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Abstract Smart batteries, i.e., equipped with internal and external sensors, are emerging as promising solutions to enhance battery state of health and optimize operating conditions. However, for accurate correlations between the evolution of the cell parameters (e.g., temperature, strain) and physicochemical degradation mechanisms, it is crucial to know the reliability of sensors. To address this question, we perform a synchrotron operando X-ray diffraction experiment to investigate the local and global impact of the presence of internal sensors on a commercial prismatic Li-ion battery cell at various (dis)charge rates. We find that, while the overall electrochemical performance is unaffected, the sensors have a substantial impact on the local graphite lithiation kinetics, especially at high (dis)charge rates. These results show the importance of controlling local deformations induced by internal sensors and tailoring the dimensions of these sensors to obtain reliable battery performance indicators and optimize smart batteries.

Background A high density of resident memory T cells (TRM) in tumors correlates with improved clinical outcomes in immunotherapy-treated patients. In most clinical studies, TRM are defined by the CD103 marker. However, it is clearly established that not all TRM express CD103, but can be defined by other markers (CD49a, CD69, etc). The frequency of these subpopulations of TRM expressing or not CD103 varies according to the location of the cancer. Little is known about their functionality and their predictive impact on response to immunotherapy. In preclinical models, only some subpopulations of TRM are associated with cancer vaccine efficacy.Methods Multiparametric cytometry analyses were used to demonstrate the presence of TRM subpopulations in the lung in mice after vaccination and in fresh ex vivo human non-small cell lung cancer (NSCLC). An analysis of the T-cell repertoire of these TRM was conducted to search for their relationships. Multiplex immunofluorescence techniques were used to quantify intratumor infiltration of TRM subpopulations in two cohorts of patients with NSCLC. The impact on the clinical outcome of the TRM tumor infiltration was also investigated.Results We identified two main TRM subpopulations in tumor-infiltrating lymphocytes derived from patients with NSCLC: one co-expressing CD103 and CD49a (double positive (DP)), and the other expressing only CD49a (simple positive (SP)); both exhibiting additional TRM surface markers like CD69. Despite higher expression of inhibitory receptors, DP TRM exhibited greater functionality compared with SP TRM. Analysis of T-cell receptor (TCR) repertoire and expression of the stemness marker TCF1 revealed shared TCRs between populations, with the SP subset appearing more progenitor-like phenotype. In the training cohort, PD-L1 (Programmed Death-Ligand 1) and TCF1+CD8+T cells predict response to anti-PD-1. In patient with NSCLC validation cohorts, only DP TRM predicted PD-1 blockade response. Multivariate analysis, including various biomarkers associated with responses to anti-PD-(L)1, such as total CD8, TCF1+CD8+T cells, and PD-L1, showed that only intratumoral infiltration by DP TRM remained significant.Conclusions This study highlights the non-equivalence of TRM subpopulations. The population of TRM co-expressing CD103 and CD49a appears to be the most functional and has the most significant capacity for predicting response to immunotherapy in multivariate analysis in patients with NSCLC.

Abstract Background HER2 expression has a prognostic and predictive impact in early-stage breast cancer (BC). HER2 positive BC (immunohistochemistry (IHC) score 3 + or 2 + with in situ hybridization (ISH) amplification) are treated with HER2 targeted therapies. The concept of HER2-low BC (IHC score 1 + or 2 + without ISH amplification) is drawing attention as anti-HER2 treatment has recently shown efficacy in this subgroup. We aimed to explore the response to neoadjuvant chemotherapy (NAC) in HER2-low early BC according to the HER2 score (1 + or 2 + without amplification). Methods We conducted a retrospective study in two French comprehensive cancer centers. All patients with HER2-low BC treated with NAC from January 2014 to December 2020 were included. The primary objective was to analyze the pathological complete response (pCR) rate to NAC using the Sataloff or RCB system, according to the HER2 score. Secondary objectives were to assess disease free survival (DFS), overall survival (OS) and to explore the immune environment through the Neutrophil-to-Lymphocyte Ratio (NLR), according to HER2 expression. Univariate and multivariate analyses were performed. Results We included 237 tumors for 229 patients. Of these, 160 (67.5%) tumors were HER2 1 + , 77 (32.5%) were HER2 2 + , and 152 (64.1%) were hormone receptor (HR) positive. The median age was 53.9 years. No differences in tumor characteristics were observed between HER2 1 + and HER2 2 + subgroups. pCR was achieved in 38 tumors (17%), without any difference between HER2 1 + and HER2 2 + subgroups (p = 0.77). DFS and OS were significantly different between HER2 1 + and HER2 2 + patients (HR = 0.41,CI95%[0.17;0.97] p = 0.037 and HR = 0.31,CI95%[0.09;1.02] p = 0.042, respectively). HER2 status was still associated with DFS and OS after adjustment for age, HR status and NLR, with better outcomes in favor of HER2 score 2 + (HR = 0.35 [0.15–0.84] and HR = 0.24 [0.07–0.81], respectively). NLR was not associated with worse DFS or OS. Conclusion In HER2-low early BC, no differences in pCR were observed between HER2 1 + and HER2 2 + tumors, however patients with HER2 2 + tumors had a better DFS and OS than those with HER2 1 + . Further investigations are needed to describe the intrinsic differences in the spectrum of HER2-low BC.

Novel 2-amino bis(2-phosphonoacetic) acids were prepared by microwave irradiation of a mixture of amine, glyoxylic acid and phosphorous acid. The reaction takes place with various amines including primary and secondary amines and polyamines, but this reaction is more sensitive to steric hindrance of amine than the similar Kabachnik–Fields reaction. Amino acids can be also transformed into the expected bis(2-phosphonoacetic) acids, with the exception of tryptophan, which gives a β-carboline product.

Abstract Background Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers. Results Transcriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype. Conclusions Using a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

We previously demonstrated that F4 peptide (CNPEDCLYPVSHAHQR) from collagen XIX was able to inhibit melanoma cell migrationin vitro and cancer progression in a mouse melanoma model. The aim of the present work was to study the anti-angiogenic properties of F4 peptide. We demonstrated that F4 peptide inhibited VEGF-induced pseudo-tube formation on Matrigel by endothelial cells and endothelial sprouting in a rat aortic ring assay. By affinity chromatography, we identified αvβ3 and α5β1 integrins as potential receptors for F4 peptide on endothelial cell surface. Using solid phase assays, we proved the direct interaction between F4 and both integrins. Taken together, our results demonstrate that F4 peptide is a potent antitumor agent inhibiting both angiogenesis and tumor cell migration.

Hop, also known as Stip1 or Sti1, facilitates substrate transfer between the Hsp70 and Hsp90 molecular chaperones. Characterization of proteostasis-related pathways in STIP1 knock-out cell lines reveals that in eukaryotes Stip1 modulates the balance between protein folding and degradation.

Abstract iMOKA (interactive multi-objective k-mer analysis) is a software that enables comprehensive analysis of sequencing data from large cohorts to generate robust classification models or explore specific genetic elements associated with disease etiology. iMOKA uses a fast and accurate feature reduction step that combines a Naïve Bayes classifier augmented by an adaptive entropy filter and a graph-based filter to rapidly reduce the search space. By using a flexible file format and distributed indexing, iMOKA can easily integrate data from multiple experiments and also reduces disk space requirements and identifies changes in transcript levels and single nucleotide variants. iMOKA is available at https://github.com/RitchieLabIGH/iMOKA and Zenodo https://doi.org/10.5281/zenodo.4008947 .

This study investigates the capacity of polyamide nanofiltration membrane (SNTE NF270-2540) to extract the lanthanum (La) (III) and its mixtures with the iron (Fe) (III). A three - level factorial design and response surface methodology was used to evaluate the effects of different parameters, such as: pH (3.0 – 9.0), concentration (10 – 100 ppm), pressure (6.0 – 13.5 bars). The results showed that the retention of La (III) varied from 29 % to 100 %, depending on the experimental condition it was possible to extract all of La (III) and Fe (III) from the same mixture. The results showed that the extraction of La (III) reaches 100 % for 10 and 55 ppm at pH = 3.0 and for 100 ppm at pH = 9.0, under the pressure of 13.5 bars. At pH = 3.0, the extraction of the mixtures La (III) / Fe (III) (50 ppm / 50 ppm) and (100 ppm / 100 ppm) whatever the pressure was all (100 %). The study confirmed a high lanthanum extraction using polyamide nanofiltration membrane.

Hepatitis C virus (HCV) is a serious disease that threatens human health. Despite consistent efforts to inhibit the virus, it has infected more than 58 million people, with 300,000 deaths per year. The HCV nonstructural protein NS5A plays a critical role in the viral life cycle, as it is a major contributor to the viral replication and assembly processes. Therefore, its importance is evident in all currently approved HCV combination treatments. The present study identifies new potential compounds for possible medical use against HCV using the quantitative structure–activity relationship (QSAR). In this context, a set of 36 NS5A inhibitors was used to build QSAR models using genetic algorithm multiple linear regression (GA-MLR) and Monte Carlo optimization and were implemented in the software CORAL. The Monte Carlo method was used to build QSAR models using SMILES-based optimal descriptors. Four splits were performed and 24 QSAR models were developed and verified through internal and external validation. The model created for split 3 produced a higher value of the determination coefficients using the validation set (R2 = 0.991 and Q2 = 0.943). In addition, this model provides interesting information about the structural features responsible for the increase and decrease of inhibitory activity, which were used to develop eight novel NS5A inhibitors. The constructed GA-MLR model with satisfactory statistical parameters (R2 = 0.915 and Q2 = 0.941) confirmed the predicted inhibitory activity for these compounds. The Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) predictions showed that the newly designed compounds were nontoxic and exhibited acceptable pharmacological properties. These results could accelerate the process of discovering new drugs against HCV.

After the synthesis of polyethylenimine supported on silica, it has been used as a new and efficient catalyst in Knoevenagel and Michael condensations. The presence of the polyethylenimine in the catalytic system together with silica displays an acido-basic character allows a better catalytic activity in the condensations. Carried out under microwave irradiation, without organic solvent and during short time, the syntheses are respectful towards green chemistry. The solid catalyst can be easily reused. This catalyst has the acido-basic character at the same time.

Wastewater cleaning strategies based on the adsorption of materials are being increasingly considered, but the wide variety of organic pollutants at low concentrations still makes their removal a challenge. The hybrid material proposed here consists of a zwitterionic polyethylenimine polymer coating a magnetic core. Polyethylenimine is phosphonated at different percentages by a one-step process and used to coat maghemite nanoparticles. It selectively extracts high amounts of cationic and anionic contaminants over a wide range of pH values, depending on the adjustable number of phosphonate groups introduced on the polymer. After recovering the nanoparticles with a magnet, pollutants are quantitatively released by repeated washing with low amounts of pH-adjusted water. The material can be reused many times without noticeable loss of efficiency and is designed to resist high temperatures, oxidation and harsh conditions.

Cloud point extraction (CPE) was used to extract uranium (VI) from an aqueous solution in acetate media. The methodology used is based on the formation of uranyl-ionic liquid (I) complexes and uranyl-D2EHPA soluble in a micellar phase of non-ionic surfactant (Triton X-100). The uranium (VI) complexes are then extracted into the surfactant-rich phase at ambient temperature. The ionic liquid (IL) used as a chelating agent was synthesized and characterized in this study. It is composed of N-butyl N’-triethoxy methyl imidazolium cation and diethylhexylphosphate (D2EHPA-H) as anion. The effect of the IL on the extraction efficiency was studied in presence and in absence of IL’s cation in acetate medium.

Research over the last few decades has shown that the characterization of microaggregates at the micrometer scale using Transmission Electron Microscopy (TEM) provides useful information on the influence of microorganisms on soil functioning. By taking soil heterogeneity into account, TEM provides qualitative information about the state of bacteria and fungi (e.g., intact state of living organisms, spores, residues) at the sampling date within organo-mineral associations, from the soil-root interface to the bulk soil, and in biogenic structures such as casts. The degree of degradation of organic matter can be related to the visualized enzymatic potential of microorganisms that degrade them, thus indicating organic matter dynamics within soil aggregates. In addition, analytical TEM characterization of microaggregates by EELS (Electron Energy Loss Spectroscopy) or EDX (Energy Dispersive X-rays spectroscopy) provides in situ identification of microbial involvement in the biogeochemical cycles of elements. Furthermore, micrometer characterization associated with other methodologies such as Nanoscale Secondary Ion Mass Spectrometry (NanoSIMS) or soil fractionation, enables monitoring both incorporation of biodegraded litter within soil aggregates and impacts of microbial dynamics on soil aggregation, particularly due to production of extracellular polymeric substances. The present focused review suggests that such an approach using micrometer characterization of soil microhabitats provides relevant qualitative and quantitative information when monitoring and modeling microbial processes in dynamics of organo-mineral associations.

Parmi les multiples dispositifs de formation à l’enseignement secondaire qui cohabitent au sein de la Confédération suisse, cet article présente et interroge celui nouvellement mis en place dans le canton de Genève qui donne aux didactiques disciplinaires une place centrale. Les raisons et les hypothèses qui sous-tendent ce « pari » des didactiques sont questionnées à partir de trois approches complémentaires: la première s’intéresse au contexte genevois, tentant de cerner l’effet du contexte local sur l’adaptation de mouvements de réformes d’envergure nationale et internationale. La deuxième analyse la nature des savoirs dispensés durant la formation en se focalisant sur l’articulation des didactiques disciplinaires avec les savoirs scientifiques, avec les savoirs issus des sciences de l’éducation et avec les savoirs issus de la pratique professionnelle. Enfin, la troisième porte sur l’inscription des didactiques dans un dispositif de formation universitaire interfacultaire qui articule recherche scientifique et formation à l’enseignement.

To investigate the influence of increasing age on clinical presentation, treatment and long-term outcome in patients with inducible paroxysmal supraventricular tachycardia (SVT) without pre-excitation syndromes.Clinical and electrophysiological study (EPS) data, as well as long-term clinical outcome (mean follow-up 2.4±4.0 years) were collected in patients referred for regular tachycardia with inducible SVT during EPS without pre-excitation.Among 1960 referred patients, 301 patients (15.4%) were aged ≥70 (70-97). In this subset, anticoagulants were prescribed in 49 patients following an erroneous diagnosis of atrial tachycardia and 14 were previously erroneously diagnosed with ventricular tachycardia because of wide QRS. Ablation was performed more frequently in patients ≥70 despite more frequent failure and complications. During follow-up, higher risks of AF, stroke, pacemaker implantation and death were observed in patients ≥70 whereas SVT recurrences were similar in both age groups. In multivariable analysis, age ≥70 was independently associated with higher risks of SVT-related adverse events prior to ablation (OR = 1.93, 1.41-2.62, p

Background: Accessory pathway (AP) ablation is not always easy. Our purpose was to assess the age-related prevalence of AP location, electrophysiological and prognostic data according to this location. Methods: Electrophysiologic study (EPS) was performed in 994 patients for a pre-excitation syndrome. AP location was determined on a 12 lead ECG during atrial pacing at maximal preexcitation and confirmed at intracardiac EPS in 494 patients. Results: AP location was classified as anteroseptal (AS)(96), right lateral (RL)(54), posteroseptal (PS)(459), left lateral (LL)(363), nodoventricular (NV)(22). Patients with ASAP or RLAP were younger than patients with another AP location. Poorly-tolerated arrhythmias were more frequent in patients with LLAP than in other patients (0.009 for ASAP, 0.0037 for RLAP,

The inhibitive effect of the piperidin-1-yl-phosphonic acid (PPA) on the corrosion of iron in 1 M H2SO4 solution has been investigated by weight loss measurement, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. The presence of (PPA) reduces remarkably the corrosion rate of iron in acidic solution. The effect of temperature on the corrosion behavior of iron was studied in the range of 298–328 K. Results clearly reveal that the (PPA) behaves as a mixed type corrosion inhibitor with the highest inhibition at 5 × 10−3 M. The adsorption of PPA on the iron surface obeys the Langmuir's adsorption isotherm.

The inhibitive effect of the hexamethylenediamine tetra(methylene phosphonic acid) (HMDTMPA) on the corrosion of carbon steel in 1.0 M HCl solution has been investigated by weight loss measurement, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. The presence of (HMDTMPA) reduces remarkably the corrosion rate of carbon steel in acidic solution. The effect of temperature on the corrosion behavior of carbon steel was studied in the range of 298–328 K. Results clearly reveal that the (HMDTMPA) behaves as a mixed type corrosion inhibitor with the highest inhibition at 4 × 10−3 M. The adsorption of HMDTMPA on the carbon steel surface obeys to the Langmuir’s adsorption isotherm. Surface analysis via scanning electron microscope (SEM) shows a significant improvement on the surface morphology of the carbon steel plate.

Quantitative Structure Activity Relationships (QSAR or SAR) have helped scientists to establish mathematical relationships between molecular structures and their biological activities. In the present article, SAR studies have been carried out on 89 tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepine (TIBO) derivatives using different classifiers, such as support vector machines, artificial neural networks, random forests, and decision trees. The goal is to propose classification models that will be able to classify TIBO compounds into two groups: high and low inhibitors of HIV-1 reverse transcriptase. Each molecular structure was encoded by 10 descriptors. To check the validity of the established models, all of them were subjected to various validation tests: internal validation, Y-randomization, and external validation. The established classification models have been successful. The correct classification rates reached 100% and 90% in the learning and test sets, respectively. Finally, molecular docking analysis was carried out to understand the interactions between reverse transcriptase enzyme and the TIBO compounds studied. Hydrophobic and hydrogen bond interactions led to the identification of active binding sites. The established models could help scientists to predict the inhibition activity of untested compounds or of novel molecules prior to their synthesis. Therefore, they could reduce the trial and error process in the design of human immunodeficiency virus (HIV) inhibitors.

The chemical and physical properties of imidazolium-based ionic liquids are determined by the interactions between the counter-ions. The C(2) position plays an important role in these interactions, as it represents the predominant site for interionic hydrogen bonding. This study shows that the directional hydrogen bonds between highly symmetrical anions (iodide, tetrafluoroborate, hexafluorophosphate) and the C(2)-H group of the 1-methyl-3-propylimidazolium cation determine the molecular and macroscopic behavior in terms of the thermal properties. Upon replacing the C(2) proton by a methyl group, the anion repositions itself at the C(4)/(5) moiety, where it forms a new hydrogen bond, apparently with only one of the two CH groups. In addition, the larger the anion is in diameter, the more likely it will establish further interactions with other parts of the cation, such as the propyl chain.