Reply to a Review

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Análises de alguns objectos pré-históricos de ouro, procedentes do Norte de Portugal.

81 (1-2) Jan.-Jun. 1971, p. 129-138

Detection of Tropheryma whippelii DNA in a patient with AIDS

A case of an AIDS patient infected with the Whipple's disease bacterium, Tropheryma whippelii, is reported. A DNA fragment with sequence specificity for the 16S rRNA gene of the bacterium was detected by PCR in a duodenal biopsy specimen from a 55-year-old male patient with AIDS and diarrhea. The biopsy specimen contained periodic acid-Schiff stain-positive macrophages which did not, however, resemble the sickleform-particle-containing cells characteristic of Whipple's disease. This observation raises two possibilities: either the patient had a coincidence of AIDS and Whipple's disease or Tropheryma whippelii acted as an opportunistic pathogen in this immunodeficient patient. The latter explanation is of interest in light of the ongoing discussion of immunologic abnormalities as predisposing factors for Whipple's disease

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning

Reinforcement learning is a growing field in AI with a lot of potential. Intelligent behavior is learned automatically through trial and error in interaction with the environment. However, this learning process is often costly. Using variational quantum circuits as function approximators can reduce this cost. In order to implement this, we propose the quantum natural policy gradient (QNPG) algorithm -- a second-order gradient-based routine that takes advantage of an efficient approximation of the quantum Fisher information matrix. We experimentally demonstrate that QNPG outperforms first-order based training on Contextual Bandits environments regarding convergence speed and stability and thereby reduces the sample complexity. Furthermore, we provide evidence for the practical feasibility of our approach by training on a 12-qubit hardware device.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. 7 pages, 5 figures, 1 tabl

Quantum Policy Gradient Algorithm with Optimized Action Decoding

Quantum machine learning implemented by variational quantum circuits (VQCs) is considered a promising concept for the noisy intermediate-scale quantum computing era. Focusing on applications in quantum reinforcement learning, we propose a specific action decoding procedure for a quantum policy gradient approach. We introduce a novel quality measure that enables us to optimize the classical post-processing required for action selection, inspired by local and global quantum measurements. The resulting algorithm demonstrates a significant performance improvement in several benchmark environments. With this technique, we successfully execute a full training routine on a 5-qubit hardware device. Our method introduces only negligible classical overhead and has the potential to improve VQC-based algorithms beyond the field of quantum reinforcement learning.Comment: Accepted to the 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii, USA. 22 pages, 10 figures, 3 table

Impact of the gut microbiota on rodent models of human disease

Traditionally bacteria have been considered as either pathogens, commensals or symbionts. The mammal gut harbors 10(14) organisms dispersed on approximately 1000 different species. Today, diagnostics, in contrast to previous cultivation techniques, allow the identification of close to 100% of bacterial species. This has revealed that a range of animal models within different research areas, such as diabetes, obesity, cancer, allergy, behavior and colitis, are affected by their gut microbiota. Correlation studies may for some diseases show correlation between gut microbiota composition and disease parameters higher than 70%. Some disease phenotypes may be transferred when recolonizing germ free mice. The mechanistic aspects are not clear, but some examples on how gut bacteria stimulate receptors, metabolism, and immune responses are discussed. A more deeper understanding of the impact of microbiota has its origin in the overall composition of the microbiota and in some newly recognized species, such as Akkermansia muciniphila, Segmented filamentous bacteria and Faecalibacterium prausnitzii, which seem to have an impact on more or less severe disease in specific models. Thus, the impact of the microbiota on animal models is of a magnitude that cannot be ignored in future research. Therefore, either models with specific microbiota must be developed, or the microbiota must be characterized in individual studies and incorporated into data evaluation

Beyond genetics. Influence of dietary factors and gut microbiota on type 1 diabetes

AbstractType 1 diabetes (T1D) is an autoimmune disease ultimately leading to destruction of insulin secreting β-cells in the pancreas. Genetic susceptibility plays an important role in T1D etiology, but even mono-zygotic twins only have a concordance rate of around 50%, underlining that other factors than purely genetic are involved in disease development. Here we review the influence of dietary and environmental factors on T1D development in humans as well as animal models. Even though data are still inconclusive, there are strong indications that gut microbiota dysbiosis plays an important role in T1D development and evidence from animal models suggests that gut microbiota manipulation might prove valuable in future prevention of T1D in genetically susceptible individuals

Sensitivity to oxazolone induced dermatitis is transferable with gut microbiota in mice

Atopic Dermatitis (AD) has been associated with gut microbiota (GM) dysbiosis in humans, indicating a causative role of GM in AD etiology. Furthermore, the GM strongly correlates to essential disease parameters in the well-known oxazolone-induced mouse model of AD. Here, we demonstrate that it is possible to transfer both a high-responding and a low-responding AD phenotype with GM from conventional mice to germ-free mice. The mice inoculated with the high-responding GM had significantly higher clinical score, increased ear thickness, and increased levels of IL-1β, TNFα, IL-4, IL-5, and IL-6 compared to the mice inoculated with the low-responding GM. The inter-individual variation was in general not affected by this increase in effect size. Germ-free mice induced with AD revealed a high disease response as well as high inter-individual variation indicating protective properties of certain microbial taxa in this model. This study underlines that the GM has a strong impact on AD in mouse models, and that the power of studies may be increased by the application of mice inoculated with a specific GM from high responders to increase the effect size