Browse Articles

Evaluating the distribution and clustering of SARS-CoV-2 antibodies in dogs across the United States of America

Fundamentals of 1/f noise reduction technique based on complementary cascode switching applied to a 52 microwatts 5.2pJ/bit 100Kb/s 120 GHz receiver

Experimental investigation of CTAB modified clay on oil recovery and emulsion behavior in low salinity water flooding

Disproportionality analysis of adverse events associated with ipilimumab and nivolumab combination therapy based on FAERS database

Association between wet-bulb globe temperature with gastroesophageal reflux disease in different geographic regions in a large Taiwanese population study

Restoration and functional analysis of the SGI1 resolution system – SGI1 multimers are eliminated by the reactivated resolution

Abstract SGI1 and the related elements that are specifically mobilized by the IncA- and IncC-family plasmids are efficient agents in the dissemination of multi-resistance in Gammaproteobacteria. The In104 gene cluster responsible for multi-resistance in these genomic islands is generally integrated into the conserved SGI1 backbone, upstream of a resolvase gene, presumably by res-hunting transposition events. In this work we demonstrate that precise deletion of In104 cluster with one copy of its flanking direct repeats restores the res site belonging to the resolvase gene, leading to an active Tn3-like resolution system. The entire res site and its subsites have been identified and the resolvase activity has been demonstrated in plasmid-based recombination assays. The major effect of the reactivated resolution system seems to be the rapid elimination of SGI1 multimers in SGI1 transconjugants. It has been shown that wt SGI1-C and the resolvase-deleted SGI1ΔIn104 variant produce significantly more concatemers, which persist for longer periods in transconjugants, than SGI1ΔIn104 with a functional resolution system. High prevalence of inactivated res systems among the multidrug-resistant members of SGI1-family suggests that the ability to produce more and more stable multimers in SGI1 transconjugants may confer evolutionary advantage to these elements.

Testing the effect of host availability on endobiont diversity: proposing the single hotel hypothesis

An ABA–ROP toggle switch orchestrates xylem differentiation and cell wall patterning

The mutual antagonistic signaling of abscisic acid (ABA) and ROP GTPases highlights an intersection between stress responses and pattern formation. Previously, we have shown that signaling of ABA in the endodermis leads to protoxylem (PX) differentiation. In this study, we demonstrate that ROPs suppress PX differentiation in the roots of both Arabidopsis and tomato. Fourier transform and Shannon’s entropy show that endodermal ABA signaling controls the periodicity and overall order of PX secondary cell wall (SCW) coils in an ROP-dependent manner. Correspondingly, in the PX, GFP-ROP11 is initially dispersed and gradually becomes distributed in an oscillatory fashion with a periodicity corresponding to that of the SCW coils. Oryzalin treatments disrupt the frequency and increase the entropy of the GFP-ROP11 signal, suggesting that microtubules delimit ROP distribution. Signaling of ABA in the endodermis encourages the enlargement of metaxylem SCW pits, while ABA signaling in the stele limits this enlargement. Pit size and density are decreased in ROP mutants while ABA enhances ROP11 expression in the stele and broadens its distribution in the endodermis. Taken together, non-cell-autonomous and cell-autonomous interactions between ABA and ROPs regulate xylem differentiation and SCW patterning.

Quantum phase transition in the Casten pyramid using entanglement entropy in the semi-classical approximation of IBM-2

Evaluation of oral hygiene and gingival parameters in pediatric nephrotic syndrome within an interdisciplinary care model

Distributed sliding mode control approach with adaptive spacing policy for vehicle platoons in communication interruption scenario

Bioinformatic prediction of key genes involved in pro-chondrogenic effect of fragmentated cartilage transplantation

Abstract Minced cartilage transplantation is thought to promote cartilage repair. However, the underlying mechanisms remain less well understood. In this study, we established a rat osteochondral defect model to evaluate fragment size-dependent repair efficacy, and tried to explore the mechanisms preliminarily. Herein, rats with cartilage defect were randomly divided into 3 groups. Small allogeneic cartilage fragments with fibrin glue, chunk allogeneic cartilage fragments with fibrin glue, and only fibrin glue were used to treat cartilage defects in each group, respectively. The results showed that the minced cartilage fragments had significantly improved outcomes in promoting cartilage repairing compared to chunk cartilage fragments and only fibrin glue. Notably, particulated cartilage transplantation-treat cartilage lesion had elevated inflammation. Following RNA-seq analysis on cartilage fragments and cartilage chunk identified 75 differentially expressed genes (DEGs), which include 70 up-regulated DEGs and 5 down-regulated DEGs in cartilage fragment group (CFG). Further GO enrichment and KEGG pathway analysis showed that the up-regulated DEGs in CFG were mainly involved in inflammation, cell proliferation and migration. We also found that the down-regulated DEGs in CFG had negative relationship with cell migration, proliferation and inflammation. This study suggest that cartilage fragmentation enhances repair efficacy compared to chunk cartilage transplantation, and the mechanism of pro-chondrogenic effect may be related to inflammatory stimulation.

Arsenic-free Ge-Te-based ovonic threshold switching material with reduced leakage current

In vitro evaluation and phytochemical analysis of Curcuma aeruginosa Roxb. against human coronavirus OC43

Technoeconomic and environmental analysis of cryogenic and MQL-assisted machining of Hastelloy X

Abstract The growing significance of superalloys like Hastelloy X, particularly in critical engineering sectors such as aerospace, chemical processing, and selective biomedical equipment (e.g., surgical instruments and medical tooling), underscores the need for advancements in their manufacturing processes. In today’s era of advanced manufacturing, it is crucial to develop machining systems that are both environmentally sustainable and cost-effective. To bridge the existing gap between economic, technological, and sustainability aspects in the machining of Hastelloy X, the present research aims to shed light on this critical interplay. Experimental investigations were conducted to evaluate the performance of various cooling techniques, including dry machining, minimum quantity lubrication (MQL), and cryogenic cooling using liquid nitrogen (LN₂) and carbon dioxide (CO₂). The results revealed that cryogenic cooling with LN₂ demonstrated superior performance across technological, sustainability, and economic metrics, outperforming other methods. Specifically, LN₂ cooling during the turning of Hastelloy X led to a reduction in tool wear and surface roughness by 21.11% and 25%, respectively, over dry machining conditions. These findings highlight the potential of advanced lubrication and cooling techniques to enhance sustainable manufacturing practices, reducing resource consumption while improving machining performance, particularly for industries involving difficult-to-machine superalloys.

Diminished angiogenic capacity in the hippocampus compared to the cortex indicates regional vulnerability

Genetic contributions to brain criticality and its relationship with human cognitive functions

Recently, extensive evidence has demonstrated that the brain operates close to a critical state, characterized by dynamic patterns known as neuronal avalanches. The critical state, reflecting the delicate balance between neural excitation and inhibition, offers numerous advantages in information processing. However, the role of genetics in shaping brain criticality is not fully understood. Whether there is any shared genetic factor influencing the critical state and cognitive functions remains elusive. Here, we aimed to address these questions by examining the heritability of brain criticality and its relation to cognitive function by analyzing resting-state functional magnetic resonance imaging (rs-fMRI) in 250 monozygotic twins, 142 dizygotic twins, and 437 Not-twin subjects. We found that genetic factors substantially influenced brain criticality across various scales, encompassing brain regions, functional networks, and the whole brain. These genetic influences exhibited heterogeneity, with the criticality of the primary sensory cortex being more strongly influenced by genetic factors compared to that of the association cortex. Furthermore, we combined rs-fMRI data with transcriptional microarray data from the Allen Brain Atlas: Human Brain (ABHB) dataset and found that the organization of regional critical dynamics was highly explained by a specific gene expression profile. Finally, our results showed that the critical state was correlated with total cognition and had a genetic link with it. These findings provide empirical evidence that brain criticality is a biological phenotype and suggest a shared genetic foundation underlying brain criticality and cognitive functions. Our results pave the way toward revealing specific biological mechanisms contributing to critical dynamics and their associations with brain function and dysfunction.

Experimental investigation of influence of age hardening temperature and cooling medium on tribological behaviour of aluminium/tungsten carbide metal matrix composite

Structural and mechanical properties of humidity-responsive Geraniaceae awns

Abstract Hygroscopic deformations in plants are passive movements within specialized structures triggered by changes in environmental humidity. In the Geraniaceae, the sterile extension of the mericarp, called awn, facilitates seed dispersal by actuating hygroscopic coiling. Notably, the morphological characteristics and regional distribution of awns vary significantly among the family species, suggesting different mechanisms at the base of dispersion. Despite these variations, no prior investigation has solely focused on examining the combination of the structural and mechanical properties of the awn. Thus, this study fills the gap by conducting an in-depth comparative analysis of the awns from two Geraniaceae species, Pelargonium appendiculatum (L.f.) Willd. and Erodium gruinum (L.) L’Her., which exhibit similar coiling behavior but possess distinct structural features. Through an interdisciplinary approach, we have identified key internal structural characteristics that profoundly impact the awn’s mechanical properties and hygroscopic response, directly influencing its movement. Our comprehensive findings highlight distinct dispersion mechanisms tailored to each species, providing new insights into the functional role of awn structures. This study not only advances our understanding of plant biomechanics but also highlights the intricate relationship between structure and function.

Comparative analysis of machine learning approaches for heatwave event prediction in India

Abstract Heatwaves, are identified as prolonged durations of unusually high temperatures, which pose significant threats to human health, animal health and agriculture. With the increasing frequency and intensity of heatwaves driven by climate change, accurate and early prediction of these extreme weather events is crucial for effective mitigation and adaptation. This research paper conducts a comparative analysis of various machine learning models for heatwave event classification using a time series dataset from a weather station in the equatorial region of India, specifically Chennai, Tamil Nadu. The study evaluates the performance of models including Random Forest, Convolutional Neural Networks, LightGBM, Long Short-Term Memory Networks, Transformer Networks, Support Vector Machines, Graph Neural Networks, Extreme Gradient Boosting and Autoencoders for Anomaly Detection in heatwave. The challenges posed by class imbalance and the limitations of traditional oversampling techniques are discussed, with insights into effective strategies for improving prediction accuracy. Accurate prediction of heatwaves enables mitigation plans to protect humans, animal and plants.