Change-Point Detection based on Weighted Two-Sample U-Statistics

We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in the case of short-range dependent data. Under some mild mixing conditions, we establish convergence of the test statistic to an extreme value distribution. A simulation study shows that the weighted tests are superior to the non-weighted versions when the change-point occurs near the boundary of the time interval, while they loose power in the center

High-throughput screening of soybean di-nitrogen fixation and seed nitrogen content using spectral sensing

Symbiotic di-nitrogen fixation of grain legumes has a substantial impact on crop performance, harvest product quality, and nitrogen (N) balance of crop rotations, particularly under organic management regimes. In soybean breeding, selection for increased nitrogen fixation is desirable for improving seed protein content and N balance of cropping systems. However, the lack of high-throughput screening methods for direct measurement of N2 fixation rates prohibits practical breeding efforts. Therefore, hyperspectral canopy reflectance measurement as a field-based phenotyping method was evaluated in three environments for indirect estimation of N fixation and uptake of soil nitrogen in a set of early maturity soybean genotypes exhibiting a wide range in seed protein content. Reflectance spectra were collected in repeated measurements during flowering and early seed filling stages. Subsequently, various spectral reflectance indices (SRIs) were calculated for characterizing nitrogen accumulation of individual genotypes. Moreover, prediction models for seed protein content as an end-of-season target trait were developed utilizing full spectral information in partial-least-square regression (PLSR) models. A number of N-related SRIs calculated from spectral reflectance data recorded at the beginning of the seed filling stage were significantly correlated to seed protein content. The best prediction of seed protein content, however, was achieved in PLSR models (validation R2 = 0.805 across all three environments). Environments lower in initial soil mineral N content appeared as more favorable selection sites in terms of prediction accuracy, because N fixation is not masked by soil N uptake in such environments. Hyperspectral reflectance data proved to be a valuable method for determining genetic variation in crop N accumulation, which might be implemented in highthroughput screening protocols for N fixation in plant breeding programs

Marker-assisted selection for soybean organic breeding

Marker-assisted selection (MAS) is a valuable tool in crop breeding, including organic breeding. The application of molecular markers allows rapid screening at early developmental stages as well as more accurate and efficient identification and selection of plants with desired traits. Besides accelerating breeding, this approach reduces the need for extensive field trials and multiple generations of selection. Considering that organic breeding emphasizes sustainable practices and minimal environmental impact, MAS can reduce the need for excessive land, water, and resources typically required for conventional breeding. In addition, it can help breeders to develop organic-compliant varieties by targeting specific traits and preserving organic standards, providing more efficient and sustainable strategies for organic production systems. Molecular markers were used to screen ECOBREED soybean germplasm harbouring traits relevant to organic farming, such as cadmium accumulation, supernodulation and disease tolerance to Sclerotinia sclerotiorum and Diaporthe complex. Genotypes with low cadmium accumulation should be used in organic food production to improve food safety, while supernodulation in soybean could be an important trait showing potential for increased nitrogen fixation. Molecular screening of genotypes for disease resistance is especially important in organic farming where chemical interventions are limited, offering an efficient and sustainable strategy for organic production

Algebraic integrability of confluent Neumann system

In this paper we study the Neumann system, which describes the harmonic oscillator (of arbitrary dimension) constrained to the sphere. In particular we will consider the confluent case where two eigenvalues of the potential coincide, which implies that the system has S^{1} symmetry. We will prove complete algebraic integrability of confluent Neumann system and show that its flow can be linearized on the generalized Jacobian torus of some singular algebraic curve. The symplectic reduction of S^{1} action will be described and we will show that the general Rosochatius system is a symplectic quotient of the confluent Neumann system, where all the eigenvalues of the potential are double. This will give a new mechanical interpretation of the Rosochatius system.Comment: 17 pages, 1 figur

Li+ distribution into V2O5 films resulting from electrochemical intercalation reactions

We studied interface effects of thin film V2O5 electrodes on top of indium tin oxide (ITO) glass for Li intercalation by means of a combination of methods: depth-profiling by secondary ion mass spectroscopy (SIMS), electrochemical insertion-extraction of lithium ions by slow-scan cyclic voltammetry (SSCV) and by potentiostatic intermittent titration technique (PITT). We show that the Li+ distribution inside the oxide film is always far from homogeneous, and that different diffusion paths (parallel to interfaces as well as perpendicular to them) have to be considered in experiments with electrodes having areas of few cm². The exposed edge formed when cutting out coupons from the coated glass plate supporting the V2O5 electrode plays a significant role in the process, because it exposes the V2O5-ITO interface to the electrolyte.Estudamos os efeitos de interface de filmes finos de eletrodos de V2O5 sobre vidros com óxido de índio-estanho (ITO) para intercalação de Li utilizando combinações de métodos: perfil de profundidade por espectrometria de massas de íons secundários (SIMS), inserção-extração eletroquímica de íons lítio por voltametria cíclica de varredura lenta (SSCV) e por técnica de titulação potenciostática intermitente (PITT). Nós demonstramos que a distribuição de Li+ no interior do filme de óxido é sempre distante de ser considerada homogênea e que diferentes etapas de difusão (paralelas às interfaces e bem como perpendiculares a elas) são consideradas por conter áreas de alguns cm² em experimentos com eletrodos. A margem exposta pelo corte da placa de vidro revestida com ITO e recoberta com V2O5 desempenha um papel importante no processo, pelo fato de expor a interface V2O5-ITO ao eletrólito.66767

Increased S-nitrosylation and proteasomal degradation of caspase-3 during infection contribute to the persistence of adherent invasive escherichia coli (AIEC) in immune cells

Adherent invasive Escherichia coli (AIEC) have been implicated as a causative agent of Crohn's disease (CD) due to their isolation from the intestines of CD sufferers and their ability to persist in macrophages inducing granulomas. The rapid intracellular multiplication of AIEC sets it apart from other enteric pathogens such as Salmonella Typhimurium which after limited replication induce programmed cell death (PCD). Understanding the response of infected cells to the increased AIEC bacterial load and associated metabolic stress may offer insights into AIEC pathogenesis and its association with CD. Here we show that AIEC persistence within macrophages and dendritic cells is facilitated by increased proteasomal degradation of caspase-3. In addition S-nitrosylation of pro- and active forms of caspase-3, which can inhibit the enzymes activity, is increased in AIEC infected macrophages. This S-nitrosylated caspase-3 was seen to accumulate upon inhibition of the proteasome indicating an additional role for S-nitrosylation in inducing caspase-3 degradation in a manner independent of ubiquitination. In addition to the autophagic genetic defects that are linked to CD, this delay in apoptosis mediated in AIEC infected cells through increased degradation of caspase-3, may be an essential factor in its prolonged persistence in CD patients

Predicting Outcomes of Prostate Cancer Immunotherapy by Personalized Mathematical Models

Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2) = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols

Understanding the benefit of metformin use in cancer treatment

Biguanides have been developed for the treatment of hyperglycemia and type 2 diabetes. Recently, metformin, the most widely prescribed biguanide, has emerged as a potential anticancer agent. Epidemiological, preclinical and clinical evidence supports the use of metformin as a cancer therapeutic. The ability of metformin to lower circulating insulin may be particularly important for the treatment of cancers known to be associated with hyperinsulinemia, such as those of the breast and colon. Moreover, metformin may exhibit direct inhibitory effects on cancer cells by inhibiting mammalian target of rapamycin (mTOR) signaling and protein synthesis. The evidence supporting a role for metformin in cancer therapy and its potential molecular mechanisms of action are discussed