bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Fe/Ni, Fe/Cu bimetallic nanoparticle synthesis process utilizing concentrated Camellia sinensis extract solution and activity evaluation through methylene blue removal reaction
Authors: Nguyen Hong Son , Nguyen Van Hoang , Nguyen Thi Thu Huong , Vu Ngoc Toan , Le Ngoc Hoan 
Published: May 2024

Abstract
In this study, we introduce a synthesis process of bimetallic nanoparticles (BNPs) Fe/Ni and Fe/Cu utilizing concentrated Camellia sinenis extract that was optimized with a solvent ratio of ethanol/H2O 4/1 (v/v), a metal ratio of 5/1 (w/w), a total polyphenol content (TPC) in the solution of 12.5 g.l−1, pH = 3–4, 25 °C, and the reaction time ranging from 30 min to 50 min. The structural and morphological characteristics of the resulting materials were determined using several techniques, such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive x-ray spectroscopy (EDX), x-ray diffraction (XRD), and x-ray photoelectron spectroscopy (XPS). The maximum removal efficiency of methylene blue (MB) by BNPs Fe/Ni and Fe/Cu materials was found to be 88.60% and 91.06%, respectively, at a concentration of MB = 25 mg.l−1 and 25 °C. According to the results of the kinetic modeling study, the adsorption process of MB on the two BNPs materials followed second-order kinetics, with the maximum adsorption capacities of MB on Fe/Ni and Fe/Cu BNPs being 26.94 mg.g−1and 28.00 mg.g−1, respectively.
Strained diamond for quantum sensing applications
Authors: Yang Limin , Wang Heyi , Yang Sen , Lu Yang 
Published: May 2024

Abstract
Apart from being an extraordinary optical and electronic material, diamond has also found applications in quantum mechanics especially in quantum sensing with the discovery and research development of various color centers. Elastic strain engineering (ESE), as a powerful modulation method, can tune the quantum properties and improve the performance of diamond quantum sensors. In recent years, deep ESE (DESE, when >5% elastic strain, or >σ
ideal/2 is achieved) has been realized in micro/nano-fabricated diamond and shows a great potential for tuning the quantum mechanical properties of diamond substantially. In this perspective, we briefly review the quantum properties of diamond and some of the corresponding sensing applications carried out with ESE, and look at how DESE could be applied for further tuning the quantum sensing properties of diamond with desired applications and what the critical challenges are.
Terror and Philanthropy
Authors: Finkel Stuart 
Published: May 2024

Abstract
This chapter begins with the maturation of “Red Cross” aid for political prisoners during the upsurge of revolutionary activity during 1879–81, describing how the otherwise deeply divided factions—the People’s Will and Black Repartition—worked jointly on these “philanthropic” concerns. After the March assassination of Alexander II led to harsh repression against the leadership of People’s Will, political aid became even more central to radical activities. The formalized “Red Cross of the People’s Will” (KKNV) coalesced with a network of branches across European Russia and Siberia, based in Moscow, and its Tomsk branch played a key role linking to exiles further east. In its brief existence (summer 1881 to 1882), the KKNV connected dispersed radical activists and established a sophisticated apparatus for gathering information on the status of political detainees and for disbursing funds. Its rapid downfall after initial arrests led to the uncovering of the full network and left a void already partly filled by other groups, such as the “Red Cross” of the Polish Proletariat party, which survived into the mid-1880s. But as this chapter concludes, another model had also already emerged in fall 1881: the St. Petersburg “Society for Aid to Political Exiles and Prisoners” (OPPSiZ), which claimed to be a fully nonpartisan alternative. Initially also known as the “Blue Cross,” it blossomed by drawing steadily from the student youth, so that when most of its founders were arrested in 1884, others continued its work without interruption.
Is the universal republic achievable?
Authors: Koenig-Archibugi Mathias 
Published: May 2024

Abstract
The chapter uses empirical data to assess whether a democratic world state is achievable. The first section uses machine learning and statistical simulations to identify the level of democracy that we could expect a hypothetical world state to attain, given the world’s current levels of ethnic, religious, and linguistic diversity, economic inequality, population size, and other features. The world state’s expected level of democracy is reasonably high. The remaining sections consider empirical evidence on the motivations of key actors in relation to world state formation, namely social movements, citizens, and governments. The survey of multiple sources of evidence fails to find insurmountable obstacles to the emergence of a democratic world state.
Universal republic or polycentric democracy?
Authors: Koenig-Archibugi Mathias 
Published: May 2024

Abstract
This chapter evaluates ‘polycentric democracy’ as an approach to global democratization that is an alternative to a democratic world state. A defining feature of polycentric democracy is the absence of an overarching governance framework that adjudicates between competing demands and manages the relationship between multiple policy issues. Representation of individuals by issue-area can restrict considerably the ability of people to exercise democratic control over decisions that affect their autonomy. Decisions on a specific issue are likely to have effects on other issue-areas and these policy externalities are often negative, which means that policies aimed at attaining one goal can be an obstacle in the promotion of other goals. This situation can be observed empirically in the trade-offs between the Sustainable Development Goals. Parliaments and programmatic political parties are mechanisms that address policy interdependencies within domestic political systems, and they could play a similar role in a democratic world state.
A simulation-based bias analysis to assess the impact of unmeasured confounding when designing nonrandomized database studies
Authors: Desai Rishi J , Bradley Marie C , Lee Hana , Eworuke Efe , Weberpals Janick , Wyss Richard , Schneeweiss Sebastian , Ball Robert 
Published: May 2024

Abstract
Unmeasured confounding is often raised as a source of potential bias during the design of nonrandomized studies, but quantifying such concerns is challenging. We developed a simulation-based approach to assess the potential impact of unmeasured confounding during the study design stage. The approach involved generation of hypothetical individual-level cohorts using realistic parameters, including a binary treatment (prevalence 25%), a time-to-event outcome (incidence 5%), 13 measured covariates, a binary unmeasured confounder (u1; 10%), and a binary measured “proxy” variable (p1) correlated with u1. Strengths of unmeasured confounding and correlations between u1 and p1 were varied in simulation scenarios. Treatment effects were estimated with (1) no adjustment, (2) adjustment for measured confounders (level 1), and (3) adjustment for measured confounders and their proxy (level 2). We computed absolute standardized mean differences in u1 and p1 and relative bias with each level of adjustment. Across all scenarios, level 2 adjustment led to improvement in the balance of u1, but this improvement was highly dependent on the correlation between u1 and p1. Level 2 adjustments also had lower relative bias than level 1 adjustments (in strong u1 scenarios: relative bias of 9.2%, 12.2%, and 13.5% at correlations of 0.7, 0.5, and 0.3, respectively, vs 16.4%, 15.8%, and 15.0% for level 1). An approach using simulated individual-level data is useful to explicitly convey the potential for bias due to unmeasured confounding while designing nonrandomized studies, and can be helpful in informing design choices.
This article is part of a Special Collection on Pharmacoepidemiology.
Characterization of particle exposure during tunnel excavation by tunnel boring machines
Authors: Ervik Torunn K , Leite Mimmi , Weinbruch Stephan , Nordby Karl-Christian , Ellingsen Dag G , Ulvestad Bente , Dahl Kari , Berlinger Balazs , Skaugset Nils Petter 
Published: May 2024

Abstract
Tunnel boring machines (TBMs) are used to excavate tunnels in a manner where the rock is constantly penetrated with rotating cutter heads. Fine particles of the rock minerals are thereby generated. Workers on and in the vicinity of the TBM are exposed to particulate matter (PM) consisting of bedrock minerals including α-quartz. Exposure to respirable α-quartz remains a concern because of the respiratory diseases associated with this exposure. The particle size distribution of PM and α-quartz is of special importance because of its influence on adverse health effects, monitoring and control strategies as well as accurate quantification of α-quartz concentrations. The major aim of our study was therefore to investigate the particle size distribution of airborne PM and α-quartz generated during tunnel excavation using TBMs in an area dominated by gneiss, a metamorphic type of rock. Sioutas cascade impactors were used to collect personal samples on 3 separate days. The impactor fractionates the dust in 5 size fractions, from 10 µm down to below 0.25 µm. The filters were weighted, and the α-quartz concentrations were quantified using X-ray diffraction (XRD) analysis and the NIOSH 7500 method on the 5 size fractions. Other minerals were determined using Rietveld refinement XRD analysis. The size and elemental composition of individual particles were investigated by scanning electron microscopy. The majority of PM mass was collected on the first 3 stages (aerodynamic diameter = 10 to 0.5 µm) of the Sioutas cascade impactor. No observable differences were found for the size distribution of the collected PM and α-quartz for the 3 sampling days nor the various work tasks. However, the α-quartz proportion varied for the 3 sampling days demonstrating a dependence on geology. The collected α-quartz consisted of more particles with sizes below 1 µm than the calibration material, which most likely affected the accuracy of the measured respirable α-quartz concentrations. This potential systematic error is important to keep in mind when analyzing α-quartz from occupational samples. Knowledge of the particle size distribution is also important for control measures, which should target particle sizes that efficiently capture the respirable α-quartz concentration.
Plant biomass allocation advances our understanding of plant adaptation to environmental gradients: a commentary on ‘Contrasting biomass allocations explain adaptations to cold and drought in the world’s highest-growing angiosperms’
Authors: De Battisti Davide 
Published: May 2024

This article comments on:
Jiří Doležal, Thinles Chondol, Zuzana Chlumská, Jan Altman, Kateřina Čapková, Miroslav Dvorský, Pavel Fibich, Kirill A. Korznikov1, Adam T. Ruka1, Martin Kopecký, Martin Macek, Klára Řeháková, Contrasting biomass allocations explain adaptations to cold and drought in the world’s highest-growing angiosperms, Annals of Botany, Volume 134, Issue 3, 1 September 2024, Pages 401–414 https://doi.org/10.1093/aob/mcae028
SpaNCMG: improving spatial domains identification of spatial transcriptomics using neighborhood-complementary mixed-view graph convolutional network
Authors: Si Zhihao , Li Hanshuang , Shang Wenjing , Zhao Yanan , Kong Lingjiao , Long Chunshen , Zuo Yongchun , Feng Zhenxing 
Published: May 2024

Abstract
The advancement of spatial transcriptomics (ST) technology contributes to a more profound comprehension of the spatial properties of gene expression within tissues. However, due to challenges of high dimensionality, pronounced noise and dynamic limitations in ST data, the integration of gene expression and spatial information to accurately identify spatial domains remains challenging. This paper proposes a SpaNCMG algorithm for the purpose of achieving precise spatial domain description and localization based on a neighborhood-complementary mixed-view graph convolutional network. The algorithm enables better adaptation to ST data at different resolutions by integrating the local information from KNN and the global structure from r-radius into a complementary neighborhood graph. It also introduces an attention mechanism to achieve adaptive fusion of different reconstructed expressions, and utilizes KPCA method for dimensionality reduction. The application of SpaNCMG on five datasets from four sequencing platforms demonstrates superior performance to eight existing advanced methods. Specifically, the algorithm achieved highest ARI accuracies of 0.63 and 0.52 on the datasets of the human dorsolateral prefrontal cortex and mouse somatosensory cortex, respectively. It accurately identified the spatial locations of marker genes in the mouse olfactory bulb tissue and inferred the biological functions of different regions. When handling larger datasets such as mouse embryos, the SpaNCMG not only identified the main tissue structures but also explored unlabeled domains. Overall, the good generalization ability and scalability of SpaNCMG make it an outstanding tool for understanding tissue structure and disease mechanisms. Our codes are available at https://github.com/ZhihaoSi/SpaNCMG.
Bayesian meta-analysis of penetrance for cancer risk
Authors: Ruberu Thanthirige Lakshika M , Braun Danielle , Parmigiani Giovanni , Biswas Swati 
Published: May 2024

Abstract
Multi-gene panel testing allows many cancer susceptibility genes to be tested quickly at a lower cost making such testing accessible to a broader population. Thus, more patients carrying pathogenic germline mutations in various cancer-susceptibility genes are being identified. This creates a great opportunity, as well as an urgent need, to counsel these patients about appropriate risk-reducing management strategies. Counseling hinges on accurate estimates of age-specific risks of developing various cancers associated with mutations in a specific gene, ie, penetrance estimation. We propose a meta-analysis approach based on a Bayesian hierarchical random-effects model to obtain penetrance estimates by integrating studies reporting different types of risk measures (eg, penetrance, relative risk, odds ratio) while accounting for the associated uncertainties. After estimating posterior distributions of the parameters via a Markov chain Monte Carlo algorithm, we estimate penetrance and credible intervals. We investigate the proposed method and compare with an existing approach via simulations based on studies reporting risks for two moderate-risk breast cancer susceptibility genes, ATM and PALB2. Our proposed method is far superior in terms of coverage probability of credible intervals and mean square error of estimates. Finally, we apply our method to estimate the penetrance of breast cancer among carriers of pathogenic mutations in the ATM gene.
Applications and implementation of generative artificial intelligence in cardiovascular imaging with a focus on ethical and legal considerations: what cardiovascular imagers need to know!
Authors: Marey Ahmed , Serdysnki Kevin Christopher , Killeen Benjamin D , Unberath Mathias , Umair Muhammad 
Published: May 2024

Abstract
Machine learning (ML) and deep learning (DL) have potential applications in medicine. This overview explores the applications of AI in cardiovascular imaging, focusing on echocardiography, cardiac MRI (CMR), coronary CT angiography (CCTA), and CT morphology and function. AI, particularly DL approaches like convolutional neural networks, enhances standardization in echocardiography. In CMR, undersampling techniques and DL-based reconstruction methods, such as variational neural networks, improve efficiency and accuracy. ML in CCTA aids in diagnosing coronary artery disease, assessing stenosis severity, and analyzing plaque characteristics. Automatic segmentation of cardiac structures and vessels using AI is discussed, along with its potential in congenital heart disease diagnosis and 3D printing applications. Overall, AI integration in cardiovascular imaging shows promise for enhancing diagnostic accuracy and efficiency across modalities. The growing use of Generative Adversarial Networks in cardiovascular imaging brings substantial advancements but raises ethical concerns. The “black box” problem in DL models poses challenges for interpretability crucial in clinical practice. Evaluation metrics like ROC curves, image quality, clinical relevance, diversity, and quantitative performance assess GAI models. Automation bias highlights the risk of unquestioned reliance on AI outputs, demanding careful implementation and ethical frameworks. Ethical considerations involve transparency, respect for persons, beneficence, and justice, necessitating standardized evaluation protocols. Health disparities emerge if AI training lacks diversity, impacting diagnostic accuracy. AI language models, like GPT-4, face hallucination issues, posing ethical and legal challenges in healthcare. Regulatory frameworks and ethical governance are crucial for fair and accountable AI. Ongoing research and development are vital to evolving AI ethics.
Neural mechanisms of social comparison in subthreshold depression
Authors: Du Xue , Yao Li , Sun Le , Chen Xiaoyi , Jiang Jun 
Published: May 2024

Abstract
Social comparison is a common phenomenon in our daily life, through which people get to know themselves, and plays an important role in depression. In this study, event-related potential (ERP) was used to explore the temporal course of social comparison processing in the subthreshold depression group. Electrophysiological recordings were acquired from 30 subthreshold depressed individuals and 31 healthy individuals while they conducted the adapted dot estimation task. The ERP results revealed that there was a significant difference of feedback-related negativity (FRN) in the process of social comparison. Especially only in the subthreshold depression, the FRN amplitudes of worse off than some, better off than many comparisons were larger than those of upward comparisons and downward comparisons. Our results suggested that the abnormal reward sensitivity for worse off than some, better off than many comparisons might be prodromal symptoms in the subthreshold depression.
Exploring circular economy transition pathways: a roadmap analysis of 15 Canadian local governments
Authors: Rajaonson Juste , Chembessi Chedrak 
Published: May 2024

Abstract
This paper explores how 15 Canadian local governments of various sizes and contexts are transitioning to a circular economy by analysing their roadmap currently in development. It provides qualitative insights into how physical, socioeconomic and institutional factors are influencing the content of roadmaps, along with their similarities and differences. Drawing from the literature on the geography of transitions, we show that while local physical and socioeconomic attributes typically shape the roadmaps by determining likely activities, their actual trajectory varies based on the roadmap instigators and the broader institutional contexts in which they operate. The findings suggest the importance of local governments supporting the roadmap instigators while also recognising that circular economy transition pathways can capitalise on policies and programs not only locally but beyond local boundaries.
Acute kidney injury after CAR-T cell therapy: exploring clinical patterns, management, and outcomes
Authors: Vincendeau Maud , Joseph Adrien , Thieblemont Catherine , Rabian Florence , Harel Stéphanie , Valade Sandrine , Zafrani Lara 
Published: May 2024

ABSTRACT

Background
Acute kidney injury (AKI) has been reported after CAR-T cells, but available data are limited. We sought to describe the incidence of AKI in a cohort of patients hospitalized in the intensive care unit (ICU) following CAR-T cell reinjection, identify the primary factors linked to the onset of AKI, and ascertain the key determinants associated with kidney outcomes and mortality.

Methods
We retrospectively analyzed 119 patients hospitalized in ICU after CAR-T cell therapy between 2017 and 2023. Factors associated with AKI, mortality, and kidney sequelae were identified using multivariate analyses.

Results
Of the 119 patients, 41 patients fulfilled diagnostic criteria of AKI (34%). By multivariate analysis, grade ≥3 cytokine release syndrome (CRS) [OR = 1.20 CI95% (1.01–1.43)] and elevated lactate dehydrogenase (LDH) levels at admission [OR = 1.44 CI95% (1.04–1.99)] were significantly associated with the occurrence of AKI during ICU stay. AKI KDIGO ≥2 was an independent risk factor for hospital mortality [OR = 1.50 (1.22–1.85), P &lt; 0.001]. Nine out of 12 (75%) and 6/9 (67%) patients who had experienced AKI and survived had chronic kidney disease (CKD) at 6 months and 1 year, respectively. We did not identify any specific factor associated with kidney recovery.

Conclusion
AKI may occur in ICU patients receiving CAR-T cell therapy, especially those who experience CRS and exhibit elevated LDH levels. Early recognition of AKI is of utmost importance as it substantially compromises survival in these patients. Future studies should aim to elucidate the underlying pathophysiological mechanisms of AKI in this context and pinpoint predictive factors for long-term risks of CKD.
Electrophysiology of Human iPSC-derived Vascular Smooth Muscle Cells and Cell-autonomous Consequences of Cantú Syndrome Mutations
Authors: Hanson Alex , McClenaghan Conor , Weng Kuo-Chan , Colijn Sarah , Stratman Amber N , Halabi Carmen M , Grange Dorothy K , Silva Jonathan R , Nichols Colin G 
Published: May 2024

Abstract
Cantú syndrome (CS), a multisystem disease with a complex cardiovascular phenotype, is caused by gain-of-function (GoF) variants in the Kir6.1/SUR2 subunits of ATP-sensitive potassium (KATP) channels and is characterized by low systemic vascular resistance, as well as tortuous, dilated, vessels, and decreased pulse-wave velocity. Thus, CS vascular dysfunction is multifactorial, with both hypomyotonic and hyperelastic components. To dissect whether such complexities arise cell autonomously within vascular smooth muscle cells (VSMCs) or as secondary responses to the pathophysiological milieu, we assessed electrical properties and gene expression in human induced pluripotent stem cell-derived VSMCs (hiPSC-VSMCs), differentiated from control and CS patient-derived hiPSCs, and in native mouse control and CS VSMCs. Whole-cell voltage clamp of isolated aortic and mesenteric arterial VSMCs isolated from wild-type (WT) and Kir6.1[V65M] (CS) mice revealed no clear differences in voltage-gated K+ (Kv) or Ca2+ currents. Kv and Ca2+ currents were also not different between validated hiPSC-VSMCs differentiated from control and CS patient-derived hiPSCs. While pinacidil-sensitive KATP currents in control hiPSC-VSMCs were similar to those in WT mouse VSMCs, they were considerably larger in CS hiPSC-VSMCs. Under current-clamp conditions, CS hiPSC-VSMCs were also hyperpolarized, consistent with increased basal K conductance and providing an explanation for decreased tone and decreased vascular resistance in CS. Increased compliance was observed in isolated CS mouse aortae and was associated with increased elastin mRNA expression. This was consistent with higher levels of elastin mRNA in CS hiPSC-VSMCs and suggesting that the hyperelastic component of CS vasculopathy is a cell-autonomous consequence of vascular KATP GoF. The results show that hiPSC-VSMCs reiterate expression of the same major ion currents as primary VSMCs, validating the use of these cells to study vascular disease. Results in hiPSC-VSMCs derived from CS patient cells suggest that both the hypomyotonic and hyperelastic components of CS vasculopathy are cell-autonomous phenomena driven by KATP overactivity within VSMCs .