bluuebunny/crossref_metadata_2025_split huggingface dataset:
Salt elicitation to enhance phytochemicals in durum wheat seedlings
Authors: Trasmundi Flaviano , Galieni Angelica , Eugelio Fabiola , Fanti Federico , Benincasa Paolo , Del Carlo Michele , Sergi Manuel , Stagnari Fabio 
Published: August 2023

AbstractBACKGROUNDSalt has been identified as an elicitor that can increase the accumulation of phytochemicals in seedlings during the germination process. However, the salinity level required to maximize the yield of phytochemicals, particularly phenolic compounds, needs further investigation for several plant species. To address this issue, we imposed increasing levels of salinity (NaCl solutions) on the sprouting substrate of Triticum durum (var. Platone) grains, at concentrations of 0, 50, 100, 150, 200, 250, and 300 mM (0_S, 50_S, 100_S, 150_S, 200_S, 250_S, and 300_S, respectively).RESULTSThe highest NaCl doses (250_S and 300_S) significantly impacted germination performance and were excluded from further analysis. The seedlings harvested at 8 days after sowing exhibited different growth stages depending on the salinity level: wheatgrass for 0_S, early wheatgrass for 50_S, intermediate between sprout and wheatgrass for 100_S, sprout for 150_S, and very early sprout for 200_S. Furthermore, salinity induced the concentration of phenolic compounds (PhCs) in the seedlings' tissues (i.e., both roots and shoots) in a salinity‐dependent manner. The highest values were observed at 200_S, with an increase of 187% of the total investigated PhCs in comparison with 0_S, averaged over shoots and roots. In particular, in 200_S, the accumulation of phenolic acids was up to fourfold higher in roots, and that of flavonoids was up to twofold higher in shoots.CONCLUSIONOur findings suggest that the use of 200 mM NaCl applied to the sprouting substrate is excessive for producing edible sprouts but may be suitable for phytochemical extraction purposes. © 2023 Society of Chemical Industry.
Impacts of open‐pit coal mining and livestock grazing on plant diversity in a steppe: From the perspective of remote sensing
Authors: Yang Xingchen , Lei Shaogang , Shi Yunxi , Gong Chuangang , Xu Jun , Wang Weizhong 
Published: August 2023

AbstractCoal mining and grazing cause land degradation. Plant diversity loss is one of the characteristics. Ground surveys cannot analyze the effects of mining and grazing on plant diversity in large areas, and remote sensing offers a novel solution. The aims of this study were as follows: (1) to analyze the impacts of mining and grazing on plant diversity composition by considering α‐, β‐, and γ‐ diversity comprehensively; (2) to determine the impacts of mining and grazing on the spatial distribution of α‐diversity; (3) to identify priority areas for ecological restoration. We applied a novel remote sensing method to obtain plant α‐, β‐, and γ‐ diversity maps and performed spatial analysis. The results were as follows: (1) mining reduced the proportion of α‐diversity in the total diversity (γ‐diversity) but increased that of β‐diversity. Grazing increased the proportion of α‐diversity but decreased that of β‐diversity. Mining increased the heterogeneity among plant communities, whereas grazing increased the homogeneity. (2) Both mining and grazing reduced α‐diversity. With increasing distance from the mine, α‐diversity increased logarithmically. (3) The severely affected range of mining on plant diversity is approximately 325 m. When there is grazing around the mine, the severely affected range is approximately 400 m. Severely affected areas are priority areas for ecological restoration. Improving the soil quality can be an effective measure. This study gains new insights into the effects of coal mining and grazing on plant diversity. These findings can provide some guidance for governments to formulate ecological restoration measures in mining areas.
A Rapidly Dissolvable Microneedle Patch with Tip‐Accumulated Antigens for Efficient Transdermal Vaccination
Authors: Zheng Yanting , Ling Zhixin , Li Zhiming , Zhao Puxuan , Wen Xueyu , Qu Fengli , Yu Haining , Chang Hao 
Published: August 2023

AbstractDissolvable microneedles (DMNs) are an attractive alternative for vaccine delivery due to their user‐friendly, skin‐targeted, and minimally invasive features. However, vaccine waste and inaccurate dosage remain significant issues faced by DMNs, as the skin's elasticity makes it difficult to insert MNs completely. Here, a simple and reliable fabrication method are introduced based on two‐casting micromolding with centrifugal drying to create a rapidly DMN patch made of hyaluronic acid. Ovalbumin (OVA), as the model antigens, is concentrated in the tip parts of the DMNs (60% of the needle height) to prevent antigen waste caused by skin elasticity. The time and temperature of the initial centrifugal drying significantly affect antigen distribution within the needle tips, with lower temperature facilitating antigen accumulation. The resulting DMN patch is able to penetrate the skin with enough mechanical strength and quickly release antigens into the skin tissue within 3 min. The in vivo study demonstrates that immunization of OVA with DMNs outperforms conventional vaccination routes, including subcutaneous and intramuscular injections, in eliciting both humoral and cellular immunity. This biocompatible DMN patch offers a promising and effective strategy for efficient and safe vaccination.
Rational Design and Development of Polymeric Nanogels as Protein Carriers
Authors: López‐Iglesias Clara , Klinger Daniel 
Published: August 2023

AbstractProteins have gained significant attention as potential therapeutic agents owing to their high specificity and reduced toxicity. Nevertheless, their clinical utility is hindered by inherent challenges associated with stability during storage and after in vivo administration. To overcome these limitations, polymeric nanogels (NGs) have emerged as promising carriers. These colloidal systems are capable of efficient encapsulation and stabilization of protein cargoes while improving their bioavailability and targeted delivery. The design of such delivery systems requires a comprehensive understanding of how the synthesis and formulation processes affect the final performance of the protein. This review highlights critical aspects involved in the development of NGs for protein delivery, with specific emphasis on loading strategies and evaluation techniques. For example, factors influencing loading efficiency and release kinetics are discussed, along with strategies to optimize protein encapsulation through protein‐carrier interactions to achieve the desired therapeutic outcomes. The discussion is based on recent literature examples and aims to provide valuable insights for researchers working toward the advancement of protein‐based therapeutics.
Enhancing the Sound and Thermal Insulation Properties of Polypropylene Foam by Preparing High Melt Strength Polypropylene
Authors: Liu Fangjun , Shen Chenxi , You Feng , Zhao Wufan , Deng Caoting , Jiang Xueliang 
Published: August 2023

AbstractHigh‐performance polypropylene (PP) foam is a vital polymer product in industrial areas. However, the poor melt strength of ordinary PP homopolymer limits its foaming molding. In this work, high melt strength polypropylene (HMSPP) is prepared by using styrene (St) and tripropylene glycol diacrylate (TPGDA) as comonomers, and then PP foams are prepared by mold foaming method. The results show that adding St in the grafting process of TPGDA will obviously improve the melt strength of the PP matrix, and its melt strength (28 184 Pa.s) is 7.4 times higher than that of pure PP. HMSPP foam has more regular and uniform cells and higher cell density, which significantly improves the sound and thermal insulation properties of PP foam. Compared with pure PP foam, the average sound transmission loss (52.9 dB) of HMSPP foam with a low foaming ratio increased by 64%, and the thermal conductivity (0.0867 W mK−1) decreased by 46%. Therefore, the obtained HMSPP foam can be used in sound insulation or thermal insulation area. This work provides an available route for the high‐performance utilization of PP foam.
Optimal brand differentiation and private brand introduction strategies considering carbon emission reduction
Authors: Wang Jia , Cao Kaiying 
Published: August 2023

AbstractThis paper constructs a theoretical model to explore whether manufacturers should launch low‐end products and whether retailers should introduce private brands. The main results show that whether retailers (manufacturers) introduce private brands or launch low‐end products depends not only on the fixed cost of introducing private brands (launching low‐end products) but also on the sensitivity of consumers to carbon reduction, product competition coefficient, manufacturer's cost of high‐end products, and carbon reduction cost coefficient. Furthermore, brand differentiation strategy and private brand introduction strategy have an impact on one another.
Absorption matters: A closer look at popular oral bioavailability rules for drug approvals
Authors: Caminero Gomes Soares Artur , Marques Sousa Gustavo Henrique , Calil Raisa Ludmila , Goulart Trossini Gustavo Henrique 
Published: August 2023

AbstractThis study examines how two popular drug‐likeness concepts used in early development, Lipinski Rule of Five (Ro5) and Veber's Rules, possibly affected drug profiles of FDA approved drugs since 1997. Our findings suggest that when all criteria are applied, relevant compounds may be excluded, addressing the harmfulness of blindly employing these rules. Of all oral drugs in the period used for this analysis, around 66 % conform to the RO5 and 85 % to Veber's Rules. Molecular Weight and calculated LogP showed low consistent values over time, apart from being the two least followed rules, challenging their relevance. On the other hand, hydrogen bond related rules and the number of rotatable bonds are amongst the most followed criteria and show exceptional consistency over time. Furthermore, our analysis indicates that topological polar surface area and total count of hydrogen bonds cannot be used as interchangeable parameters, contrary to the original proposal. This research enhances the comprehension of drug profiles that were FDA approved in the post‐Lipinski period. Medicinal chemists could utilize these heuristics as a limited guide to direct their exploration of the oral bioavailability chemical space, but they must also steer the wheel to break these rules and explore different regions when necessary.
Rank‐structured approximation of some Cauchy matrices with sublinear complexity
Authors: Lepilov Mikhail , Xia Jianlin 
Published: August 2023

AbstractIn this article, we consider the rank‐structured approximation of one important type of Cauchy matrix. This approximation plays a key role in some structured matrix methods such as stable and efficient direct solvers and other algorithms for Toeplitz matrices and certain kernel matrices. Previous rank‐structured approximations (specifically hierarchically semiseparable, or HSS, approximations) for such a matrix of size cost at least complexity. Here, we show how to construct an HSS approximation with sublinear (specifically, ) complexity. The main ideas include extensive computation reuse and an analytical far‐field compression strategy. Low‐rank compression at each hierarchical level is restricted to just a single off‐diagonal block row, and a resulting basis matrix is then reused for other off‐diagonal block rows as well as off‐diagonal block columns. The relationships among the off‐diagonal blocks are rigorously analyzed. The far‐field compression uses an analytical proxy point method where we optimize the choice of some parameters so as to obtain accurate low‐rank approximations. Both the basis reuse ideas and the resulting analytical hierarchical compression scheme can be generalized to some other kernel matrices and are useful for accelerating relevant rank‐structured approximations (though not subsequent operations like matrix‐vector multiplications).
Application of digital pathology‐based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response
Authors: Fu Xiao , Sahai Erik , Wilkins Anna 
Published: August 2023

AbstractIn recent years, the application of advanced analytics, especially artificial intelligence (AI), to digital H&E images, and other histological image types, has begun to radically change how histological images are used in the clinic. Alongside the recognition that the tumour microenvironment (TME) has a profound impact on tumour phenotype, the technical development of highly multiplexed immunofluorescence platforms has enhanced the biological complexity that can be captured in the TME with high precision. AI has an increasingly powerful role in the recognition and quantitation of image features and the association of such features with clinically important outcomes, as occurs in distinct stages in conventional machine learning. Deep‐learning algorithms are able to elucidate TME patterns inherent in the input data with minimum levels of human intelligence and, hence, have the potential to achieve clinically relevant predictions and discovery of important TME features. Furthermore, the diverse repertoire of deep‐learning algorithms able to interrogate TME patterns extends beyond convolutional neural networks to include attention‐based models, graph neural networks, and multimodal models. To date, AI models have largely been evaluated retrospectively, outside the well‐established rigour of prospective clinical trials, in part because traditional clinical trial methodology may not always be suitable for the assessment of AI technology. However, to enable digital pathology‐based advanced analytics to meaningfully impact clinical care, specific measures of ‘added benefit’ to the current standard of care and validation in a prospective setting are important. This will need to be accompanied by adequate measures of explainability and interpretability. Despite such challenges, the combination of expanding datasets, increased computational power, and the possibility of integration of pre‐clinical experimental insights into model development means there is exciting potential for the future progress of these AI applications. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Thermally conductive polypropylene composites as corrosion‐resistant materials for plate heat exchangers
Authors: Kiepfer Hendrik , Stannek Paul , Grundler Marco , Bart Hans‐Jörg 
Published: August 2023

AbstractThe suitability of polypropylene‐graphite composites as materials for corrugated heat exchanger plates is investigated, as the associated materials have low density (<2.3 g/cm3) and excellent corrosion resistance at a comparatively low price. Therefore, custom‐made polymer composite plates with a thickness of 1–2 mm and a filling degree of up to 80 wt% were evaluated for their thermal and mechanical suitability with regard to their use in plate heat exchangers. Three‐point flexural tests show that the loading of polypropylene with graphite leads to mechanical properties that are suitable for the application of heat exchanger plates. The simulated maximum overpressure is greater than 7 bar. The thermal conductivity of the composites was increased by a factor of 20 compared to pure polypropylene, resulting in thermal conductivities of up to 2.74 W/mK. Considering the density differences between the developed composites and stainless steel, similar thermal performances over a wide range of process conditions are obtained. Moreover, the composites investigated have lower crystallization fouling susceptibility compared to stainless steel, which is attributed to the low surface free energies of approximately 25 mN/m. For calcium sulfate fouling, the fouling resistance on stainless steel exceeds that on the composite by 1.5 m2K/kW after 60 h.
Item response theory in early phase clinical trials: Utilization of a reference model to analyze the Montgomery‐Åsberg Depression Rating Scale
Authors: Otto Marije E. , Bergmann Kirsten R. , de Kam Marieke L. , Recourt Kasper , Jacobs Gabriël E. , van Esdonk Michiel J. 
Published: August 2023

AbstractIn clinical trials, Montgomery‐Åsberg Depression Rating Scale (MADRS) questionnaire data are added up to total scores before analysis, assuming equal contribution of each separate question. Item Response Theory (IRT)‐based analysis avoids this by using individual question responses to determine the latent variable (ψ), which represents a measure of depression severity. However, utilization of IRT in early phase trials remains difficult, because large datasets are needed to develop IRT models. Therefore, we aimed to evaluate the application and assumptions of a reference IRT model for analysis of an early phase trial. A cross‐over, placebo‐controlled study investigating the effect of intravenous racemic ketamine on MADRS scores in patients with treatment‐resistant major depressive disorder was used as a case study. One hundred forty‐seven MADRS responses were measured in 17 patients at five timepoints (predose to 2 weeks after dosing). Two reference IRT models based on different patient populations were selected from literature and used to determine ψ, while testing multiple approaches regarding assumed data distribution. Use of ψ versus total score to determine treatment effect was compared through linear mixed model analysis. Results showed that determined ψ values did not differ significantly between assumed distributions, but were significantly different when changing reference IRT model. Estimated treatment effect size was not significantly affected by chosen approach nor reference population. Finally, increased precision to determine treatment effect was achieved by using IRT versus total scores. This demonstrates the usefulness of reference IRT model application for analysis of questionnaire data in early phase clinical trials.
Self‐repairable, high‐uniform conductive‐bridge random access memory based on amorphous NbSe2
Authors: Lu Bojing , Hu Dunan , Yang Ruqi , Du Jigang , Hu Lingxiang , Li Siqin , Wang Fengzhi , Huang Jingyun , Liu Pingwei , Zhuge Fei , Zeng Yu‐Jia , Ye Zhizhen , Lu Jianguo 
Published: August 2023

AbstractConductive‐bridge random access memory (CBRAM) emerges as a promising candidate for next‐generation memory and storage device. However, CBRAMs are prone to degenerate and fail during electrochemical metallization processes. To address this issue, herein we propose a self‐repairability strategy for CBRAMs. Amorphous NbSe2 was designed as the resistive switching layer, with Cu and Au as the top and bottom electrodes, respectively. The NbSe2 CBRAMs demonstrate exceptional cycle‐to‐cycle and device‐to‐device uniformity, with forming‐free and compliance current‐free resistive switching characteristics, low‐operation voltage, and competitive endurance and retention performance. Most importantly, the self‐repairable behavior is discovered for the first time in CBRAM. The device after failure can recover its performance to the initially normal state by operating with a slightly large reset voltage. The existence of Cu conductive filament and excellent controllability of Cu migration in the NbSe2 switching layer has been revealed by a designed broken‐down point approach, which is responsible for the self‐repairable behavior of NbSe2 CBRAMs. Our self‐repairable and high‐uniform amorphous NbSe2 CBRAM may open the door to the development of memory and storage devices in the future.
Lung proteomics combined with metabolomics reveals molecular characteristics of inflammation‐related lung tumorigenesis induced by B(a)P and LPS
Authors: Ma Pengwei , Miao Xinyi , Li Mengyuan , Kong Xiangbing , Jiang Yuting , Wang Pengpeng , Zhang Peng , Shang Pingping , Chen Yusong , Zhou Xiaolei , Wang Wei , Zhang Qiao , Liu Hong , Feng Feifei 
Published: August 2023

AbstractInflammatory microenvironment may take a promoting role in lung tumorigenesis. However, the molecular characteristics underlying inflammation‐related lung cancer remains unknown. In this work, the inflammation‐related lung tumorigenesis mouse model was established by treated with B(a)P (1 mg/mouse, once a week for 4 weeks), followed by LPS (2.5 μg/mouse, once every 3 weeks for five times), the mice were sacrificed 30 weeks after exposure. TMT‐labeled quantitative proteomics and untargeted metabolomics were used to interrogate differentially expressed proteins and metabolites in different mouse cancer tissues, followed by integrated crosstalk between proteomics and metabolomics through Spearman's correlation analysis. The result showed that compared with the control group, 103 proteins and 37 metabolites in B(a)P/LPS group were identified as significantly altered. By searching KEGG pathway database, proteomics pathways such as Leishmaniasis, Asthma and Intestinal immune network for IgA production, metabolomics pathways such as Vascular smooth muscle contraction, Linoleic acid metabolism and cGMP‐PKG signaling pathway were enriched. A total of 22 pathways were enriched after conjoint analysis of the proteomic and metabolomics, and purine metabolism pathway, the unique metabolism‐related pathway, which included significantly altered protein (adenylate cyclase 4, ADCY4) and metabolites (L‐Glutamine, guanosine monophosphate (GMP), adenosine and guanosine) was found. Results suggested purine metabolism may contribute to the inflammation‐related lung tumorigenesis, which may provide novel clues for the therapeutic strategies of inflammation‐related lung cancer.
Assessing golden‐winged warbler dispersal habitat in a highly parcelized landscape
Authors: Woodie Michaelyn B. , Tomcho Aimee , Barnhill Laurel M. , McComb Brenda C. 
Published: August 2023

AbstractGolden‐winged warblers (Vermivora chrysoptera) are facing population declines in the southern Appalachian Mountains. Breeding habitat loss is considered one of the primary reasons for golden‐winged warbler declines in the region. Expanding breeding habitat availability in a manner that promotes population expansion across an interconnected network of habitat patches is particularly problematic in a landscape dominated by private land ownership. We assessed the connectivity of golden‐winged warbler breeding habitat in a 29,680‐ha landscape with 5,664 ownership parcels between 2 state‐owned game lands in northwestern North Carolina, USA, in fall 2021. We created a connectivity map and provided examples of 3 means of prioritizing parcels for golden‐winged warbler habitat maintenance and management based on dispersal distances of fledglings that could return the following spring with prior familiarity of potential nesting areas. Prioritized parcels can guide land acquisition and conservation easement development as well as active management. Despite being highly parcelized, the area has both well‐connected and disjointed clusters of core habitat patches, but habitat management on privately owned parcels would be needed to connect core habitat patches to enable dispersing golden‐winged warbler fledglings to encounter potential breeding habitat that they could use the following spring.