Depth-of-Field-Extended Plenoptic Camera Based on Tunable Multi-Focus Liquid-Crystal Microlens Array.

Plenoptic cameras have received a wide range of research interest because it can record the 4D plenoptic function or radiance including the radiation power and ray direction. One of its important applications is digital refocusing, which can obtain 2D images focused at different depths. To achieve digital refocusing in a wide range, a large depth of field (DOF) is needed, but there are fundamental optical limitations to this. In this paper, we proposed a plenoptic camera with an extended DOF by integrating a main lens, a tunable multi-focus liquid-crystal microlens array (TMF-LCMLA), and a complementary metal oxide semiconductor (CMOS) sensor together. The TMF-LCMLA was fabricated by traditional photolithography and standard microelectronic techniques, and its optical characteristics including interference patterns, focal lengths, and point spread functions (PSFs) were experimentally analyzed. Experiments demonstrated that the proposed plenoptic camera has a wider range of digital refocusing compared to the plenoptic camera based on a conventional liquid-crystal microlens array (LCMLA) with only one corresponding focal length at a certain voltage, which is equivalent to the extension of DOF. In addition, it also has a 2D/3D switchable function, which is not available with conventional plenoptic cameras.

The Reparative Effect of Dendrobium officinale Protocorms against Photodamage Caused by UV-Irradiation in Hairless Mice.

Dendrobium officinale protocorms (DOPs) are a specific developmental stage of Dendrobium officinale KIMURA et MIGO, which is used in folk medicine to ease skin issues, such as wrinkles and erythema. The purpose of the current study was to evaluate the effect of DOPs on UV irradiation-induced skin damage in bc_nu hairless mice, using matrixyl as a positive control. Hairless mice were randomly separated into 6 groups (8 mice per group). The normal control group received solvent and was not exposed to UV irradiation, while the model control group received solvent and was exposed to UV irradiation. The positive control group was subjected to UV irradiation and then received a 10 mg/mL formulation of matrixyl. The DOPs-treated groups received a transdermal application of a DOPs formulation after 4 weeks of UV irradiation. Relevant indicators, such as catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), thiobarbituric acid reactive substances (TBARS) and matrix metalloproteinases (MMPs), were then used to evaluate the ability of DOPs to repair photodamage. The results indicated that DOPs significantly reduced erythema and protected the skin from dryness and therefore exhibits a significant anti-photoaging effect. In addition, the expression of CAT, SOD, and GSH-Px increased while TBARS and MMPs levels decreased in DOPs-treated mice. This demonstrated that DOPs can inhibit photodamage in the skin of hairless mice. DOPs could be used as a potential therapeutic agent to protect the skin against UV-induced photoaging.

Electrically Controlled Liquid Crystal Microlens Array Based on Single-Crystal Graphene Coupling Alignment for Plenoptic Imaging.

As a unique electric-optics material, liquid crystals (LCs) have been used in various light-control applications. In LC-based light-control devices, the structural alignment of LC molecules is of great significance. Generally, additional alignment layers are required for LC lens and microlens, such as rubbed polyimide (PI) layers or photoalignment layers. In this paper, an electrically controlled liquid crystal microlens array (EC-LCMLA) based on single-crystal graphene (SCG) coupling alignment is proposed. A monolayer SCG with high conductivity and initial anchoring of LC molecules was used as a functional electrode, thus no additional alignment layer is needed, which effectively simplifies the basic structure and process flow of conventional LCMLA. Experiments indicated that a uniform LC alignment can be acquired in the EC-LCMLA cell by the SCG coupling alignment effect. The common optical properties including focal lengths and point spread function (PSF) were measured experimentally. Experiments demonstrated that the proposed EC-LCMLA has good focusing performance in the visible to near-infrared range. Moreover, the plenoptic imaging in Galilean mode was achieved by integrating the proposed EC-LCMLA with photodetectors. Digital refocusing was performed to obtain a rendering image of the target.

Structural and functional insights into the LBD family involved in abiotic stress and flavonoid synthases in Camellia sinensis.

Lateral organ boundaries domain (LBD) proteins are plant-specific transcription factors that play a crucial role in growth and development, as well as metabolic processes. However, knowledge of the function of LBD proteins in Camellia sinensis is limited, and no systematic investigations of the LBD family have been reported. In this study, we identified 54 LBD genes in Camellia sinensis. The expression patterns of CsLBDs in different tissues and their transcription responses to exogenous hormones and abiotic stress were determined by RNA-seq, which showed that CsLBDs may have diverse functions. Analysis of the structural gene promoters revealed that the promoters of CsC4H, CsDFR and CsUGT84A, the structural genes involved in flavonoid biosynthesis, contained LBD recognition binding sites. The integrative analysis of CsLBD expression levels and metabolite accumulation also suggested that CsLBDs are involved in the regulation of flavonoid synthesis. Among them, CsLOB_3, CsLBD36_2 and CsLBD41_2, localized in the nucleus, were selected for functional characterization. Yeast two-hybrid assays revealed that CsLBD36_2 and CsLBD41_2 have self-activation activities, and CsLOB_3 and CsLBD36_2 can directly bind to the cis-element and significantly increase the activity of the CsC4H, CsDFR and CsUGT84A promoter. Our results present a comprehensive characterization of the 54 CsLBDs in Camellia sinensis and provide new insight into the important role that CsLBDs play in abiotic and flavonoid biosynthesis.

Effect of berberine on the HPA-axis pathway and skeletal muscle GLUT4 in type 2 diabetes mellitus rats.

PURPOSE: Activation of the hypothalamus-pituitary-adrenal (HPA) axis pathway is closely related to insulin resistance (IR), glucose, and lipid metabolism disorders in type 2 diabetes mellitus (T2DM). Berberine (BBR) has effect on regulating disorder of glucose and lipid metabolism in T2DM. In fact, activation of the HPA axis pathway is closely related to IR, glucose, and lipid metabolism disorders in T2DM. Here, we investigated whether the therapeutic effect of BBR on T2DM rats is acted through the HPA axis pathway. METHODS: In this research, we investigated the effects of BBR on the HPA-axis pathway-related indicators and expression of skeletal muscle glucose transporter 4 (GLUT4) in the high-fat diet and streptozotocin-induced T2DM rats, and identify its possible mechanism of improving IR in T2DM. RESULTS: BBR significantly reduced fasting blood glucose, total cholesterol, and low-density lipoprotein cholesterol in model rats. It also improved the abnormalities of the high-density lipoprotein cholesterol, the insulin resistance index, the insulin sensitivity index, glucagon, and insulin levels. BBR decreased levels of hypothalamic Orexin-A, the OX2R receptor, the corticotropin-releasing hormone, the pituitary and the plasma adrenocorticotropic hormone, as well as serum and urine corticosterone. At the same time, BBR increased mRNA and protein expressions of GLUT4 in skeletal muscles of model rats as well. CONCLUSION: Those results suggested that BBR can exert inhibition on the HPA-axis and increased skeletal muscle expression of GLUT4 proteins, which may be one of the important mechanisms in BBR to improve IR and regulating glucose and lipid metabolism in T2DM rats.

Breast image pre-processing for mammographic tissue segmentation.

During mammographic image acquisition, a compression paddle is used to even the breast thickness in order to obtain optimal image quality. Clinical observation has indicated that some mammograms may exhibit abrupt intensity change and low visibility of tissue structures in the breast peripheral areas. Such appearance discrepancies can affect image interpretation and may not be desirable for computer aided mammography, leading to incorrect diagnosis and/or detection which can have a negative impact on sensitivity and specificity of screening mammography. This paper describes a novel mammographic image pre-processing method to improve image quality for analysis. An image selection process is incorporated to better target problematic images. The processed images show improved mammographic appearances not only in the breast periphery but also across the mammograms. Mammographic segmentation and risk/density classification were performed to facilitate a quantitative and qualitative evaluation. When using the processed images, the results indicated more anatomically correct segmentation in tissue specific areas, and subsequently better classification accuracies were achieved. Visual assessments were conducted in a clinical environment to determine the quality of the processed images and the resultant segmentation. The developed method has shown promising results. It is expected to be useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

A Review on Automatic Mammographic Density and Parenchymal Segmentation.

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models.