Time-dependent sorption behavior of lentiviral vectors during anion-exchange chromatography

Use of lentiviral vectors (LVs) in clinical Cell and Gene Therapy applications is growing. However, functional product loss during capture chromatography, typically anion-exchange (AIEX), remains a significant unresolved challenge for the design of economic processes. Despite AIEX's extensive use, variable performance and generally low recovery is reported. This poor understanding of product loss mechanisms highlights a significant gap in our knowledge of LV adsorption and other types of vector delivery systems. This work demonstrates HIV-1-LV recovery over quaternary-amine membrane adsorbents is a function of time in the adsorbed state. Kinetic data for product loss in the column bound state was generated. Fitting a second order-like rate model, we observed a rapid drop in functional recovery due to increased irreversible binding for vectors encoding two separate transgenes ( t Y 1 / 2 ${t}_{{Y}_{1/2}}$  = 12.7 and 18.7 min). Upon gradient elution, a two-peak elution profile implicating the presence of two distinct binding subpopulations is observed. Characterizing the loss kinetics of these two subpopulations showed a higher rate of vector loss in the weaker binding peak. This work highlights time spent in the adsorbed state as a critical factor impacting LV product loss and the need for consideration in LV AIEX process development workflows

IL-11 Induces NLRP3 Inflammasome Activation in Monocytes and Inflammatory Cell Migration to the Central Nervous System

The objective of this study is to examine IL-11-induced mechanisms of inflammatory cell migration to the central nervous system (CNS). We report that IL-11 is produced at highest frequency by myeloid cells among the peripheral blood mononuclear cell (PBMC) subsets. Patients with relapsing-remitting multiple sclerosis (RRMS) have an increased frequency of IL-11+ monocytes, IL-11+ and IL-11R+ CD4+ lymphocytes, and IL-11R+ neutrophils in comparison to matched healthy controls. IL-11+ and granulocyte-macrophage colony-stimulating factor (GM-CSF)+ monocytes, CD4+ lymphocytes, and neutrophils accumulate in the cerebrospinal fluid (CSF). The effect of IL-11 in-vitro stimulation, examined using single-cell RNA sequencing, revealed the highest number of differentially expressed genes in classical monocytes, including up-regulated NFKB1, NLRP3, and IL1B. All CD4+ cell subsets had increased expression of S100A8/9 alarmin genes involved in NLRP3 inflammasome activation. In IL-11R+-sorted cells from the CSF, classical and intermediate monocytes significantly up-regulated the expression of multiple NLRP3 inflammasome-related genes, including complement, IL18, and migratory genes (VEGFA/B) in comparison to blood-derived cells. Therapeutic targeting of this pathway with αIL-11 mAb in mice with RR experimental autoimmune encephalomyelitis (EAE) decreased clinical scores, CNS inflammatory infiltrates, and demyelination. αIL-11 mAb treatment decreased the numbers of NFκBp65+, NLRP3+, and IL-1β+ monocytes in the CNS of mice with EAE. The results suggest that IL-11/IL-11R signaling in monocytes represents a therapeutic target in RRMS

Comparative Genomics and Transcriptomics of Propionibacterium acnes

The anaerobic Gram-positive bacterium Propionibacterium acnes is a human skin commensal that is occasionally associated with inflammatory diseases. Recent work has indicated that evolutionary distinct lineages of P. acnes play etiologic roles in disease while others are associated with maintenance of skin homeostasis. To shed light on the molecular basis for differential strain properties, we carried out genomic and transcriptomic analysis of distinct P. acnes strains. We sequenced the genome of the P. acnes strain 266, a type I-1a strain. Comparative genome analysis of strain 266 and four other P. acnes strains revealed that overall genome plasticity is relatively low; however, a number of island-like genomic regions, encoding a variety of putative virulence-associated and fitness traits differ between phylotypes, as judged from PCR analysis of a collection of P. acnes strains. Comparative transcriptome analysis of strains KPA171202 (type I-2) and 266 during exponential growth revealed inter-strain differences in gene expression of transport systems and metabolic pathways. In addition, transcript levels of genes encoding possible virulence factors such as dermatan-sulphate adhesin, polyunsaturated fatty acid isomerase, iron acquisition protein HtaA and lipase GehA were upregulated in strain 266. We investigated differential gene expression during exponential and stationary growth phases. Genes encoding components of the energy-conserving respiratory chain as well as secreted and virulence-associated factors were transcribed during the exponential phase, while the stationary growth phase was characterized by upregulation of genes involved in stress responses and amino acid metabolism. Our data highlight the genomic basis for strain diversity and identify, for the first time, the actively transcribed part of the genome, underlining the important role growth status plays in the inflammation-inducing activity of P. acnes. We argue that the disease-causing potential of different P. acnes strains is not only determined by the phylotype-specific genome content but also by variable gene expression

Densidade, tamanho e distribuição estomática em 35 espécies de árvores na Amazônia Central

Stomata are turgor-operated valves that control water loss and CO2 uptake during photosynthesis, and thereby water relation and plant biomass accumulation is closely related to stomatal functioning. The aims of this work were to document how stomata are distributed on the leaf surface and to determine if there is any significant variation in stomatal characteristics among Amazonian tree species, and finally to study the relationship between stomatal density (S D) and tree height. Thirty five trees (>17 m tall) of different species were selected. Stomatal type, density (S D), size (S S) and stomatal distribution on the leaf surface were determined using nail polish imprints taken from both leaf surfaces. Irrespective of tree species, stomata were located only on the abaxial surface (hypostomaty), with large variation in both S D and S S among species. S D ranged from 110 mm-2 in Neea altissima to 846 mm-2 in Qualea acuminata. However, in most species S D ranges between 271 and 543 mm-2, with a negative relationship between S D and S S. We also found a positive relationship between S D and tree height (r² = 0.14, p 17 m de altura) de diferentes espécies foram selecionadas. Tipo de complexo estomático, S D, tamanho (S S) e distribuição na superfície foliar foram determinados utilizando impressões de ambas as superfícies foliares com esmalte incolor. Independente da espécie, os estômatos foram encontrados apenas na superfície abaxial (hipoestomatia) com ampla variação na S D e no S S entre espécies. A densidade estomática variou de 110 mm-2 em Neea altissima a 846 mm-2 em Qualea acuminata. Entretanto, a maioria das espécies apresentou S D entre 271 e 543 mm-2, com uma relação negativa entre S D e S S. Observou-se uma relação positiva entre S D e altura arbórea (r² = 0.14, p < 0.01), não havendo relação entre S D e espessura foliar. Os tipos estomáticos mais comuns foram: anomocíticos (37%), seguidos de paracíticos (26%) e anisocíticos (11%). Concluiu-se que em espécies da Amazônia, a distribuição de estômatos na superfície foliar está mais relacionada a fatores genéticos de cada espécie do que a variações ambientais. Entretanto, S D é fortemente influenciada por fatores ambientais concernentes à altura da árvore

The Factors Involved in the Location of Plants for the Production of Armaments

Abstract not availabl

Ensemble learning for independent component analysis

This thesis is concerned with the problem of Blind Source Separation. Specifically we considerthe Independent Component Analysis (ICA) model in which a set of observations are modelled by xt = Ast: (1) where A is an unknown mixing matrix and st is a vector of hidden source components attime t. The ICA problem is to find the sources given only a set of observations. In chapter 1, the blind source separation problem is introduced. In chapter 2 the methodof Ensemble Learning is explained. Chapter 3 applies Ensemble Learning to the ICA model and chapter 4 assesses the use of Ensemble Learning for model selection.Chapters 5-7 apply the Ensemble Learning ICA algorithm to data sets from physics (a medical imaging data set consisting of images of a tooth), biology (data sets from cDNAmicro-arrays) and astrophysics (Planck image separation and galaxy spectra separation)

Ensemble Learning

Introduction When we say we are making a model of a system, we are setting up a tool which can be used to make inferences, predictions and decisions. Each model can be seen as a hypothesis, or explanation, which makes assertions about the quantities which are directly observable and which can only be inferred from their eect on observable quantities. In the Bayesian framework, knowledge is contained in the conditional probability distributions of the models. We can use Bayes&apos; theorem to evaluate the conditional probability distributions for the unknown parameters, y, given the set of observed quantities, x, using p (y jx ) = p (x jy ) p (y) p (x) (1) The prior distribution p (y) contains our knowledge of the unknown variables before we make any obser