24 research outputs found

    Climate change effects on phytoplankton depend on cell size and food web structure

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    We investigated the effects of warming on a natural phytoplankton community from the Baltic Sea, based on six mesocosm experiments conducted 2005–2009. We focused on differences in the dynamics of three phytoplankton size groups which are grazed to a variable extent by different zooplankton groups. While small-sized algae were mostly grazer-controlled, light and nutrient availability largely determined the growth of medium- and large-sized algae. Thus, the latter groups dominated at increased light levels. Warming increased mesozooplankton grazing on medium-sized algae, reducing their biomass. The biomass of small-sized algae was not affected by temperature, probably due to an interplay between indirect effects spreading through the food web. Thus, under the higher temperature and lower light levels anticipated for the next decades in the southern Baltic Sea, a higher share of smaller phytoplankton is expected. We conclude that considering the size structure of the phytoplankton community strongly improves the reliability of projections of climate change effects

    Motoneurons of twitch and nontwitch extraocular muscle fibers in the abducens, trochlear, and oculomotor nuclei of monkeys

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    Eye muscle fibers can be divided into two categories: nontwitch, multiply innervated muscle fibers (MIFs), and twitch, singly innervated muscle fibers (SIFs). We investigated the location of motoneurons supplying SIFs and MIFs in the six extraocular muscles of monkeys. Injections of retrograde tracers into eye muscles were placed either centrally, within the central SIF endplate zone; in an intermediate zone, outside the SIF endplate zone, targeting MIF endplates along the length of muscle fiber; or distally, into the myotendinous junction containing palisade endings. Central injections labeled large motoneurons within the abducens, trochlear or oculomotor nucleus, and smaller motoneurons lying mainly around the periphery of the motor nuclei. Intermediate injections labeled some large motoneurons within the motor nuclei but also labeled many peripheral motoneurons. Distal injections labeled small and medium-large peripheral neurons strongly and almost exclusively. The peripheral neurons labeled from the lateral rectus muscle surround the medial half of the abducens nucleus: from superior oblique, they form a cap over the dorsal trochlear nucleus; from inferior oblique and superior rectus, they are scattered bilaterally around the midline, between the oculomotor nucleus; from both medial and inferior rectus, they lie mainly in the C-group, on the dorsomedial border of oculomotor nucleus. In the medial rectus distal injections, a "C-group extension" extended up to the Edinger-Westphal nucleus and labeled dendrites within the supraoculomotor area. We conclude that large motoneurons within the motor nuclei innervate twitch fibers, whereas smaller motoneurons around the periphery innervate nontwitch, MIF fibers. The peripheral subgroups also contain medium-large neurons which may be associated with the palisade endings of global MIFs. The role of MIFs in eye movements is unclear, but the concept of a final common pathway must now be reconsidered. J. Comp. Neurol. 438:318-335, 2001. (C) 2001 Wiley-Liss, Inc

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    Assessment of tuberculosis disease activity in people infected with Mycobacterium tuberculosis and living with HIV: A longitudinal cohort study

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    Background Early detection of asymptomatic incipient tuberculosis (TB) could improve clinical outcomes and reduce the spread of Mycobacterium tuberculosis (MTB) infection, particularly in HIV endemic settings. This study assessed TB disease activity over 5 years in people living with HIV co-infected with MTB using a surrogate biomarker. Methods Between Jan 1, 2013 and Aug 31, 2018, 2014 people living with HIV were screened annually for active TB using the Xpert MTB/RIF diagnostic assay in 11 clinics in Kenya, Tanzania, Uganda, and Nigeria. Longitudinal blood mononuclear cell samples from 46 selected patients with active and recurrent tuberculosis, latent infection, or incipient TB were further analysed for MTB-specific T-cell activation (defined by CD38 expression) as a well-defined surrogate marker for TB disease covering a total of 1758 person-months. Findings MTB-specific CD4 T-cell activation differentiated active, Xpert MTB/RIF positive TB from latent TB with a sensitivity and specificity of 86% and was reduced upon TB treatment initiation. Activated MTB-specific T cells were present in 63% and 23% of incipient TB cases 6 and 12 months before diagnosis of active disease, respectively. Transient increases of MTB-specific T cell activation were also observed in individuals with latent infection, while persistent activation was a hallmark of recurrent TB after the end of treatment. Interpretation In most cases, progression to active TB disease started 6-12 months before diagnosis by clinical symptoms and sputum occurrence of bacilli. Blood biomarkers could facilitate early detection of incipient TB, improve clinical outcomes, and reduce the transmission of MTB

    Dissecting drivers of immune activation in chronic HIV-1 infection

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    Summary: Background: Immune activation is a significant contributor to HIV pathogenesis and disease progression. In virally-suppressed individuals on ART, low-level immune activation has been linked to several non-infectious comorbid diseases. However, studies have not been systematically performed in sub-Saharan Africa and thus the impact of demographics, ART and regional endemic co-infections on immune activation is not known. We therefore comprehensively evaluated in a large multinational African cohort markers for immune activation and its distribution in various settings. Methods: 2747 specimens from 2240 people living with HIV (PLWH) and 477 without HIV from the observational African Cohort Study (AFRICOS) were analyzed for 13 immune parameters. Samples were collected along with medical history, sociodemographic and comorbidity data at 12 HIV clinics across 5 programs in Uganda, Kenya, Tanzania and Nigeria. Data were analyzed with univariate and multivariate methods such as random forests and principal component analysis. Findings: Immune activation was markedly different between PLWH with detectable viral loads, and individuals without HIV across sites. Among viremic PLWH, we found that all immune parameters were significantly correlated with viral load except for IFN-α. The overall inflammatory profile was distinct between men and women living with HIV, in individuals off ART and with HIV viremia. We observed stronger differences in the immune activation profile with increasing viremia. Using machine learning methods, we found that geographic differences contributed to unique inflammatory profiles. We also found that among PLWH, age and the presence of infectious and/or noninfectious comorbidities showed distinct inflammatory patterns, and biomarkers may be used to predict the presence of some comorbidities. Interpretation: Our findings show that chronic immune activation in HIV-1 infection is influenced by HIV viral load, sex, age, region and ART use. These predictors, as well as associations among some biomarkers and coinfections, influence biomarkers associated with noncommunicable diseases. Funding: This work was supported by the President's Emergency Plan for AIDS Relief via a cooperative agreement between the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., and the U.S. Department of Defense [W81XWH-11-2-0174, W81XWH-18-2-0040]. The investigators have adhered to the policies for protection of human subjects as prescribed in AR 70–25. This article was prepared while Michael A. Eller was employed at Henry M. Jackson Foundation for the Advancement of Military Medicine for the U.S. Military HIV Research Program. The views expressed are those of the authors and should not be construed to represent the positions of the US Army or the Department of Defense. The opinions expressed in this article are the author's own, and do not reflect the view of the National Institutes of Health, the U.S. Department of Health and Human Services, or the U.S. government
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