bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of a novel Sorcin isoform with a different C-terminal but intact dimerization property
Authors: Tanwar Supriya , Qais Faizan Abul , Naaz Farheen , Rashid Naira , Ahmad Faizan , ur Rehman Sayeed 
Published: September 2023

AbstractSorcin (Sri), a member of penta EF-hand protein family plays a diverse role in maintaining calcium homeostasis, cell cycle and vesicular trafficking. Sri is highly conserved amongst mammals and consists of N-terminal glycine rich domain and C-terminal calcium binding domain that mediates its dimerization and interacts with different compounds. In the present study, with the help of combination of computational and molecular biology techniques, we have identified a novel isoform (Sri-N) in mouse which differs only in the C-terminal domain with that of Sri reported earlier. The novel isoform contains a new last exon that is different from the one present in the reported transcript (Sri). The presence of the novel isoform was further validated in different tissues by RT-PCR and DNA sequencing. The transcript was conceptually translated and subjected to in-silico analysis using different bioinformatics tools. The novel transcript variant encodes for a longer protein isoform without any change in the sub-cellular localization as predicted by PSORT-II online tool. Molecular modelling was performed to compare the structural changes in Sri-N and Sri isoforms. The structural characterization of the novel isoform using MD simulation depicted its overall stability under the physiological conditions. The molecular docking of proteins with various chemotherapeutic drugs revealed that their binding affinity is more for Sri-N as compared to that for the previously reported transcript Sri.
A principled representation of elongated structures using heatmaps
Authors: Kordon Florian , Stiglmayr Michael , Maier Andreas , Martín Vicario Celia , Pertlwieser Tobias , Kunze Holger 
Published: September 2023

AbstractThe detection of elongated structures like lines or edges is an essential component in semantic image analysis. Classical approaches that rely on significant image gradients quickly reach their limits when the structure is context-dependent, amorphous, or not directly visible. This study introduces a principled mathematical description of elongated structures with various origins and shapes. Among others, it serves as an expressive operational description of target functions that can be well approximated by Convolutional Neural Networks. The nominal position of a curve and its positional uncertainty are encoded as a heatmap by convolving the curve distribution with a filter function. We propose a low-error approximation to the expensive numerical integration by evaluating a distance-dependent function, enabling a lightweight implementation with linear time complexity. We analyze the method’s numerical approximation error and behavior for different curve types and signal-to-noise levels. Application to surgical 2D and 3D data, semantic boundary detection, skeletonization, and other related tasks demonstrate the method’s versatility at low errors.
Accelerating the characterization of dynamic DNA origami devices with deep neural networks
Authors: Wang Yuchen , Jin Xin , Castro Carlos 
Published: September 2023

AbstractMechanical characterization of dynamic DNA nanodevices is essential to facilitate their use in applications like molecular diagnostics, force sensing, and nanorobotics that rely on device reconfiguration and interactions with other materials. A common approach to evaluate the mechanical properties of dynamic DNA nanodevices is by quantifying conformational distributions, where the magnitude of fluctuations correlates to the stiffness. This is generally carried out through manual measurement from experimental images, which is a tedious process and a critical bottleneck in the characterization pipeline. While many tools support the analysis of static molecular structures, there is a need for tools to facilitate the rapid characterization of dynamic DNA devices that undergo large conformational fluctuations. Here, we develop a data processing pipeline based on Deep Neural Networks (DNNs) to address this problem. The YOLOv5 and Resnet50 network architecture were used for the two key subtasks: particle detection and pose (i.e. conformation) estimation. We demonstrate effective network performance (F1 score 0.85 in particle detection) and good agreement with experimental distributions with limited user input and small training sets (~ 5 to 10 images). We also demonstrate this pipeline can be applied to multiple nanodevices, providing a robust approach for the rapid characterization of dynamic DNA devices.
A titratable murine model of progressive emphysema using tracheal porcine pancreatic elastase
Authors: Joshi Imani , Devine Andrew J. , Joshi Rashika , Smith Noah J. , Varisco Brian M. 
Published: September 2023

AbstractProgressive emphysema often leads to end-stage lung disease. Most mouse models of emphysema are typically modest (i.e. cigarette smoke exposure), and changes over time are difficult to quantify. The tracheal porcine pancreatic elastase model (PPE) produces severe injury, but the literature is conflicted as to whether emphysema improves, is stable, or progresses over time. We hypothesized a threshold of injury below which repair would occur and above which emphysema would be stable or progress. We treated 8-week-old C57BL6 mixed sex mice with 0, 0.5, 2, or 4 activity units of PPE in 100 µL PBS and performed lung stereology at 21 and 84 days. There were no significant differences in weight gain or mouse health. Despite minimal emphysema at 21-days in the 0.5 units group (2.8 µm increased mean linear intercept, MLI), MLI increased by 4.6 µm between days 21 and 84 (p = 0.0007). In addition to larger MLI at 21 days in 2- and 4-unit groups, MLI increases from day 21 to 84 were 17.2 and 34 µm respectively (p = 0.002 and p = 0.0001). Total lung volume increased, and alveolar surface area decreased with time and injury severity. Contrary to our hypothesis, we found no evidence of alveolar repair over time. Airspace destruction was both progressive and accelerative. Future mechanistic studies in lung immunity, mechano-biology, senescence, and cell-specific changes may lead to novel therapies to slow or halt progressive emphysema in humans.
Folate-conjugated near-infrared fluorescent perfluorocarbon nanoemulsions as theranostics for activated macrophage COX-2 inhibition
Authors: Vichare Riddhi , Crelli Caitlin , Liu Lu , McCallin Rebecca , Cowan Abree , Stratimirovic Stefan , Herneisey Michele , Pollock John A. , Janjic Jelena M. 
Published: September 2023

AbstractActivated macrophages play a critical role in the orchestration of inflammation and inflammatory pain in several chronic diseases. We present here the first perfluorocarbon nanoemulsion (PFC NE) that is designed to preferentially target activated macrophages and can deliver up to three payloads (two fluorescent dyes and a COX-2 inhibitor). Folate receptors are overexpressed on activated macrophages. Therefore, we introduced a folate-PEG-cholesterol conjugate into the formulation. The incorporation of folate conjugate did not require changes in processing parameters and did not change the droplet size or fluorescent properties of the PFC NE. The uptake of folate-conjugated PFC NE was higher in activated macrophages than in resting macrophages. Flow cytometry showed that the uptake of folate-conjugated PFC NE occurred by both phagocytosis and receptor-mediated endocytosis. Furthermore, folate-conjugated PFC NE inhibited the release of proinflammatory cytokines (TNF-α and IL-6) more effectively than nonmodified PFC NE, while drug loading and COX-2 inhibition were comparable. The PFC NEs reported here were successfully produced on multiple scales, from 25 to 200 mL, and by using two distinct processors (microfluidizers: M110S and LM20). Therefore, folate-conjugated PFC NEs are viable anti-inflammatory theranostic nanosystems for macrophage drug delivery and imaging.
Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae
Authors: Vieira Andressa de Almeida , Piccoli Bruna Candia , y Castro Thaís Regina , Casarin Bruna Campestrini , Tessele Luiza Funck , Martins Roberta Cristina Ruedas , Schwarzbold Alexandre Vargas , Trindade Priscila de Arruda 
Published: September 2023

AbstractAntimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory diagnosis, but there is limited evidence about pipeline validation to parse generated data. Thus, the present study aimed to validate a bioinformatics pipeline for the identification of antimicrobial resistance genes from carbapenem-resistant K. pneumoniae WGS. Sequences were obtained from a publicly available database, trimmed, de novo assembled, mapped to the K. pneumoniae reference genome, and annotated. Contigs were submitted to different tools for bacterial (Kraken2 and SpeciesFinder) and antimicrobial resistance gene identification (ResFinder and ABRicate). We analyzed 201 K. pneumoniae genomes. In the bacterial identification by Kraken2, all samples were correctly identified, and in SpeciesFinder, 92.54% were correctly identified as K. pneumoniae, 6.96% erroneously as Pseudomonas aeruginosa, and 0.5% erroneously as Citrobacter freundii. ResFinder found a greater number of antimicrobial resistance genes than ABRicate; however, many were identified more than once in the same sample. All tools presented 100% repeatability and reproducibility and > 75% performance in other metrics. Kraken2 was more assertive in recognizing bacterial species, and SpeciesFinder may need improvements.
On fast simulation of dynamical system with neural vector enhanced numerical solver
Authors: Huang Zhongzhan , Liang Senwei , Zhang Hong , Yang Haizhao , Lin Liang 
Published: September 2023

AbstractThe large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.
Allele mining of eukaryotic translation initiation factor genes in Prunus for the identification of new sources of resistance to sharka
Authors: Tricon David , Faivre d’Arcier Julie , Eyquard Jean-Philippe , Liu Shuo , Decroocq Stéphane , Chague Aurélie , Liu Weisheng , Balakishiyeva Gulnara , Mammadov Alamdar , Turdiev Timur , Kostritsyna Tatiana , Asma Bayram M. , Akparov Zeynal , Decroocq Véronique 
Published: September 2023

AbstractMembers of the eukaryotic translation initiation complex are co-opted in viral infection, leading to susceptibility in many crop species, including stone fruit trees (Prunus spp.). Therefore, modification of one of those eukaryotic translation initiation factors or changes in their gene expression may result in resistance. We searched the crop and wild Prunus germplasm from the Armeniaca and Amygdalus taxonomic sections for allelic variants in the eIF4E and eIFiso4E genes, to identify alleles potentially linked to resistance to Plum pox virus (PPV). Over one thousand stone fruit accessions (1397) were screened for variation in eIF4E and eIFiso4E transcript sequences which are in single copy within the diploid Prunus genome. We identified new alleles for both genes differing from haplotypes associated with PPV susceptible accessions. Overall, analyses showed that eIFiso4E is genetically more constrained since it displayed less polymorphism than eIF4E. We also demonstrated more variations at both loci in the related wild species than in crop species. As the eIFiso4E translation initiation factor was identified as indispensable for PPV infection, a selection of ten different eIFiso4E haplotypes along 13 accessions were tested by infection with PPV and eight of them displayed a range of reduced susceptibility to resistance, indicating new potential sources of resistance to sharka.
Effect of silymarin on the relative gene expressions of some inflammatory cytokines in the liver of CCl4-intoxicated male rats
Authors: El-Kot Sarah M. , Wanas Wessam , Hafez Afaf M. , Mahmoud Nihal A. , Tolba Amina M. , Younis Abeer H. , Sayed Gamal El , Abdelwahab Huda E. 
Published: September 2023

AbstractThe intensive exposure of the liver cells to any type of noxae, such as viruses, drugs, alcohols, and xenobiotics could induce hepatic inflammation through the upregulation of gene expression of several fibrotic and inflammatory mediators. So, our study assessed the role of silymarin on the inflammatory response induced by carbon tetrachloride (CCl4) as an example of xenobiotics on liver tissues in male rats. Forty-eight Wister male rats (weight: 130 ± 10) were housed for 14 days and then divided randomly into six groups: control, SLY: rats received only silymarin orally for 12 weeks (daily), CO: rats were injected with corn oil for 8 weeks (3 times weekly), CCl4: rats were injected with CCl4 solubilized in corn oil for 8 weeks (day by day), Treated: rats received silymarin for 4 weeks after CCl4 injection, Protected: rats received silymarin for 4 weeks before and 8 weeks during CCl4 injection. When the treatment period for the rats was over, they underwent scarification after anesthesia. Then, the sera were extracted from the collected blood for the determination of irisin levels, liver functions, and lipid profiles. Liver tissues were separated for the histopathological examinations, the determination of oxidative stress (OS) parameters content, and the relative gene expression of inflammatory cytokines; nuclear factor kappa (NF)-κB, tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, cyclooxygenase (COX)-2, and transforming growth factor beta (TGF-β). The findings showed that silymarin reduced liver inflammation by overcoming the OS process and inflammatory cytokines production which was stimulated by CCl4. These results were confirmed by histopathology of liver tissues.
Membrane fouling monitoring by 3ω sensing
Authors: Jørgensen Mads Koustrup , Paulsen Frederikke Kildeberg , Bentien Anders , Kjul Astrid Ræbild , Poulsen Maiken , Mikkelsen Louise Mailund , Thavaneswaran Nikitha , Hansen Simon Abildgaard , Jensen Pernille Krogsager , Andersen Jacob , Østedgaard-Munck David N. , Bendtsen Jan Dimon , Christensen Morten Lykkegaard 
Published: September 2023

AbstractMembrane fouling significantly reduces membrane permeability, leading to higher operational expenses. In situ monitoring of membrane fouling can potentially be used to reduce operation cost by optimizing operational parameters and cleaning conditions. In this study, a platinum wire with a diameter of 20 µm was attached to the surface of a ceramic ultrafiltration membrane, and by measuring the voltage across the wire while applying an AC current, the amplitude of the third harmonic wave, the so-called 3ω signal, was obtained. Results showed increasing 3ω signals during formation of fouling layers, which correlates directly to the hydraulic resistance of the formed fouling layer in semi-dead end filtration of polymeric core shell particles and crossflow filtration of diluted milk. This is explained by the insulating effect of the fouling layers which reduces heat convection by crossflow and the different thermal conductivity in the fouling layer compared with the feed. After membrane cleaning, the permeability and the magnitude of the 3ω signal were partly restored, showing that the 3ω method can be used to monitor the effect of cleaning. The frequency of the AC current was varied so it was possible to measure the heat conductivity in the fouling layer (high frequency) and heat convection due to cross-flow (low frequency). This may potentially be used to get information of the type of fouling (heat conductivity) and thickness of the fouling layer (AC frequency where heat conductivity becomes dominating).
Modelling of compression ignition engine by soft computing techniques (ANFIS-NSGA-II and RSM) to enhance the performance characteristics for leachate blends with nano-additives
Authors: Khan Osama , Parvez Mohd , Kumari Pratibha , Yadav Ashok Kumar , Akram Wasim , Ahmad Shadab , Parvez Samia , Idrisi Mohammad Javed 
Published: September 2023

AbstractIntegrating nanoparticles in waste oil-derived biodiesel can revolutionize its performance in internal combustion engines, making it a promising fuel for the future. Nanoparticles act as combustion catalysts, enhancing combustion efficiency, reducing emissions, and improving fuel economy. This study employed a comprehensive approach, incorporating both quantitative and qualitative analyses, to investigate the influence of selected input parameters on the performance and exhaust characteristics of biodiesel engines. The focus of this study is on the potential of using oils extracted from food waste that ended up in landfills. The study's results are analysed and compared with models created using intelligent hybrid prediction approaches including adaptive neuro-fuzzy inference system, Response surface methodology-Genetic algorithm, and Non sorting genetic algorithm. The analysis takes into account engine load, blend percentage, nano-additive concentration, and injection pressure, and the desired responses are the thermal efficiency and specific energy consumption of the brakes, as well as the concentrations of carbon monoxide, unburned hydrocarbon, and oxides of nitrogen. Root-mean-square error and the coefficient of determination were used to assess the predictive power of the model. Comparatively to Artificial Intelligence and the Response Surface Methodology-Genetic Algorithm model, the results provided by NSGA-II are superior. This is because it achieved a pareto optimum front of 24.45 kW, 2.76, 159.54 ppm, 4.68 ppm, and 0.020243% for Brake Thermal Efficiency, Brake Specific Energy Consumption, Oxides of nitrogen, Unburnt Hydro Carbon, and Carbon monoxide. Combining the precision of ANFIS's prediction with the efficiency of NSGA-optimization II's gives a reliable and thorough evaluation of the engine's settings. The qualitative assessment considered practical aspects and engineering constraints, ensuring the feasibility of applying the parameters in real-world engine applications.
Treatment with Ligilactobacillus murinus lowers blood pressure and intestinal permeability in spontaneously hypertensive rats
Authors: Mukohda Masashi , Yano Takanori , Matsui Toshiyasu , Nakamura Sho , Miyamae Jiro , Toyama Kensuke , Mitsui Ryoji , Mizuno Risuke , Ozaki Hiroshi 
Published: September 2023

AbstractOne feature of hypertension is a microbial imbalance with increased intestinal permeability. In this study, we examined whether an alteration in the microbiota affects blood pressure and intestinal permeability in spontaneously hypertensive rats (SHRs). We performed a 16S metagenome analysis of feces from 10- to 15-week-old SHRs using a synthetic long-read sequencing approach, and found a candidate for the microbiome treatment, Ligilactobacillus murinus (L. murinus), that was robustly decreased. Oral administration of L. murinus to SHRs for 2 weeks significantly inhibited blood pressure elevation and improved endothelium-dependent vasodilation but did not attenuate enhanced vascular contraction in SHR mesenteric arteries. The proximal colon of SHRs exhibited increased intestinal permeability with decreased levels of the tight junction protein claudin 4, morphological changes such as decreased intestinal crypts and elevated TNF-α levels, which was reversed by treatment with L. murinus. Consistent with these intestinal phenotypes, plasma lipopolysaccharides levels were elevated in SHR but decreased following L. murinus administration. We concluded that oral administration of L. murinus to SHRs exerts protective effects on intestinal permeability via restoration of claudin 4 expression and reversal of morphologic disorder, which may improve low-grade endotoxemia and thus reduce development of hypertension via recovery of endothelial vasodilating functions.
Insights from a cross-sectional survey of neonatal resuscitation instructors from India
Authors: Patel Purvi , Nimbalkar Somashekhar , Shinde Mayur 
Published: September 2023

AbstractNeonatal resuscitation training can change outcomes of neonatal mortality due to perinatal asphyxia. Recently, in 2021, the advanced NRP course material was changed, and for Basic NRP, a hybrid course was introduced in India. We assessed the instructor’s feedback to improve the conduct of the IAP NNF NRP Program as well as get their perception of the effectiveness, usefulness, and pitfalls of the new hybrid Basic NRP course (offline + online). A cross-sectional survey was conducted amongst instructors across India with current status with IAP NRP FGM Office. The data were exported to a Microsoft Excel Spreadsheet. STATA 14.2 was used for descriptive [Frequency (percent) analysis. 827 basic and 221 advanced NRP instructors responded. Bag and mask ventilation was identified as the most important step in basic 468 (56.6%) and advanced 147 (66.5%) courses. In the basic NRP, almost two third (71.0%) participants believe that it is challenging to conduct a case scenario for bag and mask ventilation, whereas, in the advanced course, intubation 116 (52.5%) was considered the most difficult step to teach and medication 80(36.2%) followed by intubation 62(28.1%) are the most difficult steps to conduct case scenario. 725(87.7%) reported that it would be easy to explain them in an offline course after completion of an online course. Most of the instructors were satisfied with the course structure, material, overall quality of the workshop, and support from the IAP NRP office. Constructive suggestions were obtained from the instructors for improvement of the course.