein and lipids profiles. In contrast, faPWV did not show independent association with knee OA (P = 0.372) when after adjusting for confounding factors. In addition, Spearman’s correlation analysis showed cfPWV had a significant correlation with Kellgren-Lawrence score (rs = 0.2333, P = 0.008), but no correlation was founded between faPWV with Kellgren-Lawrence score (rs = 0.1624, P = 0.067) in OA patients. This study demonstrated that stiffening of aorta, but not lower limb arteries, was independently associated with knee OA. Our findings may call for further implementation of routine aortic stiffness assessments so as to evaluate cardiovascular risk in patients with OA.
Self Fourier shell correlation: properties and application to cryo-ET
Authors: Verbeke Eric J. , Gilles Marc Aurèle , Bendory Tamir , Singer Amit 
Published: January 2024

AbstractThe Fourier shell correlation (FSC) is a measure of the similarity between two signals computed over corresponding shells in the frequency domain and has broad applications in microscopy. In structural biology, the FSC is ubiquitous in methods for validation, resolution determination, and signal enhancement. Computing the FSC usually requires two independent measurements of the same underlying signal, which can be limiting for some applications. Here, we analyze and extend on an approach to estimate the FSC from a single measurement. In particular, we derive the necessary conditions required to estimate the FSC from downsampled versions of a single noisy measurement. These conditions reveal additional corrections which we implement to increase the applicability of the method. We then illustrate two applications of our approach, first as an estimate of the global resolution from a single 3-D structure and second as a data-driven method for denoising tomographic reconstructions in electron cryo-tomography. These results provide general guidelines for computing the FSC from a single measurement and suggest new applications of the FSC in microscopy.
The adhesion GPCR GPR116/ADGRF5 has a dual function in pancreatic islets regulating somatostatin release and islet development
Authors: Röthe Juliane , Kraft Robert , Ricken Albert , Kaczmarek Isabell , Matz-Soja Madlen , Winter Karsten , Dietzsch André Nguyen , Buchold Julia , Ludwig Marie-Gabrielle , Liebscher Ines , Schöneberg Torsten , Thor Doreen 
Published: January 2024

AbstractGlucose homeostasis is maintained by hormones secreted from different cell types of the pancreatic islets and controlled by manifold input including signals mediated through G protein-coupled receptors (GPCRs). RNA-seq analyses revealed expression of numerous GPCRs in mouse and human pancreatic islets, among themGpr116/Adgrf5. GPR116 is an adhesion GPCR mainly found in lung and required for surfactant secretion. Here, we demonstrate that GPR116 is involved in the somatostatin release from pancreatic delta cells using a whole-body as well as a cell-specific knock-out mouse model. Interestingly, the whole-body GPR116 deficiency causes further changes such as decreased beta-cell mass, lower number of small islets, and reduced pancreatic insulin content. Glucose homeostasis in global GPR116-deficient mice is maintained by counter-acting mechanisms modulating insulin degradation. Our data highlight an important function of GPR116 in controlling glucose homeostasis.
Co-assessment of costs and environmental impacts for off-grid direct air carbon capture and storage systems
Authors: Gutsch Moritz , Leker Jens 
Published: January 2024

AbstractLarge-scale deployment of direct air carbon capture and storage (DACS) is required to offset CO2 emissions. To guide decision-making, a combined assessment of costs and environmental impacts for DACS systems is necessary. Here we present a cost model and life cycle assessment for several combinations of off-grid DACSs, powered by photovoltaic (PV) energy and heat pumps combined with battery storages to mitigate intermittency of the PV energy source. Utilization factors of DACSs are estimated for different locations, power of PV systems and battery capacities. We find that the cost optimal layout for a DACS in Nevada (USA) with a nominal CO2 removal capacity of 100,000tCO2 per year consists of 100 MW PV and 300MWh battery. Costs are $755 and $877 for gross and net removal of 1tCO2. The cost difference is explained by a carbon removal efficiency (CRE) of 88%. Of 16 evaluated environmental impact categories mineral resource use is most problematic. We conceive a dashboard which allows to track how changes to technical parameters, such as energy consumption or adsorbent degradation, impact costs, CRE and combined environmental impacts. In an optimized scenario and including tax credits, costs for net-removal of 1tCO2 will be $216 at a CRE of 93%.
Predicting state level suicide fatalities in the united states with realtime data and machine learning
Authors: Patel Devashru , Sumner Steven A. , Bowen Daniel , Zwald Marissa , Yard Ellen , Wang Jing , Law Royal , Holland Kristin , Nguyen Theresa , Mower Gary , Chen Yushiuan , Johnson Jenna Iberg , Jespersen Megan , Mytty Elizabeth , Lee Jennifer M. , Bauer Michael , Caine Eric , De Choudhury Munmun 
Published: January 2024

AbstractDigital trace data and machine learning techniques are increasingly being adopted to predict suicide-related outcomes at the individual level; however, there is also considerable public health need for timely data about suicide trends at the population level. Although significant geographic variation in suicide rates exist by state within the United States, national systems for reporting state suicide trends typically lag by one or more years. We developed and validated a deep learning based approach to utilize real-time, state-level online (Mental Health America web-based depression screenings; Google and YouTube Search Trends), social media (Twitter), and health administrative data (National Syndromic Surveillance Program emergency department visits) to estimate weekly suicide counts in four participating states. Specifically, per state, we built a long short-term memory (LSTM) neural network model to combine signals from the real-time data sources and compared predicted values of suicide deaths from our model to observed values in the same state. Our LSTM model produced accurate estimates of state-specific suicide rates in all four states (percentage error in suicide rate of −2.768% for Utah, −2.823% for Louisiana, −3.449% for New York, and −5.323% for Colorado). Furthermore, our deep learning based approach outperformed current gold-standard baseline autoregressive models that use historical death data alone. We demonstrate an approach to incorporate signals from multiple proxy real-time data sources that can potentially provide more timely estimates of suicide trends at the state level. Timely suicide data at the state level has the potential to improve suicide prevention planning and response tailored to the needs of specific geographic communities.
Perspectives and pitfalls in preserving subterranean biodiversity through protected areas
Authors: Mammola Stefano , Altermatt Florian , Alther Roman , Amorim Isabel R. , Băncilă Raluca I. , Borges Paulo A. V. , Brad Traian , Brankovits David , Cardoso Pedro , Cerasoli Francesco , Chauveau Claire A. , Delić Teo , Di Lorenzo Tiziana , Faille Arnaud , Fišer Cene , Flot Jean-François , Gabriel Rosalina , Galassi Diana M. P. , Garzoli Laura , Griebler Christian , Konecny-Dupré Lara , Martínez Alejandro , Mori Nataša , Nanni Veronica , Ogorelec Žiga , Pallarés Susana , Salussolia Alice , Saccò Mattia , Stoch Fabio , Vaccarelli Ilaria , Zagmajster Maja , Zittra Carina , Meierhofer Melissa B. , Sánchez-Fernández David , Malard Florian 
Published: January 2024

AbstractSubterranean ecosystems (comprising terrestrial, semi-aquatic, and aquatic components) are increasingly threatened by human activities; however, the current network of surface-protected areas is inadequate to safeguard subterranean biodiversity. Establishing protected areas for subterranean ecosystems is challenging. First, there are technical obstacles in mapping three-dimensional ecosystems with uncertain boundaries. Second, the rarity and endemism of subterranean organisms, combined with a scarcity of taxonomists, delays the accumulation of essential biodiversity knowledge. Third, establishing agreements to preserve subterranean ecosystems requires collaboration among multiple actors with often competing interests. This perspective addresses the challenges of preserving subterranean biodiversity through protected areas. Even in the face of uncertainties, we suggest it is both timely and critical to assess general criteria for subterranean biodiversity protection and implement them based on precautionary principles. To this end, we examine the current status of European protected areas and discuss solutions to improve their coverage of subterranean ecosystems.
Carboxyl graphene modified PEDOT:PSS organic electrochemical transistor for in situ detection of cancer cell morphology
Authors: Song Qingyuan , Liu Hongni , Wang Weiyi , Chen Chaohui , Cao Yiping , Chen Bolei , Cai Bo , He Rongxiang 
Published: January 2024

In this study, a solution-gated organic electrochemical transistor based on PEDOT:PSS was developed to detect cancer cells in situ. The carboxyl graphene mixed in PEDOT:PSS film was used to modulate cancer cell morphology during detection.