[For a good understanding and use of the term "organoids"]. / Pour une bonne compréhension et un bon usage du terme « organoïdes ¼.

Title: Pour une bonne compréhension et un bon usage du terme « organoïdes ¼. Abstract: Depuis une dizaine d'années, des progrès considérables ont été réalisés concernant les conditions qui permettent à des cellules de s'auto-organiser dans l'espace comme elles le font lors des phases précoces du développement embryonnaire ou dans certains tissus adultes. On nomme ainsi « organoïdes ¼ des structures en trois dimensions complexes, organisées et intégrant plusieurs types cellulaires, qui peuvent reproduire in vitro certaines fonctions d'un organe. Toutefois, ces organoïdes ne peuvent actuellement reproduire à l'identique une architecture anatomique et fonctionnelle complète. Bien qu'utilisé pour des raisons de simplification pour la communication, en particulier dans la presse généraliste, il est donc abusif d'utiliser le terme « mini-organes ¼ pour décrire ces structures.

At the crossroads of epidemiology and biology: Bridging the gap between SARS-CoV-2 viral strain properties and epidemic wave characteristics.

The COVID-19 pandemic has given rise to numerous articles from different scientific fields (epidemiology, virology, immunology, airflow physics …) without any effort to link these different insights. In this review, we aim to establish relationships between epidemiological data and the characteristics of the virus strain responsible for the epidemic wave concerned. We have carried out this study on the Wuhan, Alpha, Delta and Omicron strains allowing us to illustrate the evolution of the relationships we have highlighted according to these different viral strains. We addressed the following questions. 1) How can the mean infectious dose (one quantum, by definition in epidemiology) be measured and expressed as an amount of viral RNA molecules (in genome units, GU) or as a number of replicative viral particles (in plaque-forming units, PFU)? 2) How many infectious quanta are exhaled by an infected person per unit of time? 3) How many infectious quanta are exhaled, on average, integrated over the whole contagious period? 4) How do these quantities relate to the epidemic reproduction rate R as measured in epidemiology, and to the viral load, as measured by molecular biological methods? 5) How has the infectious dose evolved with the different strains of SARS-CoV-2? We make use of state-of-the-art modelling, reviewed and explained in the appendix of the article (Supplemental Information, SI), to answer these questions using data from the literature in both epidemiology and virology. We have considered the modification of these relationships according to the vaccination status of the population.

Risk assessment for long- and short-range airborne transmission of SARS-CoV-2, indoors and outdoors.

Preventive measures to reduce infection are needed to combat the COVID-19 pandemic and prepare for a possible endemic phase. Current prophylactic vaccines are highly effective to prevent disease but lose their ability to reduce viral transmission as viral evolution leads to increasing immune escape. Long-term proactive public health policies must therefore complement vaccination with available nonpharmaceutical interventions aiming to reduce the viral transmission risk in public spaces. Here, we revisit the quantitative assessment of airborne transmission risk, considering asymptotic limits that considerably simplify its expression. We show that the aerosol transmission risk is the product of three factors: a biological factor that depends on the viral strain, a hydrodynamical factor defined as the ratio of concentration in viral particles between inhaled and exhaled air, and a face mask filtering factor. The short-range contribution to the risk, present both indoors and outdoors, is related to the turbulent dispersion of exhaled aerosols by air drafts and by convection (indoors), or by the wind (outdoors). We show experimentally that airborne droplets and CO2 molecules present the same dispersion. As a consequence, the dilution factor, and therefore the risk, can be measured quantitatively using the CO2 concentration, regardless of the room volume, the flow rate of fresh air, and the occupancy. We show that the dispersion cone leads to a concentration in viral particles, and therefore a short-range transmission risk, inversely proportional to the squared distance to an infected person and to the flow velocity. The aerosolization criterion derived as an intermediate result, which compares the Stokes relaxation time to the Lagrangian time-scale, may find application for a broad class of aerosol-borne pathogens and pollutants.

[Explore the history of artificial intelligence, to better define and understand it]. / Parcourir l'histoire de l'intelligence artificielle, pour mieux la définir et la comprendre.

TITLE: Parcourir l'histoire de l'intelligence artificielle, pour mieux la définir et la comprendre. ABSTRACT: L'intelligence artificielle est une expression fourre-tout, qui suscite autant d'espoirs que de craintes. Cette locution a envahi les médias, les conférences, les conversations, mais aussi les appels à projets des institutions de recherche et de diverses associations. On ne peut quasiment plus élaborer de projet de recherche sans mentionner une interface avec l'intelligence artificielle. Dans cet article, après la présentation d'une brève vision historique, nous proposerons une définition de l'intelligence artificielle et un paysage des possibles offerts par celle-ci.

Using Data Mining to Explore Calmodulin Bibliography.

In this chapter, we present a strategy and the techniques to approach a scientific field from a set of articles gathered from the bibliographic database "Web of Science." The strategy is based on methods developed to analyze social networks. We illustrate its use in studying the calmodulin field. The method allows to structure a huge number of articles when writing a review, to detect the key opinion leaders in a given field, and to locate their own research topic in the landscape of themes deciphered by our own community.We show that the free software VOSviewer may be used without knowledge in computing science and with a short learning period.

Facts and conjectures on calmodulin and its cousin proteins, parvalbumin and troponin C.

This review aims at giving a rational frame to understand the diversity of EF hand containing calcium binding proteins and their roles, with special focus on three members of this huge protein family, namely calmodulin, troponin C and parvalbumin. We propose that these proteins are members of structured macromolecular complexes, termed calcisomes, which constitute building devices allowing treatment of information within eukaryotic cells and namely calcium signals encoding and decoding, as well as control of cytosolic calcium levels in resting cells. Calmodulin is ubiquitous, present in all eukaryotic cells, and pleiotropic. This may be explained by its prominent role in regulating calcium movement in and out of the cell, thus maintaining calcium homeostasis which is fundamental for cell survival. The protein is further involved in decoding transient calcium signals associated with calcium movements after cell stimulation. We will show that the specificity of calmodulin's actions may be more easily explained if one considers its role in the light of calcisomes. Parvalbumin should not be considered as a simple intracellular calcium buffer. It is also a key factor for regulating calcium homeostasis in specific cells that need a rapid retrocontrol of calcium transients, such as fast muscle fibers. Finally, we propose that troponin C, with its four calcium binding domains distributed between two lobes presenting different calcium binding kinetics, exhibits all the characteristics needed to trigger and then post modulate muscle contraction and thus appears as a typical Feed Forward Loop system. If the present conjectures prove accurate, the way will be paved for a new pharmacology targeting the cell calcium signaling machinery. This article is part of a Special Issue entitled: ECS Meeting edited by Claus Heizmann, Joachim Krebs and Jacques Haiech.

Discovery of a Locally and Orally Active CXCL12 Neutraligand (LIT-927) with Anti-inflammatory Effect in a Murine Model of Allergic Airway Hypereosinophilia.

We previously reported Chalcone-4 (1) that binds the chemokine CXCL12, not its cognate receptors CXCR4 or CXCR7, and neutralizes its biological activity. However, this neutraligand suffers from limitations such as poor chemical stability, solubility, and oral activity. Herein, we report on the discovery of pyrimidinone 57 (LIT-927), a novel neutraligand of CXCL12 which displays a higher solubility than 1 and is no longer a Michael acceptor. While both 1 and 57 reduce eosinophil recruitment in a murine model of allergic airway hypereosinophilia, 57 is the only one to display inhibitory activity following oral administration. Thereby, we here describe 57 as the first orally active CXCL12 neutraligand with anti-inflammatory properties. Combined with a high binding selectivity for CXCL12 over other chemokines, 57 represents a powerful pharmacological tool to investigate CXCL12 physiology in vivo and to explore the activity of chemokine neutralization in inflammatory and related diseases.

Quiescence status of glioblastoma stem-like cells involves remodelling of Ca2+ signalling and mitochondrial shape.

Quiescence is a reversible cell-cycle arrest which allows cancer stem-like cells to evade killing following therapies. Here, we show that proliferating glioblastoma stem-like cells (GSLCs) can be induced and maintained in a quiescent state by lowering the extracellular pH. Through RNAseq analysis we identified Ca2+ signalling genes differentially expressed between proliferating and quiescent GSLCs. Using the bioluminescent Ca2+ reporter EGFP-aequorin we observed that the changes in Ca2+ homeostasis occurring during the switch from proliferation to quiescence are controlled through store-operated channels (SOC) since inhibition of SOC drives proliferating GSLCs to quiescence. We showed that this switch is characterized by an increased capacity of GSLCs' mitochondria to capture Ca2+ and by a dramatic and reversible change of mitochondrial morphology from a tubular to a donut shape. Our data suggest that the remodelling of the Ca2+ homeostasis and the reshaping of mitochondria might favours quiescent GSLCs' survival and their aggressiveness in glioblastoma.

WNK1 kinase and its partners Akt, SGK1 and NBC-family Na+/HCO3- cotransporters are potential therapeutic targets for glioblastoma stem-like cells linked to Bisacodyl signaling.

Glioblastoma is a highly heterogeneous brain tumor. The presence of cancer cells with stem-like and tumor initiation/propagation properties contributes to poor prognosis. Glioblastoma cancer stem-like cells (GSC) reside in hypoxic and acidic niches favoring cell quiescence and drug resistance. A high throughput screening recently identified the laxative Bisacodyl as a cytotoxic compound targeting quiescent GSC placed in acidic microenvironments. Bisacodyl activity requires its hydrolysis into DDPM, its pharmacologically active derivative. Bisacodyl was further shown to induce tumor shrinking and increase survival in in vivo glioblastoma models. Here we explored the cellular mechanism underlying Bisacodyl cytotoxic effects using quiescent GSC in an acidic microenvironment and GSC-derived 3D macro-spheres. These spheres mimic many aspects of glioblastoma tumors in vivo, including hypoxic/acidic areas containing quiescent cells. Phosphokinase protein arrays combined with pharmacological and genetic modulation of signaling pathways point to the WNK1 serine/threonine protein kinase as a mediator of Bisacodyl cytotoxic effect in both cell models. WNK1 partners including the Akt and SGK1 protein kinases and NBC-family Na+/HCO3- cotransporters were shown to participate in the compound's effect on GSC. Overall, our findings uncover novel potential therapeutic targets for combatting glioblastoma which is presently an incurable disease.

Efficient Modeling and Simulation of Space-Dependent Biological Systems.

We recently demonstrated the possibility to model and to simulate biological functions using hardware description languages (HDLs) and associated simulators traditionally used for microelectronics. Nevertheless, those languages are not suitable to model and simulate space-dependent systems described by partial differential equations. However, in more and more applications space- and time-dependent models are unavoidable. For this purpose, we investigated a new modeling approach to simulate molecular diffusion on a mesoscopic scale still based on HDL. Our work relies on previous investigations on an electrothermal simulation tool for integrated circuits, and analogies that can be drawn between electronics, thermodynamics, and biology. The tool is composed of four main parts: a simple but efficient mesher that divides space into parallelepipeds (or rectangles in 2D) of adaptable size, a set of interconnected biological models, a SPICE simulator that handles the model and Python scripts that interface the different tools. Simulation results obtained with our tool have been validated on simple cases for which an analytical solution exists and compared with experimental data gathered from literature. Compared with existing approaches, our simulator has three main advantages: a very simple algorithm providing a direct interface between the diffusion model and biological model of each cell, the use of a powerful and widely proven simulation core (SPICE) and the ability to interface biological models with other domains of physics, enabling the study of transdisciplinary systems.

Ca2+-Dependent Transcriptional Repressors KCNIP and Regulation of Prognosis Genes in Glioblastoma.

Glioblastomas (GBMs) are the most aggressive and lethal primary astrocytic tumors in adults, with very poor prognosis. Recurrence in GBM is attributed to glioblastoma stem-like cells (GSLCs). The behavior of the tumor, including proliferation, progression, invasion, and significant resistance to therapies, is a consequence of the self-renewing properties of the GSLCs, and their high resistance to chemotherapies have been attributed to their capacity to enter quiescence. Thus, targeting GSLCs may constitute one of the possible therapeutic challenges to significantly improve anti-cancer treatment regimens for GBM. Ca2+ signaling is an important regulator of tumorigenesis in GBM, and the transition from proliferation to quiescence involves the modification of the kinetics of Ca2+ influx through store-operated channels due to an increased capacity of the mitochondria of quiescent GSLC to capture Ca2+. Therefore, the identification of new therapeutic targets requires the analysis of the calcium-regulated elements at transcriptional levels. In this review, we focus onto the direct regulation of gene expression by KCNIP proteins (KCNIP1-4). These proteins constitute the class E of Ca2+ sensor family with four EF-hand Ca2+-binding motifs and control gene transcription directly by binding, via a Ca2+-dependent mechanism, to specific DNA sites on target genes, called downstream regulatory element (DRE). The presence of putative DRE sites on genes associated with unfavorable outcome for GBM patients suggests that KCNIP proteins may contribute to the alteration of the expression of these prognosis genes. Indeed, in GBM, KCNIP2 expression appears to be significantly linked to the overall survival of patients. In this review, we summarize the current knowledge regarding the quiescent GSLCs with respect to Ca2+ signaling and discuss how Ca2+ via KCNIP proteins may affect prognosis genes expression in GBM. This original mechanism may constitute the basis of the development of new therapeutic strategies.

Changes in chromatin state reveal ARNT2 at a node of a tumorigenic transcription factor signature driving glioblastoma cell aggressiveness.

Although a growing body of evidence indicates that phenotypic plasticity exhibited by glioblastoma cells plays a central role in tumor development and post-therapy recurrence, the master drivers of their aggressiveness remain elusive. Here we mapped the changes in active (H3K4me3) and repressive (H3K27me3) histone modifications accompanying the repression of glioblastoma stem-like cells tumorigenicity. Genes with changing histone marks delineated a network of transcription factors related to cancerous behavior, stem state, and neural development, highlighting a previously unsuspected association between repression of ARNT2 and loss of cell tumorigenicity. Immunohistochemistry confirmed ARNT2 expression in cell sub-populations within proliferative zones of patients' glioblastoma. Decreased ARNT2 expression was consistently observed in non-tumorigenic glioblastoma cells, compared to tumorigenic cells. Moreover, ARNT2 expression correlated with a tumorigenic molecular signature at both the tissue level within the tumor core and at the single cell level in the patients' tumors. We found that ARNT2 knockdown decreased the expression of SOX9, POU3F2 and OLIG2, transcription factors implicated in glioblastoma cell tumorigenicity, and repressed glioblastoma stem-like cell tumorigenic properties in vivo. Our results reveal ARNT2 as a pivotal component of the glioblastoma cell tumorigenic signature, located at a node of a transcription factor network controlling glioblastoma cell aggressiveness.

Modeling and simulation of biological systems using SPICE language.

The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology).

The adaptors Grb10 and Grb14 are calmodulin-binding proteins.

We identified the Grb7 family members, Grb10 and Grb14, as Ca2+ -dependent CaM-binding proteins using Ca2+ -dependent CaM-affinity chromatography as we previously did with Grb7. The potential CaM-binding sites were identified and experimentally tested using fluorescent-labeled peptides corresponding to these sites. The apparent affinity constant of these peptides for CaM, and the minimum number of calcium ions bound to CaM that are required for effective binding to these peptides were also determined. We prepared deletion mutants of the three adaptor proteins lacking the identified sites and determined that they lost or strongly diminished their CaM-binding capacity following the sequence Grb7 > > Grb14 > Grb10. More than one CaM-binding site and/or accessory CaM-binding sites appear to exist in Grb10 and Grb14, as compared to a single one present in Grb7.

[Application of microelectronics CAD tools to synthetic biology]. / Application à la biologie synthétique des méthodes et outils de CAO de la microélectronique.

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper.