Robustness and modularity properties of a non-covalent DNA catalytic reaction

The biophysics of nucleic acid hybridization and strand displacement have been used for the rational design of a number of nanoscale structures and functions. Recently, molecular amplification methods have been developed in the form of non-covalent DNA catalytic reactions, in which single-stranded DNA (ssDNA) molecules catalyze the release of ssDNA product molecules from multi-stranded complexes. Here, we characterize the robustness and specificity of one such strand displacement-based catalytic reaction. We show that the designed reaction is simultaneously sensitive to sequence mutations in the catalyst and robust to a variety of impurities and molecular noise. These properties facilitate the incorporation of strand displacement-based DNA components in synthetic chemical and biological reaction networks

Differentiable model-based adaptive optics for two-photon microscopy

Aberrations limit scanning fluorescence microscopy when imaging in scattering materials such as biological tissue. Model-based approaches for adaptive optics take advantage of a computational model of the optical setup. Such models can be combined with the optimization techniques of machine learning frameworks to find aberration corrections, as was demonstrated for focusing a laser beam through aberrations onto a camera [arXiv:2007.13400]. Here, we extend this approach to two-photon scanning microscopy. The developed sensorless technique finds corrections for aberrations in scattering samples and will be useful for a range of imaging application, for example in brain tissue

Adaptive optics with reflected light and deep neural networks

Light scattering and aberrations limit optical microscopy in biological tissue, which motivates the development of adaptive optics techniques. Here, we develop a method for adaptive optics with reflected light and deep neural networks compatible with an epi-detection configuration. Large datasets of sample aberrations which consist of excitation and detection path aberrations as well as the corresponding reflected focus images are generated. These datasets are used for training deep neural networks. After training, these networks can disentangle and independently correct excitation and detection aberrations based on reflected light images recorded from scattering samples. A similar deep learning approach is also demonstrated with scattering guide stars. The predicted aberration corrections are validated using two photon imaging

Differentiable model-based adaptive optics with transmitted and reflected light

Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires datasets that cover a wide range of possible aberrations, which however becomes limiting for more strongly scattering samples, and does not take advantage of prior information about the imaging process. Here, we show that combining model-based adaptive optics with the optimization techniques of machine learning frameworks can find aberration corrections with a small number of measurements. Corrections are determined in a transmission configuration through a single aberrating layer and in a reflection configuration through two different layers at the same time. Additionally, corrections are not limited by a predetermined model of aberrations (such as combinations of Zernike modes). Focusing in transmission can be achieved based only on reflected light, compatible with an epidetection imaging configuration

DNA as a universal substrate for chemical kinetics

Molecular programming aims to systematically engineer molecular and chemical systems of autonomous function and ever-increasing complexity. A key goal is to develop embedded control circuitry within a chemical system to direct molecular events. Here we show that systems of DNA molecules can be constructed that closely approximate the dynamic behavior of arbitrary systems of coupled chemical reactions. By using strand displacement reactions as a primitive, we construct reaction cascades with effectively unimolecular and bimolecular kinetics. Our construction allows individual reactions to be coupled in arbitrary ways such that reactants can participate in multiple reactions simultaneously, reproducing the desired dynamical properties. Thus arbitrary systems of chemical equations can be compiled into real chemical systems. We illustrate our method on the Lotka–Volterra oscillator, a limit-cycle oscillator, a chaotic system, and systems implementing feedback digital logic and algorithmic behavior

A Macrophage Phenotype for a Constitutive, Class II Antigen-Expressing, Human Dermal Perivascular Dendritic Cell

A previously uncharacterized population of class II antigen-bearing dendritic cells that are intimately associated with the dermal microvasculature was identified in normal human skin using a double-label, indirect immunofluorescence technique. The only other major HLA-DR positive dermal cell type noted in these studies, the dermal microvascular endothelial cell (DMVEC), appeared to express lesser amounts of HLA-DR region gene product than did this dermal perivascular dendritic cell (DPDC). These DPDC were particularly common around small vessels in the superficial vascular plexus of the papillary dermis and were distinct from the mast cell, another cell type normally seen in a similar location. Phenotypic and ultrastructural studies have determined that the DPDC is more closely related to the monocyte/macro-phage lineage than the dendritic cell lineage. The perivascular location and phenotype of this cell distinguishes it from other previously described constitutive dermal cell types such as the classic “histiocyte,” veiled cell, and dendrocyte. The relatively rich expression of all three major HLA-D region gene products by this dermal perivascular dendritic macro-phage would suggest that it could play a significant role in the immunobiology of the dermal microvascular unit

A reassessment of Antarctic plateau reactive nitrogen based on ANTCI 2003 airborne and ground based measurements

The first airborne measurements of nitric oxide (NO) on the Antarctic plateau have demonstrated that the previously reported elevated levels of this species extend well beyond the immediate vicinity of South Pole. Although the current database is still relatively weak and critical laboratory experiments are still needed, the findings here suggest that the chemical uniqueness of the plateau may be substantially greater than first reported. For example, South Pole ground-based findings have provided new evidence showing that the dominant process driving the release of nitrogen from the snowpack during the spring/summer season (post-depositional loss) is photochemical in nature with evaporative processes playing a lesser role. There is also new evidence suggesting that nitrogen, in the form of nitrate, may undergo multiple recycling within a given photochemical season. Speculation here is that this may be a unique property of the plateau and much related to its having persistent cold temperatures even during summer. These conditions promote the efficient adsorption of molecules like HNO3 (and very likely HO2NO2) onto snow-pack surface ice where we have hypothesized enhanced photochemical processing can occur, leading to the efficient release of NOx to the atmosphere. In addition, to these process-oriented tentative conclusions, the findings from the airborne studies, in conjunction with modeling exercises suggest a new paradigm for the plateau atmosphere. The near-surface atmosphere over this massive region can be viewed as serving as much more than a temporary reservoir or holding tank for imported chemical species. It defines an immense atmospheric chemical reactor which is capable of modifying the chemical characteristics of select atmospheric constituents. This reactor has most likely been in place over geological time, and may have led to the chemical modulation of some trace species now found in ice cores. Reactive nitrogen has played a critical role in both establishing and in maintaining this reactor. © 2007 Elsevier Ltd. All rights reserved

Selenium-Binding Protein 1 Indicates Myocardial Stress and Risk for Adverse Outcome in Cardiac Surgery

Selenium-binding protein 1 (SELENBP1) is an intracellular protein that has been detected in the circulation in response to myocardial infarction. Hypoxia and cardiac surgery affect selenoprotein expression and selenium (Se) status. For this reason, we decided to analyze circulating SELENBP1 concentrations in patients (n = 75) necessitating cardioplegia and a cardiopulmonary bypass (CPB) during the course of the cardiac surgery. Serum samples were collected at seven time-points spanning the full surgical process. SELENBP1 was quantified by a highly sensitive newly developed immunological assay. Serum concentrations of SELENBP1 increased markedly during the intervention and showed a positive association with the duration of ischemia (ρ = 0.6, p < 0.0001). Elevated serum SELENBP1 concentrations at 1 h after arrival at the intensive care unit (post-surgery) were predictive to identify patients at risk of adverse outcome (death, bradycardia or cerebral ischemia, "endpoint 1"; OR 29.9, CI 3.3-268.8, p = 0.00027). Circulating SELENBP1 during intervention (2 min after reperfusion or 15 min after weaning from the CPB) correlated positively with an established marker of myocardial infarction (CK-MB) measured after the intervention (each with ρ = 0.5, p < 0.0001). We concluded that serum concentrations of SELENBP1 were strongly associated with cardiac arrest and the duration of myocardial ischemia already early during surgery, thereby constituting a novel and promising quantitative marker for myocardial hypoxia, with a high potential to improve diagnostics and prediction in combination with the established clinical parameters