Automatic cell segmentation by adaptive thresholding (ACSAT) for large-scale calcium imaging datasets

Advances in calcium imaging have made it possible to record from an increasingly larger number of neurons simultaneously. Neuroscientists can now routinely image hundreds to thousands of individual neurons. An emerging technical challenge that parallels the advancement in imaging a large number of individual neurons is the processing of correspondingly large datasets. One important step is the identification of individual neurons. Traditional methods rely mainly on manual or semimanual inspection, which cannot be scaled for processing large datasets. To address this challenge, we focused on developing an automated segmentation method, which we refer to as automated cell segmentation by adaptive thresholding (ACSAT). ACSAT works with a time-collapsed image and includes an iterative procedure that automatically calculates global and local threshold values during successive iterations based on the distribution of image pixel intensities. Thus, the algorithm is capable of handling variations in morphological details and in fluorescence intensities in different calcium imaging datasets. In this paper, we demonstrate the utility of ACSAT by testing it on 500 simulated datasets, two wide-field hippocampus datasets, a wide-field striatum dataset, a wide-field cell culture dataset, and a two-photon hippocampus dataset. For the simulated datasets with truth, ACSAT achieved >80% recall and precision when the signal-to-noise ratio was no less than ∼24 dB.DP2 NS082126 - NINDS NIH HHSPublished versio

A hexahomotrioxacalix[3]arene-based ditopic receptor for alkylammonium ions controlled by Ag + ions 4

A receptor cone-1 based on a hexahomotrioxacalix[3]arene bearing three pyridyl groups 21 was successfully synthesized, which has a C3-symmetric conformation and is capable of binding 22 alkylammonium and metal ions simultaneously in a cooperative fashion. It can bind 23 alkylammonium ions through the -cavity formed by three aryl rings. This behaviour is consistent 24 with the cone-in/cone-out conformational rearrangement needed to reorganize the cavity for 25 endo-complexation. As a C3-symmetrical pyridyl-substituted calixarene, receptor cone-1 can also 26 bind a Ag + ion and the nitrogen atoms are turned towards the inside of the cavity and interact with 27 Ag +. After complexation of tris(2-pyridylamide) derivative receptor cone-1 with Ag + , the original 28 C3-symmetry was retained and higher complexation selectivity for n-BuNH3 + versus t-BuNH3 + was 29 observed. Thus, it is believed that this receptor will have a role to play in the sensing, detection, and 30 recognition of Ag + and n-BuNH3 + ions. 3

The Baryon Content of Cosmic Structures

We make an inventory of the baryonic and gravitating mass in structures ranging from the smallest galaxies to rich clusters of galaxies. We find that the fraction of baryons converted to stars reaches a maximum between M500 = 1E12 and 1E13 Msun, suggesting that star formation is most efficient in bright galaxies in groups. The fraction of baryons detected in all forms deviates monotonically from the cosmic baryon fraction as a function of mass. On the largest scales of clusters, most of the expected baryons are detected, while in the smallest dwarf galaxies, fewer than 1% are detected. Where these missing baryons reside is unclear.Comment: ApJ Letters, in pres

An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy

Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes. We use a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules. We demonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells

Simulation of the many-body dynamical quantum Hall effect in an optical lattice

We propose an experimental scheme to simulate the many-body dynamical quantum Hall effect with ultra-cold bosonic atoms in a one-dimensional optical lattice. We first show that the required model Hamiltonian of a spin-1/2 Heisenberg chain with an effective magnetic field and tunable parameters can be realized in this system. For dynamical response to ramping the external fields, the quantized plateaus emerge in the Berry curvature of the interacting atomic spin chain as a function of the effective spin-exchange interaction. The quantization of this response in the parameter space with the interaction-induced topological transition characterizes the many-body dynamical quantum Hall effect. Furthermore, we demonstrate that this phenomenon can be observed in practical cold-atom experiments with numerical simulations.Comment: 8 pages, 3 figures; accepted in Quantum Information Processin