bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long‐term taurine supplementation regulates brain mitochondrial dynamics in mice
Authors: Rezaei Heresh , Wang Hong‐Wei , Tian Weishun , Zhao Jing , Najibi Asma , Retana‐Márquez Socorro , Rafiei Elahe , Rowhanirad Ayeh , Sabouri Samira , Kiafar Mohammadreza , Fazlinezhad Rahil , Niknahad Amir Mohammad , Evazzadeh Fatemeh , Anousheh Seyedeh Tayebeh , Ommati Mohammad Mehdi , Niknahad Hossein , Heidari Reza 
Published: November 2024

AbstractBackgroundTaurine (TAU) is the most abundant non‐protein amino acid in the central nervous system (CNS). However, the molecular mechanism of TAU in the CNS is still poorly understood. Meanwhile, disruption in mitochondrial dynamics is evident in CNS disorders. This study aimed to investigate the effect of TAU on mitochondrial dynamics.MethodsTAU (0.25, 0.5 and 1% in drinking water) was administered to young mice for six months. Several memory/cognition parameters and indices of anxiety/depression were assessed. Meanwhile, various mitochondrial indices and the expression/activity of genes involved in mitochondrial biogenesis and dynamics (Akt, CREB, NRF1, TFAM, PGC‐1α, Mfn1, Mfn2, UCP2, PINK1, OPA1, Drp1 and Fis1) were examined.ResultsTAU significantly enhanced memory performance, suppressed anxiety and depression‐like behaviour, increased mitochondrial biogenesis/dynamics and improved mitochondrial indices. It should be mentioned that there was no significant difference between different concentrations of TAU in changing most brain mitochondrial dynamic biomarkers in the current study.ConclusionsThese findings offer more insights into the molecular mechanism for TAU's action in the CNS. However, there is a need for further research to confirm these effects in humans. Overall, this study suggests the potential application of TAU in various neurological disorders and the need for clinical studies on the effects of this amino acid in the brain.
Myositis‐specific/associated autoantibodies as diagnostic keys and disease drivers
Authors: Yamashita Satoshi 
Published: November 2024

AbstractBackgroundMyositis‐specific autoantibodies (MSAs) and myositis‐associated autoantibodies (MAAs) have emerged as crucial biomarkers in idiopathic inflammatory myopathies (IIMs).MethodsThis review synthesizes recent research on MSAs and MAAs in various IIM subtypes.ResultsSpecific autoantibodies correlate with distinct clinical manifestations and pathological features. For example, anti‐MDA5 antibodies are linked to rapidly progressive interstitial lung disease, while anti‐TIF1‐γ antibodies are associated with increased malignancy risk in adult dermatomyositis. Animal models have demonstrated the pathogenic potential of certain antibodies, such as anti‐TIF1‐γ, anti‐SRP, and anti‐HMGCR, in inducing experimental myositis.ConclusionsUnderstanding the roles of MSAs and MAAs is crucial for elucidating disease mechanisms, developing targeted therapies, and improving patient outcomes. Further research is needed to fully characterize their functional implications and explore their potential as biomarkers for disease activity, prognosis, and treatment response.
Assessing disturbances in surviving primary forests of Europe
Authors: Barredo José I. , Marí Rivero Inés , Janoušková Klára 
Published: November 2024

AbstractPrimary forests are of paramount importance for biodiversity conservation and the provision of ecosystem services. In Europe, these forests are scarce and threatened by human activities. However, a comprehensive assessment of the magnitude of disturbances in these forests is lacking, due in part to their incomplete mapping. We sought to provide a systematic assessment of disturbances in primary forests in Europe based on remotely sensed imagery from 1986 to 2020. We assessed the total area disturbed, rate of area disturbed, and disturbance severity, at the country, biogeographical, and continental level. Maps of potential primary forests were used to mitigate gaps in maps of documented primary forests. We found a widespread and significant increase in primary forest disturbance rates across Europe and heightened disturbance severity in many biogeographical regions. These findings are consistent with current evidence and associate the ongoing decline of primary forests in Europe with human activity in many jurisdictions. Considering the limited extent of primary forests in Europe and the high risk of their further loss, urgent and decisive measures are imperative to ensure the strict protection of remnants of these invaluable forests. This includes the establishment of protected areas around primary forests, expansion of old‐growth zones around small primary forest fragments, and rewilding efforts.
AgriFusion: A Low‐Carbon Sustainable Computing Approach for Precision Agriculture Through Probabilistic Ensemble Crop Recommendation
Authors: Mahesh T. R. , Thakur Arastu , Velmurugan A. K. , Khan Surbhi Bhatia , Gadekallu Thippa Reddy , Alzahrani Saeed , Alojail Mohammed 
Published: November 2024

ABSTRACTOptimizing crop production is essential for sustainable agriculture and food security. This study presents the AgriFusion Model, an advanced ensemble‐based machine learning framework designed to enhance precision agriculture by offering highly accurate and low‐carbon crop recommendations. By integrating Random Forest, Gradient Boosting, and LightGBM, the model combines their strengths to boost predictive accuracy, robustness, and energy efficiency. Trained on a comprehensive dataset of 2200 instances covering key parameters like nitrogen, phosphorus, potassium, temperature, humidity, pH, rainfall, and crop type, the model underwent rigorous preprocessing for data integrity. The RandomizedSearchCV method was employed to do hyperparameter tuning, namely improving the number of trees in the Random Forest algorithm and the learning rates in the Gradient Boosting algorithm. This ensemble approach achieves a remarkable accuracy rate of 99.48%, optimizes computer resources, lowers carbon footprint, and responds efficiently to a variety of agricultural situations. The model's performance is confirmed using metrics including cross‐validation, accuracy, precision, recall, and F1 score. This demonstrates how the model might improve agricultural decision‐making, make the most use of available resources, and promote ecologically responsible farming practices.
SDKT: Similar Domain Knowledge Transfer for Multivariate Time Series Classification Tasks
Authors: Wen Jiaye , Zhou Wenan 
Published: November 2024

ABSTRACTMultivariate time series data classification has a wide range of applications in reality. With rapid development of deep learning, convolutional networks are widely used in this task and have achieved the current best performance. However, due to high difficulty and cost of collecting this type of data, labeled data is still scarce. In some tasks, the model shows overfitting, resulting in relatively poor classification performance. In order to improve the classification performance under such situation, we proposed a novel classification method based on transfer learning—similar domain knowledge transfer (call SDKT for short). Firstly, we designed a multivariate time series domain distance calculation method (call MTSDDC for short), which helped selecting the source domain that is most similar to target domain; Secondly, we used ResNet as a pre‐trained classifier, transferred the parameters of the similar domain network to the target domain network and continue to fine‐tune the parameters. To verify our method, we conducted experiments on several public datasets. Our study has also shown that the transfer effect from the source domain to the target domain is highly negatively correlated with the distance between them, with an average Pearson coefficient of −0.78. For the transfer of most similar source domain, compared to the ResNet model without transfer and the current best model, the average accuracy improvements on the datasets we used are 4.01% and 1.46% respectively.
GABAergic signalling in the suprachiasmatic nucleus is required for coherent circadian rhythmicity
Authors: Klett Nathan , Gompf Heinrich S. , Allen Charles N. , Cravetchi Olga , Hablitz Lauren M. , Gunesch Ali N. , Irwin Robert P. , Todd William D. , Saper Clifford B. , Fuller Patrick M. 
Published: November 2024

AbstractThe suprachiasmatic nucleus is the circadian pacemaker of the mammalian brain. Suprachiasmatic nucleus neurons display synchronization of their firing frequency on a circadian timescale, which is required for the pacemaker function of the suprachiasmatic nucleus. However, the mechanisms by which suprachiasmatic nucleus neurons remain synchronized in vivo are poorly understood, although synaptic communication is considered indispensable. Suprachiasmatic nucleus neurons contain the neurotransmitter GABA and express GABA receptors. This has inspired the hypothesis that GABA signalling may play a central role in network synchronization, although this remains untested in vivo. Here, using local genetic deletion, we show that disruption of GABA synaptic transmission within the suprachiasmatic nucleus of adult mice results in the eventual deterioration of physiological and behavioural rhythmicity in vivo and concomitant cellular desynchrony in vitro. These findings suggest that intercellular GABA signalling is essential for behavioural rhythmicity and cellular synchrony of the suprachiasmatic nucleus neural network.
A preventive intervention promoting toddlers' self‐regulation improves parental resilience in the future
Authors: Park Ye Rang , Nix Robert L. , Francis Lori A. , Gill Sukhdeep , Feinberg Mark E. , Hostetler Michelle L. , Stifter Cynthia A. 
Published: November 2024

AbstractObjectiveThe current study tested whether participating in a family‐focused preventive intervention designed to promote toddlers' self‐regulation improves parental resilience among families living in poverty.BackgroundFamily‐focused preventive interventions can help strengthen family functioning, but it is unclear how parents apply what they have learned to new child‐rearing challenges.MethodTwo hundred and forty‐two families with toddlers (37% White, 25% Black, 19% Latino, 17% multiracial, 2% Asian; median income = $1,555 per month) enrolled in Early Head Start were randomly assigned to the Recipe 4 Success preventive intervention or usual practice home visits. Parents reported on parental resilience, which included aspects of social problem‐solving, personal control, engagement coping, and self‐regulation, assessed 18 months after the end of the intervention.ResultsA structural equations model revealed that parents in the intervention group, compared to parents in the control group, reported greater parental resilience and used more competent strategies to address child‐rearing challenges (β = .33, p = .03). Subgroup analyses indicated that the intervention effects were similar across families with different demographic characteristics.ConclusionThis study demonstrates how a family‐focused preventive intervention designed to improve parents' skills in one specific domain at one point in their toddlers' development can have positive ripple effects, enhancing parental resilience in the future.ImplicationsThese findings reinforce the potential widespread value of providing rigorous, evidence‐based family‐focused preventive interventions during early childhood.
LAST BUT NOT LEAST: LAGGARD FIRMS, TECHNOLOGY DIFFUSION, AND ITS STRUCTURAL AND POLICY DETERMINANTS
Authors: Berlingieri Giuseppe , Calligaris Sara , Criscuolo Chiara , Verlhac Rudy 
Published: November 2024

AbstractUsing a unique microaggregated data set on firm‐level productivity in 13 countries from 1995 to 2014, this article provides new evidence on technology‐ and knowledge‐diffusion barriers for laggard firms. We show that, although the least productive firms benefit from a catch‐up effect, their speed of catchup is lower in digital‐ and skill‐intensive industries. This is especially true in countries with high skill mismatch, high financing frictions, and low absorptive capacity. These barriers to diffusion, combined with the rising importance of tacit knowledge and intangibles, could help explain the productivity growth slowdown observed in the last decades.
Photoplastic effect in II–VI semiconductors: The role of hole redistribution in dislocation glide
Authors: Shen Yidi , Li Mingqiang , Luo Kun , Zou Yu , An Qi 
Published: November 2024

AbstractPhotoplasticity in semiconductors, characterized by the modification of plastic deformation under light, has long been recognized but its underlying mechanisms remain elusive. Here, we integrated quantum mechanics (QM) simulations with nanoindentation experiments to investigate the impact of light‐induced electron‐hole pairs on the plastic deformation in two typical II–IV semiconductors: ZnS and CdTe. For ZnS, the QM simulations indicate an increase in the energy for breaking the Zn‐S bond within the S‐core dislocation in its glide process, due to the redistribution of excited holes. This enhancement in bond energy elevates the energy barrier for dislocation glide, eventually saturating at high electron‐hole concentrations and leading to reduced dislocation mobility in ZnS under light. These findings align well with the nanoindentation experiments, which demonstrate an increase followed by a plateau in the hardness of ZnS under light. In contrast, CdTe exhibits a reduced energy barrier for the glide of Te‐core dislocation due to the lack of hole redistribution, likely causing an enhanced dislocation mobility.
Outstanding pure green upconversion luminescence in LaZrTa3O11:Er3+/Yb3+ phosphors prepared by molten salt synthesis with B2O3 flux
Authors: Wang Xuekai , Cao Yongze , Yan Xianglan , Li Guojian , Li Xiangping , Zhang Jinshu , Chen Baojiu 
Published: November 2024

AbstractHexagonal Er3+/Yb3+ co‐doped LaZrTa3O11 (LZTO) phosphor was prepared by molten salt synthesis with B2O3 flux. Holding temperature, holding time, solute and solvent ratio were regulated. The green upconversion luminescence (UCL) integral intensity of the optimal sample can reach 29.2% of β‐NaYF4:Er3+/Yb3+ under 980 nm laser excitation. This outstanding pure green UCL is due to the low phonon energy, Er3+/Yb3+ monolayer (2D) distribution, asymmetry of Er3+/Yb3+ doped lattice sites, and low oxygen vacancy. The maximum relative temperature sensitivity attains 0.01221 K−1 at 303 K by employing luminescence intensity ratio (LIR) technique. LZTO:Er3+/Yb3+ phosphor can be used in temperature sensing.
Electrocardiographic Characteristics of Brugada Syndrome Type I During Exercise Stress Test
Authors: Miná Camila Pinto Cavalcante , Lima Neiberg de Alcantara , de Andrade Antonio Thomaz , Pérez‐Riera Andrés Ricardo , Rocha Eduardo Arrais 
Published: November 2024

ABSTRACTIntroductionBrugada syndrome (BS) is a genetic channelopathy characterized by an increased risk of sudden cardiac death (SCD) in the absence of structural heart disease. Prognostic stratification is necessary to determine which patients are candidates for implantable cardioverter defibrillator (ICD). The present study aims to evaluate EKG changes during exercise stress tests in patients with BS and to identify any poor prognosis variables.MethodsThis was an observational, case‐control study. Three comparison groups were created: patients with Type 1 BS with or without prior arrhythmic events (BE and BNoE subgroups) and age‐ and sex‐matched healthy individuals. Patients underwent EST and electrocardiographic variables were analyzed.ResultsThe study recruited 36 patients with type 1 BS, 12 with prior Event (BE) and 24 without (BNoE). Patients in the BE group, in all postexercise recordings, had lower heart rates, notably in the first minute. A significant difference was also observed in the HR drop in the recovery phase, with a greater drop in relation to maximum HR in the first minute in the group of patients who had events.ConclusionBS patients with prior events had a lower capacity to increase heart rate at peak effort and a greater proportional drop in the recovery phase. No relationship was observed between the occurrence of arrhythmic events and ST‐segment elevation during the exercise test.
Five Criteria Predict Induction and Ablation of Supraventricular Tachycardia
Authors: McGarry Thomas J. , Jared Bunch T. , Ranjan Ravi , Stoddard Gregory J. 
Published: November 2024

ABSTRACTIntroductionCurrent guidelines recommend electrophysiological study (EPS) and ablation for primary treatment of supraventricular tachycardia (SVT), but there is little information to guide patient selection for the procedure. The purpose of this study was to identify preoperative features that would predict whether patients with signs or symptoms of tachycardia were likely to have SVT induced and ablated at EPS.MethodsWe performed a retrospective chart review of 1089 patients referred for EPS and ablation of SVT at 2 high volume centers. The population consisted of a derivation cohort of 810 patients and a validation cohort of 279 patients. We evaluated various clinical, EKG, and monitor features to determine which ones correlated with SVT induction or ablation.ResultsFive preoperative findings predicted a high probability that SVT would be induced and ablated at EPS:

A characteristic EKG recording of SVT.
Termination of SVT with adenosine.
Termination of SVT or symptoms with vagal maneuvers.
An episode of SVT lasting ≥ 30 s on a monitor recording.
Pre‐excitation on the baseline EKG.Patients exhibiting at least one of these features had a high probability of SVT induction and ablation, while those exhibiting none had a low probability (Induction, 76% vs. 19%, RR = 3.96 (2.76–5.69), p < .001; Ablation, 88% versus 26%, RR = 3.32 (2.48–4.46), p < .001). A point‐based score was derived and validated that can be used to estimate the probability of induction and ablation for individual patients.ConclusionSimple criteria classify patients as having a high or low probability of SVT induction and ablation at EPS. They can be used as a guide for clinical decision making when considering invasive testing for patients with symptoms of tachycardia.
CIRCEE, the CIRCular Energy Economy model: Bridging the gap between economic and industrial ecology concepts
Authors: Corbier Darius , Pettifor Hazel , Agnew Maureen , Drouet Laurent 
Published: November 2024

AbstractTransitioning to a circular economy (CE) can contribute to the achievement of long‐term climate targets. A comprehensive evaluation of CE strategies requires a macro‐level approach that integrates environmental, social, and economic goals. Policy support, behavioral changes, innovation, and new business models play key roles in this transition. Additionally, understanding the potential synergies, benefits, and trade‐offs associated with these strategies is essential for their effective implementation. This paper proposes a novel approach, using macroeconomic modeling, industrial ecology, and behavioral concepts to evaluate the impacts of CE strategies on socioeconomic and climate systems. As an application, the paper investigates the environmental and economic effects in Japan of increasing the extended producer responsibility (EPR) fee on energy‐using durable goods. We show that increasing the fee makes households substitute conventional goods for circular services. Also, while increasing EPR fees for energy‐using durable goods may decrease the materials needed to produce and operate these goods, the overall impact on sustainability goals is rather low.
Image‐based prediction of residential building attributes with deep learning
Authors: Huang Weimin , Olson Alexander W. , Khalil Elias B. , Saxe Shoshanna 
Published: November 2024

AbstractThis study estimates building attributes—floor area and age—using image‐based machine learning. Building age and floor area are key inputs to the studies of urban metabolism, material stocks and flows, and embodied greenhouse gases (GHGs) in the built environment. However, these data are challenging to generate and maintain using traditional survey methods, their availability is uneven and often, even when available, very uncertain. Improving our understanding and future management of built environment resource flows and associated environmental impacts requires more complete access to building age and floor area data. The study formulates area prediction as a regression problem and age prediction as a classification problem over six historical periods, achieving a mean absolute percentage error of 19.42% for area prediction and an accuracy of 70.27% for age prediction in Toronto. These results are obtained using an EfficientNetV2 module for feature extraction from Google Street View images, followed by fully connected layers for estimating the two building attributes. The performance of the Toronto‐trained model in five other Canadian cities is also reported, highlighting the model's varying effectiveness in different urban contexts and the benefit of local training. Our findings demonstrate the feasibility of using machine learning for building attribute estimation from street‐view images, offering a basis for future automated large‐scale material flow and stock analysis.
Diagnostic electron microscopy in human infectious diseases – Methods and applications
Authors: Laue Michael 
Published: November 2024

AbstractDiagnostic electron microscopy (EM) is indispensable in all cases of infectious diseases which deserve or profit from the detection of the entire pathogen (i.e. the infectious unit). The focus of its application has shifted during the last decades from routine diagnostics to diagnostics of special cases, emergencies and the investigation of disease pathogenesis. While the focus of application has changed, the methods remain more or less the same. However, since the number of cases for diagnostic EM has declined as the number of laboratories that are able to perform such investigations, the preservation of the present knowledge is important. The aim of this article is to provide a review of the methods and strategies which are useful for diagnostic EM related to infectious diseases in our days. It also addresses weaknesses as well as useful variants or extensions of established methods. The main techniques, negative staining and thin section EM, are described in detail with links to suitable protocols and more recent improvements, such as thin section EM of small volume suspensions. Sample collection, transport and conservation/inactivation are discussed. Strategies of sample examination and requirements for a proper recognition of structures are outlined. Finally, some examples for the actual application of diagnostic EM related to infectious diseases are presented. The outlook section will discuss recent trends in microscopy, such as automated object recognition by machine learning, regarding their potential in supporting diagnostic EM.
Disseminated Lichtheimia sp. Infection in a Buff‐Headed Capuchin (Sapajus xanthosternos)
Authors: Rocha Fernanda C. , Pereira Asheley Henrique B. , Leal Davi S. , Moreira Silvia B. , Pissinatti Alcides , Maruyama Fernanda H. , Nakazato Luciano , Dutra Valéria , Ubiali Daniel G. 
Published: November 2024

ABSTRACTA clinicopathologic picture caused by Lichtheimia sp. in a 33‐year‐old male Sapajus xanthosternos kept in a conservationist center is described. Acute apathy, vomiting, fever, and polydipsia were associated with pneumonia, enteritis, and gastritis presenting fibrinoid vasculitis containing hyphae. The fungi were demonstrated molecularly, highlighting the spontaneous disease in primates.