Engineered Antibody and Monobody Domains with T Cell Receptor-Like Selectivity for Tumor Associated Peptide-MHC Antigens

Monoclonal antibody (mAb)-based therapeutics have established themselves as meaningful components of the treatment paradigm for a variety of tumors. However, since the approval of rituximab in 1997 as the first mAb-based therapy for cancer, there has been a paucity of novel, validated cancer targets for therapeutic intervention by mAbs. In effect, numerous challenges lie in the discovery of suitable extracellular or transmembrane antigens that permit the differentiation of tumor from healthy tissue. The adaptive immune system, though, mediates recognition of foreign antigens derived from the intracellular proteome by T cell receptor (TCR) binding to peptide-loaded major histocompatibility complex (pMHC) molecules. Because cancer is associated with large-scale alterations in the genome, there are a vast number of novel epitopes presented to the adaptive immune system. Although natural TCRs have exquisite functionality in distinguishing these foreign epitopes, and several tumor-reactive TCRs have, in fact, been characterized, the molecules themselves are poorly developable as therapeutic candidates. Thus, in order to enable TCR-like binding of a broader class of protein agents, this study explores the transfer of TCR binding domains to other mAb-based scaffolds, including the fibronectin-derived Fn3 and the IgG-derived 4D5 scaffolds. By using a combination of rational design and directed evolution to guide binding domain transfer, evidence for TCR-like binding was demonstrated for several engineered molecules. In addition to conferring binding functionality, the grafted TCR domains had a deleterious effect on the biophysical properties of these inherently robust protein scaffolds. Thus, this work provides novel insight into the objective of developing mAb-based agents with TCR-like binding specificity for pMHC antigens, informing future efforts to target the abundance of intracellular tumor epitopes

Policy gradient learning methods for stochastic control with exit time and applications to share repurchase pricing

We develop policy gradients methods for stochastic control with exit time in a model-free setting. We propose two types of algorithms for learning either directly the optimal policy or by learning alternately the value function (critic) and the optimal control (actor). The use of randomized policies is crucial for overcoming notably the issue related to the exit time in the gradient computation. We demonstrate the effectiveness of our approach by implementing our numerical schemes in the application to the problem of share repurchase pricing. Our results show that the proposed policy gradient methods outperform PDE or other neural networks techniques in a model-based setting. Furthermore, our algorithms are flexible enough to incorporate realistic market conditions like e.g. price impact or transaction costs.Comment: 19 pages, 6 figure

Generative modeling for time series via Schr{\"o}dinger bridge

We propose a novel generative model for time series based on Schr{\"o}dinger bridge (SB) approach. This consists in the entropic interpolation via optimal transport between a reference probability measure on path space and a target measure consistent with the joint data distribution of the time series. The solution is characterized by a stochastic differential equation on finite horizon with a path-dependent drift function, hence respecting the temporal dynamics of the time series distribution. We can estimate the drift function from data samples either by kernel regression methods or with LSTM neural networks, and the simulation of the SB diffusion yields new synthetic data samples of the time series. The performance of our generative model is evaluated through a series of numerical experiments. First, we test with a toy autoregressive model, a GARCH Model, and the example of fractional Brownian motion, and measure the accuracy of our algorithm with marginal and temporal dependencies metrics. Next, we use our SB generated synthetic samples for the application to deep hedging on real-data sets. Finally, we illustrate the SB approach for generating sequence of images

Application of PCR-DGGE to the study of dynamics and biodiversity of microbial contaminants during the processing of Hibiscus sabdariffa drinks and concentrates

Introduction. Bissap (Hibiscus sabdariffa L.) is a common plant in the tropics. In Senegal, the calyces are used to make a popular juice. In the food industry, small and medium-sized enterprises (SMEs) are responsible for the transformation of bissap calyces into drinks, concentrates, jam, etc. In spite of the very low pH of the juice (pH < 3), problems of contamination and fermentation are often observed in the final products post-pasteurization. They are mainly due to Pseudomonas spp., E. coli, Klebsiella spp. and Pichia opuntiae. To solve this issue, monitoring of the microbial ecology was performed during the full process of bissap products. Methods and results. Fresh calyces and dried mixed calyces of the two varieties of Hibiscus sabdariffa ('Koor' and 'Vimto'), as well as juice samples, were collected at every stage of the processing of a bissap drink and syrup in a Senegalese SME. The monitoring of microbial flora was performed by using molecular fingerprinting. The molecular technique PCR-DGGE was employed to evaluate the microbial dynamics using bacterial 16S rDNA, yeast 26S rDNA and 28S rDNA mold profiles at each critical stage of the process. Results and discussion. The genetic profiles generated contributed to identifying the critical points in the manufacturing processes. A multivariate analysis based on the presence or absence of spots in the denaturing gradient electrophoresis gels (DGGE) showed that the microbial flora (bacteria, yeasts, molds) of bissap evolved during the following phases: harvest (fresh flower), drying (dried calyces) and processing (before filtration, after pasteurization and before packaging). Conclusion. Our work contributed to determining the microorganisms responsible for the microbial contamination of the final products, and highlighted the origin of these contaminants. The most important critical point was identified as the pasteurization step. (Résumé d'auteur

Discrimination des procédés de transformation post-récolte du Cacao et du Café par analyse globale de l’écologie microbienne

Cocoa and coffee are the most traded agricultural commodities in the world. They undergo many post-harvest transformations in producing countries (tropical) before being exported. Post-harvest processes differ from one country to another and from one production site to another. The technological transformation of cocoa on commercial beans and of coffee to green coffee requires a primary process handling. These practices play a crucial role in global and organoleptic quality of the products that will be processed. Our work hypothesis isthat different post-harvest processing applied to coffee and cocoa have an influence on the structure of microbial communities. The main objective was to measure this effect by performing a global analysis of microbial ecology using a molecular biology tool (PCR-DGGE, PCR amplification coupled to denaturing gradient gel electrophoresis). This technique allows variations in microbial communities to be detected and the main microbial species to be identified by sequencing.Our approach permitted to discriminate treatments, and the geographical origin of Cameroonian and Indonesian coffees. Notably, we showed that geographical origin and coffee species have a minor impact on the structure of the microbial communities when compared to the type of process used (wet or dry).By applying the approach to cocoa, we could link the global analysis of microbial ecology (PCR-DGGE) to the analysis of volatile compounds (SPME-GC-MS) to discriminate the different post-harvest treatments. Micro-fermentation were carried out with strains isolated from cocoa (L. fermentum, A. pasteurianus, P. kudriavzevii and P. mashurica) in order to identify the origin of the volatile compounds detected in the fermented cocoa. This study contributed to to show that fermentation combined with a short storage duration before fermentation is the best method to obtain cocoa beans with more desirable aromatic compounds. The statistical analysis was used to combine the results of the two types of analyzes (microbial ecology and aromatic compounds) and get relations between the detected microbial species and volatile compounds. The identified aromatic profiles prompted us to consider the use of the tested microbial strains as starter culture for cocoa fermentation.Le cacao et le café sont les produits agricoles les plus échangés dans le monde. Ils subissent de nombreuses transformations post-récolte au niveau des pays producteurs (tropicaux) avant d'être exportés. Les procédés de traitements post-récolte diffèrent d'un pays à l'autre voire d'un agriculteur à l'autre. La transformation technologique du cacao en fèves marchandes et des grains de café en café vert nécessite un processus primaire de manutention. Ces pratiques participent et influencent, en général, la qualité marchande et organoleptique des produits destinés à la transformation. Notre hypothèse de travail est que les différents procédés de transformation post-récolte appliqués sur le café et le cacao ont une influence sur la structure des communautés microbiennes. L'objectif principal était de pouvoir mesurer cet effet en réalisant l'analyse globale des communautés microbienne en utilisant un outil de biologie moléculaire, la PCR-DGGE (Amplification par PCR couplée à l'électrophorèse sur gel en gradient dénaturant). Cette technique a été associée au séquençage afin d'identifier les espèces microbiennes majoritaires. Cette étude a montré que les communautés microbiennes associées aux grains de café et aux fèves de cacao varient au cours des différentes étapes pour chaque type de traitement post-récolte appliqué.Notre approche a permis de discriminer les voies de traitements, et l'origine géographique du café Camerounais et Indonésien. Notamment, nous avons montré que l'origine géographique et l'espèce de café utilisée ont un impact sur l'écologie microbienne du café moins important par rapport à celui du procédé. L'application au cacao nous a permis de relier l'analyse globale de l'écologie microbienne (DGGE) à l'analyse des composés volatils (SPME-GC-MS) afin de discriminer les différents traitements post-récolte. Des micro-fermentations ont été réalisées avec des souches microbiennes isolées du cacao (L. fermentum, A. pasteurianus, P. kudriavzevii et P. mashurica) dans le but d‘identifier l'origine des composés volatils détectés sur le cacao fermenté. Notre étude a contribué à montrer que la fermentation combinée à une courte durée de stockage avant fermentation est le procédé qui permet d'obtenir des fèves contenant plus de composés aromatiques désirables sur le cacao. Une analyse statistique a permis de combiner les résultats des deux types d'analyses (écologie microbienne et composés aromatiques) et de créer des relations entre les espèces détectées et les composés volatils présents. Les profils aromatiques identifiés ont permis d'envisager l'utilisation des souches testées comme starters de culture pour la fermentation du cacao

Discrimination of post-harvest processing on microbial ecology of cacao and coffee

Le cacao et le café sont les produits agricoles les plus échangés dans le monde. Ils subissent de nombreuses transformations post-récolte au niveau des pays producteurs (tropicaux) avant d'être exportés. Les procédés de traitements post-récolte diffèrent d'un pays à l'autre voire d'un agriculteur à l'autre. La transformation technologique du cacao en fèves marchandes et des grains de café en café vert nécessite un processus primaire de manutention. Ces pratiques participent et influencent, en général, la qualité marchande et organoleptique des produits destinés à la transformation. Notre hypothèse de travail est que les différents procédés de transformation post-récolte appliqués sur le café et le cacao ont une influence sur la structure des communautés microbiennes. L'objectif principal était de pouvoir mesurer cet effet en réalisant l'analyse globale des communautés microbienne en utilisant un outil de biologie moléculaire, la PCR-DGGE (Amplification par PCR couplée à l'électrophorèse sur gel en gradient dénaturant). Cette technique a été associée au séquençage afin d'identifier les espèces microbiennes majoritaires. Cette étude a montré que les communautés microbiennes associées aux grains de café et aux fèves de cacao varient au cours des différentes étapes pour chaque type de traitement post-récolte appliqué.Notre approche a permis de discriminer les voies de traitements, et l'origine géographique du café Camerounais et Indonésien. Notamment, nous avons montré que l'origine géographique et l'espèce de café utilisée ont un impact sur l'écologie microbienne du café moins important par rapport à celui du procédé. L'application au cacao nous a permis de relier l'analyse globale de l'écologie microbienne (DGGE) à l'analyse des composés volatils (SPME-GC-MS) afin de discriminer les différents traitements post-récolte. Des micro-fermentations ont été réalisées avec des souches microbiennes isolées du cacao (L. fermentum, A. pasteurianus, P. kudriavzevii et P. mashurica) dans le but d‘identifier l'origine des composés volatils détectés sur le cacao fermenté. Notre étude a contribué à montrer que la fermentation combinée à une courte durée de stockage avant fermentation est le procédé qui permet d'obtenir des fèves contenant plus de composés aromatiques désirables sur le cacao. Une analyse statistique a permis de combiner les résultats des deux types d'analyses (écologie microbienne et composés aromatiques) et de créer des relations entre les espèces détectées et les composés volatils présents. Les profils aromatiques identifiés ont permis d'envisager l'utilisation des souches testées comme starters de culture pour la fermentation du cacao.Cocoa and coffee are the most traded agricultural commodities in the world. They undergo many post-harvest transformations in producing countries (tropical) before being exported. Post-harvest processes differ from one country to another and from one production site to another. The technological transformation of cocoa on commercial beans and of coffee to green coffee requires a primary process handling. These practices play a crucial role in global and organoleptic quality of the products that will be processed. Our work hypothesis isthat different post-harvest processing applied to coffee and cocoa have an influence on the structure of microbial communities. The main objective was to measure this effect by performing a global analysis of microbial ecology using a molecular biology tool (PCR-DGGE, PCR amplification coupled to denaturing gradient gel electrophoresis). This technique allows variations in microbial communities to be detected and the main microbial species to be identified by sequencing.Our approach permitted to discriminate treatments, and the geographical origin of Cameroonian and Indonesian coffees. Notably, we showed that geographical origin and coffee species have a minor impact on the structure of the microbial communities when compared to the type of process used (wet or dry).By applying the approach to cocoa, we could link the global analysis of microbial ecology (PCR-DGGE) to the analysis of volatile compounds (SPME-GC-MS) to discriminate the different post-harvest treatments. Micro-fermentation were carried out with strains isolated from cocoa (L. fermentum, A. pasteurianus, P. kudriavzevii and P. mashurica) in order to identify the origin of the volatile compounds detected in the fermented cocoa. This study contributed to to show that fermentation combined with a short storage duration before fermentation is the best method to obtain cocoa beans with more desirable aromatic compounds. The statistical analysis was used to combine the results of the two types of analyzes (microbial ecology and aromatic compounds) and get relations between the detected microbial species and volatile compounds. The identified aromatic profiles prompted us to consider the use of the tested microbial strains as starter culture for cocoa fermentation

A novel fault location approach for radial power distribution systems

Power distribution systems (PDS) are increasingly complex and spread over long distances and in different locations. Given their radial configuration, the loads could be inserted at the same distances from the substation. This leads to multiple estimation of fault location (FL) and yields time consuming for iterative FL algorithms. In this article, we provide a novel practical approach to fault localization in order to defeat these limitations. The central idea of the proposed approach is to divide the multilateral distribution system into a possible number of mono-lateral sub systems (MLS) using a proposed communicating sensor. Next, we apply two different fault locator algorithms only to the defective MLS. The first variant of the approach is based on the impedance method, while the second variant is non-parametric used only when there is lack in the line data. To test the proposed technique in practice, we used the IEEE 13 Node test feeder, and a real Algerian PDS. The results obtained clearly show the contribution of the dedicated method for locating faults in the PDS

Preliminary PCR-TTGE analyses of bacterial communities associated with pollen from anemophilous trees: potential impacts on plants and human health

International audiencePollen from wind-pollinated plants is the predominant cause of pollinosis which corresponds mainly to allergic rhinitis and conjunctivitis. Bacterial communities associated to leaves and roots surface were analysed for many years with both culture-dependent and independent methods. However, microbiota of pollen grains was rarely investigated and never with a molecular fingerprint technique. The aim of this study was to perform a preliminary analysis of the pollen microbiota by applying PCR-TTGE method. Pollen samples were collected from various anemophilous trees genera (Cephalotaxus, Cupressus, Pinus, Platanus and Quercus) in Montpellier (France) in 2013. Thorough pollen preparation was essential to a successful recovery of DNA from pollen. Regarding the results, pollen microbiota was tree genus-dependent. In addition, intra-tree genus variations were also observed. The Gammaproteobacteria class was the most represented in pollen samples whatever the tree genus. Among this class, some bacteria were recognized as phytopathogens (Pseudomonas, Erwinia) but also opportunistic human pathogens (Pseudomonas, some enterobacteria). PCR-TTGE is a suitable tool to analyse the microbiota associated with pollen responsible for phytopathogenicity or affecting the human respiratory tract