Building momentum through networks: Bioimaging across the Americas.

In September 2023, the two largest bioimaging networks in the Americas, Latin America Bioimaging (LABI) and BioImaging North America (BINA), came together during a 1-week meeting in Mexico. This meeting provided opportunities for participants to interact closely with decision-makers from imaging core facilities across the Americas. The meeting was held in a hybrid format and attended in-person by imaging scientists from across the Americas, including Canada, the United States, Mexico, Colombia, Peru, Argentina, Chile, Brazil and Uruguay. The aims of the meeting were to discuss progress achieved over the past year, to foster networking and collaborative efforts among members of both communities, to bring together key members of the international imaging community to promote the exchange of experience and expertise, to engage with industry partners, and to establish future directions within each individual network, as well as common goals. This meeting report summarises the discussions exchanged, the achievements shared, and the goals set during the LABIxBINA2023: Bioimaging across the Americas meeting.

Fluorescence fluctuation-based super-resolution microscopy: Basic concepts for an easy start.

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of approximately half of the wavelength of visible light, that is, within the range of 200 to 350 nm. Fluorescence fluctuation-based super-resolution microscopy (FF-SRM) is a term used to encompass a collection of image analysis techniques that rely on the statistical processing of temporal variations of the fluorescence signal. FF-SRM aims to reduce the uncertainty of the location of fluorophores within an image, often improving spatial resolution by several tens of nanometers. FF-SRM is suitable for live-cell imaging due to its compatibility with most fluorescent probes and relatively simple instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are described. Their operational parameters are explained and guidance for their selection is provided.

Due to light's wave nature, an optical microscope's resolution range is 200 to 350 nanometers. Several techniques enhance resolution; this work encompasses several fluorescence fluctuation super-resolution (FF-SMR) methods capable of achieving nanoscopic scales. FF-SRM is known to be suitable for fixed or live-cell imaging and compatible with most conventional microscope setups found in a laboratory. However, each FF-SRM approach has its strengths and weaknesses, which depend directly on the underlying principles through which enhanced spatial resolution is achieved. Therefore, the basic concepts and principles behind diverse FF-SRM methods are revisited in this review. In addition, their operational parameters are explained, and guidance for their selection is provided for microscopists interested in FF-SRM.

Feature-based 3D+t descriptors of hyperactivated human sperm beat patterns.

The flagellar movement of the mammalian sperm plays a crucial role in fertilization. In the female reproductive tract, human spermatozoa undergo a process called capacitation which promotes changes in their motility. Only capacitated spermatozoa may be hyperactivated and only those that transition to hyperactivated motility are capable of fertilizing the egg. Hyperactivated motility is characterized by asymmetric flagellar bends of greater amplitude and lower frequency. Historically, clinical fertilization studies have used two-dimensional analysis to classify sperm motility, despite the inherently three-dimensional (3D) nature of sperm motion. Recent research has described several 3D beating features of sperm flagella. However, the 3D motility pattern of hyperactivated spermatozoa has not yet been characterized. One of the main challenges in classifying these patterns in 3D is the lack of a ground-truth reference, as it can be difficult to visually assess differences in flagellar beat patterns. Additionally, it is worth noting that only a relatively small proportion, approximately 10-20% of sperm incubated under capacitating conditions exhibit hyperactivated motility. In this work, we used a multifocal image acquisition system that can acquire, segment, and track sperm flagella in 3D+t. We developed a feature-based vector that describes the spatio-temporal flagellar sperm motility patterns by an envelope of ellipses. The classification results obtained using our 3D feature-based descriptors can serve as potential label for future work involving deep neural networks. By using the classification results as labels, it will be possible to train a deep neural network to automatically classify spermatozoa based on their 3D flagellar beating patterns. We demonstrated the effectiveness of the descriptors by applying them to a dataset of human sperm cells and showing that they can accurately differentiate between non-hyperactivated and hyperactivated 3D motility patterns of the sperm cells. This work contributes to the understanding of 3D flagellar hyperactive motility patterns and provides a framework for research in the fields of human and animal fertility.

3D+t feature-based descriptor for unsupervised flagellar human sperm beat classification.

Human spermatozoa must swim through the female reproductive tract, where they undergo a series of biochemical and biophysical reactions called capacitation, a necessary step to fertilize the egg. Capacitation promotes changes in the motility pattern. Historically, a two-dimensional analysis has been used to classify sperm motility and clinical fertilization studies. Nevertheless, in a natural environment sperm motility is three-dimensional (3D). Imaging flagella of freely swimming sperm is a difficult task due to their high beating frequency of up to 25 Hz. Very recent studies have described several sperm flagellum 3D beating features (curvature, torsion, asymmetries, etc.). However, up to date, the 3D motility pattern of hyperactivated spermatozoa has not been characterized. The main difficulty in classifying these patterns in 3D is the lack of a ground truth reference since differences in flagellar beat patterns are very difficult to assess visually. Moreover, only around 10-20% of induced to capacitate spermatozoa are truly capacitated, i.e., hyperactivated. We used an image acquisition system that can acquire, segment, and track spermatozoa flagella in 3D+t. In this work, we propose an original three-dimensional feature vector formed by ellipses describing the envelope of the 3D+t spatio-temporal flagellar sperm motility patterns. These features allowed compressing an unlabeled 3D+t dataset to separate hyperactivated cells from others (capacitated from non-capacitated cells) using unsupervised hierarchical clustering. Preliminary results show three main clusters of flagellar motility patterns. The first principal component of these 3D flagella measurements correlated with 2D OpenCASA head determinations as a first approach to validate the unsupervised classification, showing a reasonable correlation coefficient near to 0.7. Clinical relevance- The novelty of this work is defining a 3D+t feature-based descriptor consisting of a set of ellipses enveloping the flagellar motion of human sperm for its unsu-pervised classification. This is a new promising tool to determine the viability of human sperm to fertilize the egg.

Extending resolution within a single imaging frame.

The resolution of fluorescence microscopy images is limited by the physical properties of light. In the last decade, numerous super-resolution microscopy (SRM) approaches have been proposed to deal with such hindrance. Here we present Mean-Shift Super Resolution (MSSR), a new SRM algorithm based on the Mean Shift theory, which extends spatial resolution of single fluorescence images beyond the diffraction limit of light. MSSR works on low and high fluorophore densities, is not limited by the architecture of the optical setup and is applicable to single images as well as temporal series. The theoretical limit of spatial resolution, based on optimized real-world imaging conditions and analysis of temporal image stacks, has been measured to be 40 nm. Furthermore, MSSR has denoising capabilities that outperform other SRM approaches. Along with its wide accessibility, MSSR is a powerful, flexible, and generic tool for multidimensional and live cell imaging applications.