29 research outputs found

    Vasopressin excites interneurons to suppress hippocampal network activity across a broad span of brain maturity at birth

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    During birth in mammals, a pronounced surge of fetal peripheral stress hormones takes place to promote survival in the transition to the extrauterine environment. However, it is not known whether the hormonal signaling involves central pathways with direct protective effects on the perinatal brain. Here, we show that arginine vasopressin specifically activates interneurons to suppress spontaneous network events in the perinatal hippocampus. Experiments done on the altricial rat and precocial guinea pig neonate demonstrated that the effect of vasopressin is not dependent on the level of maturation (depolarizing vs. hyperpolarizing) of postsynaptic GABA(A) receptor actions. Thus, the fetal mammalian brain is equipped with an evolutionarily conserved mechanism well-suited to suppress energetically expensive correlated network events under conditions of reduced oxygen supply at birth.Peer reviewe

    Feedback control can change the apparent stiffness a cell experiences.

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    <p>(a) A contracting cell in a soft extracellular matrix (ECM) experiences little resistance to its contraction and can be modeled with a soft spring. (b) A contracting cell in a stiff ECM experiences a large resistance to its contraction and can be modeled with a stiff spring. Using the AFM stiffness clamp, a soft spring can be made to appear stiff (or vice-versa) by controlling the spring's extension as a function of the cell's contraction. This approach can be broadly applied to make springs appear stiffer or softer than their actual value.</p

    Cell contraction rapidly responds to stiffness changes.

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    <p>(a) An AFM was used to expose a single fibroblast cell to dynamically changeable apparent stiffness values with the AFM stiffness clamp. The piezo-controlled substrate was moved in response to deflections of the cantilever, which were precisely measured with an optical lever system. (b) Force and cell height as the cell contracts under different apparent stiffnesses from a typical experiment. A total of 30 cells were tested, all exhibiting the same stiffness-dependent behavior shown above. Each interval is under an apparent stiffness of 3.6, 18, or 90 nN/µm as indicated at the top of the graph. The traction rate and contraction velocity rapidly change with a step change in stiffness. A segmented linear regression fit is plotted highlighting the change in traction rate (inset). Data displayed in (c) and (d) are compiled from this trace. (c) Traction rate increases with apparent stiffness while corresponding contraction velocity decreases. The rates are determined from a linear regression fit where the 95% confidence interval for each slope is within 0.4 nN/min and 20 nm/min for the force and height, respectively. (d) Plot of force versus cell height. The three linear, distinct traces each have slopes that indicate that the desired apparent stiffnesses were achieved. The * marks the trace without any feedback loop. Each interval was translated to begin at the origin for comparison.</p

    Response of expanding hydrogel to step changes in stiffness.

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    <p>(a) The AFM stiffness clamp was applied to a rehydrated hydrogel that deflected an AFM cantilever as it expanded. Cantilever position is precisely measured using an optical lever system. Feedback was implemented by moving a piezo-controlled substrate. (b) A typical trace of how force and gel height () changed over time as the cantilever deflected in response to the expansion of the hydrogel against apparent stiffnesses of 1, 10, and 100 nN/µm. Separate experiments conducted on 5 different gels all exhibited the same stiffness-dependent behavior shown above. Note that the slope of the force trace clearly changes when the apparent stiffness changes, while the slope of the height trace remains basically constant over this range of stiffness. (c) Categorical plot of the force rate and velocity of gel expansion under three different apparent stiffnesses from the trace depicted in (b). The rates are determined from a linear regression fit where the 95% confidence interval for each slope is within 0.25 nN/min and 5 nm/min for the force and height, respectively. Force rate changes with stiffness while expansion rate does not over this range of stiffness. (d) Plot of force versus gel height as the gel expanded under a wide range of apparent stiffnesses. Each trace represents a different apparent stiffness listed in the table and applied using the stiffness clamp algorithm. The traces were translated to begin at the origin for comparison. The horizontal and vertical traces represent desired stiffnesses approaching 0 and , corresponding to a force and position clamp with standard deviations of 15 pN and 0.34 nm. Inset depicts the discrete but highly linear nature of the data. The * marks the trace without any feedback loop and whose slope is the spring constant of the cantilever, 42 nN/µm.</p

    Conceptual design of the AFM stiffness clamp.

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    <p>(a) A stiff spring can be simulated using a spring of a smaller stiffness. A cell applying a given force against a stiff spring achieves a smaller change in height than a softer spring. Moving the spring base up as the cell contracts makes a softer spring appear stiffer to the contracting cell. Plotting contractile traction force versus cell height produces a trace whose steep slope is the apparent stiffness, (dotted line) and is greater than the native spring stiffness, (solid line). (b) A soft spring can be simulated using a spring of a greater stiffness. A cell applying a given force against a soft spring achieves a greater change in height than a stiffer spring. Moving the spring base down as the cell contracts makes a stiffer spring appear softer to the contracting cell. Plotting traction force versus cell height produces a trace whose gradual slope is the apparent stiffness, (dotted line) and is less than the native spring stiffness, (solid line).</p

    Inhibition of VEGF-C modulates distal lymphatic remodeling and secondary metastasis.

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    Tumor-associated lymphatics are postulated to provide a transit route for disseminating metastatic cells. This notion is supported by preclinical findings that inhibition of pro-lymphangiogenic signaling during tumor development reduces cell spread to sentinel lymph nodes (SLNs). However, it is unclear how lymphatics downstream of SLNs contribute to metastatic spread into distal organs, or if modulating distal lymph transport impacts disease progression. Utilizing murine models of metastasis, longitudinal in vivo imaging of lymph transport, and function blocking antibodies against two VEGF family members, we provide evidence that distal lymphatics undergo disease course-dependent up-regulation of lymph transport coincidental with structural remodeling. Inhibition of VEGF-C activity with antibodies against VEGF-C or NRP2 prevented these disease-associated changes. Furthermore, utilizing a novel model of adjuvant treatment, we demonstrate that antagonism of VEGF-C or NRP2 decreases post SLN metastasis. These data support a potential therapeutic strategy for inhibiting distant metastatic dissemination via targeting tumor-associated lymphatic remodeling

    Inhibiting VEGF-C, but not VEGF-A, reduces secondary metastatic spread to the lung in a model of adjuvant therapy.

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    <p>(A) Schematic of the adjuvant therapy model. (B) Representative images of lungs collected 14 days post primary tumor resection, circles indicate metastatic lesions. Animals were dosed weekly with the indicated antibodies starting at day 12, the day of ear resection. Anti-VEGF-C clone VC4.5 was used for two experiments, VC1.12 for the third, in all cases the results were comparable. (C and D) Quantification of the average number of secondary metastatic lesions per animal or the frequency of animals containing at least one secondary metastatic lesion, respectively, plotted per experiment normalized to IgG control (O) and as the average across experiments (+) per treatment condition. (E and F) Relative size of primary and secondary metastatic lesion size, respectively, plotted per experiment normalized to IgG control (O) and as the average across experiments (+) per treatment condition. As plots represent multiple experiments, the mean (–) and 95% confidence intervals (- -) are plotted, instead of SEM, for comparison.</p
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