161 research outputs found

    Beneficial insects and control of crop pests

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    The pollinators of Echinacea angustifolia in Saskatchewan

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    Non-Peer ReviewedEchinacea (Asteraceae) is grown as a nutraceutical crop and is one of the best selling medicinal plants on the North American market today, accounting for over 300 million dollars annually in sales. Echinacea angustifolia accounts for the majority of Echinacea produced in Saskatchewan and is native to the southern regions of the Canadian Prairies. Echinacea must be cross-pollinated to set seed, as is typical of members of the Asteraceae, and only insects can effect cross-pollination. An in-depth knowledge of Echinacea’s pollination system is essential to developing Echinacea as a sustainable market crop. E. angustifolia’s native pollinators are being identified and their pollination efficiencies assessed by pollen-tube quantification after visiting previously unvisited inflorescences. Interestingly, the recent abundance of grasshoppers in Saskatchewan has supported large populations of potential pollinators of E. angustifolia. For instance, the grasshopper bee fly (Systoechus vulgaris) and the golden blister beetle (Epicauta ferruginea) were particularly abundant on E. angustifolia inflorescences in the summer of 2003 and their contributions to pollination are being assessed. Alfalfa leafcutting bees (Megachile rotundata) managed in Saskatchewan as pollinators of alfalfa (Medicago sativum) have the potential to be excellent managed pollinators of Echinacea; this project will evaluate their pollination efficiency

    Adult Height, Insulin Levels and 17β-Estradiol in Young Women

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    Background: Adult height and insulin levels have independently been associated with breast cancer risk. However, little is known about whether these factors influence estradiol levels. Thus, we hypothesize that adult height in combination with insulin levels may influence premenopausal 17β-estradiol throughout the entire menstrual cycle of possible importance of breast cancer risk. Methods: Among 204 healthy women, aged 25-35 years who participated in the Norwegian EBBA I study, birth weight and age at menarche were assessed by questionnaire, personal health record and interview. 17β-estradiol concentrations were estimated by daily saliva samples throughout one entire menstrual cycle using radioimmunoassay (RIA). Measures of height (cm) were taken as well as waist circumference (cm), body mass index (BMI kg/m2) and total fat percentage (DEXA % fat). Fasting blood samples were drawn, and serum concentrations of insulin were determined. Results: The women reported a mean height of 166.5 cm, birth weight of 3389 g and age at menarche 13.1 years. Mean BMI was 24.4 kg/m2, mean waist circumference 79.5 cm and mean total fat percentage 34.1%. Women with an adult height of more than 170 cm and insulin levels higher than 90 pmol/L experienced on average an 37.2 % increase in 17β- estradiol during an entire menstrual cycle compared to those with the same height, and insulin levels below 90 pmol/L. Moreover, this was also observed throughout the entire menstrual cycle. Conclusion: Our findings support that premenopausal levels of 17β-estradiol vary in response to adult height and insulin levels, suggesting that women who become taller are put at risk for higher estradiol levels when their insulin levels rise of possible importance for breast cancer risk.Anthropolog

    Polymorphisms in the estrogen receptor alpha gene (ESR1), daily cycling estrogen and mammographic density phenotypes

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    Background Single nucleotide polymorphisms (SNPs) involved in the estrogen pathway and SNPs in the estrogen receptor alpha gene (ESR1 6q25) have been linked to breast cancer development, and mammographic density is an established breast cancer risk factor. Whether there is an association between daily estradiol levels, SNPs in ESR1 and premenopausal mammographic density phenotypes is unknown. Methods We assessed estradiol in daily saliva samples throughout an entire menstrual cycle in 202 healthy premenopausal women in the Norwegian Energy Balance and Breast Cancer Aspects I study. DNA was genotyped using the Illumina Golden Gate platform. Mammograms were taken between days 7 and 12 of the menstrual cycle, and digitized mammographic density was assessed using a computer-assisted method (Madena). Multivariable regression models were used to study the association between SNPs in ESR1, premenopausal mammographic density phenotypes and daily cycling estradiol. Results We observed inverse linear associations between the minor alleles of eight measured SNPs (rs3020364, rs2474148, rs12154178, rs2347867, rs6927072, rs2982712, rs3020407, rs9322335) and percent mammographic density (p-values: 0.002–0.026), these associations were strongest in lean women (BMI, ≤23.6 kg/m2.). The odds of above-median percent mammographic density (>28.5 %) among women with major homozygous genotypes were 3–6 times higher than those of women with minor homozygous genotypes in seven SNPs. Women with rs3020364 major homozygous genotype had an OR of 6.46 for above-median percent mammographic density (OR: 6.46; 95 % Confidence Interval 1.61, 25.94) when compared to women with the minor homozygous genotype. These associations were not observed in relation to absolute mammographic density. No associations between SNPs and daily cycling estradiol were observed. However, we suggest, based on results of borderline significance (p values: 0.025–0.079) that the level of 17β-estradiol for women with the minor genotype for rs3020364, rs24744148 and rs2982712 were lower throughout the cycle in women with low (28.5 %) percent mammographic density, when compared to women with the major genotype. Conclusion Our results support an association between eight selected SNPs in the ESR1 gene and percent mammographic density. The results need to be confirmed in larger studies

    Antigen clasping by two antigen-binding sites of an exceptionally specific antibody for histone methylation

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    Extensive studies of the structure–function relationship of antibodies have established that conventional immunoglobulins contain two copies of the antigen-binding fragment (Fab), each of which serves as an autonomous and complete unit for recognizing an antigen. In this paper, we report a previously unidentified mode of antibody–antigen recognition, dubbed “antigen clasping,” where two antigen-binding sites cooperatively clasp one antigen, and the design of a long-neck antibody format that facilitates antigen clasping. Antigen clasping led to recombinant antibodies for histone posttranslational modifications with extraordinarily high specificity, valuable tools for epigenetic research. This study substantially broadens the long-standing paradigm for antibody–antigen recognition

    Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes

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    RationaleEvidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers.MethodsFrom the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated.ResultsThere were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group.ConclusionMetabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks

    Exploration of human serum lipoprotein supramolecular phospholipids using statistical heterospectroscopy in n-Dimensions (SHY-n): Identification of potential cardiovascular risk biomarkers related to SARS-CoV-2 infection

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    SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS)

    Diffusion and relaxation edited proton NMR spectroscopy of plasma reveals a high-fidelity supramolecular biomarker signature of SARS-CoV-2 infection

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    We have applied nuclear magnetic resonance spectroscopy based plasma phenotyping to reveal diagnostic molecular signatures of SARS-CoV-2 infection via combined diffusional and relaxation editing (DIRE). We compared plasma from healthy age-matched controls (n = 26) with SARS-CoV-2 negative non-hospitalized respiratory patients and hospitalized respiratory patients (n = 23 and 11 respectively) with SARS-CoV-2 rRT-PCR positive respiratory patients (n = 17, with longitudinal sampling time-points). DIRE data were modelled using principal component analysis and orthogonal projections to latent structures discriminant analysis (O-PLS-DA), with statistical cross-validation indices indicating excellent model generalization for the classification of SARS-CoV-2 positivity for all comparator groups (area under the receiver operator characteristic curve = 1). DIRE spectra show biomarker signal combinations conferred by differential concentrations of metabolites with selected molecular mobility properties. These comprise the following: (a) composite N-acetyl signals from α-1-acid glycoprotein and other glycoproteins (designated GlycA and GlycB) that were elevated in SARS-CoV-2 positive patients [p = 2.52 × 10–10 (GlycA) and 1.25 × 10–9 (GlycB) vs controls], (b) two diagnostic supramolecular phospholipid composite signals that were identified (SPC-A and SPC-B) from the –+N–(CH3)3 choline headgroups of lysophosphatidylcholines carried on plasma glycoproteins and from phospholipids in high-density lipoprotein subfractions (SPC-A) together with a phospholipid component of low-density lipoprotein (SPC–B). The integrals of the summed SPC signals (SPCtotal) were reduced in SARS-CoV-2 positive patients relative to both controls (p = 1.40 × 10–7) and SARS-CoV-2 negative patients (p = 4.52 × 10–8) but were not significantly different between controls and SARS-CoV-2 negative patients. The identity of the SPC signal components was determined using one and two dimensional diffusional, relaxation, and statistical spectroscopic experiments. The SPCtotal/GlycA ratios were also significantly different for control versus SARS-CoV-2 positive patients (p = 1.23 × 10–10) and for SARS-CoV-2 negatives versus positives (p = 1.60 × 10–9). Thus, plasma SPCtotal and SPCtotal/GlycA are proposed as sensitive molecular markers for SARS-CoV-2 positivity that could effectively augment current COVID-19 diagnostics and may have value in functional assessment of the disease recovery process in patients with long-term symptoms

    Principles of Modular Tumor Therapy

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    Nature is interwoven with communication and is represented and reproduced through communication acts. The central question is how may multimodal modularly acting and less toxic therapy approaches, defined as modular therapies, induce an objective response or even a continuous complete remission, although single stimulatory or inhibitingly acting drugs neither exert mono-activity in the respective metastatic tumor type nor are they directed to potentially ‘tumor-specific’ targets. Modularity in the present context is a formal pragmatic communicative systems concept, describing the degree to which systems objects (cells, pathways etc.) may be communicatively separated in a virtual continuum, and recombined and rededicated to alter validity and denotation of communication processes in the tumor. Intentional knowledge, discharging in reductionist therapies, disregards the risk-absorbing background knowledge of the tumor’s living world including the holistic communication processes, which we rely on in every therapy. At first, this knowledge constitutes the validity of informative intercellular processes, which is the prerequisite for therapeutic success. All communication-relevant steps, such as intentions, understandings, and the appreciation of messages, may be modulated simultaneously, even with a high grade of specificity. Thus, modular therapy approaches including risk-absorbing and validity-modifying background knowledge may overcome reductionist idealizations. Modular therapies show modular events assembled by the tumor’s living world as an additional evolution-constituting dimension. This way, modular knowledge may be acquired from the environment, either incidentally or constitutionally. The new communicatively defined modular coherency of environment, i.e. the tumor-associated microenvironment, and tumor cells open novel ways for the scientific community in ‘translational medicine’
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