bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gastrointestinal transit mathematical model in mice treated with antibiotics
Authors: Maskawa Rie , Takayasu Lena , Takayasu Hideki , Watanabe Keiji , Takemine Shusuke , Kakimoto Takashi , Takeshita Kozue , Narushima Seiko , Suda Wataru , Takayasu Misako 
Published: May 2023

ABSTRACTFecal pharmacokinetics is crucial in developing treatment design and evaluating gastrointestinal motility; however, it has not been yet elucidated. This study aimed to elucidate the fecal pharmacokinetics in mice orally administered vancomycin and establish a pharmacokinetic model with interpretable system parameters. In this study, we quantified the antibiotic concentrations in fecal samples collected at high frequency from C57BL/6J mice treated with single oral doses of low and high (1 and 20 mg/mL) concentrations of vancomycin. Samples were taken at approximately 4-hour intervals after administration of antibiotics, making it possible to track the dynamics of vancomycin in the feces with high resolution. Mice structurally pool contents in the stomach and cecum, so we constructed an intestinal transit model that compartmentalizes these organs. Two models were built based on the functional form of gastric content elimination, and physiological parameters such as gastric emptying and intestinal transit time were estimated using high-resolution actual data from each mouse. Fortunately, both models were suitable for evaluating the antibiotic concentrations in feces. By simulation, we confirmed that our estimates of model parameters, which are quite difficult to measure experimentally, are satisfactory. Importantly, this study is applicable to fundamental research relating to pharmacokinetics in the gastrointestinal tract.NEW & NOTEWORTHYThis study tracked the pharmacokinetics of orally administered vancomycin by measuring its concentration in feces and described it using a mathematical model based on the physiological characteristics of mice to replicate these dynamics. As a predictive model, it allows for estimation of drug dynamics outside of the sampling time and extrapolation to individuals with different physiological characteristics.
A Comparative Study of Protein Structure Prediction Tools for Challenging Targets: Snake Venom Toxins
Authors: Kalogeropoulos Konstantinos , Bohn Markus-Frederik , Jenkins David E. , Ledergerber Jann , Sørensen Christoffer V. , Hofmann Nils , Wade Jack , Fryer Thomas , Nguyen Giang Thi Tuyet , auf dem Keller Ullrich , Laustsen Andreas H. , Jenkins Timothy P. 
Published: May 2023

AbstractProtein structure determination is a critical aspect of biological research, enabling us to understand protein function and potential applications. Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as AlphaFold2 and ColabFold. However, their performance has primarily been evaluated on well-characterised proteins, and comparisons using proteins with poor reference templates are lacking. In this study, we evaluated three modelling tools on their prediction of over 1000 snake venom toxin structures with no reference templates. Our findings show that AlphaFold2 (AF2) performed the best across all assessed parameters. We also observed that ColabFold (CF) only scored slightly worse than AF2, while being computationally less intensive. All tools struggled with regions of intrinsic disorder, such as loops and propeptide regions, and performed well in predicting the structure of functional domains. Overall, our study highlights the importance of exercising caution when working with proteins that have poor reference templates, are large, and contain flexible regions. Nonetheless, leveraging computational structure prediction tools can provide valuable insights into the modelling of protein interactions with different targets and reveal potential binding sites, active sites, and conformational changes, as well as into the design of potential molecular binders for reagent, diagnostic, or therapeutic purposes.StatementRecent advances in machine learning have led to the development of new protein structure prediction tools. However, these tools have mainly been tested on well-known proteins and their performance on proteins without known templates is unclear. This study evaluated the performance of three tools on over 1000 snake venom toxins. We found that while caution is required when studying poorly characterised proteins, these tools offer valuable opportunities to understand protein function and applications.
Introgression of a dominant phototropin1 mutant superenhances carotenoids and boosts flavor-related volatiles in genome-edited tomatoRINmutants
Authors: Nizampatnam Narasimha Rao , Sharma Kapil , Gupta Prateek , Pamei Injangbuanang , Sarma Supriya , Sreelakshmi Yellamaraju , Sharma Rameshwar 
Published: May 2023

AbstractThe tomato (Solanum lycopersicum) ripening inhibitor (rin) mutation is known to completely repress fruit ripening. The heterozygous (RIN/rin) fruits have extended shelf life, ripen normally, but have poor taste and flavour. Even the CRISPR/Cas9-generatedrinalleles have these undesirable attributes associated with therinmutation. To address this, we used genome editing to generate newer alleles ofRIN(rinCR) by targeting the K domain, which is essential for the oligomerization of MADS-box transcription factors. Unlike previously reported CRISPR alleles, therinCRalleles displayed delayed onset of ripening, suggesting that the mutated K domain represses the onset of ripening. TherinCRfruits had extended shelf life and accumulated carotenoids at an intermediate level betweenrinand wild-type parent. Besides, the metabolites and hormonal levels inrinCRfruits were more akin torin. To overcome the negative attributes ofrin, we crossed therinCRalleles withNps1, which enhances carotenoid levels in tomato fruits.Nps1harbours a dominant-negative mutation in the plant photoreceptor phototropin1. The resultingNps1/rinCRhybrids had extended shelf life and 4.4-7.1-fold higher carotenoid levels than the wild-type parent. TheNps1/rinCRfruits had higher auxin and reduced ABA levels, which are reportedly linked with slower ripening. The metabolome ofNps1/rinCRfruits revealed higher sucrose, malate, and volatiles associated with tomato taste and flavour. Notably, the boosted volatile levels inNps1/rinCRwere only observed in fruits bearing the homozygousNps1(Nps1/Nps1) mutation. Our findings suggest that theNps1introgression into tomato ripening mutants provides a promising strategy for developing tomato cultivars with extended shelf life, improved taste, and flavour.
Mesoscale simulation of biomembranes with FreeDTS
Authors: Pezeshkian Weria , Ipsen John H. 
Published: May 2023

AbstractWe present FreeDTS software for performing computational research on biomembranes at the mesoscale. In this software, a membrane is represented by a dynamically triangulated surface equipped with vertex-based inclusions to integrate the effects of integral and peripheral membrane proteins. Several algorithms are included in the software to simulate complex membranes at different conditions such as framed membranes with constant tension, vesicles and high-genus membranes with various fixed volumes or constant pressure differences and applying external forces to membrane regions. Furthermore, the software allows the user to turn off the shape evolution of the membrane and focus solely on the organization of proteins. As a result, we can take realistic membrane shapes obtained from, for example, cryo-electron tomography and backmap them into a finer simulation model. In addition to many biomembrane applications, this software brings us a step closer to simulating realistic biomembranes with molecular resolution. Here we provide several interesting showcases of the power of the software but leave a wide range of potential applications for interested users.
Deciphering the rule of antigen-antibody amino acid interaction
Authors: Jiang Min , Fang Changyin , Ma Yongping 
Published: May 2023

AbstractAntigenic drift is the biggest challenge for mutagenic RNA virus vaccine development. The most fundamental but neglected thing is to determine the immune escape mutation map (IEMM) of 20 amino acids to reveal the rule of the viral immune escape. We use universal protein tags as a linear epitope model to determine the relationship between the epitope mutation and immune escape. To describe and draw amino acid interaction maps, mutations of protein tags are classified into four types: IEM (immune escape mutation), ADERM (antibody-dependent enhancement risk mutation), EQM (equivalent mutation), and IVM (invalid mutation). To make up for the data limitation, the amino acid interaction pairs determined by 3D structure through literature search are simultaneously used to form a more systematic and universal antigen-antibody interaction maps. The results are: (i) one residue interacts with multiple amino acids in antigen-antibody interaction; (ii) Most amino acid replacements are IVM and EQM. (iii) Once aromatic amino acids replace non-aromatic amino acids, the mutation is often inactive. (iv) Substituting residues with the same physical and chemical properties easily lead to IEM. Therefore, this study had important theoretical significance for future research on antigenic drift, antibody rescue and vaccine renewal design.ImportanceWe typed the antigenic epitope mutations into IEM, ADERM, EQM, and IVM types to describe and quantify the results of antigenic mutations. According to the results, the antigen-antibody interaction rule was summarized as one-to-many interaction rule. To sum up, the Epitope mutation rules were defined as IVM and EQM predomination rule, aryl mutation escape rule and homogeneous mutation escape rule.
Skin permeable polymer for noninvasive transdermal insulin delivery
Authors: Wei Qiuyu , He Zhi , Xiang Jiajia , Piao Ying , Huang Jianxiang , Geng Yu , Zhu Haoru , Li Zifan , Zeng Jiaheng , Zhang Yan , Lu Hongrui , Zhou Quan , Shao Shiqun , Tang Jianbin , Zhou Zhuxian , Zhou Ruhong , Shen Youqing 
Published: May 2023

AbstractSubcutaneous injection of insulin is the current standard medication for many diabetic patients. Convenient and painless noninvasive transdermal insulin delivery has long been pursued but yet succeeded due to no such technologies for large biomacromolecules. We find a tertiary amine oxide-based polyzwitterion, OPDMA, that can efficiently penetrate both the stratum corneum (SC) and viable epidermis into circulation. So its conjugate with insulin, OPDMA-I, applied on the skin can exhibit hypoglycemic effects as efficiently as subcutaneously injected insulin in type-1 diabetic mice and minipigs. The unique pH-dependent cationic-to-zwitterionic transition of OPDMA in the characteristic acidic-to-neutral pH gradient from the skin surface to deep SC enables fast transdermal delivery of OPDMA and its conjugate. On the skin, OPDMA binds to carboxylic acids in the acidic sebum layer, enriching OPDMA-I on the SC. As pH increases in deeper SC layers, binding between OPDMA-I and the skin weakens gradually, allowing for diffusion through inter-corneocyte gaps and penetration into viable epidermis and finally entering the systemic circulation via dermal lymphatic vessels. This process does not alter SC microstructures or cause any physiological changes in the skin. This study represents a groundbreaking example of noninvasive transdermal protein delivery.
Pangenome calculation beyond the species level using RIBAP: A comprehensive bacterial core genome annotation pipeline based on Roary and pairwise ILPs
Authors: Lamkiewicz Kevin , Barf Lisa-Marie , Sachse Konrad , Hölzer Martin 
Published: May 2023

AbstractPangenome analysis is a computational method for identifying genes that are present or absent from a group of genomes, which helps to understand evolutionary relationships and to identify essential genes. While current state-of-the-art approaches for calculating pangenomes comprise various software tools and algorithms, these methods can have limitations such as low sensitivity, specificity, and poor performance on specific genome compositions. A common task is the identification of core genes, i.e., genes that are present in (almost) all input genomes. However, especially for species with high sequence diversity, e.g., higher taxonomic orders like genera or families, identifying core genes is challenging for current methods. We developed RIBAP (Roary ILP Bacterial core Annotation Pipeline) to specifically address these limitations. RIBAP utilizes an integer linear programming (ILP) approach that refines the gene clusters initially predicted by the pangenome pipeline Roary. Our approach performs pairwise all-versus-all sequence similarity searches on all annotated genes for the input genomes and translates the results into an ILP formulation. With the help of these ILPs, RIBAP has successfully handled the complexity and diversity ofChlamydia, Klebsiella, Brucella, and Enterococcusgenomes, even when genomes of different species are part of the analysis. We compared the results of RIBAP with other established and recent pangenome tools (Roary, Panaroo, PPanGGOLiN) and showed that RIBAP identifies all-encompassing core gene sets, especially at the genus level. RIBAP is freely available as a Nextflow pipeline under the GPL3 license:https://github.com/hoelzer-lab/ribap.
Neural representation strength of predicted category features biases decision behavior
Authors: Yan Yuening , Zhan Jiayu , Garrod Oliver , Cui Xuan , Ince Robin A.A. , Schyns Philippe G. 
Published: May 2023

AbstractTheories of prediction-for-perception propose that the brain predicts the information contents of upcoming stimuli to facilitate their perceptual categorization. A mechanistic understanding should therefore address where, when, and how the brain predicts the stimulus features that change behavior. However, typical approaches do not address these predicted stimulus features. Instead, multivariate classifiers are trained to contrast the bottom-up patterns of neural activity between two stimulus categories. These classifiers then quantify top-down predictions as reactivations of the category contrast. However, a category-contrast cannot quantify the features reactivated for each category–which might be from either category, or both. To study the predicted category-features, we randomly sampled features of stimuli that afford two categorical perceptions and trained multivariate classifiers to discriminate the features specific to each. In a cueing design, we show where, when and how trial-by-trial category-feature reactivation strength directly biases decision behavior, transforming our conceptual and mechanistic understanding of prediction-for-perception.
Insights from a genome-wide truth set of tandem repeat variation
Authors: Weisburd Ben , Tiao Grace , Rehm Heidi L. 
Published: May 2023

AbstractTools for genotyping tandem repeats (TRs) from short read sequencing data have improved significantly over the past decade. Extensive comparisons of these tools to gold standard diagnostic methods like RP-PCR have confirmed their accuracy for tens to hundreds of well-studied loci. However, a scarcity of high-quality orthogonal truth data limited our ability to measure tool accuracy for the millions of other loci throughout the genome. To address this, we developed a TR truth set based on the Synthetic Diploid Benchmark (SynDip). By identifying the subset of insertions and deletions that represent TR expansions or contractions with motifs between 2 and 50 base pairs, we obtained accurate genotypes for 139,795 pure and 6,845 interrupted repeats in a single diploid sample. Our approach did not require running existing genotyping tools on short read or long read sequencing data and provided an alternative, more accurate view of tandem repeat variation. We applied this truth set to compare the strengths and weaknesses of widely-used tools for genotyping TRs, evaluated the completeness of existing genome-wide TR catalogs, and explored the properties of tandem repeat variation throughout the genome. We found that, without filtering, ExpansionHunter had higher accuracy than GangSTR and HipSTR over a wide range of motifs and allele sizes. Also, when errors in allele size occurred, ExpansionHunter tended to overestimate expansion sizes, while GangSTR tended to underestimate them. Additionally, we saw that widely-used TR catalogs miss between 16% and 41% of variant loci in the truth set. These results suggest that genome-wide analyses would benefit from genotyping a larger set of loci as well as further tool development that builds on the strengths of current algorithms. To that end, we developed a new catalog of 2.8 million loci that captures 95% of variant loci in the truth set, and created a modified version of ExpansionHunter that runs 2 to 3x faster than the original while producing the same output.
Theranostic gold in a gold cage nanoparticle for photothermal ablation and photoacoustic imaging of skin and oral infections
Authors: Hajfathalian Maryam , de Vries Christiaan R. , Hsu Jessica C. , Amirshaghaghi Ahmad , Dong Yuxi C. , Ren Zhi , Liu Yuan , Huang Yue , Li Yong , Knight Simon , Jonnalagadda Pallavi , Zlitni Aimen , Grice Elizabeth , Bollyky Paul L. , Koo Hyun , Cormode David. P. 
Published: May 2023

AbstractBiofilms are structured communities of microbial cells embedded in a self-produced matrix of extracellular polymeric substances. Biofilms are associated with many health issues in humans, including chronic wound infections and tooth decay. Current antimicrobials are often incapable of disrupting the polymeric biofilm matrix and reaching the bacteria within. Alternative approaches are needed. Here, we describe a unique structure of dextran coated gold in a gold cage nanoparticle that enables photoacoustic and photothermal properties for biofilm detection and treatment. Activation of these nanoparticles with a near infrared laser can selectively detect and kill biofilm bacteria with precise spatial control and in a short timeframe. We observe a strong biocidal effect against both Streptococcus mutans and Staphylococcus aureus biofilms in mouse models of oral plaque and wound infections respectively. These effects were over 100 times greater than that seen with chlorhexidine, a conventional antimicrobial agent. Moreover, this approach did not adversely affect surrounding tissues. We conclude that photothermal ablation using theranostic nanoparticles is a rapid, precise, and non-toxic method to detect and treat biofilm-associated infections.
TGF-β Ligand Cross-Subfamily Interactions in the Response ofCaenorhabditis elegansto Bacterial Pathogens
Authors: Ciccarelli Emma Jo , Wing Zachary , Bendelstein Moshe , Johal Ramandeep Kaur , Singh Gurjot , Monas Ayelet , Savage-Dunn Cathy 
Published: May 2023

AbstractThe Transforming Growth Factor beta (TGF-β) family consists of numerous secreted peptide growth factors that play significant roles in cell function, tissue patterning, and organismal homeostasis, including wound repair and immunity. Typically studied as homodimers, these ligands have the potential to diversify their functions through ligand interactions that are synergistic, cooperative, additive, and/or antagonistic. In the nematodeCaenorhabditis elegans, there are only five TGF-β ligands, providing an opportunity to dissect ligand interactions in fewer combinations than in vertebrates. As in vertebrates, these ligands can be divided into bone morphogenetic protein (BMP) and TGF-β/Activin subfamilies that predominantly signal through discrete signaling pathways. The BMP subfamily ligand DBL-1 has been well studied for its role in the innate immune response inC. elegans. Here we show that all five TGF-β ligands play a role in the immune response. We also demonstrate that multiple TGF-β ligands act cooperatively as part of this response. We show that the two BMP-like ligands – DBL-1 and TIG-2 – function independently of each other in the immune response, while TIG-2/BMP and the TGF-β/Activin-like ligand TIG-3 function cooperatively. Structural modeling supports the potential for TIG-2 and TIG-3 to form heterodimers. Finally, we show that canonical DBL-1/BMP receptor and Smad signal transducers function in the response to bacterial pathogens, while components of the DAF-7 TGF-β/Activin signaling pathway do not play a role in survival. These results demonstrate a novel potential for BMP and TGF-β/Activin subfamily ligands to interact, and may provide a mechanism for distinguishing the developmental and homeostatic functions of these ligands from an acute response such as the innate immune response to bacterial pathogens.
Association of Seizure with COVID-19 Vaccines in Persons with Epilepsy: A Systematic Review and Meta-analysis
Authors: Rafati Ali , Jameie Melika , Amanollahi Mobina , Jameie Mana , Pasebani Yeganeh , Sakhaei Delaram , Ilkhani Saba , Rashedi Sina , Pasebani Mohammad Yazdan , Azadi Mohammadreza , Rahimlou Mehran , Kwon Churl-Su 
Published: May 2023

AbstractObjectiveSeizure following immunization, especially in persons with epilepsy (PwE), has long been a concern, and seizure aggravation followed by Coronavirus Disease 2019 (COVID-19) vaccines is a serious issue for PwE. The immunization rate in PwE has been lower compared to same-age controls due to vaccine hesitancy and concerns about seizure control. Herein, we systematically reviewed the seizure activity-related events in PwE following COVID-19 vaccination.MethodsFour search engines were searched from inception until January 31, 2023, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was followed. Random- and fixed-effect models using the logit transformation method were used for meta-analysis. The quality of the studies was evaluated by the Newcastle-Ottawa scale. Outcomes of interest included (a) pooled proportion of increased seizure frequency and (b) pooled incidence proportion of status epilepticus (SE) in PwE receiving COVID-19 vaccines.ResultsOf the 2207 studies identified, 18 met eligibility criteria, of which 16 entered the meta-analysis. The pooled proportion of increased seizure frequency (16 studies-4197 PwE) was 5% (95CI: 3%-6%, I2=57%), further subcategorized into viral vector (3%, 95CI: 2%-7%, I2=0%), mRNA (5%, 95CI: 4%-7%, I2=48%), and inactivated (4%, 95CI: 2%-8%, I2=77%) vaccines. The pooled incidence proportion of SE (15 studies-2480 PwE) was 0.08% (95CI: 0.02%-0.32%, I2=0%), further subcategorized into the viral vector (0.00%, 95CI: 0.00%-1.00%, I2=0%), mRNA (0.09%, 95CI: 0.01%-0.62%, I2=0%), and inactivated (0.00%, 95CI: 0.00%-1.00%, I2=0%) vaccines. No significant difference was observed between mRNA and viral vector vaccines (5 studies, 1122 vs. 198 PwE, respectively) regarding increased seizure frequency (OR: 1.10, 95CI: 0.49-2.50, p-value=0.81, I2=0%).SignificanceThe meta-analysis proposed a 5% increased seizure frequency following COVID-19 vaccination in PwE, with no difference between mRNA and viral vector vaccines. Furthermore, we found a 0.08% incidence proportion for SE. While this safety evidence is noteworthy, this cost should be weighed against vaccination benefits.