Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.
Abstract Most cervical cancers develop from squamous cells in the exocervix followed by stromal invasion, which alters the organization and morphology of collagen fibers. Therefore, morpho‐structural remodeling of collagen fibers is closely associated with cancer progression. Collagen‐based cancer detection requires not only techniques capable of qualified large‐depth imaging but also computational sensitivity to extract subtle changes. Here, optical coherence tomography (OCT) is applied to collagen fibers in the exocervix. High‐quality imaging into deep stroma is guaranteed by an all‐fiber probe designed to have an extended depth of focus through the formation of the quasi‐Bessel focusing beam. Collagen fibers provide dominant scattering signals in OCT images, and volume information is utilized to establish an optical biomarker reflecting variation gradient in fiber alignment and crimping. Detection of cervical cancer with a multi‐parametric method is then evaluated by ex vivo imaging of human specimens and in vivo imaging of a murine model harboring human cervical cancer. Finally, the tumor potential index (TPI) is proposed by merging multiple metrics. The TPI map provides an intuitive illustration of cancer risk, which may guide clinicians more accurately to the correct location for biopsy.
The shower shape of n, n, p, p, K+, π+ and photons, generated by JPCIAE code for 5.5 TeV/A 208Pb+208Pb collisions, incident on the ALICE photon spectrometer (PHOS), is analyzed with the principal component analysis (PCA) method. The efficiency dependence of purity for the photon discrimination is simulated for the deposited energy ranges 0.5–2 GeV, 2–10 GeV, 10–50 GeV and 50–100 GeV. The result shows that in the energy range of 0.5 to 100 GeV, the efficiency of the photon identification can reach 90% with purity of 90%.
Abstract With the progression of diseases, modified cell–matrix interactions have major effects not only upon key cellular functions but also upon the structure of extracellular matrix and vasculature, which are two of the most prevalent fiber‐like structures in biological tissues. Unfortunately, quantitative approaches to assessing these structural changes are lacking. Herein, a multiparametric imaging system is established to resolve subtle organizational changes of collagen fibers and vasculature in disease progression. The pixel‐wise, automated waviness (paWav) is developed as a novel biomarker, and a multimodal analysis system combining paWav with orientation and alignment assessments is constructed. Aggregation‐induced emission luminogens (AIEgens) with second near‐infrared excitation or emission are developed for in vivo deep‐penetration vasculature imaging. The organization remodeling of cortical blood vessels in stroke in marmosets is quantitatively characterized using biologically excretable AIE dots that highlight the clinical translation potential, and a distance dependence law in vessel morphological remodeling is identified. Finally, the multiparametric analysis relying completely on collagen fiber signatures successfully differentiates cancerous from normal pancreatic tissues using a predictive classification approach. Collectively, the combined use of these structural changes in fibrillar tissue components may enable a better understanding of cell–matrix interactions in pathogenesis and identification of new potential treatment targets.
Acidic leucine-rich nuclear phosphoprotein-32A (ANP32A) has been reported to play an essential role in the development and progression of various human cancers. However, its expression pattern and possible mechanism in human hepatocellular carcinoma (HCC) remain to be elucidated. In this study, we used western blot and immunohistochemical staining to detect protein expression. The effects of ANP32A on the proliferation, migration and invasion of HCC cells were examined using 5-ethynyl-20-deoxyuridine (EdU), colony formation, CCK-8, and transwell assays. RT-qPCR was performed to detect mRNA expression. The interaction between ANP32A and the high mobility group A1 (HMGA1) mRNA was assessed using RNA immunoprecipitation (RIP). The tumorigenicity of ANP32A was assessed by establishing a xenograft tumor model in Balb/c nude mice. We found that the ANP32A protein was expressed at high levels in patients with HCC, which was associated with a poor prognosis. Functional experiments revealed that the silencing of ANP32A inhibited the proliferation, migration, and invasion of HCC cells, whereas overexpression of ANP32A promoted these processes. Further investigations indicated that ANP32A bound the HMGA1 mRNA and maintained its stability to promote the expression of HMGA1, thereby increasing the expression and activation of STAT3. Finally, a xenograft tumor model of Balb/c nude mice confirmed the tumorigenicity of ANP32A. This study found that ANP32A is up-regulated in patients with HCC and may accelerate the proliferation, migration and invasion of HCC cells by modulating the HMGA1/STAT3 pathway.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)