On the suitability of SIFT technique to deal with image modifications specific to confocal scanning laser microscopy

Fully Affine Invariant Methods for Cross-Session Registration of Calcium Imaging Data

In vivo two-photon microscopy permits simultaneous recording of the activity of the same neuronal population across multiple sessions in days or weeks, which is crucial for addressing many fundamental questions of neuroscience. The field-of-view (FOV) alignment is a necessary step for identifying the same neurons across multiple imaging sessions. Accurate FOV alignment becomes challenging in the situations of image blurring, insufficient common neurons, or uneven background brightness. The existing methods largely fail to align FOV pairs in these situations. The fully affine invariant approach has been applied in computer vision to register real scene images with different backgrounds. However, its performance in calcium imaging data is unknown. We explored the feasibility of using the fully affine invariant approach to align calcium FOV images across multiple sessions by examining the performance of five methods. Further, we compared their performance with common feature-based methods as well as some classical methods with or without adaptive contrast enhancement. Using cellular resolution calcium imaging data recorded from two areas of the mouse motor cortex over weeks, we show that all fully affine invariant methods provide more accurate FOV alignment results than other methods in general and in the case of a few common neurons identified, uneven background brightness or image blurring. This study demonstrated the feasibility and reliability of the fully affine invariant methods in cross-session FOV alignment. These methods could be useful for neuroscience research, especially on questions that involve experience-dependent plasticity spanning over days or weeks.

The enhancement of Arg1 and activated ERβ expression in microglia HMC3 by induction of 96% ethanol extract of Marsilea crenata Presl. leaves

Background Phytoestrogens have a high potential to overcome the neuroinflammation caused by estrogen deficiency. Marsilea crenata Presl. is a plant known to contain phytoestrogens. This research aimed to report the activity of a 96% ethanol extract of M. crenata leaves in inducing activation of microglia HMC3 cell to M2 polarity, which has anti-inflammatory characteristics. Methods The study was done by culturing microglia HMC3 cell in 24-well microplate and inducing it with IFN-γ for 24 h to activate the cell to M1 polarity, which has proinflammatory characteristics. The 96% ethanol extract was added with various doses of 62.5, 125, and 250 ppm. Genistein, 50 μM, was used as a positive control. The analysis of the immunofluorescence of Arginase-1 (Arg1) and ERβ as markers was done using a convocal laser scanning microscope. Results The result of Arg1 shows a significant difference in Arg1 expression in the microglia HMC3 cell line between the negative control and all treatment groups at p < 0.05, with the best result at 250 ppm, whereas for ERβ, the results show, at doses of 125 and 250 ppm, that the 96% ethanol extract of M. crenata leaves decrease the activated ERβ expression at p < 0.05, with the best result at 250 ppm. The Arg1 and activated ERβ expression have a weak negative relationship with the Pearson correlation test. Conclusions The 96% ethanol extract of M. crenata leaves has an antineuroinflammation activity through the induction of Arg1 and activated ERβ expression in microglia HMC3 cell, with the best dose at 250 ppm.

Antineuroinflammation activity of n-butanol fraction of Marsilea crenata Presl. in microglia HMC3 cell line

Background Neuroinflammation is one of the main causes of neurodegenerative events. Phytoestrogen is a group compounds that have an estrogen-like structure or function. Phytoestrogen has a high potential to overcome neuroinflammation caused by estrogen deficiency in postmenopausal women. Marsilea crenata Presl. is a plant known to contain phytoestrogens. This research aimed to analyze the activity of an n-butanol fraction of M. crenata leaves in inhibiting the classical pathway activation of microglia HMC3 cell line to M1 polarity, which has proinflammatory characteristics. Methods Microglia HMC3 cell line was cultured in Eagle's minimum essential medium and induced with IFN-γ for 24 h to activate the cell to M1 polarity in 24-well microplates. The n-butanol fraction was added with various doses of 62.5, 125, and 250 ppm and genistein 50 μM as a positive control. The expression of major histocompatibility complex II (MHC II) as a marker was tested using a confocal laser scanning microscope. Results The result of MHC II measurement shows a significant difference in the MHC II expression in the microglia HMC3 cell line between the negative control and all treatment groups at p<0.05, indicating a non-monotonic dose-response profile. Conclusions The best dosage to inhibit MHC II expression was 250 ppm with the value of 200.983 AU. It is then concluded that n-butanol fraction of M. crenata leaves has antineuroinflammation activity due to its phytoestrogens.

Experimenting liver fibrosis diagnostic by two photon excitation microscopy and Bag-of-Features image classification

The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.

Influence of confocal scanning laser microscopy specific acquisition parameters on the detection and matching of speeded-up robust features

The robustness and distinctiveness of local features to various object or scene deformations and to modifications of the acquisition parameters play key roles in the design of many computer vision applications. In this paper we present the results of our experiments on the behavior of a recently developed technique for local feature detection and description, Speeded-Up Robust Features (SURF), regarding image modifications specific to Confocal Scanning Laser Microscopy (CSLM). We analyze the repeatability of detected SURF keypoints and the precision-recall of their matching under modifications of three important CSLM parameters: pinhole aperture, photomultiplier (PMT) gain and laser beam power. During any investigation by CSLM these three parameters have to be modified, individually or together, in order to optimize the contrast and the Signal Noise Ratio (SNR), being also inherently modified when changing the microscope objective. Our experiments show that an important amount of SURF features can be detected at the same physical locations in images collected at different values of the pinhole aperture, PMT gain and laser beam power, and further on can be successfully matched based on their descriptors. In the final part, we exemplify the potential of SURF in CSLM imaging by presenting a SURF-based computer vision application that deals with the mosaicing of images collected by this technique.