Comment

Most scientific instruments currently discard rich streams of commands, data and metadata from which AI systems could learn to conduct experiments with expert-level decision-making and troubleshooting skills. Recording and using this data at scale requires rethinking what data to store, incentivizing large-scale cooperation, and determining how to quantify the reliability of such autonomous systems.

As connectomics datasets grow in size and quantity, future reconstruction methods will have to work with minimal or no human supervision. For that, we will need methods that can quantify data and model uncertainty in order to assess the level of trust we can put in the downstream analysis of connectomes.

Functional connectomics is a new approach, involving calcium imaging of neuronal activity followed by correlated electron microscopy connectomics of the same neurons, that relates connections made by neurons to their in vivo function. I believe that this combined approach for studying structure and function will continue with ever-larger networks, including entire nervous systems.

Advances in connectomics are enabling the mapping of connectomes across individuals, sexes or species. Multiple comparisons enable the categorization of differences in these wiring diagrams as either technical or biological variability, or those that might impact circuit function. Testing these predictions experimentally will help us understand how evolution operates in neural circuits.

Connectomics has so far outpaced the Moore’s law predictions about technological progress. At this pace, many whole-brain connectomes and connectomic screening will soon be realistic.

Detailed maps, or connectomes, of the fly brain and nervous system reveal how circuit architecture (wiring) shapes both neural activity and behavior. These maps already demonstrate that it is possible to predict function from structure, and provide the essential foundation for biologically realistic models of circuit function.

Connectomics, the comprehensive mapping of neural circuits at nanoscale resolution, has historically relied on electron microscopy (EM), both transmission (TEM) and scanning (SEM). However, as connectomics scales towards larger brain volumes and whole mammalian brains, substantial technical challenges emerge. Here, we highlight key challenges and advancing approaches that hold promise, particularly those that integrate three-dimensional, multi-resolution and time-resolved imaging to capture both long-range and local wiring, down to supramolecular resolution.

Experiments with high-risk pathogens are routinely conducted under strict conditions of biosafety and biosecurity. In this Comment, we propose a Minimum Information about a High Containment Laboratory Experiment (MIHCLE) reporting standard. Although conceived particularly for work in biosafety level (BSL) 4 laboratories, it can be generally applicable to any research performed in both high (BSL-3) and maximum (BSL-4) containment facilities.

As a computational neuroscientist, I study the brain through models that reduce it to data points and 3D reconstructions, yet watching Dr. Obaid perform live neurosurgeries showed me what models alone could not capture. Here I describe how witnessing the living human brain — fragile, unique, and devoid of clear landmarks — became a turning point, reminding me that our models must not only simulate the brain, but also stay grounded in its complexity and individuality.

As a vast and diverse country, Brazil faces significant regional disparities that highlight the urgent need to democratize access to scientific resources and opportunities. To help develop solutions to address this challenge, we launched the Bioimaging Brasil initiative, aimed at expanding access to advanced bioimaging techniques such as intravital microscopy. By leveraging a broad spectrum of technologies — from standard microscopes paired with cell phone cameras to cutting-edge laser scanning confocal microscopes — the initiative fosters collaboration, strengthens research capacity and serves as a global model for equitable technology dissemination.

Advances in cellular physiology research have created the need to visualize metabolic processes in both time and space. Vibrational microscopy has emerged as a promising method at the forefront of this field. Here, we summarize recent progress and offer perspectives on the application of vibrational microscopy for uncovering metabolic actions in vivo.

Raman microscopy enables label-free, high-resolution molecular imaging, treating the entire Raman spectrum as a phenotype for profiling cell heterogeneity. While challenges remain in speed, sensitivity and resolution, advancements in coherent Raman scattering, spatial multiplexing and Raman probe techniques continue to expand its potential for characterizing complex biological systems and fostering exploratory and data-driven biology.

Vibrational microscopy opens a new window onto understanding life at the molecular level. Yet the vibrational signals from chemical bonds are weaker than the fluorescence signal from a dye by many orders of magnitude. Detecting such weak signal from a tight focus under a microscope is extremely challenging. I have devoted my career to overcoming such a daunting barrier through the development of advanced chemical microscopes over the past 25 years. In this historical Comment, I am honored to share my journey of serendipity-driven innovation and entrepreneurship in the growing field of chemical imaging, with a focus on the invention of vibrational photothermal microscopy.

It has been 25 years since the first 3D coherent Raman microscope was reported. Owing to the contributions of many researchers worldwide, coherent Raman microscopy has blossomed as a field of its own and found wide applications in chemical, material, environmental, biological and medical applications. Here I highlight the emergence of nonlinear optical spectroscopy and microscopy and their key technical milestones that led to the rapid expansion and wide use of this imaging modality for biomedicine.

Discussions at a recent conference on microscopy technology dissemination spotlighted the importance of setting technology adoption capable of producing scientific outcome as the end goal. This Comment examines current global efforts in microscopy dissemination and summarizes the challenges and paths forward.

In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm.

Spatial proteomics holds the potential to transform the study of proteins in situ in complex tissues, but it needs to be integrated with other layers of omics data to gain a holistic view of cellular function, heterogeneity and interactions, and the underlying mechanisms of these processes. I highlight current challenges and emerging opportunities for multi-omic spatial protein profiling to advance basic research and translational applications.

Spatial proteomics is advancing rapidly, transforming physiological and biomedical research by enabling the study of how multicellular structures and intercellular communication shape tissue function in health and disease. Through the analysis of large human tissue collections, spatial proteomics will reveal the complexities of human tissues and uncover multicellular modules that can serve as drug targets and diagnostics, paving the way for precision medicine and revolutionizing histopathology.

Multiplexed tissue imaging has transformed tissue biology by revealing cellular diversity and interactions, but the analysis of its massive datasets remains a bottleneck. Here, we provide an overview of computational advancements, discuss current challenges and envision an AI-driven future in which integrated tools streamline analysis and visualization, unlocking the full potential of multiplexed imaging for breakthroughs in spatial biology.

Spatial mass spectrometry (MS)-proteomics is a rapidly evolving technology, particularly in the form of Deep Visual Proteomics (DVP), which allows the study of single cells directly in their native environment. We believe that this approach will reshape our understanding of tissue biology and redefine fundamental concepts in cell biology, tissue physiology and ultimately human health and disease.