Drug Discovery in Soil Bacteria from Unique Ecosystems of India and Indonesia

Natural products isolated from bacteria can be developed into new therapeutic agents. The soil bacteria actinomycetes, specifically the Streptomyces species, are prolific producers of antibiotics. This thesis is composed of two projects which focus on novel drug discovery from soil bacteria collected from the Indonesian Black Water Ecosystem (the ICBB strains) and soil bacteria from the abandoned Hundung Cement Factory in India (the MBRL 201 and 251 strains). The ICBB strains were cultured in Yeast Peptone Glucose Malt Extract and Modified Bennet media and the MBRL strains were cultured in Yeast Malt Extract Glucose medium. Following a week of cultivation, the culture broths were centrifuged. The supernatant was extracted sequentially with EtOAc and BuOH. The remaining aqueous solution after the extraction process was lyophilized and prepared for biological activity testing. The mycelia of the MBRL strains were also subjected to further extraction using a mixture of MeOH and acetone. Biological assays were carried out against several microbial and fungal organisms. Active extracts from the ICBB strains were noted, but due to time constraints no follow-up experiments were carried out. On the other hand, the active extracts from the MBRL strains were extensively investigated using bioassay-guided isolation and purification. On the basis of the sequence of their 16S rRNA genes, MBRL 201 and 251 strains were identified to be Streptomyces sp. and Pseudomonas sp., respectively. Active extracts from these strains were subjected to bioassay-guided fractionations. The MBRL 251 BuOH extract and the MBRL 201 EtOAc extract were investigated most extensively because the TLC and bioassay results indicated the presence of bioactive natural products in these extracts. The MBRL 251 BuOH extract was fractionated and purified with a series of open column chromatography. The active compound was analyzed using mass spectrometry, ¹H and ¹³C Nuclear Magnetic Resonance (NMR) spectroscopy. In addition, ANTIBASE®, a searchable database that contains descriptive, physico-chemical and spectroscopic data, was used to quickly identify known compounds. The results revealed that the bioactive compound in MBRL 251 is phenazine-1- carboxylic acid. The MBRL 201 extract was fractionated with preparative thin layer chromatography and purified with size exclusion chromatography. However, at this time, further experiments are necessary to determine the chemical structure of the active MBRL 201 compound

Trade-off between Losses and EMI Issues in Three-Phase SiC Inverters for More Electrical Aircrafts

Power converters will only be effectively used in future aircrafts if they are compact, efficient and reliable. All these aspects can be improved by the use of disruptive technology such as the so-called Wide Bandgap (WBG) semiconductors made of Silicon Carbide (SiC) or Gallium Nitride (GaN). These components can switch much faster than their silicon counterpart, which can reduce converter losses and also decrease differential mode filter given the increase of switching frequency. However, such a fast commutation increases Electromagnetic Interference (EMI) issues in the converter and load connected to it. This paper shows the approach developed at the French Institute of Technology (IRT) Saint-Exupery, in order to evaluate the trade-offs between losses and EMI issues of three-phase inverters used in future aircraft applications. Given the high voltage DC bus of 540V, SiC MOSFETs are investigated and experimental results show the impact of these components on losses and EMI for different parameters

General sensitivity analysis in data assimilation

International audienceThe problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to nd the initial condition function (analysis). The operator of the model, and hence the optimal solution, depend on the parameters which may contain uncertainties. A response function is considered as a functional of the solution after assimilation. Based on the second-order adjoint techniques, the sensitivity of the response function to the parameters of the model is studied. The gradient of the response function is related to the solution of a non-standard problem involving the coupled system of direct and adjoint equations. The solvability of the non-standard problem is studied. Numerical algorithms for solving the problem are developed. The results are applied for the 2D hydraulic and pollution models. Numerical examples on computation of the gradient of the response function are presented

Efficient regret bounds for online bid optimisation in budget-limited sponsored search auctions

We study the problem of an advertising agent who needs to intelligently distribute her budget across a sequence of online keyword bidding auctions. We assume the closing price of each auction is governed by the same unknown distribution, and study the problem of making provably optimal bidding decisions. Learning the distribution is done under censored observations, i.e. the closing price of an auction is revealed only if the bid we place is above it. We consider three algorithms, namely ε—First, Greedy Product-Limit (GPL) and LuekerLearn, respectively, and we show that these algorithms provably achieve Hannan-consistency. In particular, we show that the regret bound of ε—First is at most O(T⅔) with high probability. For the other two algorithms, we first prove that, by using a censored data distribution estimator proposed by Zeng [19], the empirical distribution of the closing market price converges in probability to its true distribution with a O(1/√t) rate, where t is the number of updates. Based on this result, we prove that both GPL and LuekerLearn achieve O(√T) regret bound with high probability. This in fact provides an affirmative answer to the research question raised in [1]. We also evaluate the abovementioned algorithms using real bidding data, and show that although GPL achieves the best performance on average (up to 90% of the optimal solution), its long running time may limit its suitability in practice. By contrast, LuekerLearn and ε— First proposed in this paper achieve up to 85% of the optimal, but with an exponential reduction in computational complexity (a saving up to 95%, compared to GPL)

Regional Cerebral Blood Flow Patterns in Children vs. Adults with ADHD Combined and Inattentive Types: A SPECT Study

Objective: The current study sought to determine whether ADHD Combined Type (ADHD-C) and ADHD Primarily Inattentive Type (ADHD-PI) showed differential regional cerebral blood flow (rCBF) patterns in children vs. adults. Participants and Methods: The overall sample (N=1484) was effectively split into four groups: adults with ADHD-PI (n=519), adults with ADHD-C (n=405), children with ADHD-PI (n=192), children with ADHD-C (n=368). All participants were void of bipolar, schizophrenia, autism, neurocognitive disorders, and TBI. The data were collected from a de-identified archival database of individuals who underwent SPECT scans at rest. Results: Using αConclusions: Overall, the current study suggested that children may show rCBF differences between different ADHD subtypes, but adults may not. The current study did not find significance in any of the 17 brain regions examined when comparing adults with ADHD-C to adults with ADHD-PI. All significant findings were attributed to the children with ADHD-C group showing aberrant blood flow rate than at least one other group. Previous research has supported that the differentiation of these subtypes as distinctive disorders is difficult to make in adults (Sobanski et al., 2006). Other research has indicated the potential of imaging techniques to differentiate the two in children (Al-Amin, Zinchenko, & Geyer, 2018). The current findings support nuanced ways in which rCBF patterns of ADHD-C and ADHD-PI differ between children and adults