bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling cell adaptation using internal variables: accounting for cell plasticity in continuum mathematical biology
Authors: Pérez-Aliacar Marina , Ayensa-Jiménez Jacobo , Doblaré Manuel 
Published: May 2023

AbstractCellular adaptation is the ability of cells to change in response to different stimuli and environmental conditions. It occurs via phenotypic plasticity, that is, changes in gene expression derived from changes in the physiological environment. This phenomenon is important in many biological processes, in particular in cancer evolution and its treatment. Therefore, it is crucial to understand the mechanisms behind it. Specifically, the emergence of the cancer stem cell phenotype, showing enhanced proliferation and invasion rates, is an essential process in tumour progression.We present a mathematical framework to simulate phenotypic heterogeneity in different cell populations as a result of their interaction with chemical species in their microenvironment, through a continuum model using the well-known concept of internal variables to model cell phenotype. The resulting model, derived from conservation laws, incorporates the relationship between the phenotype and the history of the stimuli to which cells have been subjected, together with the inheritance of that phenotype. To illustrate the model capabilities, it is particularised for glioblastoma adaptation to hypoxia. A parametric analysis is carried out to investigate the impact of each model parameter regulating cellular adaptation, showing that it permits reproducing different trends reported in the scientific literature. The framework can be easily adapted to any particular problem of cell plasticity, with the main limitation of having enough cells to allow working with continuum variables. With appropriate calibration and validation, it could be useful for exploring the underlying processes of cellular adaptation, as well as for proposing favorable/unfavourable conditions or treatments.
Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods
Authors: Blenkmann Alejandro Omar , Leske Sabine Liliana , Llorens Anaïs , Lin Jack J. , Chang Edward , Brunner Peter , Schalk Gerwin , Ivanovic Jugoslav , Larsson Pål Gunnar , Knight Robert Thomas , Endestad Tor , Solbakk Anne-Kristin 
Published: May 2023

AbstractPrecise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations.To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first presentGridFit,an algorithm that simultaneously localizes all contacts in grids, strips, or depth arrays by fitting flexible models to the electrodes’ CT artifacts. We observed localization errors of less than one millimeter (below 8% relative to the inter-electrode distance) and robust performance under the presence of noise, unrelated artifacts, and high-density implants when we ran ∼6000 simulated scenarios. Furthermore, we validated the method with real data from 20 intracranial patients.As a second registration step, we introduceCEPA,a brain-shift compensation algorithm that combines orthogonal-based projections, spring-mesh models, and spatial regularization constraints. When tested with real data from 15 patients, anatomical registration errors were smaller than those obtained for well-established alternatives. Additionally,CEPAaccounted simultaneously for simple mechanical deformation principles, which is not possible with other available methods. Inter-electrode distances of projected coordinates smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Moreover, in an additional validation procedure, we found that modeling resting-state high-frequency activity (75-145 Hz) in five patients further supported our new algorithm.Together,GridFitandCEPAconstitute a versatile set of tools for the registration of subdural grid, strip, and depth electrode coordinates that provide highly accurate results even in the most challenging implantation scenarios. The methods presented here are implemented in the iElectrodes open-source toolbox, making their use simple, accessible, and straightforward to integrate with other popular toolboxes used for analyzing electrophysiological data.
Estimating the mean in the space of ranked phylogenetic trees
Authors: Berling Lars , Collienne Lena , Gavryushkin Alex 
Published: May 2023

AbstractReconstructing evolutionary histories of biological entities, such as genes, cells, organisms, populations, and species, from phenotypic and molecular sequencing data is central to many biological, palaeontological, and biomedical disciplines. Typically, due to uncertainties and incompleteness in data, the true evolutionary history (phylogeny) is challenging to estimate. Statistical modelling approaches address this problem by introducing and studying probability distributions over all possible evolutionary histories. In practice, computational methods are deployed to learn those distributions typically by sampling them. This approach, however, is fundamentally challenging as it requires designing and implementing various statistical methods over a space of phylogenetic trees (or treespace).Although the problem of developing statistics over a treespace has received substantial attention in the literature and numerous breakthroughs have been made, it remains largely unsolved. The challenge of solving this problem is two-fold: a treespace has non-trivial often counter-intuitive geometry implying that much of classical Euclidean statistics does not immediately apply; many parametrisations of treespace with promising statistical properties are computationally hard, so they cannot be used in data analyses. As a result, there is no single conventional method for estimating even the most fundamental statistics over any treespace, such as mean and variance, and various heuristics are used in practice. Despite the existence of numerous tree summary methods to approximate means of probability distributions over a treespace based on its geometry, and the theoretical promise of this idea, none of the attempts resulted in a practical method for summarising tree samples.In this paper we present such a method along with useful properties of our chosen treespace while focusing on its impact on phylogenetic analyses of real datasets. We perform an extensive benchmark study and demonstrate that our method outperforms currently most popular methods with respect to a number of important “quality” statistics. Further, we apply our method to three real datasets ranging from cancer evolution to linguistics and find novel insights into corresponding evolutionary problems in all of them. We hence conclude that this treespace is a promising candidate to serve as a foundation for developing statistics over phylogenetic trees analytically, as well as new computational tools for evolutionary data analyses.
NRF2 connects Src tyrosine kinase to ferroptosis resistance in glioblastoma
Authors: Cirotti Claudia , Taddei Irene , Contadini Claudia , Pepe Gerardo , Bardi Marco De , Borsellino Giovanna , Helmer-Citterich Manuela , Barilà Daniela 
Published: May 2023

ABSTRACTGlioblastoma (GBM) is a severe brain tumor characterized by an extremely poor survival rate of patients. GBM cancer cells escape to standard therapeutic protocols consisting of combination of ionizing radiation (IR) and alkylating drugs that trigger DNA damage, by rewiring of signaling pathways. In recent years, the upregulation of factors that counteract ferroptosis has been highlighted as a major driver of cancer resistance to IR, although the molecular connection between the activation of oncogenic signaling and the modulation of ferroptosis has not been clarified yet.Here we provide the first evidence for a molecular connection between the constitutive activation of tyrosine kinases and resistance to ferroptosis. Src tyrosine kinase, a central hub on which Receptor Tyrosine Kinases deregulated signaling converge in cancer, leads to the stabilization and activation of NRF2 pathway, thus promoting resistance to IR-induced ferroptosis. These data suggest that the upregulation of Src-NRF2 axis may represent a vulnerability for combined strategies that, by targeting ferroptosis resistance, enhance radiation sensitivity in glioblastoma.
Comprehensive characterization of the neurogenic and neuroprotective action of a novel TrkB agonist using mouse and human stem cell models of Alzheimer’s Disease
Authors: Charou Despoina , Rogdakis Thanasis , Latorrata Alessia , Valcarcel Maria , Papadogiannis Vasileios , Athanasiou Christina , Tsengenes Alexandros , Papadopoulou Maria Anna , Lypitkas Dimitrios , Lavigne Matthieu D. , Katsila Theodora , Wade Rebecca C. , Cader M. Zameel , Calogeropoulou Theodora , Gravanis Achille , Charalampopoulos Ioannis 
Published: May 2023

SUMMARYNeural stem cell (NSC) proliferation and differentiation in the mammalian brain decreases to minimal levels postnatally. Nevertheless, neurogenic niches persist in the adult cortex and hippocampus in rodents, primates and humans, with adult NSC differentiation sharing key regulatory mechanisms with development. Adult neurogenesis impairments have been linked to Alzheimer’s Disease (AD) pathology. Addressing these impairments is a promising new avenue for therapeutic intervention based on neurogenesis. However, this possibility has been hindered by technical difficulties of using in-vivo models to conduct screens, including working with scarce NSCs in the adult brain and differences between human and mouse models or ethical limitations. In our study, we use a combination of mouse and human stem cell models to circumvent these issues and perform comprehensive characterization of a novel neurogenic compound usingin vitroscreening. Our work focuses on the brain-derived neurotrophic factor (BDNF) pathway, a pivotal neurotrophin in the regulation of neuronal growth and differentiation via its receptor tyrosine receptor kinase B (TrkB). We describe the design, chemical synthesis and biological characterization of ENT-A011, a steroidal dehydroepiandrosterone (DHEA) derivative and BDNF mimetic with neuroprotective and neurogenic actions. The compound is able to increase proliferation of mouse primary adult hippocampal NSCs and embryonic cortical NSCs, in the absence of EGF/FGF, while reducing Amyloid-β (Aβ) induced cell death, acting specifically through TrkB activation. The compound is also able to increase astrocytic gene markers involved in NSC maintenance, protect hippocampal neurons from Αβ toxicity and prevent synapse loss after Aβ treatment. To provide a translational link to human cells, we also used neural progenitor cells (NPCs) differentiated from three human induced pluripotent stem cell lines from healthy and AD donors. Our findings suggest that ENT-A011 successfully induces proliferation and prevents cell death after Aβ toxicity of human NPCs. Additionally, using RNAseq profiling, we demonstrate that the compound acts through a core gene network shared with BDNF. Our work characterizes a novel synthetic BDNF mimetic with potential neurogenic and neuroprotective actions in Alzheimer’s disease via stem cell-based screening, demonstrating the promise of stem cell systems for short-listing competitive candidates for further testing.
Metastatic potentials classified with hypoxia-inducible factor 1 downstream gene in pan-cancer cell lines
Authors: Nakamichi Kazuya , Semba Kentaro , Nakayama Jun 
Published: May 2023

AbstractHypoxia-inducible factor 1 (HIF1) gene codes a transcription factor that is stabilized under hypoxia conditions via post-translational modifications. HIF1 regulates tumor malignancy and metastasis by gene transcriptions, such as Warburg effect- and angiogenesis-related genes, in cancer cells. However, the HIF1 downstream genes show varied expressional patterns in different cancer types. Herein, we performed the hierarchical clustering based on the HIF1 downstream gene expression patterns using 1,406 cancer cell lines crossing 30 types of cancer to understand the relationship between HIF1 downstream genes and the metastatic potential of cancer cell lines. Four types of cancer were classified by HIF1 downstream genes with significantly altered metastatic potentials. Furthermore, different HIF1 downstream gene subsets were extracted to discriminate each subtype for the four cancer types. HIF1 downstream subtyping classification will help understand the novel insight into tumor malignancy and metastasis in each cancer type.FundingThis work was supported by Project for JSPS KAKENHI (Grant-in-Aid for Scientific Research (C): JP23K06665 to JN, Grant-in-Aid for Early-Carrier Scientists: JP21K15562 to JN), and in part by translational research program from Fukushima Prefecture (KS).Competing Interests statementThe authors have declared that no conflict of interest exists.
CoCoNat: a novel method based on deep-learning for coiled-coil prediction
Authors: Madeo Giovanni , Savojardo Castrense , Manfredi Matteo , Martelli Pier Luigi , Casadio Rita 
Published: May 2023

AbstractMotivationCoiled-coil domains (CCD) are widespread in all organisms performing several crucial functions. Given their relevance, the computational detection of coiled-coil domains is very important for protein functional annotation. State-of-the art prediction methods include the precise identification of coiled-coil domain boundaries, the annotation of the typical heptad repeat pattern along the coiled-coil helices as well as the prediction of the oligomerization state.ResultsIn this paper we describe CoCoNat, a novel method for predicting coiled-coil helix boundaries, residue-level register annotation and oligomerization state. Our method encodes sequences with the combination of two state-of-the-art protein language models and implements a three-step deep learning procedure concatenated with a Grammatical-Restrained Hidden Conditional Random Field (GRHCRF) for CCD identification and refinement. A final neural network (NN) predicts the oligomerization state. When tested on a blind test set routinely adopted, CoCoNat obtains a performance superior to the current state-of-the-art both for residue-level and segment-level coiled-coil detection. CoCoNat significantly outperforms the most recent state-of-the art method on register annotation and prediction of oligomerization states.AvailabilityCoCoNat is available athttps://coconat.biocomp.unibo.it.Contactpierluigi.martelli@unibo.it
Progressive Senescence Programs Induce Intrinsic Vulnerability to Aging-related Breast Cancer
Authors: Bai Huiru , Liu Xiaoqin , Lin Meizhen , Meng Yuan , Li Nan , Clarke Michael F. , Cai Shang 
Published: May 2023

SUMMARYCancer incidence escalates exponentially with advancing age; however, the underlying mechanism remains unclear. In this study, we built a chronological molecular clock at the single-cell transcription level with a mammary stem cell-enriched population to depict physiological aging dynamics in mice. We found that the mammary aging process was asynchronous and progressive, initiated by an early senescence program with elevated NF-kB and P53 signaling, succeeded by an entropic late senescence program with reduced NF-kB and P53 signaling and enhanced PI3K-Akt-mTOR, Wnt, Notch and pluripotent activity, vulnerable to cancer predisposition. The transition towards senescence program was governed by the master stem cell factorBcl11b, loss of which accelerated mammary ageing with enhanced DMBA-induced tumor formation. We identified a drug TPCA-1 that can elevateBcl11b, rejuvenate mammary cells and significantly reduce aging-related cancer incidence. Our findings established a molecular portrait of progressive mammary cell aging and elucidated the transcriptional regulatory network bridging mammary aging and cancer predisposition, which can be modulated to control cancer initiation; therefore, this study has potential implications for the management of cancer prevalence in the aged.
Increase of cell surface vimentin (CSV) is associated with vimentin network disruption and subsequent stress-induced premature senescence (SIPS) in human chondrocytes
Authors: Riegger Jana , Brenner Rolf E. 
Published: May 2023

AbstractAccumulation of dysfunctional chondrocytes has detrimental consequences on the cartilage homeostasis and is thus thought to play a crucial role during the pathogenesis of osteoarthritis (OA). However, the underlying mechanisms of phenotypical alteration in chondrocytes are incompletely understood.Here, we provide evidence that disruption of the intracellular vimentin network and consequent phenotypical alteration in human chondrocytes results in an externalization of the intermediate filament. The presence of so-called cell surface vimentin (CSV) on chondrocytes was associated with the severity of tissue degeneration in clinical OA samples and was enhanced after mechanical injury of cartilage tissue. By means of a doxorubicine-based in vitro model of stress-induced premature senescence (SIPS), we could confirm the connection between cellular senescence and amount of CSV. Although siRNA-mediated silencing ofCDKN2Aclearly reduced the senescent phenotype as well as CSV levels of human chondrocytes, cellular senescence could not be completely reversed. Interestingly, knockdown of vimentin resulted in a SIPS-like phenotype and consequently increased CSV. Therefore, we concluded that the integrity of the intracellular vimentin network is crucial to maintain cellular function in chondrocytes. This assumption could be confirmed by chemically-induced collapse of the vimentin network, which resulted in cellular stress and enhanced CSV expression. Regarding its biological function, CSV was found to be associated with enhanced chondrocyte adhesion and plasticity. While osteogenic capacities seemed to be enhanced in chondrocytes expressing high levels of CSV, the chondrogenic potential was clearly compromised.Overall, our study reinforces the importance of the vimentin network in maintenance of the chondrogenic phenotype and introduces CSV as a novel membrane-bound marker of dysfunctional chondrocytes.
Gene networks reveal stem-cell state convergence during preneoplasia and progression to malignancy in multistage skin carcinogenesis
Authors: Taylor Mark A. , Kandyba Eve , Halliwill Kyle , Delrosario Reyno , Koroshkin Matvei , Goodarzi Hani , Quigley David , Li Yun Rose , Wu Di , Bollam Saumya , Mirzoeva Olga , Akhurst Rosemary J. , Balmain Allan 
Published: May 2023

AbstractAdult mammalian stem cells play critical roles in normal tissue homeostasis, as well as in tumor development, by contributing to cell heterogeneity, plasticity, and development of drug resistance. The relationship between different types of normal and cancer stem cells is highly controversial and poorly understood. Here, we carried out gene expression network analysis of normal and tumor samples from genetically heterogeneous mice to create network metagenes for visualization of stem-cell networks, rather than individual stem-cell markers, at the single-cell level during multistage carcinogenesis. We combined this approach with lineage tracing and single-cell RNASeq of stem cells and their progeny, identifying a previously unrecognized hierarchy in whichLgr6+ stem cells from tumors generate progeny that express a range of other stem-cell markers includingSox2, Pitx1, Foxa1, Klf5, andCd44. Our data identify a convergence of multiple stem-cell and tumor-suppressor pathways in benign tumor cells expressing markers of lineage plasticity and oxidative stress. This same single-cell population expresses network metagenes corresponding to markers of cancer drug resistance in human tumors of the skin, lung and prostate. Treatment of mouse squamous carcinomasin vivowith the chemotherapeuticcis-platin resulted in elevated expression of the genes that mark this cell population. Our data have allowed us to create a simplified model of multistage carcinogenesis that identifies distinct stem-cell states at different stages of tumor progression, thereby identifying networks involved in lineage plasticity, drug resistance, and immune surveillance, providing a rich source of potential targets for cancer therapy.One-Sentence SummaryGenes act in networks to drive cancer, and we identify these groups of genes from bulk-tissue and trace them at single-cell resolution.
The dynamic hypoosmotic response ofVibrio choleraerelies on the mechanosensitive channel MscS
Authors: Ramsey Kristen , Britt Madolyn , Maramba Joseph , Ushijima Blake , Moller Elissa , Anishkin Andriy , Häse Claudia , Sukharev Sergei 
Published: May 2023

AbstractLike other intestinal bacteria, the facultative pathogenVibrio choleraeadapts to a wide range of osmotic environments. Under drastic osmotic down-shifts,Vibrioavoids mechanical rupture by rapidly releasing excessive metabolites through mechanosensitive (MS) channels that belong to two major types, low-threshold MscS and high-threshold MscL. To investigate each channel’s individual contribution toV. cholerae’sosmotic permeability response, we generated individualΔmscS, ΔmscL, and doubleΔmscL ΔmscSmutants inV. choleraeO395 and characterized their tension-dependent activation in patch-clamp experiments, as well as their millisecond-scale osmolyte release kinetics using a stopped-flow light scattering technique. We additionally generated numerical models reflecting the kinetic competition of osmolyte release with water influx. Both mutants lacking MscS exhibited delayed osmolyte release kinetics and decreased osmotic survival rates compared to WT. TheΔmscLmutant showed comparable release kinetics to WT, but a higher osmotic survival, while ΔmscShad low survival, comparable to the doubleΔmscLΔmscSmutant. By analyzing release kinetics following rapid medium dilution, we illustrate the sequence of events and define the set of parameters that characterize discrete phases of the osmotic response. Osmotic survival rates are directly correlated to the extent and duration of cell swelling, the rate of osmolyte release and the onset time, and the completeness of the post-shock membrane resealing. Not only do the two channels interact functionally during the resealing phase, but there is also a compensatory up-regulation of MscS in theΔmscLstrain suggesting some transcriptional crosstalk. The data reveal the advantage of the low-threshold MscS channel in curbing tension surges, without which MscL becomes toxic, and the role of MscS in the proper termination of the osmotic permeability response inVibrio.