bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-frequency complex impedance analysis of the two-dimensional semiconducting MXene Ti2CO2
Authors: Mandia Anup Kumar , Kumar Rohit , Koshi Namitha Anna , Lee Seung-Cheol , Bhattacharjee Satadeep , Muralidharan Bhaskaran 
Published: August 2023

Abstract
The two-dimensional compound group of MXenes, which exhibit unique optical, electrical, chemical, and mechanical properties, are an exceptional class of transition metal carbides and nitrides. In addition to traditional applications in Li-S, Li-ion batteries, conductive electrodes, hydrogen storage, and fuel cells, the low lattice thermal conductivity coupled with high electron mobility in the semiconducting oxygen-functionalized MXene Ti2CO2 has led to the recent interests in high-performance thermoelectric and nanoelectronic devices. Apart from the above dc- transport applications, it is crucial to also understand ac- transport across them, given the growing interest in applications surrounding wireless communications and transparent conductors. In this work, we investigate using our recently developed ab
initio transport model, the real and imaginary components of electron mobility and conductivity to conclusively depict carrier transport beyond the room temperature for frequency ranges upto the terahertz range. We also contrast the carrier mobility and conductivity with respect to the Drude’s model to depict its inaccuracies for a meaningful comparison with experiments. Our calculations show the effect of acoustic deformation potential scattering, piezoelectric scattering, and polar optical phonon scattering mechanisms. Without relying on experimental data, our model requires inputs calculated from first principles using density functional theory. Our results set the stage for providing ab
initio based ac- transport calculations given the current research on MXenes for high-frequency applications.
Electrochemical detection of dopamine using WSe2 microsheets modified platinum electrode
Authors: Alhazmi Hassan A , Imran Mohd , Ahmed Shahzad , Albratty Mohammed , Makeen Hafiz A , Najmi Asim , Alam Md Shamsher 
Published: August 2023

Abstract
Transition metal dichalcogenides (TMDs) have been proven to possess many properties that are beneficial for the application of electrochemical detection. In this study, the tungsten diselenide (WSe2) was synthesized utilizing the hydrothermal method and used to modify the platinum electrode. The electrochemical behaviour of the WSe2-modified electrode was examined utilizing cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) methods. The electrode displays a wide linear range of 5–100 μM with a linear correlation coefficient of 0.986. The detection limit of this method was found to be 5 μM. The method has good stability and linear dependency on the scan rate.
Spin alignment of vector mesons from quark dynamics in a rotating medium*
Authors: Wei 魏 Minghua 明华 , Huang 黄 Mei 梅 
Published: August 2023

Abstract
Vorticities in heavy-ion collisions (HICs) are supposed to induce spin alignment and polarization phenomena of quarks and mesons. In this work, we analyze the spin alignment of vector mesons ϕ and ρ induced by rotation from quark dynamics in the framework of the Nambu-Jona-Lasinio (NJL) model. The rotating angular velocity induces mass splitting of spin components for vector

mesons

. This behavior contributes to the spin alignment of vector mesons

in an equilibrium medium and naturally explains the negative deviation of

for vector mesons. Incidentally, the positive deviation of

under the magnetic field can also be easily understood from quark dynamics.
A Better Candidate for Dark Matter is Cosmic Plasma
Authors: Zheng Yi-Jia 
Published: August 2023

Abstract
In the ΛCDM cosmological model, based on observations of supernovae Ia, the cosmic dark energy density is assumed to be ΩΛ ∼ 0.70 and the gravitational mass density is assumed to be Ω
m
∼ 0.30. Based on the assumption that the observed cosmic microwave background (CMB) is a thermal relic of the early hot universe, the cosmic plasma density should be small, i.e., Ω
b
∼ 0.05 (otherwise the Sunyaev-Zeldovich effect of the cosmic plasma would ruin the observed CMB's perfect blackbody spectrum). To fill the gap between Ω
m
and Ω
b
, non-baryonic dark matter Ω
c
∼ 0.25 is introduced into the ΛCDM model. If the CMB is the result of a partial thermal equilibrium between cosmic radiation and cosmic plasma, then the observed perfect blackbody spectrum of the CMB can coexist with cosmic plasma. In this case, it is not necessary to introduce non-baryonic cold dark matter into cosmological models. A better candidate for dark matter is the cosmic plasma.
Recent advancements and theranostics strategies in glioblastoma therapy
Authors: Baddam Sudhakar Reddy , Kalagara Sudhakar , Kuna Krishna , Enaganti Sreenivas 
Published: August 2023

Abstract
Glioblastoma (GBM) is the most aggressive and lethal malignant brain tumor, and it is challenging to cure with surgery and treatment. The prevention of permanent brain damage and tumor invasion, which is the ultimate cause of recurrence, are major obstacles in GBM treatment. Besides, emerging treatment modalities and newer genetic findings are helping to understand and manage GBM in patients. Accordingly, researchers are focusing on advanced nanomaterials-based strategies for tackling the various problems associated with GBM. In this context, researchers explored novel strategies with various alternative treatment approaches such as early detection techniques and theranostics approaches. In this review, we have emphasized the recent advancement of GBM cellular models and their roles in designing GBM therapeutics. We have added a special emphasis on the novel genetic and drug target findings as well as strategies for early detection. Besides, we have discussed various theranostic approaches such as hyperthermia therapy, phototherapy and image-guided therapy. Approaches utilized for targeted drug delivery to the GBM were also discussed. This article also describes the recent in vivo, in vitro and ex vivo advances using innovative theranostic approaches.
Generation of cell-laden GelMA microspheres using microfluidic chip and its cryopreservation method
Authors: Tan Jia , Li Jiahui , Zhou Xinli 
Published: August 2023

Abstract
Gelatin methacrylate (GelMA) hydrogels have been widely used in tissue engineering because of their excellent biological and physical properties. Here, we used a microfluidic flow-focusing chip based on polymethyl methacrylate to fabricate cell-laden GelMA hydrogel microspheres. Structures of the throat region and photo crosslinking region on the chip, flow rate ratio of GelMA and oil phase, and GelMA concentration were optimized to obtain the stable and suitable size of microspheres. Cell-laden GelMA microspheres can be cryopreserved by slow freezing and rapid freezing. The survival rate of encapsulated cells after rapid freezing was significantly higher than that of unencapsulated cells. There was no significant difference between the results of the rapid freezing of encapsulated cells with 5% DMSO and the traditional slow freezing of suspended cells with 10% DMSO. It demonstrates the possibility that GelMA hydrogel itself can replace some of the cryoprotective agents and has some protective effect on cells. Our study provides new ideas to optimize GelMA hydrogels for cell cryopreservation, facilitating the off-the-shelf availability of tissue-engineered constructs.
Processing and characterization of aligned electrospun gelatin/polycaprolactone nanofiber mats incorporating borate glass (13-93B3) microparticles
Authors: Ege Duygu , Pourshahrestani Sara , Iorio Francesco , Reinfelder Heike , de Ligny Dominique , Boccaccini Aldo R 
Published: August 2023

Abstract
Aligned biodegradable fibers incorporating bioactive glass particles are being highly investigated for tissue engineering applications. In this study, 5, 7 and 10 wt% melt-derived 1393B3 borate glass (BG) microparticles (average size: 3.15 µm) were incorporated in 83 wt% polycaprolactone (PCL) and 17 wt% gelatin (GEL) (83PCL/17GEL) solutions to produce aligned electrospun composite nanofiber mats. Addition of 5 wt% BG particles significantly increased the alignment of the nanofibers. However, further incorporation of BG particles led to reduced degree of alignment, likely due to an increase of viscosity. Mechanical tests indicated a tensile modulus and tensile strength of approximately 51 MPa and 3.4 MPa, respectively, for 5 wt% addition of 1393B3 BG microparticles, values considered suitable for soft tissue engineering applications. However, with the increasing amount of 1393B3 BG, the nanofiber mats became brittle. Contact angle was reduced after the addition of 5 wt% of 1393B3 BG particles from ∼45° to ∼39°. Cell culture studies with normal human dermal fibroblast (NHDF) cells indicated that 5 wt% 1393B3 BG incorporated nanofiber mats were cytocompatible whereas higher doping with 1393B3 BGs reduced biocompatibility. Overall, 5 wt% 1393B3 BG doped PCL/GEL nanofiber mats were aligned with high biocompatibility exhibiting desirable mechanical properties for soft tissue engineering, which indicates their potential for applications requiring aligned nanofibers, such as peripheral neural regeneration.
Repeated fires in forested peatlands in sporadic permafrost zone in Western Canada
Authors: Kuosmanen Niina , Väliranta Minna , Piilo Sanna , Tuittila Eeva-Stiina , Oksanen Pirita , Wallenius Tuomo 
Published: August 2023

Abstract
Wildfires play a crucial role in northern boreal peatland ecosystems, influencing the functioning of these ecosystems by affecting vegetation composition and biomass, peat accumulation patterns, and soil carbon stocks. Northern peatland ecosystems are under pressure due to climate warming and increasing anthropogenic stress. The frequency and severity of wildfires is predicted to increase in the coming years. Therefore, understanding long-term natural fire dynamics and their effect on peatland functionality will provide crucial information for peatland management and preservation policies. To investigate the long-term fire history of Western Canada and its effect on peat accumulation and vegetation succession, we analyzed macroscopic plant remains and charcoal within peat cores taken from five peatlands in the region. Records of the most recent fire events were derived from fire scars and documented fires in the study area. Regional long-term peatland fire patterns were examined by pooling together macroscopic charcoal records and calculating 100 year moving averages. All studied sites, except the northernmost one, demonstrated repeated fires throughout the past 1500 years, suggesting that fires have been an integral part of the peatland ecosystem in Western Canada. Compiled charcoal records indicated a peak in fire activity, with the highest abundance of charcoal for the period from the 1300s to the 1550s and decreasing fire activity during recent centuries. The clear and consistent post-fire increase in the abundance of Sphagnum mosses suggests a relatively rapid recovery of peatland ecosystems after burning. The regeneration pattern, where pre-fire vegetation repeatedly re-establishes, suggests that from a long-term perspective, fires do not necessarily have a negative effect on peatland functioning and peat accumulation. In conclusion, peatlands could remain as effective carbon sinks if their natural state is secured.
Divergent responses of permafrost degradation to precipitation increases at different seasons on the eastern Qinghai–Tibet Plateau based on modeling approach
Authors: Yang Jingjing , Wang Taihua , Yang Dawen 
Published: August 2023

Abstract
The Qinghai–Tibet Plateau (QTP) has responded to remarkable climate warming with dramatic permafrost degradation over the past few decades. Previous studies have mostly focused on permafrost responses to rising air temperature, while the effects of accompanying increases in precipitation remain contentious and largely unknown. In this study, a distributed process-based model was applied to quantify the impacts of increased precipitation on permafrost thermal regimes in a warming climate by employing model experiments in the source region of Yellow River (SRYR) on the eastern QTP. The results showed that the active layer thickness (ALT) of permafrost increased by 0.25 m during 2010–2019 compared to 2000 across the SRYR, which was primarily driven by climate warming. In contrast, the increased annual precipitation played a relatively limited role and just slightly mitigated active layer thickening by 0.03 m. Intriguingly, increased precipitation in the cold and warm seasons exerted opposite effects on permafrost across the SRYR. The increased precipitation in the cold season mainly promoted ALT increases, while the increased precipitation in the warm season mitigated ALT increases. In ∼81.0% of the permafrost across the SRYR, the cooling effects of warm season wetting outweighed the warming effects of cold season wetting; while at the transition zone where permafrost was unstable and degrading to seasonally frozen ground, the warming effects of cold season wetting played a relatively larger role which contributed to permafrost degradation. This study explored the physical mechanisms of permafrost thermal responses to climate wetting, thus providing a better understanding of permafrost change in a warmer and wetter climate on the QTP.
Diagnostic accuracy of eNose ‘breathprints’ for therapeutic drug monitoring of Tacrolimus trough levels in lung transplantation
Authors: Wijbenga Nynke , Muller Marjolein M , Hoek Rogier A S , Mathot Bas J , Seghers Leonard , Aerts Joachim G J V , de Winter Brenda C M , Bos Daniel , Manintveld Olivier C , Hellemons Merel E 
Published: August 2023

Abstract
In order to prevent long-term immunity-related complications after lung transplantation, close monitoring of immunosuppressant levels using therapeutic drug monitoring (TDM) is paramount. Novel electronic nose (eNose) technology may be a non-invasive alternative to the current invasive procedures for TDM. We investigated the diagnostic and categorization capacity of eNose breathprints for Tacrolimus trough blood plasma levels (TACtrough) in lung transplant recipients (LTRs). We performed eNose measurements in stable LTR attending the outpatient clinic. We evaluated (1) the correlation between eNose measurements and TACtrough, (2) the diagnostic capacity of eNose technology for TACtrough, and (3) the accuracy of eNose technology for categorization of TACtrough into three clinically relevant categories (low: <7 µg ml−1, medium: 7–10 µg ml−1, and high: >10 µg ml−1 ). A total of 186 measurements from 86 LTR were included. There was a weak but statistically significant correlation (r = 0.21, p = 0.004) between the eNose measurements and TACtrough. The root mean squared error of prediction for the diagnostic capacity was 3.186 in the training and 3.131 in the validation set. The accuracy of categorization ranged between 45%–63% for the training set and 52%–69% in the validation set. There is a weak correlation between eNose breathprints and TACtrough in LTR. However, the diagnostic as well as categorization capacity for TACtrough using eNose breathprints is too inaccurate to be applicable in TDM.
Enhance the photocatalytic activity of fluoride graphdiyne/TiO2 through introducing organic components
Authors: Wang Kaihang , Liu Jingyi , Zhang Luwei , Wang Ning 
Published: August 2023

Abstract
Structure engineering of hybrid materials has been proved to be an efficient method to screen out superior photocatalysis. The distribution and bonding environment of covalent linkage segments can be well regulated through structure decoration. Here, we propose a controlled strategy to optimize the photocatalytic performance of hybrid catalysts. Systematic adjusting of the performance can be achieved by introducing organic components into the carbon supporter. Under the guidance of this strategy, fluoride graphdiyne (FGDY) and phloroglucinol regulating FGDY (P-FGDY) is compounded with titanium dioxide (TiO2) under solvent thermal condition to obtain hybrid catalyst FGDY/TiO2 and P-FGDY/TiO2, respectively. Notably, the as-prepared P-FGDY/TiO2 exhibits superior enhancements towards photocatalytic degradation of rhodamine B, methylene blue, and levofloxacin under visible-light irradiation compared with FGDY/TiO2. These enhanced photocatalytic activities stem from the fact that the regulation of FGDY could further increase the photogenerated electron and hole separation efficiency of hybrid catalyst. This work provides a novel regulating pathway to optimize the photocatalytic activity of carbon-based hybrid photocatalysis material systems.
Anisotropic energy transfer near multi-layer black phosphorus
Authors: Nayem Suzit Hasan , Sikder Bejoy , Uddin Shiekh Zia 
Published: August 2023

Abstract
Energy transfer (ET) between quantum emitters is a key process for many scientific domains and technological applications, and can be influenced by strategic placement of appropriate materials in the vicinity. However, all explored conventional isotropic materials lacks directional control over this process. Here, we show that multilayered black phosphorus (bP), a novel anisotropic two-dimensional material, can simultaneously dramatically boost and directionally control ET rates in the near-field regime. We find that bP exhibits a critical thickness above which the ET rates increase by several orders of magnitude compared to vacuum. Moreover, we demonstrate that bP can manipulate the ET in specific in-plane directions due to its strong in-plane anisotropy. Our results build the framework and provide fundamental insights into the mechanisms of ET near anisotropic materials, and open up new possibilities for designing and optimizing ET-based devices, systems and applications.
Deep learning-based detection and identification of brain tumor biomarkers in quantitative MR-images
Authors: Tampu Iulian Emil , Haj-Hosseini Neda , Blystad Ida , Eklund Anders 
Published: August 2023

Abstract
The infiltrative nature of malignant gliomas results in active tumor spreading into the peritumoral edema, which is not visible in conventional magnetic resonance imaging (cMRI) even after contrast injection. MR relaxometry (qMRI) measures relaxation rates dependent on tissue properties and can offer additional contrast mechanisms to highlight the non-enhancing infiltrative tumor. To investigate if qMRI data provides additional information compared to cMRI sequences when considering deep learning-based brain tumor detection and segmentation, preoperative conventional (T1w per- and post-contrast, T2w and FLAIR) and quantitative (pre- and post-contrast R1, R2 and proton density) MR data was obtained from 23 patients with typical radiological findings suggestive of a high-grade glioma. 2D deep learning models were trained on transversal slices (n = 528) for tumor detection and segmentation using either cMRI or qMRI. Moreover, trends in quantitative R1 and R2 rates of regions identified as relevant for tumor detection by model explainability methods were qualitatively analyzed. Tumor detection and segmentation performance for models trained with a combination of qMRI pre- and post-contrast was the highest (detection Matthews correlation coefficient (MCC) = 0.72, segmentation dice similarity coefficient (DSC) = 0.90), however, the difference compared to cMRI was not statistically significant. Overall analysis of the relevant regions identified using model explainability showed no differences between models trained on cMRI or qMRI. When looking at the individual cases, relaxation rates of brain regions outside the annotation and identified as relevant for tumor detection exhibited changes after contrast injection similar to region inside the annotation in the majority of cases. In conclusion, models trained on qMRI data obtained similar detection and segmentation performance to those trained on cMRI data, with the advantage of quantitatively measuring brain tissue properties within a similar scan time. When considering individual patients, the analysis of relaxation rates of regions identified by model explainability suggests the presence of infiltrative tumor outside the cMRI-based tumor annotation.
Developing Consensus-Based Guidelines for Case Reporting in Aesthetic Medicine: Enhancing Transparency and Standardization
Authors: Rahman Eqram , Philip-Dormston Wolfgang G , Webb William Richard , Rao Parinitha , Carruthers Jean Diana , Carruthers Alastair , Swift Arthur , Goodman Greg Julian , Mosahebi Afshin , Nahai Foad 
Published: August 2023

Abstract
Clinical case reporting plays a vital role in sharing detailed patient narratives, providing insights into rare conditions, innovative treatments, and unexpected outcomes. However, existing reporting guidelines in aesthetic medicine fail to capture the specific nuances of procedures and outcomes in this field. The authors’ objectives were to develop comprehensive guidelines for Case REporting in Aesthetic Medicine (CREAM). The study employed a 3-phase consensus process, including a literature review, expert interviews, and a consensus meeting. A diverse group of 10 expert participants (plastic surgeons, dermatologists, noncore specialists, evidence-based medicine expert, and research scientist) in Phase I and 30 experienced aesthetic practitioners in Phase II contributed to the research. Statistical analysis was conducted to assess agreement levels among participants and explore associations and variations within the data. The participants represented various specialties, genders, LGBTQ+ identities, and ethnic backgrounds. The research resulted in the development of the CREAM guidelines, consisting of a 16-item checklist. The guidelines covered essential aspects of case reporting, such as patient and practice information, procedure details, clinical assessment and outcomes, adverse events, and ethical considerations. Statistical analysis indicated a high level of consensus among participants, as well as significant associations between checklist items. CREAM guidelines represent a step toward enhancing transparency and standardization in case reporting in aesthetic medicine. Adhering to these guidelines will allow authors to contribute to a robust evidence base, prioritize patient safety, and drive advancements aesthetic medicine.
Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis
Authors: Wang Robert , Helbig Ingo , Edmondson Andrew C , Lin Lan , Xing Yi 
Published: August 2023

Abstract
Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.