bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilities Develop New Lines of Business to Deliver Clean Energy Customer Solutions
Authors: McLean‐Conner Penni
Published: March 2023

Utility work has historically been centered around customers. For more than 100 years, utilities have invested in infrastructure and energy solutions that enable consumers to power their lives and businesses. Our energy systems, natural gas and electric, have grown to support economic growth and the increased demand and reliability customers expect to power their lives.
Bolstering the Battery Storage Supply Chain for Battery Electric Vehicles and Grid Storage
Authors: Vangala Shreyas , Casagranda Blake
Published: March 2023

Reducing worldwide greenhouse gas (GHG) emissions within the power and transportation sectors is required for mitigating the worst impacts of climate change. According to the United Nations Intergovernmental Panel on Climate Change (IPCC), reducing annual GHG emissions by 45 percent by 2030, compared to 2010 levels, will limit net global temperature increases to 1.5°C. Reduction in carbon‐based pollutants, largely in the forms of carbon dioxide (CO2) and methane (CH4), are the principal aims of GHG reduction efforts constituting the bulk of global “decarbonization” efforts. Upon taking office, President Biden's Administration (Administration) sought to cut US economy‐wide GHG emissions by between 50–52 percent by 2030 as compared to 2005 levels. As of 2022, the United States has consistently been the second largest contributor of GHG emissions behind China since 2006, with these two nations combined contributing a total of 52 percent of global GHG emissions according to the US Environmental Protection Agency (EPA). Battery storage has emerged as a critical technology coupled with renewable and distributed energy resources (DERs) in efforts to decarbonize both sectors.
Water pollution from pharmaceutical use in livestock farming: Assessing differences between livestock types and production systems
Authors: Wöhler Lara , Hogeboom Rick J. , Berger Markus , Krol Maarten S.
Published: March 2023

Livestock production is a major source of pharmaceutical emissions to the environment. The current scientific discourse focuses on measuring and modeling emissions as well as assessing their risks. Although several studies corroborate the severity of pharmaceutical pollution resulting from livestock farming, differences in pollution between livestock types and production systems are largely unknown. In fact, there is no comprehensive analysis of factors influencing pharmaceutical use—the emission's source—in the diverse production systems. To address these knowledge gaps, we developed a framework to investigate pharmaceutical pollution from different livestock production systems and applied it in a first pilot assessment to compare pollution from organic and conventional cattle, pig, and chicken production systems on selected indicator substances, covering antibiotics, antiparasitics, hormones, and nonsteroidal anti-inflammatory drugs (NSAIDs). Given the lack of statistics, for this article we retrieved novel qualitative information about influential factors for pharmaceutical use and pollution from expert interviews and combined this with quantitative data on, among other factors, the environmental behavior of specific substances from the literature. Our analysis reveals that factors across a pharmaceutical's entire life cycle influence pollution. However, not all factors are livestock type or production-system dependent. The pilot assessment furthermore reveals that differences in pollution potential between conventional and organic production exist, but for antibiotics, NSAIDs, and partially for antiparasitics, some factors lead to greater pollution potential in conventional systems, and others in organic systems. For hormones, we identified a comparatively greater pollution potential from conventional systems. Among the indicator substances, the assessment over the entire pharmaceutical life cycle illustrates that flubendazole in broiler production has the greatest per unit impact. The framework and its application in the pilot assessment generated insights useful to identifying which substances, livestock types, production systems, or the combination thereof have great or little pollution potential, informing more sustainable agricultural management practices. Integr Environ Assess Manag 2023;19:1495–1509. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Data‐driven structural descriptor for predicting platinum‐based alloys as oxygen reduction electrocatalysts
Authors: Zhang Xue , Wang Zhuo , Lawan Adam Mukhtar , Wang Jiahong , Hsieh Chang‐Yu , Duan Chenru , Pang Cheng Heng , Chu Paul. K. , Yu Xue‐Feng , Zhao Haitao
Published: March 2023

Owing to increasing global demand for carbon neutral and fossil‐free energy systems, extensive research is being conducted on efficient and inexpensive electrocatalysts for catalyzing the kinetically sluggish oxygen reduction reaction (ORR) at the cathode of fuel cells. Platinum (Pt)‐based alloys are considered promising candidates for replacing expensive Pt catalysts. However, the current screening process of Pt‐based alloys is time‐consuming and labor‐intensive, and the descriptor for predicting the activity of Pt‐based catalysts is generally inaccurate. This study proposed a strategy by combining high‐throughput first‐principles calculations and machine learning to explore the descriptor used for screening Pt‐based alloy catalysts with high Pt utilization and low Pt consumption. Among the 77 prescreened candidates, we identified 5 potential candidates for catalyzing ORR with low overpotential. Furthermore, during the second and third rounds of active learning, more Pt‐based alloys ORR candidates are identified based on the relationship between structural features of Pt‐based alloys and their activity. In addition, we highlighted the role of structural features in Pt‐based alloys and found that the difference between the electronegativity of Pt and heteroatom, the valence electrons number of the heteroatom, and the ratio of heteroatoms around Pt are the main factors that affect the activity of ORR. More importantly, the combination of those structural features can be used as structural descriptor for predicting the activity of Pt‐based alloys. We believe the findings of this study will provide new insight for predicting ORR activity and contribute to exploring Pt‐based electrocatalysts with high Pt utilization and low Pt consumption experimentally.

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Research and development needs in agricultural water management to achieve sustainable development goals*1
Authors: Bjornlund Henning , van Rooyen Andre , Pittock Jamie , Bjornlund Vibeke
Published: March 2023

The United Nations calls for action to achieve 17 sustainable development goals (SDGs). We argue that the current development paradigm is an impediment to achieving several of these goals. We identify 14 agricultural research and development (R&D) needs, which ought to be addressed to achieve critical SDGs. We also identify the paradigm shifts required, particularly from global and international organizations, to facilitate this R&D and implement its outcomes. Importantly, the Global North2 would have to divert its focus from securing access to cheap land, water and labour that is primarily used to generate agricultural exports and business opportunities for Global North investors. Instead, the focus needs to be on creating opportunities for local farming communities to produce food for domestic markets, increase income and generate local jobs and business opportunities. Circular food systems can support a range of SDG goals, such as no hunger and zero poverty and slow migration, especially of youth, to big cities or foreign lands with insecure jobs.
Associations between the type of help after sexual harm and adolescents' suicidal ideation
Authors: Yoon Na‐Young , Yun Il , Jung Yun Hwa , Park Eun‐Cheol , Jang Sung‐In
Published: March 2023

Introduction

This cross‐sectional study aimed to determine the association between receiving external help after sexual harm and suicidal ideation among Korean adolescents. The help received was classified into professional and nonprofessional to test the strength of the association according to the type of help.

Methods

Using data from the 2017−2019 Korean children and youth rights study, we analyzed a total of 18,740 middle and high school students. The dependent variable was suicidal ideation; the primary and secondary independent variable was experience of sexual harm and receiving help after sexual harm, respectively. Data were analyzed using χ2 tests and multivariable logistic regression analyses.

Results

Experience of sexual harm was significantly associated with higher suicidal ideation, and receiving help after sexual harm was significantly associated with lower suicidal ideation compared with not receiving help, regardless of gender. Furthermore, lower suicidal ideation was more strongly associated with receiving professional help in female adolescents, and receiving nonprofessional help in male adolescents.

Conclusions

Receiving help after sexual harm was negatively associated with suicidal ideation, and the strength of this association varied with gender and the type of help received. These results can aid the development of evidence‐based crisis intervention for victims of sexual harm.
Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI
Authors: Zhang Hongbo , Zhang Hanwen , Zhang Yuze , Zhou Beibei , Wu Lei , Lei Yi , Huang Biao
Published: March 2023

Background

Studies have shown that magnetic resonance imaging (MRI)‐based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear.

Purpose

To evaluate the value of deep learning (DL) in multiparametric MRI‐based radiomics in identifying TERT promoter mutations in patients with GBM preoperatively.

Study Type

Retrospective.

Population

A total of 274 patients with isocitrate dehydrogenase‐wildtype GBM were included in the study. The training and external validation cohorts included 156 (54.3 ± 12.7 years; 96 males) and 118 (54 .2 ± 13.4 years; 73 males) patients, respectively.

Field Strength/Sequence

Axial contrast‐enhanced T1‐weighted spin‐echo inversion recovery sequence (T1CE), T1‐weighted spin‐echo inversion recovery sequence (T1WI), and T2‐weighted spin‐echo inversion recovery sequence (T2WI) on 1.5‐T and 3.0‐T scanners were used in this study.

Assessment

Overall tumor area regions (the tumor core and edema) were segmented, and the radiomics and DL features were extracted from preprocessed multiparameter preoperative brain MRI images—T1WI, T1CE, and T2WI. A model based on the DLR signature, clinical signature, and clinical DLR (CDLR) nomogram was developed and validated to identify TERT promoter mutation status.

Statistical Tests

The Mann–Whitney U test, Pearson test, least absolute shrinkage and selection operator, and logistic regression analysis were applied for feature selection and construction of radiomics and DL signatures. Results were considered statistically significant at P‐value <0.05.

Results

The DLR signature showed the best discriminative power for predicting TERT promoter mutations, yielding an AUC of 0.990 and 0.890 in the training and external validation cohorts, respectively. Furthermore, the DLR signature outperformed CDLR nomogram (P = 0.670) and significantly outperformed clinical models in the validation cohort.

Data Conclusion

The multiparameter MRI‐based DLR signature exhibited a promising performance for the assessment of TERT promoter mutations in patients with GBM, which could provide information for individualized treatment.

Level of Evidence

3

Technical Efficacy

Stage 2
A machine learning‐derived neuroanatomical pattern predicts delayed reward discounting in the Human Connectome Project Young Adult sample
Authors: Xu Hui , MacKillop James , Owens Max M.
Published: March 2023

Delayed reward discounting (DRD) is defined as the extent to which person favors smaller rewards that are immediately available over larger rewards available in the future. Higher levels of DRD have been identified in individuals with a wide range of clinical disorders. Although there have been studies adopting larger samples and using only gray matter volume to characterize the neuroanatomical correlates of DRD, it is still unclear whether previously identified relationships are generalizable (out‐of‐sample) and how cortical thickness and cortical surface area contribute to DRD. In this study, using the Human Connectome Project Young Adult dataset (N = 1038), a machine learning cross‐validated elastic net regression approach was used to characterize the neuroanatomical pattern of structural magnetic resonance imaging variables associated with DRD. The results revealed a multi‐region neuroanatomical pattern predicted DRD and this was robust in a held‐out test set (morphometry‐only R2 = 3.34%, morphometry + demographics R2 = 6.96%). The neuroanatomical pattern included regions implicated in the default mode network, executive control network, and salience network. The relationship of these regions with DRD was further supported by univariate linear mixed effects modeling results, in which many of the regions identified as part of this pattern showed significant univariate associations with DRD. Taken together, these findings provide evidence that a machine learning‐derived neuroanatomical pattern encompassing various theoretically relevant brain networks produces robustly predicts DRD in a large sample of healthy young adults.
Chemical profiling of Ziziphi spinosae semen using on‐line comprehensive two‐dimensional liquid chromatography‐mass spectrometry based on a novel phthalic anhydride bonded stationary phase
Authors: Zhao Xinwei , Yu Dongping , Zhou Weijia , Yu Long , Zhou Han , Liu Yanfang , Guo Zhimou , Shen Aijing , Han Ziwei , Wang Chaoran , Wang Jixia , Liang Xinmiao
Published: March 2023

Ziziphi spinosae semen has been widely used to treat insomnia and anxiety. To profile its chemical components, an online comprehensive two‐dimensional liquid chromatography‐mass spectrometry was developed. In this two‐dimensional liquid chromatography system, a novel phthalic anhydride‐bonded stationary phase column was combined with a C18 column. As a result, this new stationary phase exhibited remarkable differences in separation selectivity from C18, achieving a good orthogonality of 83.3%. Moreover, this new stationary phase with weaker hydrophobicity than C18 realized solvent compatibility in the online configuration. Coupled with tandem MS, 154 compounds were identified, including 51 unreported compounds. Compared with one‐dimensional liquid chromatography‐mass spectrometry, this online two‐dimensional liquid chromatography‐mass spectrometry system exhibited a much higher resolving power in isomer separation. This work provided an effective separation and characterization method for the material basis of Ziziphi spinosae semen. This strategy provides ideas for the material basis research of other traditional Chinese medicines.
Contrast‐enhanced Ultrasound Combined With Elastography for the Evaluation of Muscle‐invasive Bladder Cancer in Rats
Authors: Hu Xing , Sun Chuanyu , Ren Xinping , Ge Shengyang , Xie Chunmei , Li Xiangyu , Zhu Yingfeng , Ding Hong
Published: March 2023

Objectives

By comparing with the control group, we evaluated the usefulness of contrast‐enhanced ultrasound (CEUS) combined with elastography for the assessment of muscle invasion by bladder cancer (MIBC) in a Sprague–Dawley (SD) rat model.

Methods

In the experimental group, 40 SD rats developed in situ bladder cancer (BLCA) in response to N‐methyl‐N‐nitrosourea treatment, whereas 40 SD rats were included in the control group for comparison. We compared PI, Emean, microvessel density (MVD), and collagen fiber content (CFC) between the two groups. In the experimental group, Bland–Altman test was used to assess the relationships between various parameters. The largest Youden value was used as the cut‐off point, and binomial logistic regression analysis was performed to analyze the PI and Emean. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic power of parameters, individually and in combination.

Results

The PI, Emean, MVD, and CFC were significantly lower in the control group than in the experimental group (P < .05). The PI, Emean, MVD, and CFC were significantly higher for MIBC than for non‐muscle‐invasive bladder cancer (P < .05). There were significant correlations between PI and MVD, and between Emean and CFC. The diagnostic efficiency analysis showed PI had the highest sensitivity, CFC had the highest specificity, and PI + Emean had the highest diagnostic efficacy.

Conclusion

CEUS and elastography can distinguish lesions from normal tissue. PI, MVD, Emean, and CFC were useful for the detection of BLCA myometrial invasion. The comprehensive utilization of PI and Emean improved diagnostic accuracy and have clinical application.
Bacterial proton motive force as an unprecedented target to control antimicrobial resistance
Authors: Yang Bingqing , Tong Ziwen , Shi Jingru , Wang Zhiqiang , Liu Yuan
Published: March 2023

Novel antibacterial therapies are urgently required to tackle the increasing number of multidrug‐resistant pathogens. Identification of new antimicrobial targets is critical to avoid possible cross‐resistance issues. Bacterial proton motive force (PMF), an energetic pathway located on the bacterial membrane, crucially regulates various biological possesses such as adenosine triphosphate synthesis, active transport of molecules, and rotation of bacterial flagella. Nevertheless, the potential of bacterial PMF as an antibacterial target remains largely unexplored. The PMF generally comprises electric potential (ΔΨ) and transmembrane proton gradient (ΔpH). In this review, we present an overview of bacterial PMF, including its functions and characterizations, highlighting the representative antimicrobial agents that specifically target either ΔΨ or ΔpH. At the same time, we also discuss the adjuvant potential of bacterial PMF‐targeting compounds. Lastly, we highlight the value of PMF disruptors in preventing the transmission of antibiotic resistance genes. These findings suggest that bacterial PMF represents an unprecedented target, providing a comprehensive approach to controlling antimicrobial resistance.
Detection of gonosomal mosaicism by ultra‐deep sequencing and droplet digital PCR in patients with Emery–Dreifuss muscular dystrophy
Authors: Xie Yanshu , Luo Jingsi , Zhong Jingzi , Liu Xu , Tang Jing , Lan Dan
Published: March 2023

Background

Emery–Dreifuss muscular dystrophy (EDMD2) is a rare form of muscular dystrophy that is inherited as an autosomal dominant trait. In some patients, it is inherited from parental mosaicism, and this increases the recurrence risk significantly. The presence of mosaicism is underestimated due to the limitations of genetic testing and the difficulty in obtaining samples.

Methods

A peripheral blood sample from a 9‐year‐old girl with EDMD2 was analyzed by enhanced whole exome sequencing (WES). Sanger sequencing in her unaffected parents and younger sister was performed for validation. In the mother, ultra‐deep sequencing and droplet digital PCR (ddPCR) in multiple samples (blood, urine, saliva, oral epithelium, and nail clippings) were performed in order to identify the suspected mosaicism of the variant.

Results

WES revealed a heterozygous mutation (LMNA, c.1622G>A) in the proband. Sanger sequencing of the mother suggested the presence of mosaicism. The ratio of mosaic mutation was confirmed in different samples by ultra‐deep sequencing and ddPCR (19.98%–28.61% and 17.94%–28.33%, respectively). This inferred that the mosaic mutation may have occurred early during embryonic development and that the mother had gonosomal mosaicism.

Conclusion

We described a case of EDMD2 caused by maternal gonosomal mosaicism which was confirmed by using ultra‐deep sequencing and ddPCR. This study illustrates the importance of a systematic and comprehensive screening of parental mosaicism with more sensitive approaches and the use of multiple tissue samples.
Factors associated with poor prognosis of hip arthritis in juvenile idiopathic arthritis: Data from the JIR cohort
Authors: Hamdi Wafa , Ferjani Hanene , Carlomagno Raffaella , Dusser Perrine , Echaubard Stéphane , Belot Alexandre , Bouayed Kenza , Wouters Carine , Richer Olivier , Hentgen Véronique , Lohse Anne , Dan Diana , Kaiser Daniela , Barbier Catherine , Cannizzaro Elvira , Poignant Sylvaine , Melki Isabelle ,   JIRcohort Consortium, Hofer Michaël
Published: March 2023

Objectives

Hip involvement remains a predictor of severe juvenile idiopathic arthritis (JIA) course and carries a high risk of disability. This study aims to determine the factors of poor prognosis of hip involvement in patients with JIA and to assess the treatment response.

Methods

This is a multicenter observational cohort study. Patients were selected from the JIR Cohort database. Hip involvement was defined as clinically suspected and confirmed by an imaging tool. Follow‐up data were collected during 5 years.

Results

Among the 2223 patients with JIA, 341(15%) patients had hip arthritis. Male gender, enthesitis‐related arthritis, and North African origin were factors associated with hip arthritis. Hip inflammation was associated with disease activity parameters during the first year, particularly Physician Global Assessment, joint count, and inflammatory marks. Structural hip progression was associated with early onset of the disease, a longer time to diagnosis, geographic origin, and JIA subtypes. Anti‐TNF therapy was found to be the only treatment able to effectively reduce structural damage progression.

Conclusion

The early onset diagnostic delay, origin, and systemic subtype of JIA predict a poor prognosis of hip arthritis in children with JIA. The use of anti‐TNF was associated with a better structural prognosis.
How coaching training transforms nurses' behaviour: The effectiveness of coaching training according to objective measures
Authors: Sato Asuka , Harada Nobue , Suzukamo Yoshimi , Tonomura Itsushi , Izumi Shin‐Ichi
Published: March 2023

Aim

To evaluate the transition of behavioural changes of participants before and after the training using a scale that can objectively evaluate coaching training for nurses.

Design

After a cross‐sectional study, a quasi‐experimental study was conducted.

Methods

We examined the reliability and validity of the Coaching Skill Assessment plus (CSAplus), which was developed to measure the effectiveness of coaching training for corporate leaders. Next, a repeated measures analysis of variance was conducted on two types of coaching training for nurses conducted at a university hospital, with the CSAplus scores of participants before, 1 month and 6 months after the training as the dependent variable.

Results

The CSAplus is a three‐factor instrument with good reliability and validity. Participants' CSAplus scores improved after training, but there were differences in the magnitude and persistence of the training effects.

Public Contribution

Hospital staff, professional coaches and their clients were involved in data collection.
Advanced analysis of internal quantum efficiency measurements using machine learning
Authors: Abdullah‐Vetter Zubair , Dwivedi Priya , Buratti Yoann , Sowmya Arcot , Trupke Thorsten , Hameiri Ziv
Published: March 2023

The internal quantum efficiency (IQE) is given as the ratio between the externally collected electron current and the photon current absorbed by the device. Spectral analysis of IQE measurements is a powerful method to identify performance‐limiting mechanisms in solar cells. It also enables the extraction of key electrical and optical parameters. However, the potential of IQE measurements is only rarely fully utilized, presumably due to the significant complexity associated with the fitting process and its sensitivity to noise. In this study, machine learning is proposed as an efficient method to extract quantitative information from IQE measurements. The extraction method is automated and easy to use, providing an array of specific device parameters. By simplifying the analytical process, the developed machine learning algorithms also extract the parasitic absorption of the antireflection coating, a key parameter that is difficult to obtain by traditional methods. Although the method has been developed for and tested on silicon solar cells, it can be adapted and applied to other types of solar cells.
Dynamic elastomers based on bio‐derived crosslinker
Authors: Kumar Ashwani , Gresil Matthieu , Connal Luke A.
Published: March 2023

Petroleum‐derived monomers are the most common building blocks for ester‐based thermosets. Bio‐derived thermoset elastomers are becoming viable alternatives to conventional thermosets. Herein, we developed a biobased vitrimer‐type thermoset elastomers using abundant and sustainable raspberry ketone as feedstock. We utilize raspberry ketone to create building blocks for dynamic oxime chemistry and crosslinked these through free radical polymerization with poly(ethylene glycol) methyl ether methacrylate as a comonomer. In contrast to other dynamic networks based on ester bonds, which need catalysts, this is undesirable since catalyst deactivation or leaching lowers its effect over time and may impair reuse. This network incorporates catalyst‐free bond exchange reactions in catalyst‐dependent polyester networks by substituting oxime‐esters for typical ester linkages. The elastomer exhibits stress relaxation, a low glass transition temperature (Tg) (−55 to −40.2°C) and tensile strength up to 5.2 ± 3.0 kPa. Furthermore, the dynamic oxime transesterification exchange mechanism allows elastomers to be reprocessed using a hot press at 160°C and 8 × 103 kPa pressure. After reprocessing, the tensile strength of elastomers can be recovered up to 78.1 ± 10.9%. This work integrates the principles of catalyst‐free dynamic exchange process and mechanical recycling coupled with biobased components to provide a rational solution towards conventional elastomers. In the future, these elastomers can be exploited for the development of hydrogels, recyclable elastomers, and commodity plastics.
Synthesis of submicron‐sized silver azide by multi‐nozzle spray flash synthesis**
Authors: Galland Guillaume , Comet Marc , Ott Anna K. , Schnell Fabien , Lallemand Bastien , Bonnet Benjamin , Spitzer Denis
Published: March 2023

Submicron‐sized powders of silver azide (AgN3) were prepared by Curtius’ reaction between silver nitrate (AgNO3) and sodium azide (NaN3) in aqueous solutions by a new process: the Spray Flash Synthesis (SFS). The SFS process consists in spraying the two precursor solutions in a heated atomization chamber (130–190 °C), maintained under low vacuum (15–30 kPa). The reaction occurs in the droplets which have collided; the final size of particles is limited by the fast evaporation of water and the small amount of matter available in each droplet which can be considered as an individual micro‐reactor. The mean particle sizes of silver azide synthesized by the SFS process range from 220 nm to 390 nm, which means that these particles are three times smaller than those obtained by the conventional precipitation method. Submicron‐sized AgN3 powders can be initiated by a photographic flash.
PK/PD modeling to characterize placebo and treatment effect of omalizumab for chronic spontaneous urticaria
Authors: Oh Elise , Wada Russ , Le Kha , Zheng Yanan , Jin Jin , Poon Victor , Wong Kit , Owen Ryan , Yoshida Kenta
Published: March 2023

The pharmacokinetic (PK) characteristics of omalizumab and its pharmacodynamic (PD) effect in patients has yet to be fully characterized in chronic spontaneous urticaria, which could elucidate its pathogenesis and treatment response. This study has two objectives; (1) characterize the population PK of omalizumab and its PD effect on IgE, and (2) develop a drug effect model of omalizumab in urticaria (via change in weekly itch severity score). The target‐mediated population of PK/PD model incorporating omalizumab‐IgE binding and turnover adequately described PK and PD of omalizumab. The effect compartment model and linear drug effect and additive placebo response adequately described placebo and treatment effects of omalizumab. Several baseline covariates were identified for PK/PD and drug effect models. The developed model has the potential to aid in understanding variability in PK/PD as well as response to omalizumab treatment.
Adaptive compensation control of nonlinear systems with unknown actuator failures
Authors: Wei Lu , Zhang Zhengqiang
Published: March 2023

In this paper, by using bound estimation method, Nussbaum function, K‐filters and higher‐order Lyapunov function, an adaptive output feedback compensation control scheme is proposed for uncertain nonlinear systems with infinite number of actuator failures and unknown control direction. A parametric model with unknown system uncertainties and infinite actuator failures is established, which is different from the existing results. This scheme ensures that closed‐loop signals are globally uniformly bounded. By properly selecting the design parameters, the tracking errors converges to a small neighborhood of the origin. Finally, two simulation examples are given to demonstrate its efficiency of the proposed design scheme.
Combining unmanned aerial vehicles and satellite imagery to quantify areal extent of intertidal brown canopy‐forming macroalgae
Authors: Lewis Pippa H. , Roberts Benjamin P. , Moore Pippa J. , Pike Samuel , Scarth Anthony , Medcalf Katie , Cameron Iain
Published: March 2023

Brown macroalgae habitats provide a range of ecosystem services, offering coastal protection, supporting and increasing biodiversity, and more recently have been recognized for their potential role as blue carbon habitats. Consequently, accurate areal estimates of these habitats are vitally important. Satellite imagery is often utilized for areal estimates of vegetated habitats due to their ability to capture vast areas but are disadvantaged by their lower resolution. In contrast, imagery collected by unmanned aerial vehicles (UAV) provide high‐resolution datasets but are unable to cover the necessary spatial scale required for calculating areal estimates at regional, national or international scales. This study successfully and accurately corrects the outputs from low‐resolution Sentinel 2 imagery to the standard of high‐resolution UAV imagery by using a novel brown algae index and a simple regression model to provide accurate spatial estimates. This model was applied to rocky shores across Wales, UK to predict a spatial extent of 6.2 km2 for three fucoid macroalgae species; Ascophyllum nodosum, Fucus vesiculosus and F. serratus. The regression model was validated in two ways. First, the data used to create the regression model was split to train and test (50:50) the model, with a root mean square error of ~8%–14%. Secondly, spatial estimates of fucoids in independent aerial imagery were assessed using aerial photography interpretation and compared to that of the regression model (7% difference). The carbon standing stock of fucoids calculated from the spatial estimate (6.2 km2) was found to be significantly lower than that of other marine carbon stores, indicating that fucoids do not significantly contribute as a blue carbon habitat based on biomass alone. This study produces a robust and accurate remote sensing technique to estimate spatial extent of macroalgae at large spatial scales, with possible worldwide applicability.
Evidence of Eu(III) Dual Binding in a PVC‐Based Electrochemical Sensor with N,N,N’,N’‐Tetrapentyl Diglycolamide (TPDGA) as the Ionophore: Potentiometric and Luminescence studies
Authors: Mahanty Bholanath , Verma Parveen K. , Mohapatra Prasanta K.
Published: March 2023

The present investigation deals with the development of a polyvinyl chloride (PVC) based potentiometric sensor for Eu(III) containing N,N,N’,N’‐tetrapentyl diglycolamide (TPDGA) as ionophore, 2‐nitrophenyl octylether (NPOE) as plasticizer and sodium tetraphenylborate (NaTPB) as ionic additive. The membrane with 8.7 % TPDGA, 29.7 % PVC, 59.0 % NPOE, 2.5 % NaTPB exhibited a linear response behaviour from 1.5×10−6 m to 1.1×10−2 m Eu(III) with a slope of 23.4±0.3 mV/decade and a limit of detection (LOD) of 1.2×10−6 m. The sensor showed fast response times (<5 s) and a lifetime of two months. It showed good tolerance for monovalent/divalent interfering ions and moderate/poor tolerance for trivalent ions. The membrane was characterized using photoluminesce (PL) spectroscopy which suggested NPOE can alter the nature of species in the membrane and evidence the presence of two species. The membrane can be used as an indicator electrode for the potentiometric titration of Eu(III) and in the estimation of europium in the synthetic and laboratory bearing waste which compared well with the x‐ray fluorescene (XRF) results.
Investigation on the immunotoxicity induced by Emamectin benzoate on THP‐1 macrophages based on metabolomics analysis
Authors: Wei Ziyi , Wang Weiguo , Feng Hao , Xu Wenping , Tao Liming , Li Zhong , Zhang Yang , Shao Xusheng
Published: March 2023

Emamectin benzoate (EMB) is an insecticide extensively used in agricultural area. Assessing the toxic effects of EMB in mammals or humans and its endogenous metabolites alteration are the appropriate means of evaluating its risks to human health. In the study, THP‐1 macrophage, a human immune model, was applied to investigate the immunotoxicity of EMB. A global metabolomics approach was developed to analyze metabolic perturbation on macrophages and discover the potential biomarkers of EMB‐induced immunotoxicity. The results indicated that EMB could inhibit immune functions of macrophages. Based on metabolomics analysis, our results illustrated that EMB caused significant alterations in metabolic profiles on macrophages. 22 biomarkers associated with immune response were screened by pattern recognition and multivariate statistical analysis. Furthermore, pathway analysis identified purine metabolism was the most relevant pathway in the metabolic process and the abnormal conversion of AMP to xanthosine regulated by NT5E might be a potential mechanism of immunotoxicity induced by EMB. Our study provides important insights for understanding and underlying mechanism of immunotoxicity exposed to EMB.
An extensible vector toolkit and parts library for advanced engineering of plant genomes
Authors: Chamness James C. , Kumar Jitesh , Cruz Anna J. , Rhuby Elissa , Holum Mason J. , Cody Jon P. , Tibebu Redeat , Gamo Maria Elena , Starker Colby G. , Zhang Feng , Voytas Daniel F.
Published: March 2023

Plant biotechnology is rife with new advances in transformation and genome engineering techniques. A common requirement for delivery and coordinated expression in plant cells, however, places the design and assembly of transformation constructs at a crucial juncture as desired reagent suites grow more complex. Modular cloning principles have simplified some aspects of vector design, yet many important components remain unavailable or poorly adapted for rapid implementation in biotechnology research. Here, we describe a universal Golden Gate cloning toolkit for vector construction. The toolkit chassis is compatible with the widely accepted Phytobrick standard for genetic parts, and supports assembly of arbitrarily complex T‐DNAs through improved capacity, positional flexibility, and extensibility in comparison to extant kits. We also provision a substantial library of newly adapted Phytobricks, including regulatory elements for monocot and dicot gene expression, and coding sequences for genes of interest such as reporters, developmental regulators, and site‐specific recombinases. Finally, we use a series of dual‐luciferase assays to measure contributions to expression from promoters, terminators, and from cross‐cassette interactions attributable to enhancer elements in certain promoters. Taken together, these publicly available cloning resources can greatly accelerate the testing and deployment of new tools for plant engineering.
Massless spin 2 interacting with massive higher spins in d = 3
Authors: Zinoviev Yu. M.
Published: March 2023

Abstract

In this paper we consider massless spin 2 interacting with the massive arbitrary spin fermions in d = 3. First of all, we study all possible deformations for the massive fermion unfolded equations in presence of a massless spin-2 field. We find three linearly independent solutions one of which corresponds to the standard gravitational interactions. Then for all three cases we reconstruct appropriate Lagrangian formulation.
Activating NKG2C Receptor: Functional Characteristics and Current Strategies in Clinical Applications
Authors: Siemaszko Jagoda , Marzec-Przyszlak Aleksandra , Bogunia-Kubik Katarzyna
Published: March 2023

The interest in NK cells and their cytotoxic activity against tumour, infected or transformed cells continuously increases as they become a new efficient and off-the-shelf agents in immunotherapies. Their actions are balanced by a wide set of activating and inhibitory receptors, recognizing their complementary ligands on target cells. One of the most studied receptors is the activating CD94/NKG2C molecule, which is a member of the C-type lectin-like family. This review is intended to summarise latest research findings on the clinical relevance of NKG2C receptor and to examine its contribution to current and potential therapeutic strategies. It outlines functional characteristics and molecular features of CD94/NKG2C, its interactions with HLA-E molecule and presented antigens, pointing out a key role of this receptor in immunosurveillance, especially in the human cytomegalovirus infection. Additionally, the authors attempt to shed some light on receptor’s unique interaction with its ligand which is shared with another receptor (CD94/NKG2A) with rather opposite properties.
More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
Authors: Wang Tien-Cheng , Casadebaig Pierre , Chen Tsu-Wei
Published: March 2023

Key message

Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly.

Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (Pi) was least affected among 11 SI.Piwas used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield orPi. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than inPi; while light extinction coefficient and radiation use efficiency were more correlated withPithan with yield. The high number of genotypes and environments required for studyingPihighlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.
The Strong Converse Exponent of Discriminating Infinite-Dimensional Quantum States
Authors: Mosonyi Milán
Published: March 2023

The sandwiched Rényi divergences of two finite-dimensional density operators quantify their asymptotic distinguishability in the strong converse domain. This establishes the sandwiched Rényi divergences as the operationally relevant ones among the infinitely many quantum extensions of the classical Rényi divergences for Rényi parameter $$\alpha >1$$

α
>
1

. The known proof of this goes by showing that the sandwiched Rényi divergence coincides with the regularized measured Rényi divergence, which in turn is proved by asymptotic pinching, a fundamentally finite-dimensional technique. Thus, while the notion of the sandwiched Rényi divergences was extended recently to density operators on an infinite-dimensional Hilbert space (in fact, even for states of an arbitrary von Neumann algebra), these quantities were so far lacking an operational interpretation similar to the finite-dimensional case, and it has also been open whether they coincide with the regularized measured Rényi divergences. In this paper we fill this gap by answering both questions in the positive for density operators on an infinite-dimensional Hilbert space, using a simple finite-dimensional approximation technique. We also initiate the study of the sandwiched Rényi divergences, and the related problem of the strong converse exponent, for pairs of positive semi-definite operators that are not necessarily trace-class (this corresponds to considering weights in a general von Neumann algebra setting). This is motivated by the need to define conditional Rényi entropies in the infinite-dimensional setting, while it might also be interesting from the purely mathematical point of view of extending the concept of Rényi (and other) divergences to settings beyond the standard one of positive trace-class operators (positive normal functionals in the von Neumann algebra setting). In this spirit, we also discuss the definition and some properties of the more general family of Rényi $$(\alpha ,z)$$

(
α
,
z
)

-divergences of positive semi-definite operators on an infinite-dimensional separable Hilbert space.
The biopsychosocial impact of hypermobility spectrum disorders in adults: a scoping review
Authors: Clark Natalie L. , Johnson Melissa , Rangan Amar , Kottam Lucksy , Swainston Katherine
Published: March 2023

Joint hypermobility affects approximately 30% of the United Kingdom (UK) population, characterised by the ability to move joints beyond the physiological limits. Associated conditions include Ehlers-Danlos syndrome and hypermobility spectrum disorders, affecting individuals across physical, psychological and social levels detrimentally impacting their health and wellbeing. The scoping review aims to describe the known biopsychosocial impact of joint hypermobility conditions in adults over the last decade. Additional objectives include to (1) identify the types of studies that address these factors, (2) to understand how the impact of the condition is measured and managed and (3) what healthcare professionals (HCPs) are involved. The scoping review was conducted using the five-stage framework by Arksey and O’Malley. The search strategy related to two main keywords, “hypermobility” and, “biopsychosocial” across a number of electronic databases. A pilot search was conducted to determine the suitability of the databases and terms. Following the search, the data was extracted and charted, summarised and narratively reported. 32 studies met the inclusion criteria. The majority were conducted in either the UK or United States of America and case–control in design. The biopsychosocial impact was wide-ranging including, but not limited to, musculoskeletal system and dermatology, gastroenterology, mood and anxiety disorders, education and employments. This review is the first of its kind to summarise all reported symptoms and impact of joint hypermobility conditions in adults, highlighting a clear need to promote a multidisciplinary and holistic approach in raising awareness of these conditions and improving their management.
Predictors of survival in advanced oral cancers after salvage surgery with free tissue flap reconstruction
Authors: Hafström Anna , Wahlberg Peter , Klasson Stina , Greiff Lennart , Sjövall Johanna
Published: March 2023

Objective

To identify prognostic factors for patients with advanced persistent, recurrent, or 2nd primary oral cavity squamous cell carcinoma (OCSCC) potentially unsuitable for salvage surgery with free tissue flap (FTF) reconstruction.

Materials and methods

A population-based cohort of 83 consecutive patients with advanced OCSCC who underwent salvage surgery with FTF reconstruction at a tertiary referral centre between 1990 and 2017. Retrospective uni- and multivariable analyses were performed to identify factors affecting all-cause mortality (ACM), i.e., overall survival (OS), as well as disease-specific mortality (DSM), i.e., disease-specific survival (DSS) after salvage surgery.

Results

Median disease-free interval until recurrence was 15 months with recurrent stage I/II in 31% and III/IV in 69%. Median age at salvage surgery was 67 years (range 31–87) and the median follow-up (alive patients) 126 months. At 2, 5, and 10 years after salvage surgery, respectively, DSS rates were 61%, 44%, and 37% and OS rates 52%, 30%, and 22%. Median DSS was 26 and OS 43 months. Multivariable analysis identified recurrent clinical regional (cN-plus) disease [HR 3.57; p < .001] and elevated gamma-glutamyl transferase (GGT) [HR 3.30; p = .003] as independent pre-salvage predictors for poor OS after salvage, whereas initial cN-plus [HR 2.07; p = .039] and recurrent cN-plus disease [HR 5.14; p < .001] predicted poor DSS. Among post-salvage factors, extranodal extension according to histopathology [HR ACM 6.11; HR DSM 9.99; p < .001] as well as positive [HR ACM 4.98; DSM 7.51; p < 0.001] and narrow surgical margins [HR ACM 2.12; DSM HR 2.80; p < 0.01] emerged as independent factors for poor survival.

Conclusion

While salvage surgery with FTF reconstruction is the primary curative option for patients with advanced recurrent OCSCC, the present findings may help guide discussions with patients who have advanced recurrent regional disease and high GGT preoperatively, especially if there is a small chance of reaching surgical radicality.
Few-shot learning via graph embeddings with convolutional networks for low-data molecular property prediction
Authors: Torres Luis , Arrais Joel P. , Ribeiro Bernardete
Published: March 2023

Graph neural networks and convolutional architectures have proven to be pivotal in improving the prediction of molecular properties in drug discovery. However, this is fundamentally a low data problem that is incompatible with regular deep learning approaches. Contemporary deep networks require large amounts of training data, which severely limits the prediction of new molecular entities from limited available data. In this paper, we address the challenge of low data in molecular property prediction by: (1) defining a set of deep learning architectures that accept compound chemical structures in the form of molecular graphs, (2) creating a few-shot learning strategy across graph neural networks and convolutional neural networks to leverage the rich information of graph embeddings, and (3) proposing a two-module meta-learning framework to learn from task-transferable knowledge and predict molecular properties on few-shot data. Furthermore, we conduct multiple experiments on two benchmark multiproperty datasets to demonstrate a superior performance over conventional graph-based baselines. ROC-AUC results for 10-shot experiments show an average improvement of $$+11.37\%$$

+
11.37
%

on Tox21 and $$+0.53\%$$

+
0.53
%

on SIDER, which are representative small-sized biological datasets for molecular property prediction.