Histology involves the observation of structural features in tissues using a microscope. While diffraction-limited optical microscopes are commonly used in histological investigations, their resolving capabilities are insufficient to visualize details at subcellular level. Although a novel set of super-resolution optical microscopy techniques can fulfill the resolution demands in such cases, the system complexity, high operating cost, lack of multi-modality, and low-throughput imaging of these methods limit their wide adoption for histological analysis. In this study, we introduce the photonic chip as a feasible high-throughput microscopy platform for super-resolution imaging of histological samples. Using cryopreserved ultrathin tissue sections of human placenta, mouse kidney, pig heart, and zebrafish eye retina prepared by the Tokuyasu method, we demonstrate diverse imaging capabilities of the photonic chip including total internal reflection fluorescence microscopy, intensity fluctuation-based optical nanoscopy, single-molecule localization microscopy, and correlative light-electron microscopy. Our results validate the photonic chip as a feasible imaging platform for tissue sections and pave the way for the adoption of super-resolution high-throughput multimodal analysis of cryopreserved tissue samples both in research and clinical settings.
We present an open-source implementation of the fluctuation-based nanoscopy method MUSICAL for ImageJ. This implementation improves the algorithm's computational efficiency and takes advantage of multi-threading to provide orders of magnitude faster reconstructions than the original MATLAB implementation. In addition, the plugin is capable of generating super-resolution videos from large stacks of time-lapse images via an interleaved reconstruction, thus enabling easy-to-use multi-color super-resolution imaging of dynamic systems.
Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super-resolving indicator function across a fine sample grid. A key step in the algorithm is the separation of the measurements into signal and noise subspaces, based on a single user-specified parameter called the threshold. The resulting image is strongly sensitive to this parameter and the subjectivity arising from multiple practical factors makes it difficult to determine the right rule of selection. We address this issue by proposing soft thresholding schemes derived from a new generalized framework for indicator function design. We show that the new schemes significantly alleviate the subjectivity and sensitivity of hard thresholding while retaining the super-resolution ability. We also evaluate the trade-off between resolution and contrast and the out-of-focus light rejection using the various indicator functions. Through this, we create significant new insights into the use and further optimization of MUSICAL for a wide range of practical scenarios.
Photonic chip-based total internal reflection fluorescence microscopy (c-TIRFM) is an emerging technology enabling a large TIRF excitation area decoupled from the detection objective. Additionally, due to the inherent multimodal nature of wide waveguides, it is a convenient platform for introducing temporal fluctuations in the illumination pattern. The fluorescence fluctuation-based nanoscopy technique multiple signal classification algorithm (MUSICAL) does not assume stochastic independence of the emitter emission and can therefore exploit fluctuations arising from other sources, as such multimodal illumination patterns. In this work, we demonstrate and verify the utilization of fluctuations in the illumination for super-resolution imaging using MUSICAL on actin in salmon keratocytes. The resolution improvement was measured to be 2.2–3.6-fold compared to the corresponding conventional images.
Optical-lattice illumination patterns help in pushing high spatial frequency components of the sample into the optical transfer function of a collection microscope. However, exploiting these high-frequency components require precise knowledge of illumination if reconstruction approaches similar to structured illumination microscopy are employed. Here, we present an alternate blind reconstruction approach that can provide super-resolution without the requirement of extra frames. For this, the property of exploiting temporal fluctuations in the sample emissions using “multiple signal classification algorithm” is extended aptly toward using spatial fluctuation of phase-modulated lattice illuminations for super-resolution. The super-resolution ability is shown for sinusoidal and multiperiodic lattice with approximately 3- and 6-fold resolution enhancements, respectively, over the diffraction limit.
Odontostomat., 11(4):387-392, 2017. RESUMEN:El grupo de neoplasias malignas de tejido blando de la región de cabeza y cuello en pacientes pediátricos está representado por carcinomas, sarcomas, melanomas y tumores de diferenciación incierta. La neoplasia más prevalente en la población pediátrica es el Rabdomiosarcoma, seguido por el carcinoma de células escamosas. Los rangos de presentación son muy amplios, siendo los grupos entre 2-6 años y 15-19 años los que presentan mayor incidencia. Se ha planteado que la etiología de estas neoplasias es incierta. El tratamiento de estas neoplasias es comúnmente de enfoque multimodal, combinando un procedimiento quirúrgico con quimioterapia y radioterapia. El pronóstico y sobrevida del paciente dependerán principalmente del momento en que se realice el diagnóstico de la lesión. Un diagnóstico y tratamiento temprano favorecen las posibilidades de sobrevida y el pronóstico del paciente. Este estudio corresponde a la 3ra parte de "Cáncer bucomaxilofacial en niños". Se hará referencia a los distintos tumores malignos del tejido blando en la población pediátrica en el territorio de cabeza y cuello, abarcando sus generalidades, etiología, epidemiología, tratamiento y pronóstico.PALABRAS CLAVE: cáncer oral, niño, maxilares, mandíbula, mucosa bucal, neoplasias maxilomandibulares. INTRODUCCIÓNEntre los diferentes tipos de neoplasias que se desarrollan en la población pediátrica a nivel de cabeza y cuello, el grupo de las neoplasias malignas de tejido blando está representado por carcinomas, sarcomas, melanomas y tumores de diferenciación incierta. En la Tabla I se observa la clasificación de las neoplasias malignas de tejidos blandos basado en la Es considerado que la presencia de carcinomas, a diferencia de los adultos, son poco frecuente en este grupo y en caso de presentarse, generalmente ocurre a nivel nasofaríngeo y se detecta más bien por metástasis en linfonodos cervicales (Santander, 2013).El grupo de los sarcomas representa entre un 5-15 % de las neoplasias malignas pediátricas, siendo el grupo de rabdomiosarcomas de cabeza y cuello el más común de estos (Divyambika et al., 2012). Según las estadísticas del programa de cáncer infantil en Chile (PINDA), la distribución porcentual de los sarcomas de partes blandas en la infancia corresponden al 6 % de las neoplasias malignas pediátricas y se presentan con mayor frecuencia en pacientes de sexo masculino. Según el MINSAL (2011), el rango de presentación varía entre los primeros días de vida hasta los 19 años de edad, donde la mayor incidencia es entre los grupos de 2 a 6 años y de 15 a 19 años de edad. En general, la edad de presentación de los sarcomas de partes blandas pediátricos es entre los 5-10 años de edad. Según el MINSAL la sobrevida del paciente dependerá del tamaño del tumor. Si este es menor a 5 cm, la sobrevida alcanza a un 81 %, por el contrario si es mayor a 5 cm la sobrevida disminuye drásticamente a un 16 %. Cabe destacar que si la detección es temprana, la probabilidad de mejoría y sobrevida es mayor (Vargas ...
Contrast in fluorescence microscopy images allows for the differentiation between different structures by their difference in intensities. However, factors such as point-spread function and noise may reduce it, affecting its interpretability. We identified that fluctuation of emitters in a stack of images can be exploited to achieve increased contrast when compared to the average and Richardson-Lucy deconvolution. We tested our methods on four increasingly challenging samples including tissue, in which case results were comparable to the ones obtained by structured illumination microscopy in terms of contrast.
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