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Developing cathodes capable of working at intermediate temperatures (IT) is key to improving solid oxide fuel cells’ (SOFC) durability, ease of operation, and manufacturing cost reduction. BaFeO3-δ (BFO)-based perovskites are ideal candidates because of their fast kinetics, which is due to the mixed conduction of oxygen vacancies and electron-holes. Thus, maximizing their oxygen vacancy and hole concentration can further enhance oxygen reduction reaction (ORR) catalysis. This work proposes to achieve this by generating A-site deficiency, which introduces negative charges into the perovskite crystal. The paper presents a computational and experimental analysis of this strategy on BFO-based cathodes, using (Ba0.95La0.05)1-xFeO3-δ as a case study. A-site deficiency increases the concentration of oxygen vacancies and holes, improving ORR catalysis. In addition, it eases oxygen surface exchange by hindering Ba segregation. As a result, A-site deficiency improves the overall electrochemical properties of BFO-based cathodes, providing a simple and effective method to enhance their performance.

Oncolytic viruses (OVs) are novel anti-tumor agents with the ability to selectively infect and kill tumor cells while sparing normal tissue. Beyond tumor cytolysis, OVs are capable of priming an anti-tumor immune response via lysis and cross-presentation of locally expressed endogenous tumor antigens, acting as an “endovaccine.” The effectiveness of OVs, similar to other immunotherapies, can be hampered by an immunosuppressive tumor microenvironment. In this study, we modified a previously generated oncolytic herpes simplex virus (oHSV) retargeted to the human HER2 (hHER2) tumor molecule and encoding murine interleukin-12 (mIL-12), by insertion of a second immunomodulatory molecule, murine granulocyte-macrophage colony-stimulating factor (mGM-CSF), to maximize therapeutic efficacy. We assessed the efficacy of this double-armed virus (R-123) compared to singly expressing GM-CSF and IL-12 oHSVs in tumor-bearing mice. While monotherapies were poorly effective, combination with α-PD1 enhanced the anti-tumor response, with the highest efficacy of 100% response rate achieved by the combination of R-123 and α-PD1. Efficacy was T cell-dependent, and the induced immunity was long lasting and able to reject a second contralateral tumor. Importantly, systemic delivery of R-123 combined with α-PD1 was effective in inhibiting the development of tumor metastasis. As such, this approach could have a significant therapeutic impact paving the way for further development of this platform in cancer immunotherapy., Graphical Abstract, Fully virulent tumor retargeted HSV oncolytic viruses (THVs) are novel immunotherapeutic agents with increased specificity, safety, and potency. De Lucia et al. propose the use of a hHER2 THV expressing IL-12 and GM-CSF as a strategy to potentiate anti-tumor efficacy in combination with anti-PD1, opening future perspectives for local and systemic treatment.

Battery management systems require efficient battery prognostics so that failures can be prevented, and efficient operation guaranteed. In this work, we develop new models based on neural networks and ordinary differential equations (ODE) to forecast the state of health (SOH) of batteries and predict their end of life (EOL). Governing differential equations are discovered using measured capacities and voltage curves. In this context, discoveries and predictions made with neural ODEs, augmented neural ODEs, predictor-corrector recurrent ODEs are compared against established recurrent neural network models, including long short-term memory and gated recurrent units. The ODE models show good performance, achieving errors of 1% in SOH and 5% in EOL estimation when predicting 30% of the remaining battery’s cycle life. Variable cycling conditions and a range of prediction horizons are analyzed to evaluate the models’ characteristics. The results obtained are extremely promising for applications in SOH and EOL predictions.

In the previous chapter, we describe the engineering of a HSV-BAC genome by galK recombineering. Here we describe the procedures to reconstitute, or regenerate, the replicating recombinant virus, and the methods to purify it and characterize it for the correct expression of the transgene. We present the example of R-115, a recombinant expressing murine interleukin 12 (mIL12) from the US1-US2 intergenic region. A specific method for the production of highly purified virions by iodixanol gradient, suitable for in vivo applications, is also detailed.

Since the cloning of the herpes simplex virus (HSV) genome as BAC (bacterial artificial chromosome), the genetic engineering of the viral genome has become readily feasible. The advantage is that the modification of the animal virus genome is carried out in bacteria, with no replication or production of viral progeny, and is separated from the reconstitution or regeneration of the recombinant virus in mammalian cells. This allows an easy engineering of essential genes, as well. Many technologies have been developed for herpesvirus BAC engineering. In our hands the most powerful is galK recombineering that exploits a single marker (galK) for positive and negative selection and PCR amplicons for seamless modification in the desired genome locus. Here we describe the engineering of the HSV recombinant BAC 115 by the insertion of a heterologous cassette for the expression of murine interleukin 12 (mIL12) in the intergenic sequence between US1 and US2 ORFs.

Electrochemical impedance spectroscopy (EIS) is an experimental technique ubiquitously used to study electrochemical systems. However, conventional EIS data interpretation through physical and equivalent circuit models is challenging because physical models are problem-specific, and equivalent circuits are often just lumped-element analogs lacking physical meaning. The distribution of relaxation times (DRT) has emerged as a complementary approach to resolve these issues. One drawback of conventional DRT deconvolution is that the EIS data is understood to be (only) a function of frequency (i.e. 1D data) and deconvolved accordingly. This work proposes a novel deconvolution method based on deep neural networks (DNNs), allowing the analysis of multidimensional EIS spectra to bridge data dependency on both frequencies and experimental conditions. Two particularly appealing traits of the deep-DRT method developed in this article are that neither regularization nor specific spacing on the state variables defining the experiment are required. Leveraging DNN to examine complex EIS spectra and their dependence on experimental conditions, this work opens a new research direction in the area of EIS analysis and DRT deconvolution.

Since the cloning of the herpes simplex virus (HSV) genome as BAC (bacterial artificial chromosome), the genetic engineering of the viral genome has become readily feasible. The advantage is that the modification of the animal virus genome is carried out in bacteria, with no replication or production of viral progeny, and is separated from the reconstitution or regeneration of the recombinant virus in mammalian cells. This allows an easy engineering of essential genes, as well. Many technologies have been developed for herpesvirus BAC engineering. In our hands the most powerful is galK recombineering that exploits a single marker (galK) for positive and negative selection and PCR amplicons for seamless modification in the desired genome locus. Here we describe the engineering of the HSV recombinant BAC 115 by the insertion of a heterologous cassette for the expression of murine interleukin 12 (mIL12) in the intergenic sequence between US1 and US2 ORFs.

In the previous chapter, we describe the engineering of a HSV-BAC genome by galK recombineering. Here we describe the procedures to reconstitute, or regenerate, the replicating recombinant virus, and the methods to purify it and characterize it for the correct expression of the transgene. We present the example of R-115, a recombinant expressing murine interleukin 12 (mIL12) from the US1-US2 intergenic region. A specific method for the production of highly purified virions by iodixanol gradient, suitable for in vivo applications, is also detailed.

The ability of pathogens to perceive environmental conditions and modulate gene expression accordingly is a crucial feature for bacterial survival. In this respect, the heat-shock response, a universal cellular response, allows cells to adapt to hostile environmental conditions and to survive during stress. In the major human pathogen Helicobacter pylori the expression of chaperone-encoding operons is under control of two auto-regulated transcriptional repressors, HrcA and HspR, with the latter acting as the master regulator of the regulatory circuit. To further characterize the HspR regulon in H. pylori, we used global transcriptome analysis (RNA-sequencing) in combination with Chromatin Immunoprecipitation coupled with deep sequencing (ChIP-sequencing) of HspR genomic binding sites. Intriguingly, these analyses showed that HspR is involved in the regulation of different crucial cellular functions through a limited number of genomic binding sites. Moreover, we further characterized HspR-DNA interactions through hydroxyl-radical footprinting assays. This analysis in combination with a nucleotide sequence alignment of HspR binding sites, revealed a peculiar pattern of DNA protection and highlighted sequence conservation with the HAIR motif (an HspR-associated inverted repeat of Streptomyces spp.). Site-directed mutagenesis demonstrated that the HAIR motif is fundamental for HspR binding and that additional nucleotide determinants flanking the HAIR motif are required for complete binding of HspR to its operator sequence spanning over 70 bp of DNA. This finding is compatible with a model in which possibly a dimer of HspR recognizes the HAIR motif overlapping its promoter for binding and in turn cooperatively recruits two additional dimers on both sides of the HAIR motif.

Effective regulation of primary carbon metabolism is critically important for bacteria to successfully adapt to different environments. We have identified an uncharacterised transcriptional regulator; RccR, that controls this process in response to carbon source availability. Disruption of rccR in the plant-associated microbe Pseudomonas fluorescens inhibits growth in defined media, and compromises its ability to colonise the wheat rhizosphere. Structurally, RccR is almost identical to the Entner-Doudoroff (ED) pathway regulator HexR, and both proteins are controlled by the same ED-intermediate; 2-keto-3-deoxy-6-phosphogluconate (KDPG). Despite these similarities, HexR and RccR control entirely different aspects of primary metabolism, with RccR regulating pyruvate metabolism (aceEF), the glyoxylate shunt (aceA, glcB, pntAA) and gluconeogenesis (pckA, gap). RccR displays complex and unusual regulatory behaviour; switching repression between the pyruvate metabolism and glyoxylate shunt/gluconeogenesis loci depending on the available carbon source. This regulatory complexity is enabled by two distinct pseudo-palindromic binding sites, differing only in the length of their linker regions, with KDPG binding increasing affinity for the 28 bp aceA binding site but decreasing affinity for the 15 bp aceE site. Thus, RccR is able to simultaneously suppress and activate gene expression in response to carbon source availability. Together, the RccR and HexR regulators enable the rapid coordination of multiple aspects of primary carbon metabolism, in response to levels of a single key intermediate., Author summary Here we show how Pseudomonas controls multiple different primary carbon metabolism pathways by sensing levels of KDPG, an Entner Doudoroff (ED) pathway intermediate. KDPG binds to two highly similar transcription factors; the ED regulator HexR and the previously uncharacterised protein RccR. RccR inversely controls the glyoxylate shunt, gluconeogenesis and pyruvate metabolism, suppressing the first two pathways as pyruvate metabolism genes are expressed, and vice versa. This complex regulation is enabled by two distinct RccR-binding consensus sequences in the RccR regulon promoters. KDPG binding simultaneously increases RccR affinity for the glyoxylate shunt and gluconeogenesis promoters, and releases repression of pyruvate metabolism. This elegant two-regulator circuit allows Pseudomonas to rapidly respond to carbon source availability by sensing a single key intermediate, KDPG.

Electrochemical impedance spectroscopy (EIS) is a technique widely used to characterize electrochemical systems. While EIS is powerful and simple to use, interpreting EIS experiments is not a straightforward task. Equivalent circuits are by far the most commonly used EIS models. However, these circuits models are not unique. To overcome this issue, the research community has shown increasing interest in distributional methods such as the distribution of relaxation times (DRT), and the recently developed distribution of diffusion times (DDT). The DDT method captures the diffusional timescales of electrode particles, and for this reason, is particularly well suited for the study of the EIS response of batteries and supercapacitors. One major assumption of the DDT method is that the electrodes of these devices are thin. This article generalizes the DDT to electrodes of finite thickness, and this analytical model is termed the non-linear distribution of diffusion times (NL-DDT). The NL-DDT is studied using synthetic data and applying it to actual experiments. The study shows that the NL-DDT can recover the diffusional characteristics as well as the physical properties of the electrodes, including the chemical diffusion coefficient and ionic conductivities.

Hydroxylamine-mediated syntheses of stereodefined acyclic polyfunctionalized δ-azido-nitriles and 5-substituted isoxazoles, bearing a differentially protected glycerol moiety, from 2-deoxysugars and glycals are described.