Carolina Maria de Jess was a fiercely proud black Brazilian woman who lived in a So Paulo favela with her three illegitimate children (each with a different father). She had learned to read and write by continuing to study on her own after only two years of primary school. In 1958 fragments of her diary came to the attention of an enterprising journalist, Audlio Dantas, who helped her get it published. For a brief period, Carolina Maria de Jess became an international celebrity as the author of the best-selling book in Brazilian publishing history. For many reasons, however, Carolina fell from favor: the rise of a military dictatorship in 1964, which led to an accompanying reaction against social criticism, and especially the ways in which she handled her fame and related to the press and the literary elite. Within a few years, she was forced to move back into the favela and scavenge for a living. A brief flurry of publicity in 1969 about her fallen condition prompted a slight improvement in her circumstances, but she was soon forgotten again. Carolina died in 1977, on the verge of indigence. Her complete life story has never been told, and most Brazilians today are unaware that a black favelada in the 1960s became the symbol (to foreigners, at least) of the struggle to rise above poverty. Most Brazilians neither read her books nor consider them noteworthy. Evidently, the author of what The New York Times called a rarely matched essay on the meaning and the feeling of hunger, degradation, and want touched no nerve in the Brazilian sensibility.

Background: Eye movements reveal neurodegenerative disease processes due to overlap between oculomotor circuitry and disease-affected areas. Characterizing oculomotor behaviour in context of cognitive function may enhance disease diagnosis and monitoring. We therefore aimed to quantify cognitive impairment in neurodegenerative disease using saccade behaviour and neuropsychology. Methods: The Ontario Neurodegenerative Disease Research Initiative recruited individuals with neurodegenerative disease: one of Alzheimer’s disease, mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, or cerebrovascular disease. Patients (n=450, age 40-87) and healthy controls (n=149, age 42-87) completed a randomly interleaved pro- and anti-saccade task (IPAST) while their eyes were tracked. We explored the relationships of saccade parameters (e.g. task errors, reaction times) to one another and to cognitive domain-specific neuropsychological test scores (e.g. executive function, memory). Results: Task performance worsened with cognitive impairment across multiple diseases. Subsets of saccade parameters were interrelated and also differentially related to neuropsychology-based cognitive domain scores (e.g. antisaccade errors and reaction time associated with executive function). Conclusions: IPAST detects global cognitive impairment across neurodegenerative diseases. Subsets of parameters associate with one another, suggesting disparate underlying circuitry, and with different cognitive domains. This may have implications for use of IPAST as a cognitive screening tool in neurodegenerative disease.

Central to Siemerling’s impressive study of black Canadian writing is an optimism about the recuperative potential of historical knowledge. My contribution to the forum acknowledges that potential, while raising questions about the limits of such knowledge for addressing the persistence of racist ideologies and practices. My test case is Siemerling’s fine reading of Lawrence Hill’s novels.

Tomography produces complex volumetric datasets containing the entire internal structure and density of an object in three dimensions (3D). Interpreting volumetric data requires 3D visualization but needs specialized software distinguishable from more familiar tools used in animation for 3D surface data. This tutorial reviews 3D visualization techniques for volumetric data using the open-source tomviz software package. A suite of tools including two-dimensional (2D) slices, surface contours, and full volume rendering provide quantitative and qualitative analysis of volumetric information. The principles outlined here are applicable to a wide range of 3D tomography techniques and can be applied to volumetric datasets beyond materials characterization.

Electron tomography has become a valuable and widely used tool for studying the three-dimensional nanostructure of materials and biological specimens. However, the incomplete tilt range provided by conventional sample holders limits the fidelity and quantitative interpretability of tomographic images by leaving a “missing wedge” of unknown information in Fourier space. Imaging over a complete range of angles eliminates missing wedge artifacts and dramatically improves tomogram quality. Full-range tomography is usually accomplished using needle-shaped samples milled from bulk material with focused ion beams, but versatile specimen preparation methods for nanoparticles and other fine powders are lacking. In this work, we present a new preparation technique in which powder specimens are supported on carbon nanofibers that extend beyond the end of a tungsten needle. Using this approach, we produced tomograms of platinum fuel cell catalysts and gold-decorated strontium titanate photocatalyst specimens. Without the missing wedge, these tomograms are free from elongation artifacts, supporting straightforward automatic segmentation and quantitative analysis of key materials properties such as void size and connectivity, and surface area and curvature. This approach may be generalized to other samples that can be dispersed in liquids, such as biological structures, creating new opportunities for high-quality electron tomography across disciplines.