bluuebunny/crossref_metadata_2025 huggingface dataset:
Switching Behavior of the Composite Low Dimensional Structural Hybrids of Carbon After UV Exposure
Authors: Saini Sonia , Bhattacharjee Kuntala , Gouda Girish M
Published: April 2024

Low dimensional multi structural components of carbon are of great interest currently owing to their applications in developing flexible plastic electronics. In this work, we discuss emergence of different structural hybrids of carbon from as-prepared HiPCO SWCNTs subjecting them to oxidative acid purification and covalent functionalization process. Transmission electron microscopy (TEM) investigations reveal single wall carbon nanotubes (SWCNTs) serve as a building block to obtain multi wall carbon nanotubes (MWCNTs), graphene sheets (GS), carbon nano scrolls (CNS) structures which coexist in the sample. These structures when grafted with polymer binder and spray coated on Si substrate provide highly sustainable thin film coatings that are stable even in adverse space conditions [1]. These CNT and CNS based composite coatings are promising candidates for stray light control space applications exhibiting a low reflectance of the order of 2-3% in the visible spectral range [1]. Electrical switching behaviour of these films were investigated by capturing current(time) (I(t)) response, displaying promising switching character with distinct ON-OFF cycle. These coatings offer opportunities for the development of facile, cost-effective carbon-based devices without going into the nontrivial task of separating different the structures.
Influence of Zirconium substitution on electrical properties of Nickel-Zinc Ferrites
Authors: Sajjan Soumya , Kulkarni Ananda , Gounhalli Shivraj G.
Published: April 2024

The Zirconium substituted Nickel Zinc Ferrite nano particles with chemical composition of Ni(0.5-x)Zn(0.5-x)ZrxFe2O4, where the value of x varies from 0 to 0.2, have been synthesized by the sol-gel auto combustion method, using high purity nitrates and fuelling agent citric acid. The structural property was studies from X-ray diffraction spectra. The crystallite size decreases with increase in Zirconium substitution. The electrical property of the same was investigated by studying the dielectric constant, and AC conductivity. There are fluctuations in these properties with variation in Zirconium substitution in Ni-Zn Ferrite.
Predicting shock hugoniot and equation of state of single-crystal molybdenum by molecular dynamics simulation
Authors: Singla Anuradha , Ray Aditi
Published: April 2024

In the present paper, we employ non-equilibrium molecular dynamics approach to simulate impact-induced shock propagation in single-crystal Molybdenum. Shock hugoniot, generated by simulation of impact with varied strength shows excellent agreement with experimental data in the strong shock regime. The resulting hugoniot parameters obtained by linear fitting of shock velocity vs. particle velocity data are then used to estimate ambient pressure Grüneisen coefficient. Finally Mie-Grüneisen equation of state (EOS) with hugoniot as reference state, is employed to express pressure-volume-energy relationship for [001] single-crystal Mo. The influence of different analytical forms for volume dependence of Grüneisen parameter on EOS is investigated.
Influence of Zr-doping on the structure and transport properties of rare earth high-entropy oxides
Authors: Kante Mohana V , Lakshmi Nilayam Ajai R , Kreka Kosova , Hahn Horst , Bhattacharya Subramshu S , Velasco Leonardo , Tarancón Albert , Kübel Christian , Schweidler Simon , Botros Miriam
Published: April 2024

Fluorite-type ceria-based ceramics are well established as oxygen ion conductors due to their high conductivity, superseding state-of-the-art electrolytes such as yttria-stabilized zirconia. However, at a specific temperature and oxygen partial pressure they occasionally exhibit electronic conduction attributed to polaron hopping via multivalent cations (e.g. Pr and Ce). (Ce, La, Pr, Sm, Y)O2−δ
is a high-entropy oxide with a fluorite-type structure, featuring low concentrations of multivalent cations that could potentially mitigate polaron hopping. However, (Ce, La, Pr, Sm, Y)O2−δ
undergoes a structural transition to the bixbyite-type structure above 1000 °C. In this study, we introduce Zr doping into (Ce, La, Pr, Sm, Y)O2−δ
to hinder the structural transition at elevated temperatures. Indeed, the fluorite structure at elevated temperatures is stabilized at approximately 10 at.% Zr doping. The total conductivity initially increases with doping, peaking at 5 at.% Zr doping, and subsequently decreases with further doping. Interestingly, electronic conductivity in (Ce, La, Pr, Sm, Y)1−x
Zr
x
O2−δ
under oxidizing atmospheres is not significant and is lowest at 8 at.% Zr. These results suggest that ceria-based high-entropy oxides can serve as oxygen ion conductors with a significantly reduced electronic contribution. This work paves the way for new compositionally complex electrolytes as well as protective coatings for solid oxide fuel cells.
Investigating nano-SiC reinforced WE43 magnesium matrix surface composites
Authors: Kang Amardeep Singh , Singh Ravinder Pal , Singla Shivali
Published: April 2024

Magnesium matrix surface composites have been garnering attention due to their superior mechanical and corrosion resistance properties. An idea of facile fabrication of surface composite composed of nano-SiC reinforced WE43 matrix through friction stir processing was explored in this study. Also, the effects of tool geometries, tool rotations, and tool feeds on resultant properties were comprehensively investigated. Uniform dispersion of SiC nanoparticles within stir zone was evident. Square tool demonstrated the most promising results. Processing at 1700 rev min−1 and 60 mm min−1 with a square tool produced finest grains in surface composites exhibited exceptional microhardness (180.8 HV), nanohardness (1.867 GPa), elastic modulus (41.69 GPa), and wear resistance (0.0254 mm3 min−1). Besides it, WE43 substrates also exhibited superior mechanical properties when processed with a square tool at 800 rev min−1 and 60 mm min−1. This research opens up new possibilities for the development of reliable magnesium matrix surface composites for multifunctional applications.
Rational load balancing in collaborated cloud computing environments
*
Authors: Joshi Narayan A
Published: April 2024

Optimum efficiency and fault tolerance are the most demanding and challenging issues in the domain of performance and reliability management in cloud computing environments. Optimized resource utilization is a key aspect for yielding efficiency in cloud platforms. Workload balancing through resource sharing is one of the key solutions for attaining performance in cloud environments. In addition, multiple cloud environments join hands to offer performance and fault tolerance through resource sharing. We provide a better and cloud-instances’ priority-based efficient load balancing method for collaborative cloud platforms. The recommended efficient load balancing method shortens the waiting timespan and overcomes the starvation problem of low priority instances in intercloud environments. A functional prototype of the recommended load balancing method was deployed on a physical cloud infrastructure which was setup with the OpenStack cloud software on the Fedora Linux operating system. The pilot project execution findings exhibit a reduction in the timespan borne by instances for executing load balancing. This technique is useful for attaining fault tolerance and efficient resource utilization in intracloud and intercloud environments.
Amplitude chimeras and bump states with and without frequency entanglement: a toy model
Authors: Provata A
Published: April 2024

When chaotic oscillators are coupled in complex networks a number of interesting synchronization phenomena emerge. Notable examples are the frequency and amplitude chimeras, chimera death states, solitary states as well as combinations of these. In a previous study (Provata 2020 J. Phys. Complex.
1 025006), a toy model was introduced addressing possible mechanisms behind the formation of frequency chimera states. In the present study a variation of the toy model is proposed to address the formation of amplitude chimeras. The proposed oscillatory model is now equipped with an additional 3rd order equation modulating the amplitude of the network oscillators. This way, the single oscillators are constructed as bistable in amplitude and depending on the initial conditions their amplitude may result in one of the two stable fixed points. Numerical simulations demonstrate that when these oscillators are nonlocally coupled in networks, they organize in domains with alternating amplitudes (related to the two fixed points), naturally forming amplitude chimeras. A second extension of this model incorporates nonlinear terms merging amplitude together with frequency, and this extension allows for the spontaneous production of composite amplitude-and-frequency chimeras occurring simultaneously in the network. Moreover the extended model allows to understand the emergence of bump states via the continuous passage from chimera states, when both fixed point amplitudes are positive, to bump states when one of the two fixed points vanishes. The synchronization properties of the network are studied as a function of the system parameters for the case of amplitude chimeras, bump states and composite amplitude-and-frequency chimeras. The proposed mechanisms of creating domains with variable amplitudes and/or frequencies provide a generic scenario for understanding the formation of the complex synchronization phenomena observed in networks of coupled nonlinear and chaotic oscillators.
Both eyes open: Vigilant Incentives help auditors improve AI safety
Authors: Bova Paolo , Stefano Alessandro Di , Han The Anh
Published: April 2024

Auditors can play a vital role in ensuring that tech companies develop and deploy AI systems safely, taking into account not just immediate, but also systemic harms that may arise from the use of future AI capabilities. However, to support auditors in evaluating the capabilities and consequences of cutting-edge AI systems, governments may need to encourage a range of potential auditors to invest in new auditing tools and approaches. We use evolutionary game theory to model scenarios where the government wishes to incentivise auditing but cannot discriminate between high and low-quality auditing. We warn that it is alarmingly easy to stumble on ‘Adversarial Incentives’, which prevent a sustainable market for auditing AI systems from forming. Adversarial Incentives mainly reward auditors for catching unsafe behaviour. If AI companies learn to tailor their behaviour to the quality of audits, the lack of opportunities to catch unsafe behaviour will discourage auditors from innovating. Instead, we recommend that governments always reward auditors, except when they find evidence that those auditors failed to detect unsafe behaviour they should have. These ‘Vigilant Incentives’ could encourage auditors to find innovative ways to evaluate cutting-edge AI systems. Overall, our analysis provides useful insights for the design and implementation of efficient incentive strategies for encouraging a robust auditing ecosystem.
Analysis of machine learning prediction reliability based on sampling distance evaluation with feature decorrelation
Authors: Askanazi Evan , Grinberg Ilya
Published: April 2024

Despite successful use in a wide variety of disciplines for data analysis and prediction, machine learning (ML) methods suffer from a lack of understanding of the reliability of predictions due to the lack of transparency and black-box nature of ML models. In materials science and other fields, typical ML model results include a significant number of low-quality predictions. This problem is known to be particularly acute for target systems which differ significantly from the data used for ML model training. However, to date, a general method for uncertainty quantification (UQ) of ML predictions has not been available. Focusing on the intuitive and computationally efficient similarity-based UQ, we show that a simple metric based on Euclidean feature space distance and sampling density together with the decorrelation of the features using Gram–Schmidt orthogonalization allows effective separation of the accurately predicted data points from data points with poor prediction accuracy. To demonstrate the generality of the method, we apply it to support vector regression models for various small data sets in materials science and other fields. We also show that this metric is a more effective UQ tool than the standard approach of using the average distance of k nearest neighbors (k = 1–10) in features space for similarity evaluation. Our method is computationally simple, can be used with any ML learning method and enables analysis of the sources of the ML prediction errors. Therefore, it is suitable for use as a standard technique for the estimation of ML prediction reliability for small data sets and as a tool for data set design.
Continuous adaptive nonlinear model predictive control using spiking neural networks and real-time learning
Authors: Halaly Raz , Tsur Elishai Ezra
Published: April 2024

Model predictive control (MPC) is a prominent control paradigm providing accurate state prediction and subsequent control actions for intricate dynamical systems with applications ranging from autonomous driving to star tracking. However, there is an apparent discrepancy between the model’s mathematical description and its behavior in real-world conditions, affecting its performance in real-time. In this work, we propose a novel neuromorphic (brain-inspired) spiking neural network for continuous adaptive non-linear MPC. Utilizing real-time learning, our design significantly reduces dynamic error and augments model accuracy, while simultaneously addressing unforeseen situations. We evaluated our framework using real-world scenarios in autonomous driving, implemented in a physics-driven simulation. We tested our design with various vehicles (from a Tesla Model 3 to an Ambulance) experiencing malfunctioning and swift steering scenarios. We demonstrate significant improvements in dynamic error rate compared with traditional MPC implementation with up to 89.15% median prediction error reduction with 5 spiking neurons and up to 96.08% with 5,000 neurons. Our results may pave the way for novel applications in real-time control and stimulate further studies in the adaptive control realm with spiking neural networks.
Discrete Schrödinger equations and systems with mixed and concave-convex nonlinearities
Authors: Chen Guanwei , Ma Shiwang
Published: April 2024

In this paper, we obtain the existence of at least two standing waves (and homoclinic solutions) for a class of time-dependent (and time-independent) discrete nonlinear Schrödinger systems or equations. The novelties of the paper are as follows. (1) Our nonlinearities are composed of three mixed growth terms, i.e., the nonlinearities are composed of sub-linear, asymptotically-linear and super-linear terms. (2) Our nonlinearities may be sign-changing. (3) Our results can also be applied to the cases of concave-convex nonlinear terms. (4) Our results can be applied to a wide range of mathematical models.
The Springs of the Arno
Authors: Havely Nick
Published: April 2024

Chapter 2 follows the journey from the sanctuary of La Verna in the east of the Casentino to the Passo del Muraglione on the ridge between Forlì and Florence. Beginning with an account of one of the longest sections of the walk between La Verna and the hill-resort of Badia Prataglia, it then describes another ancient sanctuary, Camaldoli, and the views of its many visitors: from humanists in the fifteenth century to tourists in the eighteenth and nineteenth centuries and escaping prisoners of war in the twentieth century. It discusses the motives and perceptions of those who traced Dante’s ‘footsteps’ in the Casentino, especially around Monte Falterona and the source of the Arno, and shows through two concluding ‘diversions’ how easy it is to get lost around Falterona and the Muraglione Pass.
Hormonal profiles in dormant turions of 22 aquatic plant species: do they reflect functional or taxonomic traits?
Authors: Adamec Lubomír , Plačková Lenka , Bitomský Martin , Doležal Karel
Published: April 2024

Background and Aims

Turions are vegetative, dormant overwintering organs formed in aquatic plants in response to unfavourable ecological conditions. Contents of cytokinin (CK), auxin metabolites and abscisic acid (ABA) as main growth and development regulators were compared in innately dormant autumnal turions of 22 aquatic plant species of different functional ecological or taxonomic groups with those in non-dormant winter apices in three aquatic species and with those in spring turions of four species after their overwintering.

Methods

The hormones were analysed in miniature turion samples using ultraperformance liquid chromatography coupled with triple quadrupole mass spectrometry.

Key Results

In innately dormant turions, the total contents of each of the four main CK types, biologically active forms and total CKs differed by two to three orders of magnitude across 22 species; the proportion of active CK forms was 0.18–67 %. Similarly, the content of four auxin forms was extremely variable and the IAA proportion as the active form was 0.014–99 %. The ABA content varied from almost zero to 54 µmol kg−1 dry weight and after overwintering it usually significantly decreased. Of all functional traits studied, hormone profiles depended most on the place of turion sprouting (surface vs bottom) and we suggest that this trait is crucial for turion ecophysiology.

Conclusions

The key role of ABA in regulating turion dormancy was confirmed. However, the highly variable pattern of the ABA content in innately dormant and in overwintered turions indicates that the hormonal mechanism regulating the innate dormancy and its breaking in turions is not uniform within aquatic plants.
MerCat2: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from omics data
Authors: Figueroa Jose L , Redinbo Andrew , Panyala Ajay , Colby Sean , Friesen Maren L , Tiemann Lisa , White Richard Allen
Published: April 2024

Motivation

MerCat2 (“Mer—Catenate2”) is a versatile, parallel, scalable and modular property software package for robustly analyzing features in omics data. Using massively parallel sequencing raw reads, assembled contigs, and protein sequences from any platform as input, MerCat2 performs k-mer counting of any length k, resulting in feature abundance counts tables, quality control reports, protein feature metrics, and graphical representation (i.e. principal component analysis (PCA)).

Results

MerCat2 allows for direct analysis of data properties in a database-independent manner that initializes all data, which other profilers and assembly-based methods cannot perform. MerCat2 represents an integrated tool to illuminate omics data within a sample for rapid cross-examination and comparisons.

Availability and implementation

MerCat2 is written in Python and distributed under a BSD-3 license. The source code of MerCat2 is freely available at https://github.com/raw-lab/mercat2. MerCat2 is compatible with Python 3 on Mac OS X and Linux. MerCat2 can also be easily installed using bioconda: mamba create -n mercat2 -c conda-forge -c bioconda mercat2
For antibody sequence generative modeling, mixture models may be all you need
Authors: Parkinson Jonathan , Wang Wei
Published: April 2024

Motivation

Antibody therapeutic candidates must exhibit not only tight binding to their target but also good developability properties, especially low risk of immunogenicity.

Results

In this work, we fit a simple generative model, SAM, to sixty million human heavy and seventy million human light chains. We show that the probability of a sequence calculated by the model distinguishes human sequences from other species with the same or better accuracy on a variety of benchmark datasets containing >400 million sequences than any other model in the literature, outperforming large language models (LLMs) by large margins. SAM can humanize sequences, generate new sequences, and score sequences for humanness. It is both fast and fully interpretable. Our results highlight the importance of using simple models as baselines for protein engineering tasks. We additionally introduce a new tool for numbering antibody sequences which is orders of magnitude faster than existing tools in the literature.

Availability and implementation

All tools developed in this study are available at https://github.com/Wang-lab-UCSD/AntPack.
Programmed death receptor-1 and programmed death ligand-1 checkpoint inhibition-associated bullous pemphigoid: a propensity-matched retrospective cohort study
Authors: Sarkovics Katelyn , Kolodney Joanna A , Kolodney Michael S
Published: April 2024

We provide a comparison of the bullous pemphigoid (BP)-free survival probability in patients starting PD-1/PD-L1 inhibitors and DPP-4 inhibitors that has not been previously demonstrated in other studies. A propensity-matched retrospective cohort study performed with TriNetX participants revealed a significantly increased risk of BP in patients starting PD-1/PD-L1 inhibitors, especially in male patients and those aged > 65 years.
Leptin receptor reactivation restores brain function in early-life Lepr-deficient mice
Authors: Fernandes Caroline , Forny-Germano Leticia , Andrade Mayara M , Lyra E Silva Natalia M , Ramos-Lobo Angela M , Meireles Fernanda , Tovar-Moll Fernanda , Houzel Jean Christophe , Donato Jose , De Felice Fernanda G
Published: April 2024

Obesity is a chronic disease caused by excessive fat accumulation that impacts the body and brain health. Insufficient leptin or leptin receptor (LepR) is involved in the disease pathogenesis. Leptin is involved with several neurological processes, and it has crucial developmental roles. We have previously demonstrated that leptin deficiency in early life leads to permanent developmental problems in young adult mice, including an imbalance in energy homeostasis, alterations in melanocortin and the reproductive system and a reduction in brain mass. Given that in humans, obesity has been associated with brain atrophy and cognitive impairment, it is important to determine the long-term consequences of early-life leptin deficiency on brain structure and memory function.

Here, we demonstrate that leptin-deficient (LepOb) mice exhibit altered brain volume, decreased neurogenesis and memory impairment. Similar effects were observed in animals that do not express the LepR (LepRNull). Interestingly, restoring the expression of LepR in 10-week-old mice reverses brain atrophy, in addition to neurogenesis and memory impairments in older animals.

Our findings indicate that leptin deficiency impairs brain development and memory, which are reversible by restoring leptin signalling in adulthood.
NK-like CD8 T cell: one potential evolutionary continuum between adaptive memory and innate immunity
Authors: Wang Qiulei , Chen Shaodan , Guo Zhenhong , Xia Sheng , Zhang Minghui
Published: April 2024

CD8 T cells are crucial adaptive immune cells with cytotoxicity to fight against pathogens or abnormal self-cells via major histocompatibility complex class I-dependent priming pathways. The composition of the memory CD8 T-cell pool is influenced by various factors. Physiological aging, chronic viral infection, and autoimmune diseases promote the accumulation of CD8 T cells with highly differentiated memory phenotypes. Accumulating studies have shown that some of these memory CD8 T cells also exhibit innate-like cytotoxicity and upregulate the expression of receptors associated with natural killer (NK) cells. Further analysis shows that these NK-like CD8 T cells have transcriptional profiles of both NK and CD8 T cells, suggesting the transformation of CD8 T cells into NK cells. However, the specific induction mechanism underlying NK-like transformation and the implications of this process for CD8 T cells are still unclear. This review aimed to deduce the possible differentiation model of NK-like CD8 T cells, summarize the functions of major NK-cell receptors expressed on these cells, and provide a new perspective for exploring the role of these CD8 T cells in health and disease.
The neural representations of valence transformation in indole processing
Authors: Zou Laiquan , Qi Yue , Shen Lei , Huang Yanyang , Huang Jiayu , Xia Zheng , Fan Mingxia , Fan Wu , Chai Guo-bi , Shi Qing-zhao , Zhang Qidong , Yan Chao
Published: April 2024

Indole is often associated with a sweet and floral odor typical of jasmine flowers at low concentrations and an unpleasant, animal-like odor at high concentrations. However, the mechanism whereby the brain processes this opposite valence of indole is not fully understood yet. In this study, we aimed to investigate the neural mechanisms underlying indole valence encoding in conversion and nonconversion groups using the smelling task to arouse pleasantness. For this purpose, 12 conversion individuals and 15 nonconversion individuals participated in an event–related functional magnetic resonance imaging paradigm with low (low-indole) and high (high-indole) indole concentrations in which valence was manipulated independent of intensity. The results of this experiment showed that neural activity in the right amygdala, orbitofrontal cortex and insula was associated with valence independent of intensity. Furthermore, activation in the right orbitofrontal cortex in response to low-indole was positively associated with subjective pleasantness ratings. Conversely, activation in the right insula and amygdala in response to low-indole was positively correlated with anticipatory hedonic traits. Interestingly, while amygdala activation in response to high-indole also showed a positive correlation with these hedonic traits, such correlation was observed solely with right insula activation in response to high-indole. Additionally, activation in the right amygdala in response to low-indole was positively correlated with consummatory pleasure and hedonic traits. Regarding olfactory function, only activation in the right orbitofrontal cortex in response to high-indole was positively correlated with olfactory identification, whereas activation in the insula in response to low-indole was negatively correlated with the level of self-reported olfactory dysfunction. Based on these findings, valence transformation of indole processing in the right orbitofrontal cortex, insula, and amygdala may be associated with individual hedonic traits and perceptual differences.
Undernourished Household Contacts Are at Increased Risk of Tuberculosis (TB) Disease, but not TB Infection—a Multicenter Prospective Cohort Analysis
Authors: Sinha Pranay , Ezhumalai Komala , Du Xinyi , Ponnuraja Chinnaiyan , Dauphinais Madolyn Rose , Gupte Nikhil , Sarkar Sonali , Gupta Amita , Gaikwad Sanjay , Thangakunam Balamugesh , Paradkar Mandar , Christopher Devasahayam J , Mave Vidya , Viswanathan Vijay , Ellner Jerrold J , Kornfeld Hardy , Horsburgh C R , Padmapriyadarsini Chandrasekaran , Gupte Akshay
Published: April 2024

Undernutrition is the leading risk factor for tuberculosis (TB) globally and in India. This multicenter prospective cohort analysis from India suggests that undernutrition is associated with increased risk of TB disease but not TB infection among household contacts of persons with TB.
Social media for cardiac imagers: a review
Authors: Schuuring Mark J , Anwer Shehab , Petersen Steffen E , Moharem-Elgamal Sarah , Muraru Denisa
Published: April 2024

Cardiac imaging plays a pivotal role in the diagnosis and management of cardiovascular diseases. In the burgeoning landscape of digital technology and social media platforms, it becomes essential for cardiac imagers to know how to effectively increase the visibility and the impact of their activity. With the availability of social sites like X (formerly Twitter), Instagram, and Facebook, cardiac imagers can now reach a wider audience and engage with peers, sharing their findings, insights, and discussions. The integration of persistent identifiers, such as digital object identifiers (DOIs), facilitates traceability and citation of cardiac imaging publications across various digital platforms, further enhancing their discoverability. To maximize visibility, practical advice is provided, including the use of visually engaging infographics and videos, as well as the strategic implementation of relevant hashtags and keywords. These techniques can significantly improve the discoverability of cardiac imaging research through search engine optimization and social media algorithms. Tracking impact and engagement is crucial in the digital age, and this review discusses various metrics and tools to gauge the reach and influence of cardiac imaging publications. This includes traditional citation-based metrics and altmetrics. Moreover, this review underscores the importance of creating and updating professional profiles on social platforms and participating in relevant scientific communities online. The adoption of digital technology, social platforms, and a strategic approach to publication sharing can empower cardiac imaging professionals to enhance the visibility and impact of their research, ultimately advancing the field and improving patient care.
Intramural hematoma extending from a dissection within an implanted stent: a case report treated with fenestration using a cutting balloon
Authors: Okura Takeshi , Okabe Toshitaka , Isomura Naoei , Ochiai Masahiko
Published: April 2024

Background

Dissection after balloon dilation or stent implantation is a common complication of percutaneous coronary intervention. In general, coronary stent implantation for coronary artery dissection is safe when the dissection is completely covered by the stent, particularly when dissection occurs during pre-dilation. However, here, we report a case of severe restenosis caused by a pre-dilation hematoma that extended after stent implantation.

Case summary

A 76-year-old man was diagnosed with angina on exertion and underwent percutaneous coronary intervention in the right coronary artery. After pre-dilation with a cutting balloon, non-flow-limiting dissection occurred. An everolimus-eluting stent was implanted, completely sealing the dissection, and intravascular ultrasound revealed adequate stent expansion without stent edge dissection. Two weeks after the procedure, confirmatory coronary angiography revealed severe restenosis extending from the distal stent edge to the distal right coronary artery. Intravascular ultrasound revealed a hematoma extending from the middle of the stent to the distal segment.

Discussion

The patient had been on steroids for a long time. The cutting balloon used for pre-dilation may have created a deep dissection reaching the tunica media, already rendered vulnerable by steroids, potentially leading to injury to the vasa vasorum. The intramural hematoma from the bleeding vasa vasorum might have been the underlying cause of this phenomenon, as evidenced by its increase in size despite the entry of the dissection being completely sealed. Cardiologists should be aware of this possibility.
IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning
Authors: Yin Hengchuang , Wu Shufang , Tan Jie , Guo Qian , Li Mo , Guo Jinyuan , Wang Yaqi , Jiang Xiaoqing , Zhu Huaiqiu
Published: April 2024

Background

The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses.

Findings

We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals.

Conclusions

IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.
Predicting prognosis and immunotherapy response in colorectal cancer by pericytes insights from single-cell RNA sequencing
Authors: Wei Chen , Wang Weikai , Hu Zhihao , Huang Zhuoli , Lu Ye , Zhou Wenwen , Liu Xiaoying , Jin Xin , Yin Jianhua , Li Guibo
Published: April 2024

Immunotherapy has revolutionized the treatment of tumors, but there are still a large number of patients who do not benefit from immunotherapy. Pericytes play an important role in remodeling the immune microenvironment. However, how pericytes affect the prognosis and treatment resistance of tumors is still unknown. This study jointly analyzed single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data of multiple cancers to reveal pericyte function in the colorectal cancer microenvironment. Analyzing over 800 000 cells, it was found that colorectal cancer had more pericyte enrichment in tumor tissues than other cancers. We then combined the TCGA database with multiple public datasets and enrolled more than 1000 samples, finding that pericyte may be closely related to poor prognosis due to the higher epithelial-mesenchymal transition (EMT) and hypoxic characteristics. At the same time, patients with more pericytes have higher immune checkpoint molecule expressions and lower immune cell infiltration. Finally, the contributions of pericyte in poor treatment response have been demonstrated in multiple immunotherapy datasets (n = 453). All of these observations suggest that pericyte can be used as a potential biomarker to predict patient disease progression and immunotherapy response.
Age, metabolisms, and potential origin of dominant anammox bacteria in the global oxygen-deficient zones
Authors: Zhao Rui , Zhang Irene H , Jayakumar Amal , Ward Bess B , Babbin Andrew R
Published: April 2024

Anammox bacteria inhabiting oxygen-deficient zones (ODZs) are a major functional group mediating fixed nitrogen loss in the global ocean. However, many basic questions regarding the diversity, broad metabolisms, origin, and adaptive mechanisms of ODZ anammox bacteria remain unaddressed. Here we report two novel metagenome-assembled genomes of anammox bacteria affiliated with the Scalindua genus, which represent most, if not all, of the anammox bacteria in the global ODZs. Metagenomic read-recruiting and comparison with historical data show that they are ubiquitously present in all three major ODZs. Beyond the core anammox metabolism, both organisms contain cyanase, and the more dominant one encodes a urease, indicating most ODZ anammox bacteria can utilize cyanate and urea in addition to ammonium. Molecular clock analysis suggests that the evolutionary radiation of these bacteria into ODZs occurred no earlier than 310 million years ago, ~1 billion years after the emergence of the earliest modern-type ODZs. Different strains of the ODZ Scalindua species are also found in benthic sediments, and the first ODZ Scalindua is likely derived from the benthos. Compared to benthic strains of the same clade, ODZ Scalindua uniquely encodes genes for urea utilization but has lost genes related to growth arrest, flagellum synthesis, and chemotaxis, presumably for adaptation to thrive in the global ODZ waters. Our findings expand the known metabolisms and evolutionary history of the bacteria controlling the global nitrogen budget.
Integrated multi-omics approach reveals novel associations in the rapeseed diet–microbiota–host axis in pigs
Authors: Onarman Umu Özgün C , Mydland Liv Torunn , Chen Chi , de Nanclares Marta Pérez , Shurson Gerald C , Urriola Pedro E , Sørum Henning , Øverland Margareth
Published: April 2024

Diet-mediated host–microbiota interplay is a key factor in optimizing the gut function and overall health of the host. Gaining insight into the biological mechanisms behind this relationship is fundamental to finding sustainable, environment-friendly feed solutions in livestock production systems. Here, we apply a multi-omics integration approach to elucidate sustainable diet-associated host–gut microbiota interactions in pigs and we demonstrate novel and biologically relevant host–microbe associations in the gut, driven by a rapeseed meal-based feed (RSF). Interestingly, RSF-diet promoted the abundance of segmented filamentous bacteria Candidatus Arthromitus that was associated with the maintenance of mucosal immunity in the ileum of pigs. In the colon, RSF diet affected host mRNA splicing functions, which may result in different host gene products, through host–microbiota associations, particularly with the Faecalibacterium population, and through the interaction of dietary components such as sinapic acid with the host cells. Moreover, telomere maintenance and organization functions that may determine the overall health of the host were upregulated and notably associated with Subdoligranulum population in the colon of RSF diet-fed pigs. This integrative multi-omics approach provides more insight into the diet–microbiota–host axis, and a better understanding of mechanisms and opportunities to find new strategies for modulating host health and potentially improving caloric and nutritional efficiency in animal production.
Integrated Multiplatform Analysis and Separation of Thirteen Flavonoids and Anthraquinones in Seven Medicinal Cassia Species
Authors: Girme Aboli , Saste Ganesh , Kureshi Azazahemad A , Jagtap Shubham , Kamble Siddhi , Wadye Saurabh D , Hingorani Lal
Published: April 2024

Background

Cassia (Family: Fabaceae) species are a large group of flowering plants rich in bioactive anthraquinone and flavonoids used in botanical supplements and nutraceuticals.

Objective

A simple and reliable high-performance liquid chromatography-photodiode array (HPLC-PDA) method was developed and validated for separating and quantifying 13 anthraquinone and flavonoids. These compounds were further confirmed using an LC-based electrospray ionization mass spectrometry (ESI-MS/MS) method in the leaves and flowers of selected Cassia species. A simple and rapid HPTLC method was developed for chemical fingerprint analysis of all Cassia species.

Method

All 13 compounds were chromatographically separated on a Zorbax TC18 (4.6 × 250, 5 μm particle size) analytical column, and 0.1% formic acid and acetonitrile as elution solvents at a flow rate of 0.8 mL/min with detection at 259 nm. For HPTLC fingerprinting, the mobile phase compositions of toluene, ethyl acetate, and formic acid (5.5:4.2:0.6, v/v/v) were optimized to separate and identify all compounds using silica gel 60F254 aluminum plates.

Results

The validation data for the developed HPLC-PDA method for 13 compounds showed good linearity (r2 >0.99) with a sensitive LOD (0.082–1.969 μg/mL), LOQ (0.250–5.967 μg/mL), and excellent recoveries (85.22–100.32%). The quantification results were found to be precise and accurate (<5.0% and relative error), -0.77–0.44 with ESI-MS/MS confirmation in the Cassia samples. The novel HPTLC method was excellent separation for 13 compounds, with Rf values ranging between 0.12 and 0.61.

Conclusions

The developed HPLC-PDA method was simple and precise and could separate and quantify anthraquinones and flavonoids along with confirmation, using a novel LC-based ESI-MS/MS. The HPTLC method was found to be simple and precise, with excellent separation capabilities for these compounds.

Highlights

This novel multiplatform approach successfully identified and quantified 13 compounds simultaneously using an integration of data strategy in seven medicinally important Cassia species’ leaves and flowers.
Development of an Analytical Quality by Design RP-HPLC Method and Its Validation for Estimation of Gefitinib From Bulk, Tablet Dosage Form, and Complex Nanoformulation
Authors: More Mahesh P , Pardeshi Sagar R , Tade Rahul , Meshram Pawan D , Naik Jitendra B , Deshmukh Prashant K
Published: April 2024

Background

Estimation of the drug and development of the method is a critical aspect of formulation development and a critical factor for analytical scientists. Gefitinib is a poorly soluble anticancer drug.

Objective

The present research focuses on the topic of the development of innovative quality by design methods for the estimation of gefitinib (GF) from bulk, pharmaceutical tablet formulation, and complex nanoformulations.

Methods

To simplify the estimation of poorly soluble drugs such as GF, response surface methodology (RSM) was adopted with effective leverages to obtain precise computation design space using the Box-Behnken design (BBD) model. The major three mixed-effect independent factors (percentage of buffer, pH of buffer, and flow rate) were screened with three prominent dependent responses (viz., theoretical plate, retention time, and tailing factor) selected for optimal analysis. Furthermore, co-processed steps were employed for the estimation of the analyte from the complex formulation.

Results

The RP-HPLC method uses the quality by design (QbD) approach can effectively estimate the analyte concentration of less than 4.5 min. The developed method was economically robust and sensitive and shows a relative standard deviation (RSD, %) of less than 2% for all the selected validation parameters. The estimated design space suggests the highest desirability (R2—0.998) at 60% of buffer in the mobile phase, pH 4.25, and flow rate of 0.7 mL/min.

Conclusions

The QbD approach was used to design and develop the method by understanding the interaction between dependent and independent variables to get the optimum values. The developed method was validated successfully and can be useful for formulation scientists to estimate drug concentration and drug release profiles from complex nanoformulations.

Highlights

The analytical approach was designed and quantified using a quality-by-design approach to make the RP-HPLC method more robust and efficient for the estimation of analytes from complex nanoformulations. The method is also useful to eliminate the interfering molecule during estimation by employing co-processing steps. The developed method saves time and cost of solvent and employs QbD as a requirement of recent regulatory concern.
A two-year review of cocaine findings in impaired driving investigations in Ontario, Canada
Authors: Currie Zachary , Lamparter Christina , Gosselin Sophie , Watterson James
Published: April 2024

Drug-impaired driving is an increasing public safety concern across Canada, particularly due to the demonstrated increase in use of recreational drugs such as cocaine. Cocaine is a central nervous system stimulant drug; however, it can impair an individual’s driving ability in both the stimulant and crash phases. Despite the scientific consensus regarding cocaine’s potential for driving impairment, there is relatively little information available regarding blood concentrations and associated observations of impairment in suspected impaired drivers. Retrospective data analysis was performed to evaluate suspected impaired driving cases in which cocaine and/or benzoylecgonine were detected alone, or in combination with other drugs, in blood and urine samples submitted to the Toxicology Section of the Centre of Forensic Sciences with incident dates between 2021 and 2022. Cocaine and/or benzoylecgonine were detected in 46% (blood) and 66% (urine) of the total impaired driving samples submitted. In 41 cases where cocaine and/or benzoylecgonine were the only drug finding in blood, concentrations of cocaine and benzoylecgonine ranged from 0.0073 to 0.26 mg/L (mean 0.096 mg/L) and 0.13 to 5.3 mg/L (mean 2.1 mg/L), respectively. Driving observations reported by the arresting officer in cases where cocaine and/or benzoylecgonine were the only drug finding in blood and urine included the driver being involved in a collision, the vehicle leaving the roadway, erratic driving and the driver being asleep at the wheel; observations of drug impairment reported by the drug recognition expert at the time of driver evaluation included abnormal speech patterns, poor balance/incoordination, abnormal body movements and the individual falling asleep. The results provide concentrations of cocaine and benzoylecgonine observed in suspected impaired drivers, insight into observations that may be associated with prior cocaine use and additional information to inform on the effects of cocaine on driving.
Sorting nexin 27–dependent regulation of Lck and CD4 tunes the initial stages of T-cell activation
Authors: Rodriguez-Rodriguez Cristina , González-Mancha Natalia , Ochoa-Echeverría Ane , Mérida Isabel
Published: April 2024

Sorting nexin 27 is a unique member of the sorting nexin family of proteins that mediates the endosome-to-plasma membrane trafficking of cargos bearing a PSD95/Dlg1/ZO-1 (PDZ)–binding motif. In brain, sorting nexin 27 regulates synaptic plasticity, and its dysregulation contributes to cognitive impairment and neuronal degeneration. In T lymphocytes, sorting nexin 27 partners with diacylglycerol kinase ζ to facilitate polarized traffic and signaling at the immune synapse. By silencing sorting nexin 27 expression in a human T-cell line, we demonstrate that sorting nexin 27 is a key regulator of the early T-cell tyrosine-based signaling cascade. Sorting nexin 27 transcriptionally controls CD4 abundance in resting conditions and that of its associated molecule, Lck. This guarantees the adequate recruitment of Lck at the immune synapse, which is indispensable for subsequent activation of tyrosine phosphorylation-regulated events. In contrast, reduced sorting nexin 27 expression enhances NF-κB–dependent induction of CXCR4 and triggers production of lytic enzymes and proinflammatory cytokines. These results provide mechanistic explanation to previously described sorting nexin 27 function in the control of immune synapse organization and indicate that impaired sorting nexin 27 expression contributes to CD4 T-cell dysfunction.