An optical coherence microscope (OCM) has been designed and constructed to acquire 3-dimensional images of highly scattering biological tissue. Volume-rendering software is used to enhance 3-D visualization of the data sets. Lateral resolution of the OCM is 5 µm (FWHM), and the depth resolution is 10 µm (FWHM) in tissue. The design trade-offs for a 3-D OCM are discussed, and the fundamental photon noise limitation is measured and compared with theory. A rotating 3-D image of a frog embryo is presented to illustrate the capabilities of the instrument.

We describe the development and utilization of a new imaging technology for plant biology, optical coherence microscopy (OCM), which allows true in vivo visualization of plants and plant cells. This novel technology allows the direct, in situ (e.g. plants in soil), three-dimensional visualization of cells and events in shoot tissues without causing damage. With OCM we can image cells or groups of cells that are up to 1 mm deep in living tissues, resolving structures less than 5 m in size, with a typical collection time of 5 to 6 min. OCM measures the inherent light-scattering properties of biological tissues and cells. These optical properties vary and provide endogenous developmental markers. Singly scattered photons from small (e.g. 5 ϫ 5 ϫ 10 m) volume elements (voxels) are collected, assembled, and quantitatively false-colored to form a threedimensional image. These images can be cropped or sliced in any plane. Adjusting the colors and opacities assigned to voxels allows us to enhance different features within the tissues and cells. We show that light-scattering properties are the greatest in regions of the Arabidopsis shoot undergoing developmental processes. In large cells, high light scattering is produced from nuclei, intermediate light scatter is produced from cytoplasm, and little if any light scattering originates from the vacuole and cell wall. OCM allows the rapid, repetitive, non-destructive collection of quantitative data about inherent properties of cells, so it provides a means of continuously monitoring plants and plant cells during development and in response to exogenous stimuli.Studies in plant physiology and development characteristically follow changes in space and time that occur as part of normal plant activity or in response to exogenous stimuli. Typical studies require the destruction and analysis of a plant or a tissue sample, followed by the collection and analysis of a second distinct plant or sample. Thus, biological responses or changes are inferred by comparing different plants or samples. Such approaches have been used for centuries and have produced a great deal of knowledge. However, when scientists are able to nondestructively follow biological changes, important concepts and insights have emerged. For example, critical genes involved in programmed cell death were found in Caenorhabditis elegans partially because the developing nematode is nearly transparent, allowing the fate of each cell to be followed in vivo by light microscopy (Gilbert, 1998). Similarly, an elegant fate map for Arabidopsis roots was constructed because the relatively transparent roots allow changes in individual plants to be followed continuously (Dolan et al., 1993). This study led to new discoveries such as the presence of downward communication between mature root cells and the root apical meristem and short-range control of differentiation signals (van den Berg et al., 1997a(van den Berg et al., , 1997b.Except for the relatively transparent Arabidopsis root, plants provide a challenge for in vivo an...

No abstract

Background. Ovarian cancer (OC) is the eighth most common cause of cancer death and the second cause of gynecologic cancer death in women around the world. Ferroptosis, an iron-dependent regulated cell death, plays a vital role in the development of many cancers. Applying expression of ferroptosis-related gene to forecast the cancer progression is helpful for cancer treatment. However, the relationship between ferroptosis-related genes and OC patient prognosis is still vastly unknown, making it still a challenge for developing ferroptosis therapy for OC. Methods. The Cancer Genome Atlas (TCGA) data of OC were obtained and the datasets were randomly divided into training and test datasets. A novel ferroptosis-related gene signature associated with overall survival (OS) was constructed according to the training cohort. The test dataset and ICGC dataset were used to validate this signature. Results. We constructed a model containing nine ferroptosis-related genes, namely, LPCAT3, ACSL3, CRYAB, PTGS2, ALOX12, HSBP1, SLC1A5, SLC7A11, and ZEB1, and predicted the OS of OC in TCGA. At a suitable cutoff, patients were divided into low risk and high risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics (ROCs) were as high as 0.664, respectively. Then, the test dataset and the ICGC dataset were used to evaluate our model, and the ROCs of test dataset were 0.667 and 0.777, respectively. In addition, functional analysis and correlation analysis showed that immune-related pathways were significantly enriched. Meanwhile, we also integrated with other clinical factors and we found the synthesized clinical factors and ferroptosis-related gene signature improved prognostic accuracy relative to the ferroptosis-related gene signature alone. Conclusion. The ferroptosis-related gene signature could predict the OS of OC patients and improve therapeutic decision-making.

Background Exposure to cyclophosphamide (CTX) induces premature ovarian insufficiency (POI). Quercetin is a natural flavonoid that exhibits anti-inflammatory and antioxidant properties, and its antioxidant activity is correlated with POI. However, the mechanism underlying its protective role in CTX-induced ovarian dysfunction is unclear. This study aimed to explore whether quercetin can protect ovarian reserves by activating mitochondrial biogenesis and inhibiting pyroptosis. Methods Thirty-six female C57BL/6 mice were randomly subdivided into six groups. Except for the control group, all groups were injected with 90 mg/kg CTX to establish a POI model and further treated with coenzyme 10 or various doses of quercetin. The mice were sacrificed 48 h after 10 IU pregnant mare serum gonadotropin was injected four weeks after treatments. We used enzyme-linked immunosorbent assays to detect serum hormone expression and light and transmission electron microscopy to assess ovarian tissue morphology and mitochondria. Additionally, we tested oxidant and antioxidant levels in ovarian tissues and mitochondrial function in granulosa cells (GCs). The expression of mitochondrial biogenesis and pyroptosis-related proteins and mRNA was analyzed using western blotting and RT-qPCR. Results Quercetin elevated serum anti-Müllerian hormone, estradiol, and progesterone levels, decreased serum follicle-stimulating hormone and luteinizing hormone levels, and alleviated ovarian pathology. It reduced the mitochondrial DNA content and mitochondrial membrane potential. Furthermore, it upregulated ATP levels and the mRNA and protein expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), mitochondrial transcription factor A, and superoxide dismutase 2. In addition, it suppressed NOD-like receptor pyrin domain containing 3, caspase-1, interleukin-1β, and gasdermin D levels in the GCs of POI mice. Conclusions Quercetin protected the ovarian reserve from CTX-induced ovarian damage by reversing mitochondrial dysfunction and activating mitochondrial biogenesis via the PGC1-α pathway. Moreover, quercetin may improve ovarian functions by downregulating pyroptosis in the CTX-induced POI model. Thus, quercetin can be considered a potential agent for treating POI.

No abstract

A systematic, unified treatment of orthogonal transform methods for signal processing, data analysis and communications, this book guides the reader from mathematical theory to problem solving in practice. It examines each transform method in depth, emphasizing the common mathematical principles and essential properties of each method in terms of signal decorrelation and energy compaction. The different forms of Fourier transform, as well as the Laplace, Z-, Walsh–Hadamard, Slant, Haar, Karhunen–Loève and wavelet transforms, are all covered, with discussion of how each transform method can be applied to real-world experimental problems. Numerous practical examples and end-of-chapter problems, supported by online Matlab and C code and an instructor-only solutions manual, make this an ideal resource for students and practitioners alike.

A simple and biologically plausible model is proposed to simulate the optic flow computation taking place in the dorsal part of medial superior temporal (MSTd) area of the visual cortex in the primates' brain. The model is a neural network composed of competitive learning layers. The input layer of the network simulates the neurons in the middle temporal (MT) area that selectively respond to the visual stimuli of the input motion patterns with different local velocities. The output layer of the network simulates the MSTd neurons that selectively respond to different types of optic flow motion patterns including planar, circular, radial, and spiral motions. Simulation results obtained from this model show that the behaviors of the output nodes of the network resemble very closely the known responsive properties of the MSTd neurons found neurophysiologically, such as the existence of three types of MSTd neurons that respond, respectively, to one, two, or three types of the input motion patterns with different position dependences, and the continuum of response selectivity formed by the three types of neurons.