bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of thigh muscle characteristics between older and young women using tensiomyography
Authors: Chai Jung Hoon , Kim Chul-Hyun , Bae Sang-Won 
Published: August 2022

AbstractTensiomyography is a non-invasive method of evaluating neuromuscular function through skeletal muscle contraction. The objective of this study was to compare the thigh muscle characteristics of older and young women using tensiomyography. Nineteen older and fifteen young women without musculoskeletal diseases were included. For the quadriceps, the bilateral vastus medialis (VM), vastus lateralis (VL), and rectus femoris (RF) and for the hamstrings, the bilateral semitendinosus (ST) and biceps femoris (BF) were measured. Result variables—maximal displacement (Dm), contraction time (Tc), and contraction velocity (Vc)—were compared. Dm values of the hamstrings of both legs and their summed values were significantly smaller in older women than in young women; no difference was found in the Dm values of the quadriceps. Tc and Vc of the hamstrings, VM, and VL were longer and slower, respectively, in older women than in young women. There were no significant differences in the Dm, Tc, or Vc of the RF between older and young women. Decreased Dm of the hamstrings in older women occurred due to changes in muscle function, but not muscle mass. The changes in the Tc of the hamstrings, VM, and VL indicate that type II muscle fibers were converted to type I in older women. There was no difference in RF between older and young women, implying that the RF is not affected by age. Our findings indicate that resistance exercises, which preserve the type II fibers, and flexibility exercises, which reduce stiffness, are appropriate for the lower extremity in older women.
Combined online Bayesian and windowed estimation of background and signal localization facilitates active-feedback particle tracking in complex environments
Authors: Niver Anastasia , Welsher Kevin D. 
Published: August 2022

AbstractDespite successes in tracking single molecules in vitro, the extension of active-feedback single-particle methods to tracking rapidly diffusing and unconfined proteins in live cells has not been realized. Since existing active-feedback localization methods localize particles in real time assuming zero background, they are ill-suited to track in the inhomogeneous background environment of a live cell. Here, we develop a windowed estimation of signal and background levels which uses recent data to estimate the current particle brightness and background intensity. These estimates facilitate recursive Bayesian position estimation, improving upon current Kalman-based localization methods. Combined, online Bayesian and windowed estimation of background and signal (COBWEBS) surpasses existing localization methods. Simulations demonstrate improved localization accuracy and responsivity in a homogenous background for selected particle and background intensity combinations. Improved or similar performance of COBWEBS tracking extends to the majority of signal and background combinations explored. Furthermore, improved tracking durations are demonstrated in the presence of heterogeneous backgrounds for multiple particle intensities, diffusive speeds, and background patterns. COBWEBS can accurately track particles in the presence of high and non-uniform backgrounds including intensity changes of up to three-fold that of the particle’s intensity, making it a prime candidate for advancing active-feedback single-fluorophore tracking to the cellular interior.
Evaluation of an image-derived input function for kinetic modeling of nicotinic acetylcholine receptor-binding PET ligands
Authors: Zammit Matthew , Kao Chien-Min , Zhang Hannah J. , Holderman Nathanial , Mitchell Samuel , Tanios Eve , Zhang Vincent , Bhuiyan Mohammed , Freifelder Richard , Green William N. , Mukherjee Jogeshwar , Chen Chin-Tu 
Published: August 2022

AbstractDevelopment of positron emission tomography (PET) radiotracers that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allows for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. One challenge associated with preclinical PET imaging involves the lack of true tissue reference regions free of specific tracer binding in the rodent brain, impeding accurate quantification of the tracer binding potential. Here, we investigate the use of an image-derived arterial input function for kinetic analysis of radiotracer binding in male and female mice. Two radiotracers were explored in this study: 2-[18F]FA85380 (2-FA), which displays similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, which displays similar pKa and binding affinity to nicotine. For both radiotracers, time-activity curves of the left ventricle of the heart displayed similar standardized uptake values (SUVs) across wild type mice, mice lacking the β2 subunit for tracer binding, and acute nicotine-treated mice, whereas typical reference tissue SUVs displayed high variation between groups. Binding potential values estimated from a two-tissue compartment model (2TCM) fit of the data with the image-derived input function were significantly higher than estimates from reference tissue-based estimations. Rate constants of radiotracer dissociation were very slow for 2-FA and very fast for Nifene, similar to the in vitro dissociation rates reported for varenicline and nicotine, respectively. We conclude that use of an image-derived input function for kinetic modeling of nicotinic PET ligands improves quantification compared to reference tissue-based methods, and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.
Endothelial TIE1 restricts angiogenic sprouting to coordinate vein assembly in synergy with its homologue TIE2
Authors: Cao Xudong , Li Taotao , Xu Beibei , Ding Kai , Li Weimin , Shen Bin , Chu Man , Zhu Dengwen , Rui Li , Shang Zhi , Li Xiao , Wang Yinyin , Zheng Shuyu , Alitalo Kari , Liu Ganqiang , Tang Jing , Kubota Yoshiaki , He Yulong 
Published: August 2022

AbstractObjectiveVascular growth followed by vessel specification is crucial for the establishment of a hierarchical blood vascular network. We have here investigated mechanisms underlying venogenesis, particularly the molecular control over venous fate acquisition during vascular development.Approach and ResultsWe analyzed the function of TIE1 as well as its synergy with TIE2 in the regulation of vein formation by employing genetic mouse models targeting Tie1 and Tek. Cardinal vein growth appeared normal in TIE1 deficient mice, whereas TIE2 deficiency altered the identity of cardinal vein endothelial cells with the aberrant expression of DLL4. Interestingly, the parallel growth of murine cutaneous veins along with arteries, which was initiated at approximately embryonic day 13.5, was retarded in mice lack of TIE1. Tie1 deletion disrupted also venous integrity, displaying increased sprouting angiogenesis and vascular bleeding. Abnormal venous sprouts with defective arteriovenous alignment were also observed in the mesenteries of Tie1 deleted mice. Mechanistically, TIE1 deficiency resulted in the decreased expression of venous regulators including TIE2 while angiogenic regulators were upregulated. The alteration of TIE2 level by TIE1 insufficiency was further confirmed by the siRNA-mediated knockdown of Tie1 in cultured endothelial cells. Additionally, combining the endothelial deletion of Tie1 with one null allele of Tek resulted in a progressive increase of vein-associated angiogenesis leading to the formation of vascular tufts in retinas, whereas the loss of Tie1 alone produced only a relatively mild venous defect.ConclusionsFindings from this study imply that TIE1 and TIE2 act in a synergistic manner to restrict sprouting angiogenesis during vein formation.
State-dependent evolutionary models reveal modes of solid tumor growth
Authors: Lewinsohn Maya A. , Bedford Trevor , Müller Nicola F. , Feder Alison F. 
Published: August 2022

AbstractSpatial properties of tumor growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumor cell division remains difficult to evaluate in clinical tumors. Here, we demonstrate that elevated cellular growth rates on the tumor periphery leave characteristic patterns in the genomes of cells sampled from different parts of a tumor, which become evident when they are used to construct a tumor phylogenetic tree. Namely, rapidly-dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing lineages in the tumor center. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential cell division rates between peripheral and central cells jointly from the branching and mutational patterns of single-time point, multi-region sequencing data. We validate this approach on simulated tumors by demonstrating its ability to accurately infer spatially-varying birth rates under a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods which ignore differential mutational acquisition. Finally, we apply SDevo to multi-region sequencing data from clinical hepatocellular carcinomas and find evidence that cells on the tumor edge divide 3-6x faster than those in the center. As multi-region and single-cell sequencing increase in resolution and availability, we anticipate that SDevo will be useful in interrogating spatial restrictions on tumor growth and could be extended to model non-spatial factors that influence tumor progression, including hypoxia and immune infiltration.
Characterizing Transient Protein-Protein Interactions by Trp-Cys Quenching and Computer Simulations
Authors: Heo Lim , Gamage Katukurunde , Valdes-Garcia Gilberto , Lapidus Lisa J. , Feig Michael 
Published: August 2022

AbstractTransient protein-protein interactions occur frequently under the crowded conditions encountered in biological environments, yet they remain poorly understood. Here, tryptophan-cysteine quenching is introduced as an experimental approach that is ideally suited to characterize such interactions between proteins with minimal labeling due to its sensitivity to nano- to microsecond dynamics on sub-nanometer length scales. The experiments are paired with computational modeling at different resolutions including fully atomistic molecular dynamics simulations to provide interpretation of the experimental observables and add further insights at the molecular level. This approach is applied to model systems, villin variants and the drkN SH3 domain, in the presence of protein G crowders. It is demonstrated that Trp-Cys quenching experiments are able to not only distinguish between overall attractive and repulsive interactions between different proteins, but they can also discern variations in interaction preferences at different protein surface locations. The close integration between experiment and simulations also provides an opportunity to evaluate different molecular force fields for the simulation of concentrated protein solutions.Significance StatementBiological environments typically involve a variety of different proteins at very high concentrations where non-specific interactions are unavoidable. These interactions may go beyond simple crowding effects and involve transient contacts that may impact structure, dynamics, and ultimately function of proteins in vivo. While computer simulations have partially characterized such interactions, experimental data remain limited because established techniques are generally not well-suited to the characterization of dynamic processes on microsecond time and nanometer length scales. Tryptophan quenching by cysteine is introduced here as a new approach for studying transient protein encounters under concentrated conditions with the support of computational modeling. The study demonstrates that such experiments can resolve not just differences between different proteins but also residue-specific interaction preferences.
MetaTiME: Meta-components of the Tumor Immune Microenvironment
Authors: Zhang Yi , Xiang Guanjue , Jiang Alva Yijia , Lynch Allen , Zeng Zexian , Wang Chenfei , Zhang Wubing , Fan Jingyu , Kang Jiajinlong , Gu Shengqing Stan , Wan Changxin , Zhang Boning , Liu X. Shirley , Brown Myles , Meyer Clifford A 
Published: August 2022

AbstractRecent advances in single-cell RNA sequencing have revealed heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can reveal common cell types and states in the tumor microenvironment (TME). We developed a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.
Engineering a Single Extracellular Vesicle Protein and RNA Assay (siEVPRA) via In Situ Fluorescence Microscopy in a UV Micropatterned Array
Authors: Zhang Jingjing , Wang Xinyu , Rima Xilal Y. , Nguyen Luong T. H. , Huntoon Kristin , Ma Yifan , Walters Nicole , Kwak Kwang Joo , Yoon Min Jin , Lee Daeyong , Wang Yifan , Ha Jonghoon , Scherler Kelsey , Fallen Shannon , Lee Inyoul , Palmer Andre F. , Jiang Wen , Wang Kai , Kim Betty Y.S. , Lee L. James , Reátegui Eduardo 
Published: August 2022

AbstractThe physical and molecular heterogeneity of extracellular vesicles (EVs) confounds bulk biomarker characterization, thus encouraging the development of novel assays capable of profiling EVs at a single-vesicle resolution. Here, we present a single EV (siEV) protein and RNA assay (siEVPRA) to simultaneously detect proteins, messenger RNAs (mRNAs), and microRNAs (miRNAs) in siEVs. ThesiEVPRA consists of an array of microdomains embedded on a polyethylene glycol (PEG)-coated glass surface produced via UV photopatterning, functionalized with antibodies to target siEV subpopulations. Fluorescently labeled antibodies and RNA-targeting molecular beacons (MBs) were used to generate signals for proteins, mRNAs, and miRNAs on siEVs detected by total internal reflection fluorescence microscopy (TIRFM), outperforming the sensitivities of ELISA and PCR by three orders of magnitude. Using thesiEVPRA, we analyzed EVs harvested from glioblastoma (GBM) cell lines and demonstrated vesicular heterogeneity in protein, mRNA, and miRNA expression through colocalization analyses, and validated the results by bulk RNA sequencing. We further demonstrated the clinical utility of thesiEVPRA by detecting different mRNAs and miRNAs associated with GBM in patient samples. Together, these results indicate that thesiEVPRA provides an effective platform to investigate the heterogeneity of proteins and RNAs in subpopulations of EVs.
Structure-based prediction of T cell receptor:peptide-MHC interactions
Authors: Bradley Philip 
Published: August 2022

AbstractThe regulatory and effector functions of T cells are initiated by the binding of their cell-surface T cell receptor (TCR) to peptides presented by major histocompatibility complex (MHC) proteins on other cells. The specificity of TCR:peptide-MHC interactions thus underlies nearly all adaptive immune responses. Despite intense interest, generalizable predictive models of TCR:peptide-MHC specificity remain out of reach; two key barriers are the diversity of TCR recognition modes and the paucity of training data. Inspired by recent breakthroughs in protein structure prediction achieved by deep neural networks, we evaluated structural modeling as a potential avenue for prediction of TCR epitope specificity. We show that a specialized version of the neural network predictor AlphaFold can generate models of TCR:peptide-MHC interactions that can be used to discriminate correct from incorrect peptide epitopes with substantial accuracy. Although much work remains to be done for these predictions to have widespread practical utility, we are optimistic that deep learning-based structural modeling represents a path to generalizable prediction of TCR:peptide-MHC interaction specificity.
Birth, cell fate and behavior of progenitors at the origin of the cardiac mitral valve
Authors: Farhat Batoul , Bordeu Ignacio , Jagla Bernd , Blanc Hugo , Loulier Karine , Simons Benjamin D. , Beaurepaire Emmanuel , Livet Jean , Pucéat Michel 
Published: August 2022

Congenital heart malformations often include mitral valve defects which remain largely unexplained. During embryogenesis, a restricted population of endocardial cells within the atrioventricular canal (AVC) undergoes endothelial to mesenchymal transition (EndMT) to give rise to mitral valvular cells. However, the identity, fate decisions of these progenitors as well as the distribution of their derivatives in valve leaflets remain unknown.Here, we use scRNA-seq of genetically labeled mouse AVC endocardial cells and of micro-dissected embryonic and postnatal mitral valves to characterize the developmental road. We uncovered the genetic, cell signaling and metabolic processes underlying specification of the progenitors and how they contribute to subtypes of endothelial and interstitial embryonic and postnatal valvular cells. Using clonal genetic tracing with multicolor reporter, we describe specific modes of growth of endocardial cell-derived clones which build up in a proper manner functional valve leaflets.Our data reveal how both genetic and metabolic specification mechanisms specifically drive the fate of a subset of endocardial cells toward valve progenitors and their distinct clonal contribution to the formation of the valve.
Culex tarsalis is a competent host of the insect-specific alphavirus Eilat virus (EILV)
Authors: Joseph Renuka E. , Urakova Nadya , Werling Kristine L. , Metz Hillery C. , Montanari Kaylee , Rasgon Jason L. 
Published: August 2022

ABSTRACTEilat virus (EILV) is an insect-specific alphavirus that has the potential to be developed into a tool to combat mosquito-borne pathogens. However, its mosquito host range and transmission routes are not well understood. Here we fill this gap by investigating EILV’s host competence and tissue tropism in five mosquito species: Aedes aegypti, Culex tarsalis, Anopheles gambiae, Anopheles stephensi, and Anopheles albimanus. Of the tested species, Cx. tarsalis was the most competent host for EILV. The virus was found in Cx. tarsalis ovaries, but no vertical or venereal transmission was observed. Culex tarsalis also transmitted EILV via saliva, suggesting the potential for horizontal transmission between an unknown vertebrate or invertebrate host. We found that reptile (turtle and snake) cells lines were not competent for EILV infection. We tested a potential invertebrate host (Manduca sexta caterpillars) but found they were not susceptible to EILV infection. Together, our results suggest that EILV could be developed as a tool to target pathogenic viruses that use Culex tarsalis as a vector. Our work sheds light on the infection and transmission dynamics of a poorly understood insect-specific virus and reveals it may infect a broader range of mosquito species than previously recognized.IMPORTANCEThe recent discovery of insect-specific alphaviruses presents opportunities both to study the biology of virus host range and to develop them into tools against pathogenic arboviruses. Here we characterize the host range and transmission of Eilat virus in five mosquito species. We find that Culex tarsalis—a vector of harmful human pathogens including West Nile Virus—is a competent host of Eilat virus. However, how this virus is transmitted between mosquitoes remains unclear. We find that Eilat virus infects the tissues necessary for both vertical and horizontal transmission—a crucial step in discerning how Eilat virus maintains itself in nature.
Does intellectual capital matter to MFIs’ financial sustainability?
Authors: Githaiga Peter Nderitu , Soi Neddy , Buigut Kibet Koskei 
Published: August 2022

PurposeThis paper examines the effect of intellectual capital (IC) on the financial sustainability of microfinance institutions (MFIs). The study is motivated by the increased calls for MFIs to be self-sustainable and the growing importance of knowledge-based assets as contributors of competitive advantage and sustained performance.Design/methodology/approachWith a global sample of 444 MFIs and data for 2013–2018, which yielded 2,664 MFIs-year observations, this study examines the effect of IC on MFIs’ financial sustainability. The data are extracted from the MIX Market database. Value added intellectual capital coefficients are used as proxy measures of IC. Operational self-sufficiency is used to measure financial sustainability. Data are analyzed using three-panel data estimation models: the fixed effect, the random effect and the dynamic panel system generalized method of moments.FindingsThe results show that human capital efficiency and capital employed efficiency have a positive and significant effect on the financial sustainability of MFIs. However, structural capital efficiency has a significantly negative effect on financial sustainability. These results confirm the relative importance of both tangible and intangible assets as important positive contributors of financial sustainability of MFIs.Research limitations/implicationsThe paper focused on the association between IC and financial sustainability of MFIs. Therefore, examining nonfinancial institution may validate the contributions of this study.Practical implicationsBased on the findings, MFIs’ managers are encouraged to leverage IC, physical and financial capital to attain financial sustainability. In particular, MFIs should invest in employees training and development. Additionally, owing to the positive relationship between physical capital and financial sustainability, there is need for policy interventions to ensure MFIs access adequate funding. The study further recommends mandatory disclosure of IC among MFIs.Originality/valueThis is the first paper to investigate the relationship between IC and the financial sustainability of MFIs using panel data and a global sample of MFIs; therefore, it lays an empirical ground for future studies.