bluuebunny/crossref_metadata_2025_split huggingface dataset:
Degradable Bottlebrush Polypeptides and the Impact of their Architecture on Cell Uptake, Pharmacokinetics, and Biodistribution In Vivo
Authors: Strasser Paul , Montsch Bianca , Weiss Silvia , Sami Haider , Kugler Christoph , Hager Sonja , Schueffl Hemma , Mader Robert , Brüggemann Oliver , Kowol Christian R. , Ogris Manfred , Heffeter Petra , Teasdale Ian 
Published: February 2023

AbstractBottlebrush polymers are highly promising as unimolecular nanomedicines due to their unique control over the critical parameters of size, shape and chemical function. However, since they are prepared from biopersistent carbon backbones, most known bottlebrush polymers are non‐degradable and thus unsuitable for systemic therapeutic administration. Herein, we report the design and synthesis of novel poly(organo)phosphazene‐g‐poly(α‐glutamate) (PPz‐g‐PGA) bottlebrush polymers with exceptional control over their structure and molecular dimensions (Dh ≈ 15–50 nm). These single macromolecules show outstanding aqueous solubility, ultra‐high multivalency and biodegradability, making them ideal as nanomedicines. While well‐established in polymer therapeutics, it has hitherto not been possible to prepare defined single macromolecules of PGA in these nanosized dimensions. A direct correlation was observed between the macromolecular dimensions of the bottlebrush polymers and their intracellular uptake in CT26 colon cancer cells. Furthermore, the bottlebrush macromolecular structure visibly enhanced the pharmacokinetics by reducing renal clearance and extending plasma half‐lives. Real‐time analysis of the biodistribution dynamics showed architecture‐driven organ distribution and enhanced tumor accumulation. This work, therefore, introduces a robust, controlled synthesis route to bottlebrush polypeptides, overcoming limitations of current polymer‐based nanomedicines and, in doing so, offers valuable insights into the influence of architecture on the in vivo performance of nanomedicines.
High‐Entropy Perovskites for Energy Conversion and Storage: Design, Synthesis, and Potential Applications
Authors: Wang Yuhao , Liu Jiapeng , Song Yufei , Yu Jing , Tian Yunfeng , Robson Matthew James , Wang Jian , Zhang Zhiqi , Lin Xidong , Zhou Guodong , Wang Zheng , Shen Longyun , Zhao Hailei , Grasso Salvatore , Ciucci Francesco 
Published: February 2023

AbstractPerovskites have shown tremendous promise as functional materials for several energy conversion and storage technologies, including rechargeable batteries, (electro)catalysts, fuel cells, and solar cells. Due to their excellent operational stability and performance, high‐entropy perovskites (HEPs) have emerged as a new type of perovskite framework. Herein, this work reviews the recent progress in the development of HEPs, including synthesis methods and applications. Effective strategies for the design of HEPs through atomistic computations are also surveyed. Finally, an outlook of this field provides guidance for the development of new and improved HEPs.
X‐ray spectral characteristics of typical clays in China and their application in clay classification
Authors: Zhai Juan , Lai Wanchang , Lin Hongjian , Li Dan , Shi Jie , Wang Guangxi , Yang Qiang , Liu Guanhua 
Published: February 2023

AbstractThe variety and content of minerals in clay determine its quality and use. The x‐ray fluorescence characteristics of seven elements, that is, Mg, Al, Si, K, Ca, Ti, and Fe, in clay samples were studied using the energy‐dispersive x‐ray fluorescence (EDXRF) method. The application of wavelet transform was used to analyze the overlapping peaks of the FeKα and MnKβ and the CaKα and KKβ spectral lines and to measure the spectral peak count rate and the content of seven elements. The weight of classified elements in clay was calculated through principal component analysis, and the clay samples from four clay‐producing areas were classified using the K‐means clustering method. The results showed that the accuracy of classification using the count rate of seven elements reached 97.73%. The average accuracy of the classification results of the content of seven elements reached 80.68%. A comparison of the results showed that the EDXRF spectral peak information provides a reliable scientific method for the identification and tracing of clay and its products. In addition, tracing the origin of clay and its products can also indirectly assess the radiation level and its impact on the radiation environment based on the radiation index test results.
Propagation of plane waves in a nonlocal transversely isotropic thermoelastic medium with voids and rotation
Authors: Poonia Ravinder , Deswal Sunita , Kalkal Kapil Kumar 
Published: February 2023

AbstractThe objective of present research work is to investigate the propagation of time harmonic plane waves in a rotating, nonlocal, transversely isotropic thermoelastic half‐space having void pores in the context of Lord–Shulman theory. It has been observed that four coupled plane waves travel in such type of medium with distinct speeds. Using appropriate boundary conditions, the amplitude and energy ratios for the reflected waves are presented. Numerical computations for a magnesium crystal‐like material are performed with the help of MATLAB software to study the effects of material anisotropy, nonlocal, void and rotation parameters on the amplitude ratios. The computational results are displayed and explained through graphs. The phase velocities of plane waves in transversely isotropic medium are found to depend upon the incident angle, whereas these attain constant values in an isotropic medium. The energy conservation law is also justified during the reflection phenomena.
Integrative analyses of bulk microarray data to discover genes, pathways, and immune infiltration characteristics associated with targeting of Ewing sarcoma
Authors: Cao Binjie , Sun Haijian , Fan Zhehao , Khawar Muhammad Babar , Cai Liangliang , Yu Shiyi , Liang Zhengyan , Lv Dan , Wang Ning , Bi Caili , Sun Haibo 
Published: February 2023

Abstract
Purpose
To explore transcriptome and immunological features of patients with Ewing sarcoma (ES) using all publicly available microarray data.

Methods

Data of 479 ES tissues were integrated and normalized. Gene expression, immune infiltration, and cancer-specific pathways were analyzed. Genes of interest were knocked down, followed by cell proliferation and colony formation assays.

Results

Consistent with the previous reports of differential expressed genes (DEGs) in ES, our analysis identified CCND1, HMCN1, and NKX2-2 were among the most highly expressed, while TWNC1, MYBPC1, and CKM were among the lowest expressed genes. GO, KEGG, and GSEA enrichment analysis identified that the DEGs related to bone and muscle functioning, those that contributed to crucial cellular, and metabolism pathways such as actin binding, apoptosis, TCA cycle, and cell cycle were also significantly enriched. Immune infiltration analysis discovered that many T cell subsets including CD4T, CD8 T, and Gamma delta T cells were highly infiltrated, while monocytes and B cells were less infiltrated in tumors. A total of 138 genes were both significantly up-regulated in tumors and associated with decreased survival, while 38 significantly down-regulated genes were associated with increased survival, many of which were previously reported as oncogenes and tumor suppressors in ES and other cancers. Silencing of four newly identified top ranked up-regulated genes with decreased survivals in ES inhibited proliferation and colony formation of ES cells.

Conclusion

This study may provide a clear representative transcriptome profile of ES, providing diagnostic biomarkers, pathways, and immune infiltrative characteristics targets for ES.
Sequential treatment of metastatic renal cell carcinoma patients after first-line vascular endothelial growth factor targeted therapy in a real-world setting: epidemiologic, noninterventional, retrospective–prospective cohort multicentre study
Authors: Cesas Alvydas , Urbonas Vincas , Tulyte Skaiste , Janciauskiene Rasa , Liutkauskiene Sigita , Grabauskyte Ingrida , Gaidamavicius Ignas 
Published: February 2023

Abstract
Purpose
The purpose of our study was to determine whether data on the clinical effectiveness of second-line therapy collected in a real-world setting provide additional valuable information on the optimal sequence of metastatic renal cell carcinoma (mRCC) treatment.

Methods
Patients diagnosed with mRCC who were treated with at least one dose of first-line vascular endothelial growth factor (VEGF)-targeted therapy with either sunitinib or pazopanib and with at least one dose of second-line everolimus, axitinib, nivolumab, or cabozantinib were included. The efficacy of different treatment sequences was analyzed based on the time to the second objective disease progression (PFS2) and the time to the first objective disease progression (PFS).

Results
Data from 172 subjects were available for analysis. PFS2 was 23.29 months. The 1-year PFS2 rate was 85.3%, and the 3-year PFS2 rate was 25.9%. The 1-year overall survival rate was 97.0%, and the 3-year overall survival rate was 78.6%. Patients with a lower IMDC prognostic risk group had a significantly (p < 0.001) longer PFS2. Patients with metastases in the liver had a shorter PFS2 than patients with metastases in the other sites (p = 0.024). Patients with metastases in the lungs and lymph nodes (p = 0.045) and patients with metastases in the liver and bones (p = 0.030) had lower PFS2 rates than patients with metastases in other sites.

Conclusions
Patients with a better IMDC prognosis have a longer PFS2. Metastases in the liver lead to a shorter PFS2 than metastases in other sites. One metastasis site means a longer PFS2 than 3 or more metastasis sites. Nephrectomy performed in an earlier stage of disease or metastatic setting means higher PFS and higher PFS2. No PFS2 difference was found between different treatment sequences of TKI–TKI or TKI-immune therapy.
On the potential of mapping sea level anomalies from satellite altimetry with Random Forest Regression
Authors: Passaro Marcello , Juhl Marie-Christin 
Published: February 2023

AbstractThe sea level observations from satellite altimetry are characterised by a sparse spatial and temporal coverage. For this reason, along-track data are routinely interpolated into daily grids. These grids are strongly smoothed in time and space and are generated using an optimal interpolation routine requiring several pre-processing steps and covariance characterisation. In this study, we assess the potential of Random Forest Regression to estimate daily sea level anomalies. Along-track sea level data from 2004 are used to build a training dataset whose predictors are the neighbouring observations. The validation is based on the comparison against daily averages from tide gauges. The generated dataset is on average 10% more correlated to the tide gauge records than the commonly used product from Copernicus. While the latter is more optimised for the detection of spatial mesoscales, we show how the methodology of this study has the potential to improve the characterisation of sea level variability.
Healing online? Social anxiety and emotion regulation in pandemic experience
Authors: Bortolan Anna 
Published: February 2023

AbstractDuring the pandemic of Covid-19, internet-based communication became for many the primary, or only, means of interaction with others, and it has been argued that this had a host of negative effects on emotional and mental health. However, some people with a lived experience of mental ill-health also perceived improvements to their wellbeing during the period in which social activities were moved online.In this paper, I explore the possibility that some of these improvements are due to the partial “disembodiment” of emotions facilitated by internet-mediated interaction. In particular, I consider the phenomenology of social anxiety and how it may be impacted upon by encountering others primarily through the medium of internet-enabled technology.I will start by reconstructing a phenomenological account of social anxiety to which disruptions of bodily experience are central. I will then move to consider how the experiential dynamics that are particularly prominent in social anxiety can be weakened when communicating with others via video calls, instant messages, and social media more broadly. I will suggest that this is the case due to the diminished visibility of the body online, and the higher degree of control and agency over one’s experience that can be exercised in this context.Finally, I will argue that the weakening of social anxiety through internet-mediated contact exemplifies some of the processes which are key to emotion regulation more widely, thus suggesting that communication and interaction online could have a positive effect on a wider range of affective disturbances.
Assessing Opioid Abuse in Chronic Pain Patients: Further Validation of the Prescription Opioid Misuse Index (POMI) Using Item Response Theory
Authors: Coloma-Carmona Ainhoa , Carballo José Luis 
Published: February 2023

AbstractDue the limitations of the previous validations, the purpose of this study was to further validate the Prescription Opioid Misuse Index (POMI) in a larger sample of chronic non-cancer pain (CNCP) patients and to examine differential item functioning (DIF) across sex. Participants (n=225 CNCP patients under long-term opioid therapy) completed patient characteristics, self-reported POMI and DSM-5 prescription opioid use disorder measurements. Reliability and factor structure were assessed using both item response theory and classical test theory. ROC curve analysis was used to establish the optimum cut-off score for detecting the presence of DSM-5 prescription opioid-use disorder. Concurrent validity was also tested. The POMI showed a unidimensional factor structure and acceptable internal consistency (ωcat =0.62). DIF analysis showed that males and females respond similarly to each item of the POMI, supporting unbiased measurement of the latent trait across both groups. A cut-off point of 2 is suggested in order to maximize the accuracy of the instrument as a first-screening tool for opioid misuse (AUC=0.78; p<0.001; CI 95%: 0.72–0.85). Concurrent validity of the POMI was high with DSM-5 moderate to severe opioid-use disorder criteria (OR=7.824, p<0.001). These results indicate that the POMI is a valid and clinically feasible screening instrument for detecting CNCP patients who misuse opioid medications. The short length of the scale could meet the needs of clinical practice as it allows clinicians to precisely identify and monitor prescription opioid misuse in both male and female patients.
Large-Kernel Attention for 3D Medical Image Segmentation
Authors: Li Hao , Nan Yang , Del Ser Javier , Yang Guang 
Published: February 2023

AbstractAutomated segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT) scans using deep learning methods can aid in diagnosing and treating cancer. However, organs often overlap and are complexly connected, characterized by extensive anatomical variation and low contrast. In addition, the diversity of tumor shape, location, and appearance, coupled with the dominance of background voxels, makes accurate 3D medical image segmentation difficult. In this paper, a novel 3D large-kernel (LK) attention module is proposed to address these problems to achieve accurate multi-organ segmentation and tumor segmentation. The advantages of biologically inspired self-attention and convolution are combined in the proposed LK attention module, including local contextual information, long-range dependencies, and channel adaptation. The module also decomposes the LK convolution to optimize the computational cost and can be easily incorporated into CNNs such as U-Net. Comprehensive ablation experiments demonstrated the feasibility of convolutional decomposition and explored the most efficient and effective network design. Among them, the best Mid-type 3D LK attention-based U-Net network was evaluated on CT-ORG and BraTS 2020 datasets, achieving state-of-the-art segmentation performance when compared to avant-garde CNN and Transformer-based methods for medical image segmentation. The performance improvement due to the proposed 3D LK attention module was statistically validated.
Using Extreme Value Theory to Assess the Mortality Risk of Tornado Outbreaks
Authors: Sales Vilane Gonçalves , Strobl Eric 
Published: February 2023

AbstractThe majority of tornado fatalities occur during severe thunderstorm occurrences that produce a large number of tornadoes, termed tornado outbreaks. This study used extreme value theory to estimate the impact of tornado outbreaks on fatalities while accounting for climate and demographic factors. The findings indicate that the number of fatalities increases with the increase of tornado outbreaks. Additionally, this study undertook a counterfactual analysis to determine what would have been the probability of a tornado outbreak under various climatic and demographic scenarios. The results of the counterfactual study indicate that the likelihood of increased mortality increases as the population forecast grows. Intensified El Niño events, on the other hand, reduce the likelihood of further fatalities. La Niña events are expected to increase probability of fatalities.
Von der romanhaften Geistesgeschichte zum Kooperationsgebot
Authors: Matuschek Stefan 
Published: February 2023

ZusammenfassungDer Beitrag schaut am Beispiel von Fritz Strich auf den Beginn der geistesgeschichtlichen Literaturforschung zurück, um dessen Methode gegen die damalige romanhafte Umsetzung zu aktualisieren.
Was für ein Zufall? Stichprobentheoretische Anmerkungen und Folgerungen aus Simulationsergebnissen für den bundesweiten Bürgerrat „Deutschlands Rolle in der Welt“
Authors: Baron Daniel 
Published: February 2023

ZusammenfassungAm Beispiel des bundesweiten Bürgerrats „Deutschlands Rolle in der Welt“, der im Frühjahr 2021 online stattfand, wird untersucht, inwieweit ein dabei angewendetes Zufallsverfahren zur Rekrutierung der 169 Teilnehmenden den Kriterien eines frequentistischen Wahrscheinlichkeitsverständnisses entsprach. Der Vorzug eines solchen frequentistischen gegenüber anderen Wahrscheinlichkeitsbegriffen, die zufallsgestützten Beteiligungsverfahren häufig zugrundeliegen, besteht darin, dass sich mittels entsprechender Ziehungsprozesse und Gütekriterien die Durchführungsbedingungen und Resultate dieser Verfahren intersubjektiv und methodisch kontrolliert beurteilen lassen. Erst auf dieser Basis sind zielorientierte Weiterentwicklung solcher Verfahren möglich. Aus einer stichprobentheoretischen Perspektive zeigt sich, dass die Annahme, wonach es sich um ein Zufallsverfahren handelte, im Falle des bundesweiten Bürgerrats nicht umgesetzt wurde und damit das Postulat einer annähernd spiegelbildlichen Abbildung der Sozialstruktur der jeweiligen Grundgesamtheit durch das entsprechende Gremium empirisch nicht überprüft werden konnte. Rekurrierend auf stochastische Simulationsstudien wird dargelegt, dass sich statt bewusster Auswahlen, wie sie im Rahmen des Bürgerrats neben Zufallselementen zum Einsatz kamen, proportional geschichtete Zufallsauswahlen eignen, um sich dem spiegelbildlichen Repräsentationsideal im Rahmen zukünftiger Bürgerräte anzunähern. Darüber hinaus sollten mittels Incentivierungsstrategien politisch unterrepräsentierte Personengruppen stärker als bislang in zufallsgestützte deliberative Gremien eingebunden werden, um die Umsetzung des spiegelbildlichen Repräsentationsideals weiter zu stärken. Praktische Empfehlungen implizieren zudem eine transparente methodische Berichtlegung, detaillierte Darstellungen der methodischen und praktischen Durchführungsbedingungen des Ziehungsverfahrens sowie die Angabe von Auswahlwahrscheinlichkeiten und Responseraten im Rahmen zukünftiger Bürgerräte und anderweitiger zufallsgestützter Beteiligungsverfahren.
Prioritisation of Environmental Improvement Projects in Deep-Level Mine Ventilation Systems
Authors: Swanepoel J. , Vosloo J. C. , van Laar J. H. , Pelser W. A. 
Published: February 2023

AbstractDeep-level underground mining costs in South Africa are continuously rising due to the increased depth at which gold is being mined, resulting in a rise in virgin rock temperature and an increase in cooling requirements. Therefore, mines must evaluate various ventilation and cooling optimisation projects required to be implemented throughout their life of mine (LOM). This study develops a method to identify and prioritise large capital expenditure (CAPEX) underground environmental improvement projects, to improve thermal comfort underground. The solution presents a ‘multi-criteria decision-making’ (MCDM) process, incorporating the ‘analytic hierarchy process’ (AHP) and the ‘technique for order performance by similarity to ideal solution’ (TOPSIS) into the method to provide for scientific decision-making. These projects are evaluated based on four criteria, namely project risk, the impact on the underground thermal comfort, cost, and implementation time. This study’s solution uses ventilation simulations to determine the impact of the projects on the underground environment. The identification and evaluation of an environmental improvement project to best suit the current economic climate, while improving underground conditions and decreasing the safety risk is an essential aspect of the solution developed in this study. The method was implemented on a mechanised deep-level underground mine and showed that surface refrigeration is the most suitable alternative, which was implemented at the case study mine as validation of the developed solution. The study proves that the MCDM method is an adequate solution to incorporate subjective criteria into the decision-making process, resulting in a scientific and structured approach to making significant and complex decisions.
One locus, several functional RNAs—emerging roles of the mechanisms responsible for the sequence variability of microRNAs
Authors: Orbán Tamás I. 
Published: February 2023

AbstractWith the development of modern molecular genetics, the original “one gene-one enzyme” hypothesis has been outdated. For protein coding genes, the discovery of alternative splicing and RNA editing provided the biochemical background for the RNA repertoire of a single locus, which also serves as an important pillar for the enormous protein variability of the genomes. Non-protein coding RNA genes were also revealed to produce several RNA species with distinct functions. The loci of microRNAs (miRNAs), encoding for small endogenous regulatory RNAs, were also found to produce a population of small RNAs, rather than a single defined product. This review aims to present the mechanisms contributing to the astonishing variability of miRNAs revealed by the new sequencing technologies. One important source is the careful balance of arm selection, producing sequentially different 5p- or 3p-miRNAs from the same pre-miRNA, thereby broadening the number of regulated target RNAs and the phenotypic response. In addition, the formation of 5', 3' and polymorphic isomiRs, with variable end and internal sequences also leads to a higher number of targeted sequences, and increases the regulatory output. These miRNA maturation processes, together with other known mechanisms such as RNA editing, further increase the potential outcome of this small RNA pathway. By discussing the subtle mechanisms behind the sequence diversity of miRNAs, this review intends to reveal this engaging aspect of the inherited “RNA world”, how it contributes to the almost infinite molecular variability among living organisms, and how this variability can be exploited to treat human diseases.