bluuebunny/crossref_metadata_2025 huggingface dataset:
Plexcitonic Nanorattles as Highly Efficient SERS‐Encoded Tags
Authors: Estévez‐Varela Carla , Núñez‐Sánchez Sara , Piñeiro‐Varela Paula , de Aberasturi Dorleta Jiménez , Liz‐Marzán Luis M. , Pérez‐Juste Jorge , Pastoriza‐Santos Isabel
Published: November 2023

Plexcitonic nanoparticles exhibit strong light‐matter interactions, mediated by localized surface plasmon resonances, and thereby promise potential applications in fields such as photonics, solar cells, and sensing, among others. Herein, these light‐matter interactions are investigated by UV‐visible and surface‐enhanced Raman scattering (SERS) spectroscopies, supported by finite‐difference time‐domain (FDTD) calculations. Our results reveal the importance of combining plasmonic nanomaterials and J‐aggregates with near‐zero‐refractive index. As plexcitonic nanostructures nanorattles are employed, based on J‐aggregates of the cyanine dye 5,5,6,6‐tetrachloro‐1,1‐diethyl‐3,3‐bis(4‐sulfobutyl)benzimidazolocarbocyanine (TDBC) and plasmonic silver‐coated gold nanorods, confined within mesoporous silica shells, which facilitate the adsorption of the J‐aggregates onto the metallic nanorod surface, while providing high colloidal stability. Electromagnetic simulations show that the electromagnetic field is strongly confined inside the J‐aggregate layer, at wavelengths near the upper plexcitonic mode, but it is damped toward the J‐aggregate/water interface at the lower plexcitonic mode. This behavior is ascribed to the sharp variation of dielectric properties of the J‐aggregate shell close to the plasmon resonance, which leads to a high opposite refractive index contrast between water and the TDBC shell, at the upper and the lower plexcitonic modes. This behavior is responsible for the high SERS efficiency of the plexcitonic nanorattles under both 633 nm and 532 nm laser illumination. SERS analysis showed a detection sensitivity down to the single‐nanoparticle level and, therefore, an exceptionally high average SERS intensity per particle. These findings may open new opportunities for ultrasensitive biosensing and bioimaging, as superbright and highly stable optical labels based on the strong coupling effect.
Dual‐Confinement Effect of Nanocages@Nanotubes Suppresses Polysulfide Shuttle Effect for High‐Performance Lithium–Sulfur Batteries
Authors: Yue Bin , Wang Lili , Zhang Ningyuan , Xie Yunrui , Yu Wensheng , Ma Qianli , Wang Jinxian , Liu Guixia , Dong Xiangting
Published: November 2023

The shuttle effect of lithium polysulfides (LiPSs) severely hinders the development and commercialization of lithium–sulfur batteries, and the design of high‐conductive carbon fiber‐host material has become a key solution to suppress the shuttle effect. In this work, a unique Co/CoN‐carbon nanocages@TiO2‐carbon nanotubes structure (NC@TiO2‐CNTs) is constructed using an electrospinning and nitriding process. Lithium–sulfur batteries using NC@TiO2‐CNTs as cathode host materials exhibit high sulfur utilization (1527 mAh g−1 at 0.2 C) and can still maintain a discharge capacity of 663 mAh g−1 at a high current density of 5 C, and the capacity loss is only 0.056% per cycle during 500 cycles at 1 C. It is worth noting that even under extreme conditions (sulfur‐loading = 90%, surface‐loading = 5.0 mg cm−2(S), and E/S = 6.63 µL mg−1), the lithium–sulfur batteries can still provide a reversible capacity of 4 mAh cm−2. Throughdensity functional theory calculations, it has been found that the Co/CoN heterostructures can adsorb and catalyze LiPSs conversion effectively. Simultaneously, the TiO2 can adsorb LiPSs and transfer Li+ selectively, achieving dual confinement for the shuttle effect of LiPSs (nanocages and nanotubes). The new findings provide a new performance enhancement strategy for the commercialization of lithium–sulfur batteries.
Probing the Mechanical Properties of 2D Materials via Atomic‐Force‐Microscopy‐Based Modulated Nanoindentation
Authors: Khan Ryan M. , Rejhon Martin , Li Yanxiao , Parashar Nitika , Riedo Elisa , Wixom Ryan R. , DelRio Frank W. , Dingreville Rémi
Published: November 2023

As the field of low‐dimensional materials (1D or 2D) grows and more complex and intriguing structures are continuing to be found, there is an emerging need for techniques to characterize the nanoscale mechanical properties of all kinds of 1D/2D materials, in particular in their most practical state: sitting on an underlying substrate. While traditional nanoindentation techniques cannot accurately determine the transverse Young's modulus at the necessary scale without large indentations depths and effects to and from the substrate, herein an atomic‐force‐microscopy‐based modulated nanomechanical measurement technique with Angstrom‐level resolution (MoNI/ÅI) is presented. This technique enables non‐destructive measurements of the out‐of‐plane elasticity of ultra‐thin materials with resolution sufficient to eliminate any contributions from the substrate. This method is used to elucidate the multi‐layer stiffness dependence of graphene deposited via chemical vapor deposition and discover a peak transverse modulus in two‐layer graphene. While MoNI/ÅI has been used toward great findings in the recent past, here all aspects of the implementation of the technique as well as the unique challenges in performing measurements at such small resolutions are encompassed.
Rethinking Electrochemical Deposition of Nickel Oxide for Photovoltaic Applications
Authors: Bogachuk Dmitry , Baretzky Clemens , Eckert Jonas , Yang Bowen , Suo Jiajia , Dangudubiyyam Uma Kousalya , Loukeris Georgios , Mohammadzadeh Hadi , Kluska Sven , Kohlstädt Markus , Würfel Uli
Published: November 2023

A thin layer of sputtered or wet‐processed nickel oxide (NiOx) is often used to fabricate perovskite solar cells (PSCs). Remarkably, NiOx can also be deposited by a recently developed electrochemical method, which is considered promising due to its short processing time, absence of high‐vacuum conditions, and ease of manufacturing. Such electrochemically deposited NiOx (eleNiOx) is obtained by applying an electric bias to the front electrode of a PSC or perovskite solar module (PSM). Therefore, the electrode sheet resistance affects the current distribution through it, creating a gradient in the amount of charge provided for the electrochemical reaction. Consequently, this leads to the inhomogeneity in the formed eleNiOx, which has numerous implications on the final photovoltaic performance of PSMs. In this work, the interdependencies between the electrode sheet resistance, current distribution, eleNiOx thickness gradient, and the caused power losses of large area PSMs are discussed. By coupling the experimental findings with our numerical simulations, it is found that heterogeneity in surface potential of even small‐sized modules can lead to severe differences in local eleNiOx thickness and photovoltaic performance. Therefore the potential drop across the front electrode is an inherent problem of this deposition method and potential approaches are proposed to minimize it.
Numerical study for MHD peristaltic flow of nanofluid with variable viscosity in the porous channel
Authors: Ahmed Bilal , Nisar Zahid , EI‐Sherbeeny Ahmed M.
Published: November 2023

Recent developments in biomedicine have raised the usage of silver (Ag) nanomaterials in enhancing the ability of drug delivery procedures. Magnetic fields are externally applied to guide the drugs towards a specific target. Peristalsis of nanofluid with variable viscosity is studied here. A porous media with varying porosity and permeability becomes saturated with the nanofluid. Temperature dependent viscosity and Maxwell's thermal conductivity models are adopted. Thermal and velocity slip constraints are considered in the study. Low Reynold number and long wavelength predictions are used to simplify governing equations. Simplified non‐dimensional equations are numerically tackled. NDSolve is built in shooting technique that are used in the Mathematica software. Effects of pertinent variables on pressure gradient, velocity, temperature and heat transport process are studied. Addition of silver nanoparticles enhances the heat transport characteristics. The axial velocity is reduced in the existence of an inclined magnetic aspects. Pressure gradient at the wall are increases by increasing the concentration of nanomaterial and magnetic field strength.
Therapeutic potential of Lawsonia inermis Linn: a comprehensive overview
Authors: Batiha Gaber El-Saber , Teibo John Oluwafemi , Shaheen Hazem M. , Babalola Benjamin Ayodipupo , Teibo Titilade Kehinde Ayandeyi , Al-kuraishy Hayder M. , Al-Garbeeb Ali I. , Alexiou Athanasios , Papadakis Marios
Published: November 2023

Lawsonia inermis Linn, commonly known as henna, is a member of the Lythraceae family and has been found to contain a variety of compounds with both industrial and medicinal applications in its stem, bark, roots, flowers, and seeds. This report provides a comprehensive review of the bioactive components, pharmacological activities, pharmacokinetics, and pharmacological side effects of Lawsonia inermis. Relevant materials were gathered from Google Scholar, PubMed, Scopus, and Web of Science and reviewed for important properties and updates about the plant. Lawsonia inermis contains a variety of bioactive compounds, including flavonoids, coumarins, triterpenoids, steroids, xanthones, polyphenols, fatty acids, alkaloids, quinones, tannins, leucocyandin, epicatechin, catechin, and quercetin. The plant is been traditionally used to treat numerous conditions, including ulcers, bronchitis, lumbago, hemicrania, leukoderma, scabies, boils, ophthalmic disorders, hair loss, and jaundice. It has also been found to possess a range of pharmacological activities, including antioxidant, anti-inflammatory, analgesic, antiparasitic, hepatoprotective, antifungal, antitumor, wound healing, and hypoglycemic effects. The potential of Lawsonia inermis for various biological applications is promising, and further studies are needed to fully explore its therapeutic benefits for various diseases of public health. Concern advances in drug development could enable the characterization of various bioactive constituents and facilitate their development and application for the benefit of humanity.
Open Innovation in Schools: A New Imperative for Organising Innovation in Education?
Authors: Pietsch Marcus , Cramer Colin , Brown Chris , Aydin Burak , Witthöft Jasmin
Published: November 2023

Schools are considered knowledge-creating organisations that find it difficult to develop and implement innovations on their own. Knowledge mobilisation is seen as the key to overcoming this problem. In particular, the use of external sources of knowledge is regarded as an important lever for change. However, there is a lack of concepts and empirical studies in educational research on the extent to which external knowledge is used for innovation in schools. Based on a sample of N = 411 schools, this article explores whether the concept of open innovation can be used in the context of education. Originating from the field of innovation research, open innovation regimes are seen as imperative if organisations are to create and benefit from technology. Multinomial logistic regression analyses show that mobilising external knowledge significantly increases the likelihood of implementing innovations in schools. A machine-learning approach reveals that it is necessary to tailor open innovation regimes to the specific conditions of any given school. In particular, with regard to the use of new technologies and innovations in the field of digitalisation, open innovation can be a lever for change.
Low circulating levels of miR-17 and miR-126-3p are associated with increased mortality risk in geriatric hospitalized patients affected by cardiovascular multimorbidity
Authors: Marchegiani Francesca , Recchioni Rina , Di Rosa Mirko , Piacenza Francesco , Marcheselli Fiorella , Bonfigli Anna Rita , Galeazzi Roberta , Matacchione Giulia , Cardelli Maurizio , Procopio Antonio Domenico , Corsonello Andrea , Cherubini Antonio , Antonicelli Roberto , Lombardi Giovanni , Lattanzio Fabrizia , Olivieri Fabiola
Published: November 2023

MultiMorbidity (MM), defined as the co-occurrence of two or more chronic conditions, is associated with poorer health outcomes, such as recurrent hospital readmission and mortality. As a group of conditions, cardiovascular disease (CVD) exemplifies several challenges of MM, and the identification of prognostic minimally invasive biomarkers to stratify mortality risk in patients affected by cardiovascular MM is a huge challenge. Circulating miRNAs associated to inflammaging and endothelial dysfunction, such as miR-17, miR-21-5p, and miR-126-3p, are expected to have prognostic relevance. We analyzed a composite profile of circulating biomarkers, including miR-17, miR-21-5p, and miR-126-3p, and routine laboratory biomarkers in a sample of 246 hospitalized geriatric patients selected for cardiovascular MM from the Report-AGE INRCA database and BioGER INRCA biobank, to evaluate the association with all-cause mortality during 31 days and 12 and 24 months follow-up. Circulating levels of miR-17, miR-126-3p, and some blood parameters, including neutrophil to lymphocyte ratio (NLR) and eGFR, were significantly associated with mortality in these patients. Overall, our results suggest that in a cohort of geriatric hospitalized patients affected by cardiovascular MM, lower circulating miR-17 and miR-126-3p levels could contribute to identify patients at higher risk of short- and medium-term mortality.
Some notes on the algebraic structure of linear recurrent sequences
Authors: Alecci Gessica , Barbero Stefano , Murru Nadir
Published: November 2023

Several operations can be defined on the set of all linear recurrent sequences, such as the binomial convolution (Hurwitz product) or the multinomial convolution (Newton product). Using elementary techniques, we prove that this set equipped with the termwise sum and the aforementioned products is an R-algebra, given any commutative ring R with identity. Moreover, we provide explicitly a characteristic polynomial of the Hurwitz product and Newton product of any two linear recurrent sequences. Finally, we also investigate whether these R-algebras are isomorphic, considering also the R-algebras obtained using the Hadamard product and the convolution product.
Clinical, Epidemiological, and Laboratory Features of Mayaro Virus Infection: a Systematic Review
Authors: Silva-Ramos Carlos Ramiro , Mejorano-Fonseca Julián A. , Hidalgo Marylin , Rodríguez-Morales Alfonso J. , Faccini-Martínez Álvaro A.
Published: November 2023

Purpose of Review

Mayaro virus is an arbovirus that circulates in a wild cycle transmitted by Haemagogus janthinomys; however, case reports in urban areas suggest that other arthropods could be acting as vectors. It shares several similarities with Chikungunya virus, being highly probable that many cases are being misdiagnosed. The disease caused by this pathogen is known as Mayaro fever, which is restricted to regions of Central and South America, mainly the Amazon rainforest. Cases of Mayaro fever have continuously been increasing, suggesting that Mayaro virus would become another major epidemic arbovirus in America.

Recent Findings

Four electronic databases were searched for articles in English and Spanish using the keywords “Mayaro” and “case.” A total of 234 cases were retrieved in the 23 selected manuscripts. Of all cases, most of them were male young adults, reported as autochthonous cases occurring mainly in Peru and Brazil, who were performing activities in wild rural areas. Fever, arthralgia, headache, myalgia, and retro-orbital pain were the main clinical manifestations. Most of the patients had laboratory parameters within the normal range, joint complications were evidenced in few cases, and all of them recovered without specific treatment.

Mayaro fever appears to be a mild self-limited disease that affects mainly males at productive age that are in contact with wild environments. However, further studies are required to establish its true pathogenic potential of Mayaro virus.
Evaluation of Biodegradability and Biocompatibility of Pure Zinc Coated with Zinc Phosphate for Cardiovascular Stent Applications
Authors: Wu Guan-Lin , Yen Chin-En , Lin Yi-Syuan , Yeh Ming-Long
Published: November 2023

Purpose

Percutaneous coronary intervention is widely used as a primary treatment for cardiovascular diseases. In this regard, it has been revealed from studies that zinc is a potential material for use in stents due to its intrinsic physiological relevance, biocompatibility, biodegradability, and pro-regeneration properties. However, localized corrosion and burst release of zinc ions might cause an early implant failure and a risky environment for vascular remodeling. To resolve these drawbacks effectively, a coating of zinc phosphate on pure zinc was fabricated in this study using a microwave-assisted chemical conversion method.

Methods

In this study, a comprehensive analysis was conducted through materials characterization, electrochemical testing, immersion testing, in vitro testing, and hemocompatibility evaluation to quantify the effect of zinc phosphate coating on zinc cardiovascular stents.

Results

It is revealed that the microstructures of the coatings are mainly composed of zinc phosphate and sodium zinc phosphate. The presence of sodium zinc phosphate could improve corrosion behavior. The assessment of in vitro biocompatibility for the zinc phosphate coatings revealed satisfactory cell viability and a stable and smooth degradation surface for cell adhesion. Furthermore, the zinc phosphate coatings exhibited nonhemolytic properties and inhibitions to the adhesion of platelets.

Conclusion

The zinc phosphate coatings could exhibit a uniform degradation behavior and a positive biological effect on vascular remodeling, and therefore, these coatings could be a promising surface treatment used in stent optimization for zinc.
Analysis and Prediction of Dockless Shared Bike Demand Evolving Around Urban Rail Transit Stations: Case Study in Shenzhen, China
Authors: Zhao Yingping , Wu Yiling , Zhang Xinfeng , Wang Yaowei , Zhang Zhenduo , Lu Hongyu , Ma Dongfang
Published: November 2023

The emergence of dockless shared bikes (DSB) has led to their use as an important transfer mode to urban rail transit (URT) stations. However, in highly populated areas such as subway stations in peak hours, there is increasing concern about the imbalance between the demand and supply of shared bikes. To promote smoother subway transfer trips using shared bikes, it is very important to estimate the DSB demand, especially the disparity in the volume of bike pick-up and drop-off demand around subway stations. This research first utilizes the Shenzhen metro usage data and DSB usage data, analyzes data regarding subway and shared bike usage, discusses their potential transfer uses, and finds great disparity in DSB demand between different subway stations. The catchment area method is used to estimate bike usage as a potential transfer mode to the subway, where the catchment area is defined as a radius of 150 m from the subway station center. The DSB trip demand is categorized into two types: pick-up and drop-off. The most recent deep learning method, adaptive graph convolutional recurrent network (AGCRN), is used to predict the DSB demand more accurately because of its ability in enabling the modeling of relationships between entities in a self-adapted graph, and the prediction is compared with long short-term memory (LSTM), spatiotemporal neural network (STNN), diffusion convolutional recurrent neural network (DCRNN), and Graph WaveNet. Results show that methods with graphs (STNN, DCRNN, Graph WaveNet, and AGCRN) perform better than LSTM, and methods with adaptive graphs (Graph WaveNet and AGCRN) outperform methods with static graphs in terms of mean absolute error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE). DSB prediction results show that AGCRN performs the best in this study. More data, particularly land use data and URT station volume data, are expected to improve the predictive accuracy of the method due to potentially improved graph representation of station characteristics and subway station volume correlations. And with more accurate prediction results, it will be possible to achieve a better balancing strategy for bike operation optimization for better bike usage, and thus for a higher transfer rate of DSB to subway.
Time series quantum classifiers with amplitude embedding
Authors: Cuéllar M. P. , Cano C. , Ruiz L. G. B. , Servadei L.
Published: November 2023

Quantum Machine Learning was born during the past decade as the intersection of Quantum Computing and Machine Learning. Today, advances in quantum computer hardware and the design of simulation frameworks able to run quantum algorithms in classic computers make it possible to extend classic artificial intelligence models to a quantum environment. Despite these achievements, several questions regarding the whole quantum machine learning pipeline remain unanswered, for instance the problem of classical data representation on quantum hardware, or the methodologies for designing and evaluating quantum models for common learning tasks such as classification, function approximation, clustering, etc. These problems become even more difficult to solve in the case of Time Series processing, where the context of past historical data may influence the behavior of the decision-making model. In this piece of research, we address the problem of Time Series classification using quantum models, and propose an efficient and compact representation of time series in quantum data using amplitude embedding. The proposal is capable of representing a time series of length n in $$log_2(n)$$

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o

g
2

(
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computational units, and experiments conducted on benchmark time series classification problems show that quantum models designed for classification can also outperform the accuracy of classic methods.
A Comparison of the Most Intense Periods (MIPs) During Competitive Matches and Training Over an 8-Week Period in a Male Elite Field Hockey Team
Authors: Büchel Daniel , Döring Michael , Baumeister Jochen
Published: November 2023

Purpose

Wearables serve to quantify the on-court activity in intermittent sports such as field hockey (FH). Based on objective data, benchmarks can be determined to tailor training intensity and volume. Next to average and accumulated values, the most intense periods (MIPs) during competitive FH matches are of special interest, since these quantify the peak intensities players experience throughout the intermittent matches. The aim of this study was to retrospectively compare peak intensities between training and competition sessions in a male FH team competing in the first german division.

Methods

Throughout an 8-week in-season period, 372 individual activity datasets (144 datasets from competitive sessions) were recorded using the Polar Team Pro sensor (Kempele, Finland). MIPs were calculated applying a rolling window approach with predefined window length (1–5 min) and calculated for Total distance, High-Intensity-Running distance (> 16 km/h), Sprinting distance (> 20 km/h) and Acceleration load. Significant differences between training and competition MIPs were analysed through non-parametric statistical tests (P < 0.05).

Results

Analyses revealed higher MIPs during competition for all considered outcomes (P < 0.001). Effect size estimation revealed strongest effects for sprinting distance (d = 1.89 to d = 1.22) and lowest effect sizes for acceleration load (d = 0.92 to d = 0.49).

Conclusion

The present findings demonstrate that peak intensities during training do not reach those experienced during competitive sessions in a male FH team. Training routines such as manipulations of court-dimensions and team sizes might contribute to this discrepancy. Coaches should compare training and competition intensities to recalibrate training routines to optimize athletes’ preparation for competition.
The ECODENT Model for Enhancing Pro-environmental Behaviors in Dentists
Authors: Antoniadou Maria
Published: November 2023

Climate change challenges people’s lives and sustainability. Environmental problems seem to derive from human behavior. Dentistry has a high ecological footprint that needs to be controlled worldwide. Thus, the behavior change of dentists is a necessary condition to improve the environmental situation. In this study, a system dynamics approach is used to analyze pro-environmental behavior in dentists. Systemic modelling and simulation allow researchers to predict how the population of non-eco-dentists will change if certain factors are affected and how much time will be needed by the system of a group of dental professionals to become eco-dentists. To this end, the ECODENT model is presented, which was developed using the Vensim software. It is based on the classic Word of Mouth (WOM) model, which simulates how the WOM influences the spread of information among colleagues and stakeholders (e.g., patients, auxiliary staff, and community). The model incorporates relevant factors such as dental income, state support, CaPex and OpEx, education hours, level of urbanization, and time to react. By changing each one of them, we can observe the changes in the groups of non-eco and eco dentists as well as the flow of the phenomenon/transition. The simulation of this model shows that by augmenting WOM parameters, state economic support, or education hours while diminishing CaPex and OpEx, changes in the pro-environmental behaviors of dentists will be reported in a shorter time. The ECODENT model can be used to further study pro-environmentalism in different dental groups and associations and design relevant eco-friendly educational programs.
Distilling base-and-meta network with contrastive learning for few-shot semantic segmentation
Authors: Chen Xinyue , Wang Yueyi , Xu Yingyue , Shi Miaojing
Published: November 2023

Current studies in few-shot semantic segmentation mostly utilize meta-learning frameworks to obtain models that can be generalized to new categories. However, these models trained on base classes with sufficient annotated samples are biased towards these base classes, which results in semantic confusion and ambiguity between base classes and new classes. A strategy is to use an additional base learner to recognize the objects of base classes and then refine the prediction results output by the meta learner. In this way, the interaction between these two learners and the way of combining results from the two learners are important. This paper proposes a new model, namely Distilling Base and Meta (DBAM) network by using self-attention mechanism and contrastive learning to enhance the few-shot segmentation performance. First, the self-attention-based ensemble module (SEM) is proposed to produce a more accurate adjustment factor for improving the fusion of two predictions of the two learners. Second, the prototype feature optimization module (PFOM) is proposed to provide an interaction between the two learners, which enhances the ability to distinguish the base classes from the target class by introducing contrastive learning loss. Extensive experiments have demonstrated that our method improves on the PASCAL-5i under 1-shot and 5-shot settings, respectively.
Writing the History of Global Slavery
Authors: Burnard Trevor
Published: November 2023

This Element shows that existing models of global slavery derived from sociology and modelled closely on antebellum American slavery being normative should be replaced a global slavery that is less American and more global. It argues that we can understand the global history of slavery if we connect it more closely to another important world institution – empires in ways that historicise the study of history as an institution with a history that changes over time and space. Moreover, we can learn from scholars of modern slavery and use more than we do the enormous proliferation of usable sources about the lives, experiences and thoughts of the enslaved, from ancient to modern times, to make these voices of the enslaved crucial drivers of how we conceptualise and describe the varied kinds of global slavery in world history. This title is also available as Open Access on Cambridge Core.
Real-time reconfigurable metasurfaces enabling agile terahertz wave front manipulation
Authors: Zhou Huixian , Zhang Cheng
Published: November 2023

Real-time controlled programmable metasurfaces, having an array-of-subarrays architecture under the control of one-bit digital coding sequence, are demonstrated for rapid and precise multifunctional Terahertz wave front engineering.
Cross-species epigenetic regulation of nucleus accumbens KCNN3 transcripts by excessive ethanol drinking
Authors: Mulholland Patrick J. , Padula Audrey E. , Wilhelm Larry J. , Park Byung , Grant Kathleen A. , Ferguson Betsy M. , Cervera-Juanes Rita
Published: November 2023

The underlying genetic and epigenetic mechanisms driving functional adaptations in neuronal excitability and excessive alcohol intake are poorly understood. Small-conductance Ca2+-activated K+ (KCa2 or SK) channels encoded by the KCNN family of genes have emerged from preclinical studies as a key contributor to alcohol-induced functional neuroadaptations in alcohol-drinking monkeys and alcohol-dependent mice. Here, this cross-species analysis focused on KCNN3 DNA methylation, gene expression, and single nucleotide polymorphisms, including alternative promoters in KCNN3, that could influence surface trafficking and function of KCa2 channels. Bisulfite sequencing analysis of the nucleus accumbens tissue from alcohol-drinking monkeys and alcohol-dependent mice revealed a differentially methylated region in exon 1A of KCNN3 that overlaps with a predicted promoter sequence. The hypermethylation of KCNN3 in the accumbens paralleled an increase in the expression of alternative transcripts that encode apamin-insensitive and dominant-negative KCa2 channel isoforms. A polymorphic repeat in macaque KCNN3 encoded by exon 1 did not correlate with alcohol drinking. At the protein level, KCa2.3 channel expression in the accumbens was significantly reduced in very heavy-drinking monkeys. Together, our cross-species findings on epigenetic dysregulation of KCNN3 represent a complex mechanism that utilizes alternative promoters to potentially impact the firing of accumbens neurons. Thus, these results provide support for hypermethylation of KCNN3 as a possible key molecular mechanism underlying harmful alcohol intake and alcohol use disorder.
Inhibition of SF3B1 improves the immune microenvironment through pyroptosis and synergizes with αPDL1 in ovarian cancer
Authors: Wang Shourong , Liu Yao , Xiao Huimin , Chen Zhongshao , Yang Xiaohang , Yin Jingjing , Li Yingwei , Yuan Cunzhong , Yan Shi , Chen Gang , Gao Qinglei , Kong Beihua , Sun Chaoyang , Song Kun
Published: November 2023

Ovarian cancer is resistant to immune checkpoint blockade (ICB) treatment. Combination of targeted therapy and immunotherapy is a promising strategy for ovarian cancer treatment benefit from an improved immune microenvironment. In this study, Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) cohorts were used to screen prognosis and cytotoxic lymphocyte infiltration-associated genes in upregulated genes of ovarian cancer, tissue microarrays were built for further verification. In vitro experiments and mouse (C57/BL6) ovarian tumor (ID8) models were built to evaluate the synergistic effect of the combination of SF3B1 inhibitor and PD-L1 antibody in the treatment of ovarian cancer. The results show that SF3B1 is shown to be overexpressed and related to low cytotoxic immune cell infiltration in ovarian cancer. Inhibition of SF3B1 induces pyroptosis in ovarian cancer cells and releases mitochondrial DNA (mtDNA), which is englobed by macrophages and subsequently activates them (polarization to M1). Moreover, pladienolide B increases cytotoxic immune cell infiltration in the ID8 mouse model as a SF3B1 inhibitor and increases the expression of PD-L1 which can enhance the antitumor effect of αPDL1 in ovarian cancer. The data suggests that inhibition of SF3B1 improves the immune microenvironment of ovarian cancer and synergizes ICB immunotherapy, which provides preclinical evidence for the combination of SF3B1 inhibitor and ICB to ovarian cancer treatment.
Mitoguardin 1 and 2 promote granulosa cell proliferation by activating AKT and regulating the Hippo-YAP1 signaling pathway
Authors: Yan Ming-Qi , Zhu Bing-Hong , Liu Xiao-Hong , Yang Yu-Meng , Duan Xiu-Yun , Wang Yong , Sun Hui , Feng Mei , Li Tao , Liu Xiao-Man
Published: November 2023

Mitochondria have been identified to be involved in oxidative phosphorylation, lipid metabolism, cell death, and cell proliferation. Previous studies have demonstrated that mitoguardin (Miga), a mitochondrial protein that governs mitochondrial fusion, mitochondria-endoplasmic reticulum (ER) contacts, lipid formation, and autophagy, is crucial for ovarian endocrine and follicular development. Nevertheless, whether mammalian MIGA1 or MIGA2 (MIGA1,-2) regulates ovarian granulosa cell proliferation remains unclear. This study revealed that mammalian MIGA1,-2 promotes cell proliferation and regulates the phosphorylation and localization of Yes-associated protein 1 (YAP1) in ovarian granulosa cells. MIGA2 upregulation resulted in reduced YAP1 activity, while MIGA2 removal led to increased YAP1 activity. Further analysis indicated that MIGA1,-2 regulated YAP1 via the Hippo signaling pathway and regulated protein kinase B (AKT) activity in collaboration with YAP1. In addition, lysophosphatidic acid (LPA) regulated MIGA2 expression and AKT activity by activating YAP1. Briefly, we demonstrated that the mitochondrial MIGA1 and MIGA2, especially MIGA2, promoted cellular proliferation by activating AKT and regulating the Hippo/YAP1 signaling pathway in ovarian granulosa cells, which may contribute to the molecular pathogenesis of reproductive endocrine diseases, such as polycystic ovary syndrome (PCOS).
Universal selective transfer printing via micro-vacuum force
Authors: Park Sang Hyun , Kim Tae Jin , Lee Han Eol , Ma Boo Soo , Song Myoung , Kim Min Seo , Shin Jung Ho , Lee Seung Hyung , Lee Jae Hee , Kim Young Bin , Nam Ki Yun , Park Hong-Jin , Kim Taek-Soo , Lee Keon Jae
Published: November 2023

Transfer printing of inorganic thin-film semiconductors has attracted considerable attention to realize high-performance soft electronics on unusual substrates. However, conventional transfer technologies including elastomeric transfer printing, laser-assisted transfer, and electrostatic transfer still have challenging issues such as stamp reusability, additional adhesives, and device damage. Here, a micro-vacuum assisted selective transfer is reported to assemble micro-sized inorganic semiconductors onto unconventional substrates. 20 μm-sized micro-hole arrays are formed via laser-induced etching technology on a glass substrate. The vacuum controllable module, consisting of a laser-drilled glass and hard-polydimethylsiloxane micro-channels, enables selective modulation of micro-vacuum suction force on microchip arrays. Ultrahigh adhesion switchability of 3.364 × 106, accomplished by pressure control during the micro-vacuum transfer procedure, facilitates the pick-up and release of thin-film semiconductors without additional adhesives and chip damage. Heterogeneous integration of III-V materials and silicon is demonstrated by assembling microchips with diverse shapes and sizes from different mother wafers on the same plane. Multiple selective transfers are implemented by independent pressure control of two separate vacuum channels with a high transfer yield of 98.06%. Finally, flexible micro light-emitting diodes and transistors with uniform electrical/optical properties are fabricated via micro-vacuum assisted selective transfer.
Discovery of a non-canonical prototype long-chain monoacylglycerol lipase through a structure-based endogenous reaction intermediate complex
Authors: Pinotsis Nikos , Krüger Anna , Tomas Nicolas , Chatziefthymiou Spyros D. , Litz Claudia , Mortensen Simon Arnold , Daffé Mamadou , Marrakchi Hedia , Antranikian Garabed , Wilmanns Matthias
Published: November 2023

The identification and characterization of enzyme function is largely lacking behind the rapidly increasing availability of large numbers of sequences and associated high-resolution structures. This is often hampered by lack of knowledge on in vivo relevant substrates. Here, we present a case study of a high-resolution structure of an unusual orphan lipase in complex with an endogenous C18 monoacylglycerol ester reaction intermediate from the expression host, which is insoluble under aqueous conditions and thus not accessible for studies in solution. The data allowed its functional characterization as a prototypic long-chain monoacylglycerol lipase, which uses a minimal lid domain to position the substrate through a hydrophobic tunnel directly to the enzyme’s active site. Knowledge about the molecular details of the substrate binding site allowed us to modulate the enzymatic activity by adjusting protein/substrate interactions, demonstrating the potential of our findings for future biotechnology applications.
Metal-organic framework boosts heterogeneous electron donor–acceptor catalysis
Authors: Lin Jiaxin , Ouyang Jing , Liu Tianyu , Li Fengxing , Sung Herman Ho-Yung , Williams Ian , Quan Yangjian
Published: November 2023

Metal-organic framework (MOF) is a class of porous materials providing an excellent platform for engineering heterogeneous catalysis. We herein report the design of MOF Zr-PZDB consisting of Zr6-clusters and PZDB (PZDB = 4,4’-(phenazine-5,10-diyl)dibenzoate) linkers, which served as the heterogeneous donor catalyst for enhanced electron donor–acceptor (EDA) photoactivation. The high local concentration of dihydrophenazine active centers in Zr-PZDB can promote the EDA interaction, therefore resulting in superior catalytic performance over homogeneous counterparts. The crowded environment of Zr-PZDB can protect the dihydrophenazine active center from being attacked by radical species. Zr-PZDB efficiently catalyzes the Minisci-type reaction of N-heterocycles with a series of C-H coupling partners, including ethers, alcohols, non-activated alkanes, amides, and aldehydes. Zr-PZDB also enables the coupling reaction of aryl sulfonium salts with heterocycles. The catalytic activity of Zr-PZDB extends to late-stage functionalization of bioactive and drug molecules, including Nikethamide, Admiral, and Myristyl Nicotinate. Systematical spectroscopy study and analysis support the EDA interaction between Zr-PZDB and pyridinium salt or aryl sulfonium salt, respectively. Photoactivation of the MOF-based EDA adduct triggers an intra-complex single electron transfer from donor to acceptor, giving open-shell radical species for cross-coupling reactions. This research represents the first example of MOF-enabled heterogeneous EDA photoactivation.
Antarctic daily mesoscale air temperature dataset derived from MODIS land and ice surface temperature
Authors: Nielsen Eva Bendix , Katurji Marwan , Zawar-Reza Peyman , Meyer Hanna
Published: November 2023

Knowledge about local air temperature variations and extremes in Antarctica is of large interest to many polar disciplines such as climatology, glaciology, hydrology, and ecology and it is a key variable to understand climate change. Due to the remote and harsh conditions of Antarctica’s environment, the distribution of air temperature observations from Automatic Weather Stations is notably sparse across the region. Previous studies have shown that satellite-derived land and ice surface temperatures can be used as a suitable proxy for air temperature. Here, we developed a daily near-surface air temperature dataset, AntAir ICE for terrestrial Antarctica and the surrounding ice shelves by modelling air temperature from MODIS skin temperature for the period 2003 to 2021 using a linear model. AntAir ICE has a daily temporal resolution and a gridded spatial resolution of 1 km2. AntAir ICE has a higher accuracy in reproducing in-situ measured air temperature when compared with the well-established climate re-analysis model ERA5 and a higher spatial resolution which highlights its potential for monitoring temperature patterns in Antarctica.
Fractal basins as a mechanism for the nimble brain
Authors: Bollt Erik , Fish Jeremie , Kumar Anil , Roque dos Santos Edmilson , Laurienti Paul J.
Published: November 2023

An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple stable states corresponding to specific patterns of brain activity/connectivity. In this article, we describe chimera states, which are patterns consisting of mixed synchrony and incoherence, in a brain-inspired dynamical systems model composed of a network with weak individual interactions and chaotic/periodic local dynamics. We illustrate the mechanism using synthetic time series interacting on a realistic anatomical brain network derived from human diffusion tensor imaging. We introduce the so-called vector pattern state (VPS) as an efficient way of identifying chimera states and mapping basin structures. Clustering similar VPSs for different initial conditions, we show that coexisting attractors of such states reveal intricately “mingled” fractal basin boundaries that are immediately reachable. This could explain the nimble brain’s ability to rapidly switch patterns between coexisting attractors.
Design and fabrication of a magnetic nanobiocomposite based on flaxseed mucilage hydrogel and silk fibroin for biomedical and in-vitro hyperthermia applications
Authors: Radinekiyan Fateme , Eivazzadeh-Keihan Reza , Naimi-Jamal Mohammad Reza , Aliabadi Hooman Aghamirza Moghim , Bani Milad Salimi , Shojaei Shirin , Maleki Ali
Published: November 2023

In this research work, a magnetic nanobiocomposite is designed and presented based on the extraction of flaxseed mucilage hydrogel, silk fibroin (SF), and Fe3O4 magnetic nanoparticles (Fe3O4 MNPs). The physiochemical features of magnetic flaxseed mucilage hydrogel/SF nanobiocomposite are evaluated by FT-IR, EDX, FE-SEM, TEM, XRD, VSM, and TG technical analyses. In addition to chemical characterization, given its natural-based composition, the in-vitro cytotoxicity and hemolysis assays are studied and the results are considerable. Following the use of highest concentration of magnetic flaxseed mucilage hydrogel/SF nanobiocomposite (1.75 mg/mL) and the cell viability percentage of two different cell lines including normal HEK293T cells (95.73%, 96.19%) and breast cancer BT549 cells (87.32%, 86.9%) in 2 and 3 days, it can be inferred that this magnetic nanobiocomposite is biocompatible with HEK293T cells and can inhibit the growth of BT549 cell lines. Besides, observing less than 5% of hemolytic effect can confirm its hemocompatibility. Furthermore, the high specific absorption rate value (107.8 W/g) at 200 kHz is generated by a determined concentration of this nanobiocomposite (1 mg/mL). According to these biological assays, this magnetic responsive cytocompatible composite can be contemplated as a high-potent substrate for further biomedical applications like magnetic hyperthermia treatment and tissue engineering.
VarLOCK: sequencing-independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance
Authors: Nan Xinsheng , Hardinge Patrick , Hoehn Sven , Dighe Shrinivas Nivrutti , Ukeri John , Pease Darius F. , Griffin Joshua , Warrington Jessica I. , Saud Zack , Hottinger Emma , Webster Gordon , Jones Davey , Kille Peter , Weightman Andrew , Stanton Richard , Castell Oliver K. , Murray James A. H. , Jurkowski Tomasz P.
Published: November 2023

The COVID-19 pandemic demonstrated the need for rapid molecular diagnostics. Vaccination programs can provide protection and facilitate the opening of society, but newly emergent and existing viral variants capable of evading the immune system endanger their efficacy. Effective surveillance for Variants of Concern (VOC) is therefore important. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. Here we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to provide rapid and sensitive discrimination of SARS-CoV-2 VOCs that can be used at point of care, implemented in the pipelines of small or large testing facilities, and even determine the proportion of VOCs in pooled population-level wastewater samples. This technology complements sequencing efforts to allow facile and rapid identification of individuals infected with VOCs to help break infection chains. We show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants and the rapid adaptability of the technique for new and emerging VOCs.
Inverse association between adult height and diabetes risk in a cohort study of Chinese population
Authors: Li Xiaoli , Cheng Tiantian , Leng Lina , Song Guangyao , Ma Huijuan
Published: November 2023

Recent studies linking adult height to diabetes risk remain controversial and few were from Asia. This study, therefore, aimed to explore the association of adult height with diabetes risk in a Chinese population. This retrospective cohort study was a secondary analysis of data from the DATADRYAD website, involving 211,172 non-diabetic individuals aged ≥ 20 years from the health screening program in China. Cox regression models were employed to evaluate hazard ratios (HRs) with 95% confidence interval (CI) of diabetes related to height. During an average 3.12-year follow-up, 4156 (1.97%) subjects reported developing diabetes. After adjusting for potential confounding factors, an inverse association of height with diabetes risk was observed among men and women [HR per 10 cm (95% CI), 0.78 (0.73–0.83) and 0.76 (0.68–0.86), respectively]. Moreover, subgroup analyses indicated the inverse association was only detected in individuals with aged < 70 years, fasting plasma glucose (FPG) < 6.1 mmol/L, and men with body mass index (BMI) < 28 kg/m2. In brief, height is inversely associated with diabetes risk in Chinese adults. Specifically, this association appears to be more pronounced in individuals with aged < 70 years, FPG < 6.1 mmol/L, and men with BMI < 28 kg/m2.