The rapid development of scientific CMOS (sCMOS) technology has greatly advanced optical microscopy for biomedical research with superior sensitivity, resolution, field-of-view, and frame rates. However, for sCMOS sensors, the parallel charge-voltage conversion and different responsivity at each pixel induces extra readout and pattern noise compared to charge-coupled devices (CCD) and electron-multiplying CCD (EM-CCD) sensors. This can produce artifacts, deteriorate imaging capability, and hinder quantification of fluorescent signals, thereby compromising strategies to reduce photo-damage to live samples. Here, we propose a content-adaptive algorithm for the automatic correction of sCMOS-related noise (ACsN) for fluorescence microscopy. ACsN combines camera physics and layered sparse filtering to significantly reduce the most relevant noise sources in a sCMOS sensor while preserving the fine details of the signal. The method improves the camera performance, enabling fast, low-light and quantitative optical microscopy with video-rate denoising for a broad range of imaging conditions and modalities. Scientific complementary metal-oxide semiconductor (sCMOS) cameras have advanced the imaging field, but they often suffer from additional noise compared to CCD sensors. Here the authors present a content-adaptive algorithm for the automatic correction of sCMOS-related noise for fluorescence microscopy.

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Fast and accurate sCMOS noise correction for fluorescence microscopy.

Does image normalization and intensity resolution impact texture classification

Mitochondria control eukaryotic cell fate by producing the energy needed to support life and the signals required to execute programmed cell death. The biochemical milieu is known to affect mitochondrial function and contribute to the dysfunctional mitochondrial phenotypes implicated in cancer and the morbidities of ageing. However, the physical characteristics of the extracellular matrix are also altered in cancer and in aging tissues. We demonstrate that cells sense the physical properties of the extracellular matrix and activate a mitochondrial stress response that adaptively tunes mitochondrial function via SLC9A1-dependent ion exchange and HSF1-dependent transcription. Overall, our data indicate that adhesion-mediated mechanosignaling may play an unappreciated role in the altered mitochondrial functions observed in aging and cancer. Graphical

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Adhesion-mediated mechanosignaling forces mitohormesis

Adhesion-mediated mechanosignaling forces mitohormesis.

DNA fluorescence in situ hybridization (FISH) is the technique of choice to map the position of genomic loci in three-dimensional (3D) space at the single allele level in the cell nucleus. High-throughput DNA FISH methods have recently been developed using complex libraries of fluorescently labeled synthetic oligonucleotides and automated fluorescence microscopy, enabling large-scale interrogation of genomic organization. Although the FISH signals generated by high-throughput methods can, in principle, be analyzed by traditional spot-detection algorithms, these approaches require user intervention to optimize each interrogated genomic locus, making analysis of tens or hundreds of genomic loci in a single experiment prohibitive. We report here the design and testing of two separate machine learning-based workflows for FISH signal detection in a high-throughput format. The two methods rely on random forest (RF) classification or convolutional neural networks (CNNs), respectively. Both workflows detect DNA FISH signals with high accuracy in three separate fluorescence microscopy channels for tens of independent genomic loci, without the need for manual parameter value setting on a per locus basis. In particular, the CNN workflow, which we named SpotLearn, is highly efficient and accurate in the detection of DNA FISH signals with low signal-to-noise ratio (SNR). We suggest that SpotLearn will be useful to accurately and robustly detect diverse DNA FISH signals in a high-throughput fashion, enabling the visualization and positioning of hundreds of genomic loci in a single experiment.

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SpotLearn: Convolutional Neural Network for Detection of Fluorescence In Situ Hybridization (FISH) Signals in High-Throughput Imaging Approaches.

attention given to probes and drugs (Supplementary Table 2). Currently, more than 800 distinct probes were acquired from six different library sources; while drugs, extracted from five sources (Supplementary Table 2 and Supplementary Note 3), account for more than 11,000 compounds—5,700 of which are annotated as approved drugs. To ensure that various chemical forms (such as stereoisomers or salts) are assigned to only one unique compound, each compound in the P&D portal is converted into its standardized form (Supplementary Note 2). However, for cases in which different stereoisomers show different biological impact, original forms still remain available. To further support the identification of suitable chemical tools, the annotation of P&D compounds is enriched with additional data, such as the bioactivities, targets and pathways in which these compounds take part. These data, obtained from and linked back to various external sources (Supplementary Table 3), are organized through ontologies. This ensures consistency between sources and contributes to a high data enrichment. A query can be saved simply by bookmarking its URL, and registered users can create custom compound sets from the arbitrary combination of compounds stored in the P&D library (Supplementary Note 8). The P&D portal is an up-to-date web resource with monthly updates that unifies various commercial and public bioactive compound libraries. Through its flexible and powerful filtering system, it helps users identify high-quality chemical tools for use in chemical biology and drug discovery research.

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sCMOS noise-correction algorithm for microscopy images

sCMOS Noise Correction Algorithm for Microscopy Images

Previously, we have shown that bulk microtubule (MT) movement correlates with neurite elongation, and blocking either dynein activity or MT assembly inhibits both processes. However, whether the contributions of MT dynamics and dynein activity to neurite elongation are separate or interdependent is unclear. Here, we investigated the underlying mechanism by testing the roles of dynein and MT assembly in neurite elongation of Aplysia and chick neurites using time-lapse imaging, fluorescent speckle microscopy, super-resolution imaging and biophysical analysis. Pharmacologically inhibiting either dynein activity or MT assembly reduced neurite elongation rates as well as bulk and individual MT anterograde translocation. Simultaneously suppressing both processes did not have additive effects, suggesting a shared mechanism of action. Single-molecule switching nanoscopy revealed that inhibition of MT assembly decreased the association of dynein with MTs. Finally, inhibiting MT assembly prevented the rise in tension induced by dynein inhibition. Taken together, our results suggest that MT assembly is required for dynein-driven MT translocation and neurite outgrowth.

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Dynein-mediated microtubule translocation powering neurite outgrowth in chick and Aplysia neurons requires microtubule assembly.

Abstract COVID took over the world starting in 2020. Everyone quickly “knew” about the novel coronavirus, but how much do they actually know about the virus behind COVID-19? This classroom activity gives students real-world practice in evaluating actual genetic sequences from SARS-CoV-2 and working with genome alignments to identify mutations and cluster different emergence patterns. This activity works through alignments, mutations/variants, protein folding, structure and function, and medical/ immunology implications of the different variants. There are seven parts to this activity, and each one can be incorporated alone into a lesson or collectively used for a lab, case study, or other supplemental activity to strengthen learning objectives in genetics, biology, immunology, and public health. This learning activity is scalable to different levels and has successfully been incorporated into K–12 education as well as college and graduate education.

https://doi.org/10.1525/abt.2023.85.5.285

Kristi McElmurry

Papers

sCMOS noise-correction algorithm for microscopy images

sCMOS Noise Correction Algorithm for Microscopy Images

Dynein-mediated microtubule translocation powering neurite outgrowth in chick and Aplysia neurons requires microtubule assembly.

Alpha, Delta, Omicron—Oh My! A SARS-CoV-2 Genome Alignment Activity to Understand Mutations and COVID Variants