Commercial counterboard for 10 ns software correlator for photon and fluorescence correlation spectroscopy.

A 10 ns time resolution, multi-tau software correlator, capable of computing simultaneous autocorrelation (A-A, B-B) and cross (A-B) correlation functions at count rates up to ∼10 MHz, with no data loss, has been developed in LabVIEW and C++ by using the National Instrument timer/counterboard (NI PCIe-6612) and a fast Personal Computer (PC) (Intel Core i7-4790 Processor 3.60 GHz ). The correlator works by using two algorithms: for large lag times (τ ≳ 1 µs), a classical time-mode scheme, based on the measure of the number of pulses per time interval, is used; differently, for τ ≲ 1 µs a photon-mode (PM) scheme is adopted and the correlation function is retrieved from the sequence of the photon arrival times. Single auto- and cross-correlation functions can be processed online in full real time up to count rates of ∼1.8 MHz and ∼1.2 MHz, respectively. Two autocorrelation (A-A, B-B) and a cross correlation (A-B) functions can be simultaneously processed in full real time only up to count rates of ∼750 kHz. At higher count rates, the online processing takes place in a delayed modality, but with no data loss. When tested with simulated correlation data and latex spheres solutions, the overall performances of the correlator appear to be comparable with those of commercial hardware correlators, but with several nontrivial advantages related to its flexibility, low cost, and easy adaptability to future developments of PC and data acquisition technology.

Hardware simulator for optical correlation spectroscopy with Gaussian statistics and arbitrary correlation functions.

We present a new hardware simulator (HS) for characterization, testing and benchmarking of digital correlators used in various optical correlation spectroscopy experiments where the photon statistics is Gaussian and the corresponding time correlation function can have any arbitrary shape. Starting from the HS developed in [Rev. Sci. Instrum. 74, 4273 (2003)], and using the same I/O board (PCI-6534 National Instrument) mounted on a modern PC (Intel Core i7-CPU, 3.07GHz, 12GB RAM), we have realized an instrument capable of delivering continuous streams of TTL pulses over two channels, with a time resolution of Δt = 50ns, up to a maximum count rate of 〈I〉 ∼ 5MHz. Pulse streams, typically detected in dynamic light scattering and diffuse correlation spectroscopy experiments were generated and measured with a commercial hardware correlator obtaining measured correlation functions that match accurately the expected ones.

A comprehensive mechanism of fibrin network formation involving early branching and delayed single- to double-strand transition from coupled time-resolved X-ray/light-scattering detection.

The formation of a fibrin network following fibrinogen enzymatic activation is the central event in blood coagulation and has important biomedical and biotechnological implications. A non-covalent polymerization reaction between macromolecular monomers, it consists basically of two complementary processes: elongation/branching generates an interconnected 3D scaffold of relatively thin fibrils, and cooperative lateral aggregation thickens them more than 10-fold. We have studied the early stages up to the gel point by fast fibrinogen:enzyme mixing experiments using simultaneous small-angle X-ray scattering and wide-angle, multi-angle light scattering detection. The coupled evolutions of the average molecular weight, size, and cross section of the solutes during the fibrils growth phase were thus recovered. They reveal that extended structures, thinner than those predicted by the classic half-staggered, double-stranded mechanism, must quickly form. Following extensive modeling, an initial phase is proposed in which single-bonded "Y-ladder" polymers rapidly elongate before undergoing a delayed transition to the double-stranded fibrils. Consistent with the data, this alternative mechanism can intrinsically generate frequent, random branching points in each growing fibril. The model predicts that, as a consequence, some branches in these expanding "lumps" eventually interconnect, forming the pervasive 3D network. While still growing, other branches will then undergo a Ca(2+)/length-dependent cooperative collapse on the resulting network scaffolding filaments, explaining their sudden thickening, low final density, and basic mechanical properties.

Modeling of fibrin gels based on confocal microscopy and light-scattering data.

Fibrin gels are biological networks that play a fundamental role in blood coagulation and other patho/physiological processes, such as thrombosis and cancer. Electron and confocal microscopies show a collection of fibers that are relatively monodisperse in diameter, not uniformly distributed, and connected at nodal points with a branching order of ∼3-4. Although in the confocal images the hydrated fibers appear to be quite straight (mass fractal dimension D(m) = 1), for the overall system 1, joined at randomly distributed nodal points. The resulting 3D network strikingly resembles real fibrin gels and can be sketched as an assembly of densely packed fractal blobs, i.e., regions of size ξ, where the fiber concentration is higher than average. The blobs are placed at a distance ξ0 between their centers of mass so that they are overlapped by a factor η =ξ/ξ0 and have D(m) ∼1.2-1.6. The in silico gels' structure is quantitatively analyzed by its 3D spatial correlation function g(3D)(r) and corresponding power spectrum I(q) = FFT(3D[g3D(r)]), from which ρ, d, D(m), η, and ξ0 can be extracted. In particular, ξ0 provides an excellent estimate of the gel mesh size. The in silico gels' I(q) compares quite well with real gels' elastic light-scattering measurements. We then derived an analytical form factor for accurately fitting the scattering data, which allowed us to directly recover the gels' structural parameters.

Fast two-dimensional bubble analysis of biopolymer filamentous networks pore size from confocal microscopy thin data stacks.

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data.