bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements
Authors: Gill K , Smith D , Joung S , Geiger B , McKee G , Zimmerman J , Coffee R , Jalalvand A , Kolemen E 
Published: July 2024

Abstract
A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µs and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F
1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.
Optimizing data acquisition: a Bayesian approach for efficient machine learning model training
Authors: Mahani M R , Nechepurenko Igor A , Rahimof Yasmin , Wicht Andreas 
Published: July 2024

Abstract
Acquiring a substantial number of data points for training accurate machine learning (ML) models is a big challenge in scientific fields where data collection is resource-intensive. Here, we propose a novel approach for constructing a minimal yet highly informative database for training ML models in complex multi-dimensional parameter spaces. To achieve this, we mimic the underlying relation between the output and input parameters using Gaussian process regression (GPR). Using a set of known data, GPR provides predictive means and standard deviation for the unknown data. Given the predicted standard deviation by GPR, we select data points using Bayesian optimization to obtain an efficient database for training ML models. We compare the performance of ML models trained on databases obtained through this method, with databases obtained using traditional approaches. Our results demonstrate that the ML models trained on the database obtained using Bayesian optimization approach consistently outperform the other two databases, achieving high accuracy with a significantly smaller number of data points. Our work contributes to the resource-efficient collection of data in high-dimensional complex parameter spaces, to achieve high precision ML predictions.
Pathways to zero emissions in California’s heavy-duty transportation sector
Authors: Hennessy Eleanor M , Singh Madalsa , Saltzer Sarah , Azevedo Inês M L 
Published: July 2024

Abstract
California contributes 0.75% of global greenhouse gas (GHG) emissions and has a target of reaching economy-wide net zero emissions by 2045, requiring all sectors to rapidly reduce emissions. Nearly 8% of California’s GHG emissions are from the heavy-duty transportation sector. In this work, we simulate decarbonization strategies for the heavy-duty vehicle (HDV) fleet using detailed fleet turnover and air quality models to track evolution of the fleet, GHG and criteria air pollutant emissions, and resulting air quality and health impacts across sociodemographic groups. We assess the effectiveness of two types of policies: zero emission vehicle sales mandates, and accelerated retirement policies. For policies including early retirements, we estimate the cost of early retirements and the cost-effectiveness of each policy. We find even a policy mandating all HDV sales to be zero emission vehicles by 2025 would not achieve fleetwide zero emissions by 2045. For California to achieve its goal of carbon neutrality, early retirement policies are needed. We find that a combination of early retirement policies and zero emission vehicle sales mandates could reduce cumulative CO2 emissions by up to 64%. Furthermore, we find that decarbonization policies will significantly reduce air pollution-related mortality, and that Black, Latino, and low-income communities will benefit most. We find that policies targeting long-haul heavy-heavy duty trucks would have the greatest benefits and be most cost-effective.
First site-specific conjugation method for native goat IgG antibodies via glycan remodeling at the conserved Fc region
Authors: Dolan Michael E , Sadiki Amissi , Wang Leo (Lei) , Wang Yan , Barton Christopher , Oppenheim Sheldon F , Zhou Zhaohui Sunny 
Published: July 2024

Abstract
Despite their triumph in treating human diseases, antibody therapies for animals have gained momentum more slowly. However, the first approvals of animal antibodies for osteoarthritic pain in cats and dogs may herald the dawn of a new era. For example, goats are vital to economies around the world for their milk, meat, and hide products. It is therefore imperative to develop therapies to safeguard goats—with antibodies at the forefront. Goat antibodies will be crucial in the development of therapeutic antibodies, for example, as tracers to study antibody distribution in vivo, reagents to develop other therapeutic antibodies, and therapeutic agents themselves (e.g., antibody-drug conjugates). Hamstringing this effort is a still-burgeoning understanding of goat antibodies and their derivatization. Historically, goat antibody conjugates were generated through stochastic chemical modifications, producing numerous attachment sites and modification ratios, thereby deleteriously impacting antigen binding. Site-specific methods exist but often require substantial engineering and have not been demonstrated with goat antibodies. Nevertheless, we present herein a novel method to site-specifically conjugate native goat antibodies: chemo-enzymatic remodeling of the native Fc N-glycan introduces a reactive azide handle, after which click chemistry with strained alkyne partners affords homogeneous conjugates labeled only on the Fc domain. This process is robust, and resulting conjugates retain their antigen binding and specificity. To our knowledge, our report is the first for site-specific conjugation of native goat antibodies. Furthermore, our approach should be applicable to other animal antibodies—even with limited structural information—with similar success.
A semiautomated microfluidic ELISA for the detection of hemophagocytic lymphohistiocytosis biomarkers
Authors: Herskovits Adrianna Zara , Johnson William T , Oved Joseph H , Irwin Spencer , Doddi Sital , John Deronna , Ocasio Angelica , Ramanathan Lakshmi V 
Published: July 2024

Abstract

Objectives
Hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening condition characterized by a massive overactivation of the immune system. Because the clinical findings are nonspecific, the development of assays to facilitate rapid diagnosis is critical for patient care. The objectives of this study were to evaluate the performance of a microfluidic enzyme-linked immunosorbent assay (ELISA) for HLH biomarkers and investigate the impact of insourcing this testing on workflow, cost, and turnaround time in a tertiary-care cancer hospital.

Methods
Trends in order volume were evaluated for C-X-C motif chemokine ligand 9 (CXCL9) and soluble interleukin 2 receptor ɑ (sIL2R), and a microfluidic ELISA was used to measure these analytes in serum samples. Analyte values, turnaround time, and costs were compared for this assay relative to reference laboratory testing.

Results
Test ordering has increased from 187 to 1030 requests annually over the past 5 years. Insourcing these analytes on a semiautomated ELISA can decrease time to result by approximately 2 days and generate a cost savings of roughly $140,000 annually within our laboratory.

Conclusions
Using a semiautomated ELISA for sIL2R and CXCL9 may help physicians arrive at a diagnosis and monitor therapy for patients with HLH while decreasing turnaround time and costs within the clinical laboratory.
The health implications of cumulative exposure to contextual (dis)advantage: methodological and substantive advances from a unique data linkage
Authors: Xu Wei , Kamis Christina , Agnew Megan , Schultz Amy , Salas Sarah , Malecki Kristen , Engelman Michal 
Published: July 2024

Abstract
Deleterious neighborhood conditions are associated with poor health, yet the health impact of cumulative lifetime exposure to neighborhood disadvantage is understudied. Using up to 5 decades of residential histories for 4177 adult participants in the Survey of the Health of Wisconsin (SHOW) and spatiotemporally linked neighborhood conditions, we developed 4 operational approaches to characterizing cumulative neighborhood (dis)advantage over the life course. We estimated their associations with self-reported general health and compared them with estimates using neighborhood (dis)advantage at the time of study enrollment. When cumulative exposures were assessed with the most granular temporal scale (approach 4), neighborhood transportation constraints (odds ratio [OR] = 1.21; 95% CI, 1.08-1.36), residential turnover (OR = 1.20; 95% CI, 1.07-1.34), education deficit (OR = 1.17; 95% CI, 1.04-1.32), racial segregation (OR = 1.20; 95% CI, 1.04-1.38), and median household income (OR = 0.85; 95% CI, 0.75-0.97) were significantly associated with risk of fair or poor health. For composite neighborhood disadvantage, cumulative exposures had a stronger association (OR = 1.05; 95% CI, 1.02-1.08) than the cross-sectional exposure (OR = 1.03; 95% CI, 1.01-1.06). Single-point-in-time neighborhood measures underestimate the relationship between neighborhood and health, underscoring the importance of a life-course approach to cumulative exposure measurement.
Caregiver burden and risk of epithelial ovarian cancer in the Nurses’ Health Studies
Authors: Barnard Mollie E , Poole Elizabeth M , Huang Tianyi , Sood Anil K , Kubzansky Laura D , Tworoger Shelley S 
Published: July 2024

Abstract
Psychosocial stress may increase ovarian cancer risk and accelerate disease progression. We examined the association between caregiver burden, a common stressor, and risk of epithelial ovarian cancer. We prospectively followed 67 724 women in the Nurses’ Health Study (1992-2012) and 70 720 women in the Nurses’ Health Study II (2001-2009) who answered questions on informal caregiving (ie, caregiving outside of work). Women who reported no informal caregiving were considered noncaregivers, while, among women who provided care outside of work, caregiver burden was categorized by time spent caregiving and perceived stress from caregiving. For the 34% of women who provided informal care for ≥15 hours per week, 42% described caregiving as moderately to extremely stressful. Pooled multivariate analyses indicated no difference in ovarian cancer risk for women providing ≥15 hours of care per week compared to noncaregivers (hazard ratio [HR] = 0.96; 95% confidence interval [CI], 0.79-1.18), and no association was evident for women who reported moderate or extreme stress from caregiving compared to noncaregivers (HR = 0.96; 95% CI, 0.75-1.22). Together with prior work evaluating job strain and ovarian cancer risk, our findings suggest that, when evaluating a stressor’s role in cancer risk, it is critical to consider how the stressor contributes to the overall experience of distress.
This article is part of a Special Collection on Gynecological Cancer.
Safe and Effective Restoration of Jawline Definition With Hyaluronic Acid Injectable Gel VYC-25L: Results From a Randomized Controlled Study
Authors: Rivkin Alexander , Green Jeremy B , Bruce Suzanne , Cox Sue Ellen , Hevia Oscar , Chawla Smita , Sartor Marta 
Published: July 2024

Abstract

Background
A well-defined jawline improves overall facial aesthetics, motivating patients to seek jawline augmentation.

Objectives
In this study we evaluated the safety and effectiveness of the hyaluronic acid injectable gel VYC-25L for restoring jawline definition.

Methods
In a US multicenter, evaluator-blinded study adults with grade 2 (moderate) or 3 (severe) Allergan Loss of Jawline Definition Scale (ALJDS) scores were randomized. Participants were randomized to the VYC-25L treatment group or control group at study onset, with 12-month follow-up. The control group had the option to receive treatment after 6 months (primary endpoint completion). Effectiveness measures included Month 6 ALJDS responders rate (proportion of participants with ≥1-grade improvement from baseline on both sides), FACE-Q Satisfaction With Lower Face and Jawline scores, and Global Aesthetic Improvement Scale (GAIS) responders (improved/much improved) as assessed by the investigator and participants. Injection site responses (ISRs) and adverse events (AEs) were monitored.

Results
At Month 6, ALJDS responder rates were 69.0% vs 38.0% in the VYC-25L treatment (n = 157) and control (n = 49) groups, respectively (P = .0001). In the VYC-25L treatment group, FACE-Q scores improved by a mean of 45.9 points from baseline at Month 6 (P &lt; .0001). Furthermore, 88.4% and 89.0% of participants in the VYC-25L treatment group were GAIS responders at Month 6 by participant and investigator assessment, respectively. Most ISRs were mild or moderate and resolved within 2 weeks. Most treatment-related AEs were mild and resolved within 1 week.

Conclusions
VYC-25L safely and effectively restores jawline definition through 1 year.

Level of Evidence: 1
EGPDI: identifying protein–DNA binding sites based on multi-view graph embedding fusion
Authors: Zheng Mengxin , Sun Guicong , Li Xueping , Fan Yongxian 
Published: July 2024

Abstract
Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and designing novel drugs. In recent years, several computational methods have been proposed as alternatives to time-consuming and expensive traditional experiments. However, accurately predicting protein-DNA binding sites still remains a challenge. Existing computational methods often rely on handcrafted features and a single-model architecture, leaving room for improvement. We propose a novel computational method, called EGPDI, based on multi-view graph embedding fusion. This approach involves the integration of Equivariant Graph Neural Networks (EGNN) and Graph Convolutional Networks II (GCNII), independently configured to profoundly mine the global and local node embedding representations. An advanced gated multi-head attention mechanism is subsequently employed to capture the attention weights of the dual embedding representations, thereby facilitating the integration of node features. Besides, extra node features from protein language models are introduced to provide more structural information. To our knowledge, this is the first time that multi-view graph embedding fusion has been applied to the task of protein–DNA binding site prediction. The results of five-fold cross-validation and independent testing demonstrate that EGPDI outperforms state-of-the-art methods. Further comparative experiments and case studies also verify the superiority and generalization ability of EGPDI.
Gba1 E326K renders motor and non-motor symptoms with pathological α-synuclein, tau and glial activation
Authors: Kweon Sin Ho , Ryu Hye Guk , Kwon Seung-Hwan , Park Hyeonwoo , Lee Saebom , Kim Nam-Shik , Ma Shi-Xun , Jee Hee-Jung , Kim Sangjune , Ko Han Seok 
Published: July 2024

Abstract
Mutations in the GBA1 gene are common genetic risk factors for Parkinson’s disease, disrupting enzymatic activity and causing lysosomal dysfunction, leading to elevated α-synuclein levels. Although the role of GBA1 in synucleinopathy is well established, recent research underscores neuroinflammation as a significant pathogenic mechanism in GBA1 deficiency.
This study investigates neuroinflammation in Gba1 E326K knock-in mice, a model associated with increased risk of Parkinson’s disease and dementia. At 9 and 24 months, we assessed GBA1 protein and activity, α-synuclein pathology, neurodegeneration, motor deficits and gliosis in the ventral midbrain and hippocampus using immunohistochemistry, western blot and glucocerebrosidase assays. Additionally, primary microglia from wild-type and Gba1E326K/E326K mice were treated with α-synuclein preformed fibrils to study microglia activation, pro-inflammatory cytokines, reactive astrocyte formation and neuronal death through quantitative PCR, western blot and immunocytochemistry analyses. We also evaluated the effects of gut inoculation of α-synuclein preformed fibrils in Gba1 E326K mice at 7 months and striatal inoculation at 10 months after injection, assessing motor/non-motor symptoms, α-synuclein pathology, neuroinflammation, gliosis and neurodegeneration via behavioural tests, immunohistochemistry and western blot assays.
At 24 months, Gba1 E326K knock-in mice showed reduced glucocerebrosidase enzymatic activity and glucosylceramide build-up in the ventral midbrain and hippocampus. Increased pro-inflammatory cytokines and reactive astrocytes were observed in microglia and astrocytes from Gba1 E326K mice treated with pathological α-synuclein preformed fibrils. Gut inoculation of α-synuclein preformed fibrils increased Lewy body accumulation in the hippocampal dentate gyrus, with heightened microglia and astrocyte activation and worsened non-motor symptoms. Intrastriatal injection of α-synuclein preformed fibrils induced motor deficits, reactive glial protein accumulation and tauopathy in the prefrontal cortex and hippocampus of Gba1 E326K mice.
GBA1 deficiency attributable to the Gba1 E326K mutation exacerbates neuroinflammation and promotes pathogenic α-synuclein transmission, intensifying disease pathology in Parkinson’s disease models. This study enhances our understanding of how the Gba1 E326K mutation contributes to neuroinflammation and the spread of pathogenic α-synuclein in the brain, suggesting new therapeutic strategies for Parkinson’s disease and related synucleinopathies.
Excitation/Inhibition balance relates to cognitive function and gene expression in temporal lobe epilepsy: a high density EEG assessment with aperiodic exponent
Authors: Duma Gian Marco , Cuozzo Simone , Wilson Luc , Danieli Alberto , Bonanni Paolo , Pellegrino Giovanni 
Published: July 2024

Abstract
Patients with epilepsy are characterized by a dysregulation of excitation/inhibition balance (E/I). The assessment of E/I may inform clinicians during the diagnosis and therapy management, even though it is rarely performed. An accessible measure of the E/I of the brain represents a clinically relevant feature. Here, we exploited the exponent of the aperiodic component of the power spectrum of the electroencephalography (EEG) signal, as a non-invasive and cost-effective proxy of the E/I balance. We recorded resting-state activity with high-density EEG from 67 patients with temporal lobe epilepsy and 35 controls. We extracted the exponent of the aperiodic fit of the power spectrum from source-reconstructed EEG and tested differences between patients with epilepsy and controls. Spearman’s correlation was performed between the exponent and clinical variables (age of onset, epilepsy duration and neuropsychology) and cortical expression of epilepsy-related genes derived from the Allen Human Brain Atlas. Patients with temporal lobe epilepsy showed a significantly larger exponent, corresponding to inhibition-directed E/I balance, in bilateral frontal and temporal regions. Lower E/I in the left entorhinal and bilateral dorsolateral prefrontal cortices corresponded to a lower performance of short-term verbal memory. Limited to patients with temporal lobe epilepsy, we detected a significant correlation between the exponent and the cortical expression of GABRA1, GRIN2A, GABRD, GABRG2, KCNA2 and PDYN genes. EEG aperiodic exponent maps the E/I balance non-invasively in patients with epilepsy and reveals a close relationship between altered E/I patterns, cognition and genetics.
The neutrophil extracellular traps in neurological diseases: an update
Authors: Yu Xiaoping , Chen Zhaoyan , Bao Wei , Jiang Yaqing , Ruan Fei , Wu Di , Le Kai 
Published: July 2024

Summary
Neutrophil extracellular traps (NETs) released by neutrophils are web-like DNA structures adhered to granulin proteins with bactericidal activity and can be an important mechanism for preventing pathogen dissemination or eliminating microorganisms. However, they also play important roles in diseases of other systems, such as the central nervous system. We tracked the latest advances and performed a review based on published original and review articles related to NETs and neurological diseases. Generally, neutrophils barely penetrate the blood–brain barrier into the brain parenchyma, but when pathological changes such as infection, trauma, or neurodegeneration occur, neutrophils rapidly infiltrate the central nervous system to exert their defensive effects. However, neutrophils may adversely affect the host when they uncontrollably release NETs upon persistent neuroinflammation. This review focused on recent advances in understanding the mechanisms and effects of NETs release in neurological diseases, and we also discuss the role of molecules that regulate NETs release in anticipation of clinical applications in neurological diseases.