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Current brain mapping methods highly depend on the regularity, or commonality, of anatomical structure, by forcing the same atlas to be matched to different brains. As a result, individualized structural information can be overlooked. Recently, we conceptualized a new type of cortical folding pattern called the 3-hinge gyrus (3HG), which is defined as the conjunction of gyri coming from three directions. Many studies have confirmed that 3HGs are not only widely existing on different brains, but also possess both common and individual patterns. In this work, we put further effort, based on the identified 3HGs, to establish the correspondences of individual 3HGs. We developed a learning-based embedding framework to encode individual cortical folding patterns into a group of anatomically meaningful embedding vectors (cortex2vector). Each 3HG can be represented as a combination of these embedding vectors via a set of individual specific combining coefficients. In this way, the regularity of folding pattern is encoded into the embedding vectors, while the individual variations are preserved by the multi-hop combination coefficients. Results show that the learned embeddings can simultaneously encode the commonality and individuality of cortical folding patterns, as well as robustly infer the complicated many-to-many anatomical correspondences among different brains.

 

Despite the availability of Cas9 variants with varied protospacer-adjacent motif (PAM) compatibilities, some genomic loci—especially those with pyrimidine-rich PAM sequences—remain inaccessible by high-activity Cas9 proteins. Moreover, broadening PAM sequence compatibility through engineering can increase off-target activity. With directed evolution, we generated four Cas9 variants that together enable targeting of most pyrimidine-rich PAM sequences in the human genome. Using phage-assisted noncontinuous evolution and eVOLVER-supported phage-assisted continuous evolution, we evolved Nme2Cas9, a compact Cas9 variant, into variants that recognize single-nucleotide pyrimidine-PAM sequences. We developed a general selection strategy that requires functional editing with fully specified target protospacers and PAMs. We applied this selection to evolve high-activity variants eNme2-T.1, eNme2-T.2, eNme2-C and eNme2-C.NR. Variants eNme2-T.1 and eNme2-T.2 offer access to N₄TN PAM sequences with comparable editing efficiencies as existing variants, while eNme2-C and eNme2-C.NR offer less restrictive PAM requirements, comparable or higher activity in a variety of human cell types and lower off-target activity at N₄CN PAM sequences.

 

Two foundational concepts in biology education are 1) offspring are not identical to their parents, and 2) organisms undergo changes throughout their lives. These concepts are included in both international and U.S. curricular standards. Research in psychology has shown that children often have difficulty understanding these concepts, as they are inconsistent with their intuitive theories of the biological world. Additionally, prior research suggests that diagrams are commonly used in instruction and that their features influence student learning. Given this prior work, we explored the characteristics of life cycle diagrams and discuss possible implications for student learning. We examined 75 life cycle diagrams from books, including five biology or general science textbooks and 25 specialized trade books focusing on biology for children. We also examined 633 life cycle diagrams from a publicly available online database of science diagrams. Most diagrams failed to show any within-species variability. Additionally, many diagrams had perceptually rich backgrounds, which prior research suggests might hinder learning. We discuss how the design characteristics of diagrams may reinforce students’ intuitive theories of biology, which might make it difficult for students to understand key biological concepts in the future. 

Reproducibility is fundamental to science, and an important component of reproducibility is computational reproducibility: the ability of a researcher to recreate the results of a published study using the original author’s raw data and code. Although most people agree that computational reproducibility is important, it is still difficult to achieve in practice. In this article, the authors describe their approach to enabling computational reproducibility for the 12 articles in this special issue of Socius about the Fragile Families Challenge. The approach draws on two tools commonly used by professional software engineers but not widely used by academic researchers: software containers (e.g., Docker) and cloud computing (e.g., Amazon Web Services). These tools made it possible to standardize the computing environment around each submission, which will ease computational reproducibility both today and in the future. Drawing on their successes and struggles, the authors conclude with recommendations to researchers and journals. 

Rhesus macaques are physiologically similar to humans and, thus, have served as useful animal models of human diseases including cardiovascular disease. The purpose of this study was to characterize the distribution, composition, and phenotype of macrophages in heart tissues of very young (fetus: 0.5 years, n = 6), young adult (2–12 years, n = 12), and older adult (13–24 years, n = 9) rhesus macaques using histopathology and immunofluorescence microscopy. Results demonstrated that macrophages were uniformly distributed throughout the heart in animals of all age groups and were more prevalent than CD3-positve T-cells and CD20-positive B-cells. Macrophages comprised approximately 2% of heart tissue cells in the younger animals and increased to a mean of nearly 4% in the older adults. CD163-positive macrophages predominated over HAM56-positive and CD206-positive macrophages, and were detected at significantly higher percentage in the animals between 13 and 24 years of age, as well as in heart tissues exhibiting severe histopathology or inflammation in animals of all age groups. In vivo dextran labeling and retention indicated that approximately half of the macrophages were longer lived in healthy adult heart tissues and may comprise the tissue-resident population of macrophages. These results provide a basis for continued studies to examine the specific functional roles of macrophage subpopulations in heart tissues during homeostasis and in cardiovascular disease for then developing intervention strategies.

 

Metastatic castration-resistant prostate cancer is typically lethal, exhibiting intrinsic or acquired resistance to second-generation androgen-targeting therapies and minimal response to immune checkpoint inhibitors¹. Cellular programs driving resistance in both cancer and immune cells remain poorly understood. We present single-cell transcriptomes from 14 patients with advanced prostate cancer, spanning all common metastatic sites. Irrespective of treatment exposure, adenocarcinoma cells pervasively coexpressed multiple androgen receptor isoforms, including truncated isoforms hypothesized to mediate resistance to androgen-targeting therapies^2,3. Resistance to enzalutamide was associated with cancer cell–intrinsic epithelial–mesenchymal transition and transforming growth factor-β signaling. Small cell carcinoma cells exhibited divergent expression programs driven by transcriptional regulators promoting lineage plasticity and HOXB5, HOXB6 and NR1D2 (refs.^4–6). Additionally, a subset of patients had high expression of dysfunction markers on cytotoxic CD8⁺T cells undergoing clonal expansion following enzalutamide treatment. Collectively, the transcriptional characterization of cancer and immune cells from human metastatic castration-resistant prostate cancer provides a basis for the development of therapeutic approaches complementing androgen signaling inhibition.