bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical and Optical Coherence Tomography Correlation of Recurrence Patterns After Femtosecond Laser–Assisted Anterior Lamellar Keratoplasty in Reis–Bucklers Corneal Dystrophy
Authors: Chaurasia Sunita , Mishra Dilip K. , Murthy Somasheila , Das Rajashree , Edward Deepak P. , Ramappa Muralidhar 
Published: September 2023

Purpose:
The aim of this study was to report the clinical profile and patterns of recurrence after femtosecond laser–assisted anterior lamellar keratoplasty (FALK) in Reis–Bucklers corneal dystrophy.

Methods:
This is a case series of 5 eyes of 4 patients with Reis–Bucklers corneal dystrophy. Clinical images of recurrence were correlated with the high-resolution optical coherence tomography. Histopathologic examination of excised corneal samples was performed when possible.

Results:
The median time to recurrence was 2 (1–5) years after FALK. Of the 5 eyes, 1 eye had primary FALK, whereas 4 eyes had secondary interventions, which included previous phototherapeutic keratectomy (once in 1 eye and twice in 2 eyes), and previous penetrating keratoplasty, followed by phototherapeutic keratectomy (1 eye). Recurrence was noted at the level of the subepithelium. In addition, 1 eye showed interface deposits along with epithelial downgrowth at the graft–host bed.

Conclusions:
The 2 distinct patterns of recurrence noted were at the subepithelial region and the interface. The clinical patterns of recurrence favor an epithelial origin of recurrent deposits.
2-bromo-2’5’-dihydroxychalcone analogue Inhibits Endothelial Migration by Targeting VEGF-induced ERK 1/2 Phosphorylation
Authors: Hussain Aamir , Festa Joseph , Singh Harprit 
Published: September 2023

AbstractAngiogenesis, the process of new blood vessel formation, is characterized by three essential hallmarks: endothelial proliferation, migration, and differentiation. Each is integral in angiogenesis related diseases, especially cancer. With drug efficacy stagnated due to acquired drug resistance and off target side effects, the need for combinatorial therapy is ever more present. To identify new compounds that could aid current antiangiogenic therapies, we report the preliminary mechanistic evaluation of a 2-bromo-2’5’-dihydroxychalcone analogue and its antimigratory effects on endothelial cells. After the synthesis and validation of the 2-bromo-2’5’-dihydroxychalcone analogue (AH9), its effect was tested in vitro using human umbilical vein endothelial cells (HUVEC). Initial investigations into 2-bromo-2’5’-dihydroxychalcone effect in vitro was conducted with a cell proliferation assay including MTT, afterward endothelial migration was measured with the scratch assay in subsequent functional studies. For mechanistic evaluation, vascular endothelial growth factor (VEGF) induced ERK phosphorylation using western blot was implemented. AH9 inhibited VEGF-induced ERK ½ phosphorylation similar to that of known antiangiogenic drug Sorafenib at all three concentrations 100 μM (46%,p= 0.003), 30 μM (64%,p= 0.0002) and 10 μM (91%,p= 0.0001). In a scratch assay model, whilst sorafenib at 3 μM was not able to limit migration after 8-hr compared to an untreated control (p = 0.0978), AH9 did (17.41%, p = 0.0079). Furthermore, AH9 was able to inhibit ERK ½ phosphorylation in a concentration dependent manner 100 μM (46%, p = 0.003), 30 μM (64%, p = 0.0002) and 10 μM (91%, p = 0.0001) compared to the VEGF control. These preliminary findings support that AH9 could be exerting antimigratory effects through the inhibition of the VEGF induced MAPK/ERK pathway. This forms the foundation for further studies to explore chalcone analogues in hope to aid current antiangiogenic therapeutic strategies as potential angiogenic inhibitors.
Numerical and analytical simulation of the growth of amyloid-β plaques
Authors: Kuznetsov Andrey V. 
Published: September 2023

AbstractNumerical and analytical solutions were employed to calculate the radius of an amyloid-β (Aβ) plaque over time. To the author’s knowledge, this study presents the first model simulating the growth of Aβ plaques. Findings indicate that the plaque can attain a diameter of 50 μm after 20 years of growth, provided the Aβ monomer degradation machinery is malfunctioning. A mathematical model incorporates nucleation and autocatalytic growth processes using the Finke-Watzky model. The resulting system of ordinary differential equations was solved numerically, and for the simplified case of infinitely long Aβ monomer half-life, an analytical solution was found. Assuming that Aβ aggregates stick together and using the distance between the plaques as an input parameter of the model, it was possible to calculate the plaque radius from the concentration of Aβ aggregates. This led to the “cube root hypothesis,” positing that Aβ plaque size increases proportionally to the cube root of time. This hypothesis helps explain why larger plaques grow more slowly. Furthermore, the obtained results suggest that the plaque size is independent of the kinetic constants governing Aβ plaque agglomeration, indicating that the kinetics of Aβ plaque agglomeration is not a limiting factor for plaque growth. Instead, the plaque growth rate is limited by the rates of Aβ monomer production and degradation.
Mechanisms of Cell Size Regulation in Slow-GrowingEscherichia coliCells: Discriminating Models Beyond the Adder
Authors: Nieto César , Vargas-García César , Pedraza Juan Manuel , Singh Abhyudai 
Published: September 2023

AbstractUnder ideal conditions,Escherichia colicells divide after adding a fixed cell size, a strategy known as theadder. This concept applies to various microbes and is often explained as the division that occurs after a certain number of stages, associated with the accumulation of precursor proteins at a rate proportional to cell size. However, under poor media conditions,E. colicells exhibit a different size regulation. They are smaller and follow asizer-likedivision strategy where the added size is inversely proportional to the size at birth. We explore three potential causes for this deviation: precursor protein degradation, nonlinear accumulation rate, and a threshold size termed thecommitment size. These models fit mean trends but predict different distributions given the birth size. To validate these models, we used the Akaike information criterion and compared them to open datasets of slow-growingE. colicells in different media. the degradation model could explain the division strategy for media where cells are larger, while the commitment size model could account for smaller cells. The power-law model, finally, better fits the data at intermediate regimes.
Non-preferential, but detrimental accumulation of macrophages with clonal hematopoiesis-driver mutations in cardiovascular tissues
Authors: Dederichs Tsai-Sang , Yerdenova Assel , Horstmann Hauke , Vico Tamara , Nübling Simone , Peyronnet Remi , von zur Muehlen Constantin , Heidt Timo , Wolf Dennis , Westermann Dirk , Hilgendorf Ingo 
Published: September 2023

SummaryClonal hematopoiesis of indeterminate potential (CHIP) is an acquired genetic risk factor for cardiovascular (CV) disease, supposedly mediated by pro-inflammatory recruited monocytes1–15. However, how these cells and their progeny behave in the CV tissue remains unclear. Here, we studied human carotid artery plaque and heart tissue samples fromDNMT3AorTET2mutation carriers to quantify the relative accumulation of mutated macrophages and to characterize tissue macrophages from carriers compared to non-carriers. Using droplet digital polymerase chain reaction (ddPCR), we detected similar sizes of CHIP clones in circulating monocytes and macrophages from atheromas and heart tissues, even among CCR2+ (infiltrative), and CCR2– (resident) cardiac macrophages. Using bulk RNA-sequencing (RNA-seq), we revealed a pro-inflammatory gene profile of myeloid cells from CHIP carriers compared to non-carriers. In summary, quantitatively, CHIP mutated myeloid cells did not preferentially accumulate in CV tissues, but qualitatively, they expressed a more disease-prone phenotype.
omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data
Authors: Lin Weiqiang , Ji Jiadong , Su Kuan-Jui , Qiu Chuan , Tian Qing , Zhao Lan-Juan , Luo Zhe , Shen Hui , Wu Chong , Deng Hongwen 
Published: September 2023

AbstractMass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometrybasedomicswith Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available athttps://github.com/WQLin8/omicsMIC.
Genomic analysis reveals limited hybridization among three giraffe species in Kenya
Authors: Coimbra Raphael T. F. , Winter Sven , Muneza Arthur , Fennessy Stephanie , Otiende Moses , Mijele Domnic , Masiaine Symon , Stacy-Dawes Jenna , Fennessy Julian , Janke Axel 
Published: September 2023

AbstractBackgroundIn the speciation continuum the strength of reproductive isolation varies, and species boundaries are blurred by gene flow. Interbreeding among giraffe (Giraffaspp.) in captivity is known and anecdotal reports of natural hybrids exist. In Kenya, Nubian (G. camelopardalis camelopardalis), reticulated (G. reticulata), and Masai giraffe sensu stricto (G. tippelskirchi tippelskirchi) are parapatric, and thus the country might be a melting pot for these taxa. We analyzed 128 genomes of wild giraffe, 113 newly sequenced, representing these three taxa.ResultsWe found varying levels of Nubian ancestry in 13 reticulated giraffe sampled across the Laikipia Plateau most likely reflecting historical gene flow between these two lineages. Although comparatively weaker signs of ancestral gene flow and potential mitochondrial introgression from reticulated into Masai giraffe were also detected, estimated admixture levels between these two lineages are minimal. Importantly, contemporary gene flow between East African giraffe lineages was not statistically significant. Effective population sizes have declined since the Late Pleistocene, more severely for Nubian and reticulated giraffe.ConclusionsDespite historically hybridizing, these three giraffe lineages have maintained their overall genomic integrity suggesting effective reproductive isolation, consistent with the previous classification of giraffe into four species.
Prediction of Interactions between Cell Surface Proteins by Machine Learning
Authors: Su Zhaoqian , Griffin Brian , Emmons Scott , Wu Yinghao 
Published: September 2023

ABSTRACTCells detect changes of external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and thus challenging to detect using traditional experimental techniques. Here we tackle this challenge by a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells, or between proteins on the same cell surface. In practice, we collected all structural data of Ig domain interactions and transformed them into an interface fragment pair library. A high dimensional profile can be then constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile, so that the probability of interaction between the query proteins can be predicted. We tested our models to an experimentally derived dataset which contains 564 cell surface proteins in human. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in C elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literatures. In conclusion, our computational platform serves a useful tool to help identifying potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study interactions of proteins in other domain superfamilies.
The αC-β4 loop controls the allosteric cooperativity between nucleotide and substrate in the catalytic subunit of protein kinase A
Authors: Olivieri Cristina , Wang Yingjie , Walker Caitlin , Subrahmanian Manu V. , Ha Kim N. , Bernlohr David A. , Gao Jiali , Camilloni Carlo , Vendruscolo Michele , Taylor Susan S. , Veglia Gianluigi 
Published: September 2023

ABSTRACTAllosteric cooperativity between ATP and substrates is a prominent characteristic of the cAMP-dependent catalytic (C) subunit of protein kinase A (PKA). Not only this long-range synergistic action is involved in substrate recognition and fidelity, but it is likely to regulate PKA association with regulatory subunits and other binding partners. To date, a complete understanding of the molecular determinants for this intramolecular mechanism is still lacking.Here, we used an integrated NMR-restrained molecular dynamics simulations and a Markov Model to characterize the free energy landscape and conformational transitions of the catalytic subunit of protein kinase A (PKA-C). We found that the apo-enzyme populates a broad free energy basin featuring a conformational ensemble of the active state of PKA-C (ground state) and other basins with lower populations (excited states). The first excited state corresponds to a previously characterized inactive state of PKA-C with the αC helix swinging outward. The second excited state displays a disrupted hydrophobic packing around the regulatory (R) spine, with a flipped configuration of the F100 and F102 residues at the tip of the αC-β4 loop. To experimentally validate the second excited state, we mutated F100 into alanine and used NMR spectroscopy to characterize the binding thermodynamics and structural response of ATP and a prototypical peptide substrate. While the activity of PKA-CF100Atoward a prototypical peptide substrate is unaltered and the enzyme retains its affinity for ATP and substrate, this mutation rearranges the αC-β4 loop conformation interrupting the allosteric coupling between nucleotide and substrate. The highly conserved αC-β4 loop emerges as a pivotal element able to modulate the synergistic binding between nucleotide and substrate and may affect PKA signalosome. These results may explain how insertion mutations within this motif affect drug sensitivity in other homologous kinases.
Anti-inflammatory role of APRIL by modulating regulatory B cells in antigen-induced arthritis
Authors: Carvalho-Santos Adriana , Kuhnert Lia Rafaella Ballard , Hahne Michael , Vasconcellos Rita , Carvalho-Pinto Carla E. , Villa-Verde Déa M. S. 
Published: September 2023

AbstractAPRIL (A Proliferation-Inducing Ligand) acts as a secreted factor and plays important roles in B cell biology and chronic inflammation. The reported capacity of APRIL to stimulate B cellsin vitroraised the hypothesis that APRIL may be a disease promoter in autoimmune diseases such as rheumatoid arthritis. In contrast, there is large evidence that B Lymphocyte Stimulator Factor (BAFF) can break B cell tolerance in mice and humans. This study was undertaken to examine the ability of APRIL to regulate B cell-mediated inflammatory response in a model of antigen-induced arthritis (AIA) in mice. AIA was induced by administration of antigen (mBSA) into the knee joints of previously immunized APRIL-transgenic (Tg) mice and their littermates. Flow cytometry was used to analyze the different inflammatory cell populations in spleen and draining lymph nodes in acute and chronic disease, while cytokine levels were assessed by ELISA. In the acute stage of disease APRIL-Tg mice displayed a decrease in joint swelling, disease score and inflammatory infiltrate in articular tissues, as compared with their littermates. In addition, we observed a decrease of cellularity in draining lymph nodes of APRIL-Tg mice. Flow cytometry analysis revealed an increase of CD19+IgM+CD5+cell population in draining lymph nodes and increase of CD19+CD21hiCD23hi(B regulatory) cells in APRIL-Tg mice with arthritis and, increase of IL-10 and CXCL13 productionin vitro.
The relationship between screen behaviors and adolescent mental health: a phenotypic and genetic analysis
Authors: Frei Evgeniia , Jaholkowski Piotr , Frei Oleksandr , Parekh Pravesh , Shadrin Alexey A. , Hagen Espen , Bakken Nora R. , Birkenæs Viktoria , Ask Helga , Andreassen Ole A. , Smeland Olav B. 
Published: September 2023

AbstractBackgroundTechnological advances have made screen devices readily available, with adolescents spending an increasing amount of time on screens. Despite rising concerns, evidence on the relationship between screen-based activities and adolescent mental health remains inconsistent.MethodsUsing self-reports from the Norwegian Mother, Father, and Child Cohort Study and ICD-10 codes for mental illness from health registries, we estimated the odds of psychiatric diagnoses among adolescents across different levels of screen usage (n= 25,079) performing logistic regression analysis. Additionally, we computed polygenic risk scores (PRS) for schizophrenia (SCZ), bipolar disorder (BP), major depressive disorder, attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and alcohol use disorder (AUD) and evaluated their association with time spent on screen-based activities using linear regression models.ResultsWe observed higher odds of psychiatric diagnoses among individuals with most time spent across all screen behaviors. However, the lowest social media usage was also associated with mental illness (OR 2.46, 95% CI: 2.10, 2.88), particularly with increased ASD occurrence. Minimum time spent on gaming was associated with lower odds of psychiatric diagnoses (OR 0.74, 95% CI: 0.68, 0.80). PRSADHDwas positively associated with time spent on social media and gaming, while PRSASDwas positively associated with gaming, but negatively – with social media usage. Additionally, social media usage was significantly associated with lower PRSSCZand PRSBP,but higher PRSAUD.ConclusionsWe show that screen behaviors are associated with mental illness among adolescents, which may partly reflect a shared genetic basis. However, to clarify the causality of genetic associations between mental illness and screen behaviors, further studies are warranted.
Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions
Authors: Wei Angela , Border Richard , Fu Boyang , Cullina Sinéad , Brandes Nadav , Jang Seon-Kyeong , Sankararaman Sriram , Kenny Eimear E. , Udler Miriam S. , Ntranos Vasilis , Zaitlen Noah , Arboleda Valerie A. 
Published: September 2023

ABSTRACTOver three percent of people carry a dominant pathogenic variant, yet only a fraction of carriers develop disease. Disease phenotypes from carriers of variants in the same gene range from mild to severe. Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (marginal epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai BioMeBiobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable carrier penetrance and disease severity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain-from loss-of-function variants. We also found that polygenic scores predicted phenotypes amongst pathogenic carriers and that epistatic effects can exceed main carrier effects by an order of magnitude.
Enhanced neutralization of SARS-CoV-2 XBB sub-lineages and BA.2.86 by a tetravalent COVID-19 vaccine booster
Authors: Wang Xun , Jiang Shujun , Ma Wentai , Li Xiangnan , Wei Kaifeng , Xie Faren , Zhao Chaoyue , Zhao Xiaoyu , Li Chen , Qiao Rui , Cui Yuchen , Chen Yanjia , Li Jiayan , Cai Guonan , Liu Changyi , Hu Zixin , Zhang Wenhong , Li Mingkun , Zhang Yanliang , Wang Pengfei 
Published: September 2023

AbstractAs the SARS-CoV-2 virus continues to evolve, novel XBB sub-lineages such as XBB.1.5, XBB.1.16, EG.5, HK.3 (FLip), and XBB.2.3, as well as the most recent BA.2.86, have been identified and aroused global concern. Understanding the efficacy of current vaccines and the immune system’s response to these emerging variants is critical for global public health. In this study, we evaluated the neutralization activities of sera from participants who received COVID-19 inactivated vaccines, or a booster vaccination of the recently approved tetravalent protein vaccine in China (SCTV01E), or had contracted a breakthrough infection with BA.5/BF.7/XBB virus. Comparative analysis of their neutralization profiles against a broad panel of 30 SARS-CoV-2 sub-lineage viruses revealed that strains such as BQ.1.1, CH.1.1, and all the XBB sub-lineages exhibited heightened resistance to neutralization than previous variants, however, despite the extra mutations carried by emerging XBB sub-lineages and BA.2.86, they did not demonstrate significantly increased resistance to neutralization compared to XBB.1.5. Encouragingly, the SCTV01E booster vaccination consistently induced robust and considerably higher neutralizing titers against all these variants than breakthrough infection did. Cellular immunity assays also showed that the SCTV01E booster vaccination elicited a higher frequency of virus-specific memory B cells but not IFN-γ secreting T cells. Our findings underline the importance of developing novel multivalent vaccines to more effectively combat future viral variants.