Gene transcription by the enzyme RNA polymerase is tightly regulated. In many cases, such as in the
lac operon in
Escherichia coli, this regulation is achieved through the action of protein factors ...on DNA. Because DNA is an elastic polymer, its response to enzymatic processing can lead to mechanical perturbations (e.g., linear stretching and supercoiling) that can affect the operation of other DNA processing complexes acting elsewhere on the same substrate molecule. Using an optical-tweezers assay, we measured the binding kinetics between single molecules of bacteriophage T7 RNA polymerase and DNA, as a function of tension. We found that increasing DNA tension under conditions that favor formation of the open complex results in destabilization of the preinitiation complex. Furthermore, with zero ribonucleotides present, when the closed complex is favored, we find reduced tension sensitivity, implying that it is predominantly the open complex that is sensitive. This result strongly supports the “scrunching” model for T7 transcription initiation, as the applied tension acts against the movement of the DNA into the scrunched state, and introduces linear DNA tension as a potential regulatory quantity for transcription initiation.
Orthostatic hypotension (OH) is a form of orthostatic intolerance (OI) and a key physiological indicator of autonomic dysfunction that is associated with an increased risk of major ...cerebrocardiovascular events. Symptoms of cerebral hypoperfusion have been reported in patients with OH, which worsens symptoms and increases the risk of syncope. Since pharmacological interventions increase blood pressure (BP) independent of posture and do not restore normal baroreflex control, nonpharmacological treatments are considered the foundation of OH management. While reductions in cerebral blood flow velocity (CBF
v
) during orthostatic stress are associated with a decrease in end-tidal CO
2
(EtCO
2
) and hypocapnia in patients with OI, their contribution to the severity of OH is not well understood. These measures have been physiological targets in a wide variety of biofeedback interventions. This study explored the relationship between cardiovascular autonomic control, EtCO
2
and cerebral hypoperfusion in patients (N = 72) referred for OI. Patients with systolic OH were more likely to be male, older, demonstrate reduced adrenal and vagal baroreflex sensitivity, and reduced cardiovagal control during head-up tilt (HUT) than patients without systolic OH. Greater reduction in CBF
v
during HUT was associated with a larger reduction in ETCO
2
and systolic BP during HUT. While deficits in cardiovascular autonomic control played a more important role in systolic OH, reduced EtCO
2
was a major contributor to orthostatic cerebral hypoperfusion. These findings suggest that biofeedback treatments targeting both the autonomic nervous system and EtCO
2
should be part of nonpharmacological interventions complementing the standard of care in OH patients with symptoms of cerebral hypoperfusion.
Single-cell techniques like Patch-seq have enabled the acquisition of multimodal data from individual neuronal cells, offering systematic insights into neuronal functions. However, these data can be ...heterogeneous and noisy. To address this, machine learning methods have been used to align cells from different modalities onto a low-dimensional latent space, revealing multimodal cell clusters. The use of those methods can be challenging without computational expertise or suitable computing infrastructure for computationally expensive methods. To address this, we developed a cloud-based web application, MANGEM (multimodal analysis of neuronal gene expression, electrophysiology, and morphology). MANGEM provides a step-by-step accessible and user-friendly interface to machine learning alignment methods of neuronal multimodal data. It can run asynchronously for large-scale data alignment, provide users with various downstream analyses of aligned cells, and visualize the analytic results. We demonstrated the usage of MANGEM by aligning multimodal data of neuronal cells in the mouse visual cortex.
We characterize all pseudo-uninorms with continuous Archimedean underlying functions. By discussing all possible combinations of strict and nilpotent underlying functions we show that a ...pseudo-uninorm with continuous Archimedean underlying functions is not a uninorm only in the case when both underlying functions are strict. Moreover, we show that in the case of pseudo-uninorms with continuous Archimedean underlying functions the set of points where the commutativity could be violated reduces to {(0,1),(1,0)}.
Balancing the scale Kalafut, Kathryn L.; Freestone, David M.
Journal of the experimental analysis of behavior,
September 2022, Letnik:
118, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Traditional discussions involving ‘basic’ and ‘applied’ behavioral research often focus on the differences, or gaps, between these areas. They take place in different environments, use different ...methods, ask different questions, and have different objectives. Applied animal behavior is no exception. Focusing on the differences in these areas is to the detriment of a cohesive and complete understanding of animal behavior. This paper instead focuses on the similarities between these two sides, and presents them as a matter of scale. A series of real‐life examples experienced by the authors is used to highlight how the skills and knowledge of both the applied and the basic sides are valuable and necessary to not only further both fields independently, but to develop a comprehensive understanding of animal behavior.
Biophysical techniques, such as single molecule FRET, fluorescence microscopy, single ion-channel patch clamping, and optical tweezers often yield data that are noisy time series containing discrete ...steps. Here we present a method enabling objective identification of nonuniform steps present in such noisy data. Our method does not require the assumption of any underlying kinetic or state models and is thus particularly useful for analysis of novel and poorly understood systems. In contrast to other model-independent methods, no parameters or other information is taken from the user. We find that, at high noise levels, our method exceeds the performance of other model-independent methods in accurately locating steps in simulated noisy data.
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