bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic map illuminates Hippo to cMyc module crosstalk driving cardiomyocyte proliferation
Authors: Harris Bryana N. , Woo Laura A. , Perry R. Noah , Civelek Mete , Wolf Matthew J. , Saucerman Jeffrey J. 
Published: October 2022

AbstractCardiac diseases are characterized by the inability of adult mammalian hearts to overcome the loss of cardiomyocytes (CMs). Current knowledge in cardiac regeneration lacks a clear understanding of the molecular systems determining whether CMs will progress through the cell cycle to proliferate. Here, we developed a computational model of cardiac proliferation signaling that identifies key regulators and provides a systems-level understanding of the cardiomyocyte proliferation regulatory network. This model defines five regulatory networks (DNA replication, mitosis, cytokinesis, growth factor, hippo pathway) of cardiomyocyte proliferation, which integrates 72 nodes and 88 reactions. The model correctly predicts 72 of 76 (94.7%) independent experiments from the literature. Network analysis predicted key signaling regulators of DNA replication (e.g., AKT, CDC25A, Cyclin D/CDK4, E2F), mitosis (e.g., Cyclin B/CDK2, CDC25B/C, PLK1), and cytokinesis, whose functions varied depending on the environmental context. Regulators of DNA replication were found to be highly context-dependent, while regulators of mitosis and cytokinesis were context-independent. We also predicted that in response to the YAP-activating compound TT-10, the Hippo module crosstalks with the growth factor module via PI3K, cMyc, and FoxM1 to drive proliferation. This prediction was validated with inhibitor experiments in primary rat cardiomyocytes and further supported by re-analysis of published data on YAP-stimulated mRNA and open chromatin of Myc from mouse hearts. This study contributes a systems framework for understanding cardiomyocyte proliferation and identifies potential therapeutic regulators that induce cardiomyocyte proliferation.
Chemical modification of human decellularized extracellular matrix for incorporation into phototunable hybrid-hydrogel models of tissue fibrosis
Authors: Hewawasam Rukshika S. , Šerbedžija Predrag , Blomberg Rachel , Magin Chelsea M. 
Published: October 2022

ABSTRACTTissue fibrosis remains a serious health condition with high morbidity and mortality rates. There is a critical need to engineer model systems that better recapitulate the spatial and temporal changes in the fibrotic extracellular microenvironment and enable study of the cellular and molecular alterations that occur during pathogenesis. Here, we present a process for chemically modifying human decellularized extracellular matrix (dECM) and incorporating it into a dynamically tunable hybrid-hydrogel system containing a poly(ethylene glycol)-alpha methacrylate (PEGαMA) backbone. Following modification and characterization, an off-stoichiometry thiol-ene Michael addition reaction resulted in hybrid-hydrogels with mechanical properties that could be tuned to recapitulate many healthy tissue types. Next, photoinitiated, free-radical homopolymerization of excess α-methacrylates increased crosslinking density and hybrid-hydrogel elastic modulus to mimic a fibrotic microenvironment. The incorporation of dECM into the PEGαMAhydrogel decreased the elastic modulus and, relative to fully synthetic hydrogels, increased the swelling ratio, the average molecular weight between crosslinks, and the mesh size of hybrid-hydrogel networks. These changes were proportional to the amount of dECM incorporated into the network. Dynamic stiffening increased the elastic modulus and decreased the swelling ratio, average molecular weight between crosslinks, and the mesh size of hybrid-hydrogels, as expected. Stiffening also activated human fibroblasts, as measured by increases in average cellular aspect ratio (1.59 ± 0.02 to 2.98 ± 0.20) and expression of α-smooth muscle actin (αSMA). Fibroblasts expressing αSMA increased from 24.4% to 51.8% upon dynamic stiffening, demonstrating that hybrid-hydrogels containing human dECM support investigation of dynamic mechanosensing. These results improve our understanding of the biomolecular networks formed within hybrid-hydrogels: this fully human phototunable hybrid-hydrogel system will enable researchers to control and decouple the biochemical changes that occur during fibrotic pathogenesis from the resulting increases in stiffness to study the dynamic cell-matrix interactions that perpetuate fibrotic diseases.
Serotonin signaling in the enteric nervous system and connection to autism spectrum disorder: a translational mathematical model
Authors: Kareva Irina 
Published: October 2022

AbstractWhile the causes of autism spectrum disorder (ASD) remain unclear, some studies have shown that serotonin-mediated effects on enteric nervous system (ENT) correlate with ASD-like behavioral phenotype in mice. Introduced here is a mathematical model of interactions between gut serotonin and its impact on ENT. The model was used to identify three key factors that affect ENT size, namely, serotonin production, its clearance, and its ability to act as a growth factor on ENT. The model was used to reproduce experimentally reported results from a mouse model by Margolis et al. (2016), which connected serotonin-mediated ENT hypoplasia to an ASD phenotype. The proposed mathematical model was used to scale the quantified relationship from mice to humans to show how the combination of these three factors can translate to a quantifiable metric that could potentially be correlated to ASD spectrum. A detailed discussion of how ENT hypoplasia could mechanistically affect CNS activity concludes this paper.
Neuropathology-basedAPOEgenetic risk score better quantifies Alzheimer’s risk
Authors: Deming Yuetiva , Vasiljevic Eva , Morrow Autumn , Miao Jiacheng , Van Hulle Carol , Jonaitis Erin , Ma Yue , Whitenack Vanessa , Kollmorgen Gwendlyn , Wild Norbert , Suridjan Ivonne , Shaw Leslie M. , Asthana Sanjay , Carlsson Cynthia M. , Johnson Sterling C. , Zetterberg Henrik , Blennow Kaj , Bendlin Barbara B. , Lu Qiongshi , Engelman Corinne D. ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: October 2022

AbstractINTRODUCTIONAPOE ε4-carrier status orε4allele count are included in analyses to account for theAPOEgenetic effect on Alzheimer’s disease (AD); however, this does not account for protective effects ofAPOE ε2or heterogeneous effect ofε2, ε3, ε4haplotypes.METHODSWe leveraged results from an autopsy-confirmed AD study to generate a weighted risk score forAPOE(APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers onAPOEvariables from the Wisconsin Registry for Alzheimer’s Prevention, Wisconsin Alzheimer’s Disease Research Center, and Alzheimer’s Disease Neuroimaging Initiative (ADNI).RESULTSTheAPOE-npscore explained more variance and provided a better model fit for all three CSF measures thanAPOE ε4-carrier status andε4allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired participants.DISCUSSIONTheAPOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account forAPOEin AD-related analyses.
Mutational Analysis and Deep Learning Classification of Uterine and Cervical Cancers
Authors: Gomez Paul 
Published: October 2022

ABSTRACTWe analyzed tumor mutations of 7 uterine and 2 cervical cancers with the goal of developing a Deep Learning (DL) software tool that can automatically classify tumors based on their somatic mutations. The data were obtained from the AACR Genie Project [1], that has a collection of more than 120,000 tumor samples for more than 750 cancer types. We performed a thorough analysis of the mutational data of tumors of the uterus and uterine cervix, selecting tumors with 3 or more mutations and cancer types with more than 15 cases. For each cancer type we then selected the top 12 most mutated genes among their neoplasms. In the introduction section we summarize our analysis of these nine diseases and in the deep learning section we present a convolutional neural network (CNN) [2] that yields an overall classification accuracy of 94.3% and 89.2% on the train and test datasets, respectively. We hope that this tool can be added to the existing arsenal of histological and immunohistochemical techniques in cases when a precise diagnosis cannot be clearly determined. Each cancer type has a unique somatic mutational profile that can be used to disambiguate two candidate malignancies with similar histologic features.
IS200/IS605 Family-Associated TnpB Increases Transposon Activity and Retention
Authors: Kaur Davneet , Kuhlman Thomas E. 
Published: October 2022

SUMMARYThe IS200/IS605 family of insertion sequences are abundant mobile elements associated with one of the most numerous genes found in nature,tnpB1–3. Previous studies suggest that TnpB protein may be an evolutionary precursor to CRISPR Cas enzymes, and TnpB has received renewed interest having itself been shown to function as a Cas-like RNA-guided DNA endonuclease3,4. However, interpretation of the fundamental role of TnpB in transposition and how it contributes to genome dynamics5remains controversial without direct, real-time measurement in live cells. Here, using a suite of fluorescent reporters coupled to transposition in liveEscherichia coli, we show that IS608-TnpB causes increased transposon activity, and assists in preventing transposon loss from host genomes. Analyzing our results through a mathematical model of transposon dynamics, we discuss the multifaceted roles it may play in transposon regulation. The mutually beneficial transposon-TnpB interaction may explain the prevalence oftnpB, creating conditions for the appropriation of TnpB’s RNA-guided endonuclease activity for adaptive immunity.SIGNIFICANCE STATEMENTPhylogenetic evidence suggests thattnpB, one of the most numerous genes found in nature, is the ancestral form of CRISPR-Cas enzymes and played a critical role in the evolution of adaptive immunity. However, the role TnpB plays in transposition that has contributed to its wide distribution remains unclear. Here, we use a unique approach that couples fluorescent reporters to transposition to non-perturbatively quantify transpositional dynamics in live cells. In contrast to previous indirect methods suggesting that TnpB suppresses transposition, our results instead clearly demonstrate that TnpB significantly increases transposition rates and enhances transposon retention within the host genome, resulting in a mutually beneficial interaction between transposons and TnpB that can account for its wide distribution.
Use of high-plex data reveals novel insights into the tumour microenvironment of clear cell renal cell carcinoma
Authors: De Filippis Raffaele , Wölflein Georg , Um In Hwa , Caie Peter D , Warren Sarah , White Andrew , Suen Elizabeth , To Emily , Arandjelović Ognjen , Harrison David J 
Published: October 2022

AbstractAlthough Immune Checkpoint Inhibitors (ICIs) have significantly improved Clear Cell Renal Cell Carcinoma (ccRCC) prognosis, about one third of patients experience recurrence. Current prognostic algorithms like the Leibovich Score (LS) rely on morphological features manually assessed by pathologists, and are therefore subject to bias. Moreover, these tools do not consider the heterogeneous molecular milieu present in the Tumour Microenvironment (TME), which may have prognostic value. We systematically developed a semi-automated method to investigate 62 markers and their combinations in 150 primary ccRCCs using multiplex Immunofluorescence (mIF), NanoString GeoMx®Digital Spatial Profiling (DSP) and Artificial Intelligence (AI)-assisted image analysis in order to find novel prognostic signatures and investigate their spatial relationship. We found that coexpression of Cancer Stem Cell (CSC) and Epithelial-to-Mesenchymal Transition (EMT) markers such as OCT4 and ZEB1 are indicative of poor outcome. OCT4 and the immune markers CD8, CD34 and CD163 significantly stratified patients at intermediate LS. Furthermore, augmenting the LS with OCT4 and CD34 improved patient stratification by outcome. Our results support the hypothesis that combining molecular markers has prognostic value and can be integrated with morphological features to improve risk stratification and personalised therapy. To conclude, GeoMx®DSP and AI image analysis are complementary tools providing high multiplexing capability required to investigate the TME of ccRCC, while reducing observer bias.Simple SummaryCancer is a complex ensemble of morphological and molecular features whose role is still unclear. Moreover, their role may change in different areas of the same tumour. Artificial intelligence (AI) allows pathologists to go beyond human perception and bias, and may help better understand how these features influence disease progression. Furthermore, by capturing variation intrinsic to the tumour, AI may improve the accuracy of current prognostic tools, such as Leibovich Score (LS), in predicting patient outcome and response to therapy. For these reasons, we studied in clear cell renal cell carcinoma (ccRCC) tissue, in which molecular features and their coexpression in the same cell were quantified and mapped using AI-based image analysis software. We demonstrated a novel approach for investigating ccRCC and revealed new potential biomarkers of prognosis which may also be able to direct patients towards the most appropriate personalised therapy.
Non-Culprit Left Main Coronary Artery Disease in Acute Myocardial Infarction Complicated by Cardiogenic Shock
Authors: Park Ik Hyun , Jang Woo Jin , Oh Ju Hyeon , Yang Jeong Hoon , Song Young Bin , Hahn Joo-Yong , Choi Seung-Hyuk , Gwon Hyeon-Cheol , Ahn Chul-Min , Yu Cheol Woong , Kim Hyun-Joong , Bae Jang-Whan , Kwon Sung Uk , Lee Hyun-Jong , Lee Wang Soo , Jeong Jin-Ok , Park Sang-Don 
Published: October 2022

ABSTRACTObjectivesWe evaluated the clinical impact of residual non-culprit left main coronary artery disease (LMCAD) on prognosis in patients undergoing emergent percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI) complicated by cardiogenic shock (CS).MethodsA total of 429 patients who underwent PCI for AMI complicated by CS was enrolled from 12 centers in the Republic of Korea. The patients were divided into two groups according to presence of non-culprit LMCAD or not: the LMCAD non-culprit group (n = 43) and the no LMCAD group (n = 386). Primary outcome was major adverse cardiac event (MACE, defined as a composite of cardiac death, myocardial infarction, or repeat revascularization). Propensity score matching analysis was performed to reduce selection bias and potential confounding factors.ResultsDuring a 12-month follow-up, a total of 168 MACEs occurred (LMCAD non-culprit group, 17 [39.5%] vs. no LMCAD group, 151 [39.1%]). Multivariate analysis revealed no significant difference in the incidence of MACE at 12 months between the LMCAD non-culprit and no LMCAD groups (adjusted hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.56 to 1.58,p= 0.817). After propensity score matching, the incidence of MACE was still similar between the two groups(HR 1.07; 95% CI 0.49 to 2.36;p= 0.857). The similarity of MACEs between the two groups was consistent across a variety of subgroups.ConclusionsAfter adjusting for baseline differences, residual non-culprit LMCAD does not appear to increase the risk of MACEs at 12 months in patients undergoing emergent PCI for AMI complicated by CS.
Predicting chemoresponsiveness in epithelial ovarian cancer patients using circulating small extracellular vesicle-derived plasma gelsolin
Authors: Gerber Emma , Asare-Werehene Meshach , Reunov Arkadiy , Burger Dylan , Le Tien , Carmona Euridice , Mes-Masson Anne-Marie , Tsang Benjamin K. 
Published: October 2022

AbstractBackgroundResistance to chemotherapy continues to be a challenge when treating epithelial ovarian cancer (EOC), contributing to low patient survival rates. While CA125, the conventional EOC biomarker, has been useful in monitoring patients’ response to therapy, there are no biomarkers used to predict treatment response prior to chemotherapy. Previous workin vitroshowed that plasma gelsolin (pGSN) is highly expressed in chemoresistant EOC cell lines, where it is secreted in small extracellular vesicles (sEVs). Whether sEVs from tumour cells are secreted into the circulation of EOC patients and could be used to predict patient chemoresponsiveness is yet to be determined. This study aims to determine if sEV-pGSN in the circulation could be a predictive biomarker for chemoresistance in EOC.MethodsSandwich ELISA was used to measure pGSN concentrations from plasma samples of 96 EOC patients (primarily high grade serous EOC). sEVs were isolated using ExoQuick ULTRA and characterized using western blot, nanoparticle tracking analysis, and electron microscopy after which pGSN was measured from the sEVs. Patients were stratified as platinum sensitive or resistant groups based on first progression free interval (PFI) of 6 or 12 months.ResultsTotal circulating pGSN was significantly decreased and sEV-pGSN increased in patients with a PFI ≤ 12 months (chemoresistant) compared to those with a PFI > 12 months (chemosensitive). The ratio of total pGSN to sEV-pGSN further differentiated these groups and was a strong predictive marker for chemoresistance (sensitivity: 73.91%, specificity: 72.46%). Predetermined CA125 was not different between chemosensitive and chemoresistant groups and was not predictive of chemoresponsiveness prior to treatment. When CA125 was combined with the ratio of total pGSN/sEV-pGSN, it was a significant predictor of chemoresponsiveness, but the test performance was not as robust as the total pGSN/sEV-pGSN alone.ConclusionsTotal pGSN/sEV-pGSN was the best predictor of chemoresponsiveness prior to treatment, outperforming the individual biomarkers (CA125, total pGSN, and sEV-pGSN). This multianalyte predictor of chemoresponsiveness could help to inform physicians’ treatment and follow up plan at the time of EOC diagnosis, thus improving patients’ outcomes.
Mechanistic insights into GTP-dependence and kinetic polarity of FtsZ filament assembly
Authors: Chakraborty Joyeeta , Poddar Sakshi , Dutta Soumyajit , Bahulekar Vaishnavi , Harne Shrikant , Srinivasan Ramanujam , Gayathri Pananghat 
Published: October 2022

AbstractFtsZ, the tubulin homolog essential for bacterial cell division, assembles as Z-ring at the division site, and directs peptidoglycan synthesis by treadmilling. A key unanswered question is how FtsZ achieves its kinetic polarity that drives treadmilling. To obtain insights into fundamental features of FtsZ assembly dynamics independent of peptidoglycan synthesis, we report the characterization of FtsZ from the cell wall-less bacteria,Spiroplasma melliferum(SmFtsZ). SmFtsZ is a slower GTPase and has higher critical concentration (CC) for polymerization compared toEscherichia coliFtsZ (EcFtsZ). Analysis of the crystal structures of FtsZ structures reveal that the interaction of gamma phosphate of the nucleotide with the T3 loop leads to a peptide flip at Gly71. We propose that the flipped peptide conformation results in a key interaction that facilitates preferential binding of the N-terminal domain (NTD) of a GTP-bound FtsZ monomer to the C-terminal domain (CTD) exposed end of FtsZ filament. In FtsZs, a conformational switch from R- to T-state favors polymerization. We identified a residue, Phe224, located at the interdomain cleft of SmFtsZ, which is crucial for R- to T-state transition. The mutation F224M in SmFtsZ cleft resulted in higher GTPase activity and lower CC, whereas the corresponding M225F in EcFtsZ resulted in cell division defects inE. coli. Our results demonstrate that relative rotation of the domains is a rate-limiting step of polymerization. This step, in addition to the GTP-dependence of the T3 loop conformation, slows down the addition of monomers to the NTD-exposed end of filament in comparison to CTD end, thus explaining kinetic polarity.
Metabolic rewiring of mitochondria in senescence revealed by time-resolved analysis of the mitochondrial proteome
Authors: Kim Jun Yong , Atanassov Ilian , Dethloff Frederik , Kroczek Lara , Langer Thomas 
Published: October 2022

AbstractMitochondrial dysfunction and cellular senescence are hallmarks of aging. However, the relationship between these two phenomena remains incompletely understood. In this study, we investigated the rewiring of mitochondria upon development of the senescent state in human IMR90 fibroblasts. Determining the bioenergetic activities and abundance of mitochondria, we demonstrate that senescent cells accumulate mitochondria with reduced OXPHOS activity, resulting in an overall increase of mitochondrial activities in senescent cells. Time-resolved proteomic analyses revealed extensive reprogramming of the mitochondrial proteome upon senescence development and allowed the identification of metabolic pathways that are rewired with different kinetics upon establishment of the senescent state. Among the early-responding pathways, the degradation of branched-chain amino acid (BCAA) was increased, while the one carbon-folate metabolism was decreased. Late-responding pathways include lipid metabolism and mitochondrial translation. These signatures were confirmed by metabolic tracing experiments, highlighting metabolic rewiring as a central feature of mitochondria in cellular senescence. Together, our data provide an unprecedentedly comprehensive view on the metabolic status of mitochondria in senescent cells and reveal how the mitochondrial proteome adapts to the induction of senescence.
Studying metal-protein interactions using fluorescent protein indicators
Authors: Rosenbaum Joel C. , Carlson Anne E. 
Published: October 2022

AbstractMetals are widespread environmental toxins that disrupt normal cellular processes through their interactions with proteins and other macromolecules. In this study, we developed the metalsensitive fluorescent protein mseGFP as a ratiometric reporter capable of binding heavy metals. We found that mseGFP bound mercury and lead tightly but had substantially lower sensitivity to other metals. By comparison, the redox sensor roGFP2 functioned as a ratiometric indicator for transition metals, with the highest sensitivity for copper, followed by nickel and cobalt. mseGFP and roGFP2 could also report metal binding through fluorescence quenching, and we used this effect to measure high affinity interactions for both proteins with copper and iron. Crystal structure analysis of mseGFP complexed with phenylarsine oxide revealed an unexpected mode of heavy metal interaction, with mseGFP binding PAO with 2:2 stoichiometry. Glutathione strongly inhibited most metal interactions with the fluorescent protein reporters, but increased the affinity of arsenic and cadmium for mseGFP. When expressed in HEK293T cells, mseGFP reported uptake of mercury and phenylarsine oxide from surrounding media. Glutathione depletion enhanced binding of phenylarsine oxide to mseGFP in cells, validating the importance of glutathione in modulating metal-protein interactions.