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In Hawai‘i and across much of Oceania, Pacific Islanders celebrate the connections between our islands and the ocean that surrounds us. Since the beginning of time, we have relied upon precise observations of marine and celestial realms to intentionally navigate thousands of miles across vast expanses of open ocean. Through our migrations, we have created—and continue to create—purposeful relationships by observing the movements of swells, weather patterns, celestial bodies, and marine life. In direct opposition to colonial Western thought, we view Oceania as a metaphorical road that connects rather than separates island people (Hau’ofa, 1994). As descendants of the ocean, the dearth of Native Hawaiians and Pacific Islanders (NHPIs) in ocean science seems inconsonant. We wonder, where are all our island people in the ocean sciences? In better defining the persistent, systemic, and collective barriers that NHPIs face within Western society and the academy, we identify gaps that conventional professional development programs aimed at minoritized groups in the geosciences have been unsuccessful in filling. We share lessons learned from building two wa‘a (canoes) in programs that center oceanic ways of knowing. 

Purpose Prior studies show convolutional neural networks predicting self-reported race using x-rays of chest, hand and spine, chest computed tomography, and mammogram. We seek an understanding of the mechanism that reveals race within x-ray images, investigating the possibility that race is not predicted using the physical structure in x-ray images but is embedded in the grayscale pixel intensities. Approach Retrospective full year 2021, 298,827 AP/PA chest x-ray images from 3 academic health centers across the United States and MIMIC-CXR, labeled by self-reported race, were used in this study. The image structure is removed by summing the number of each grayscale value and scaling to percent per image (PPI). The resulting data are tested using multivariate analysis of variance (MANOVA) with Bonferroni multiple-comparison adjustment and class-balanced MANOVA. Machine learning (ML) feed-forward networks (FFN) and decision trees were built to predict race (binary Black or White and binary Black or other) using only grayscale value counts. Stratified analysis by body mass index, age, sex, gender, patient type, make/model of scanner, exposure, and kilovoltage peak setting was run to study the impact of these factors on race prediction following the same methodology. Results MANOVA rejects the null hypothesis that classes are the same with 95% confidence (F 7.38, P < 0.0001) and balanced MANOVA (F 2.02, P < 0.0001). The best FFN performance is limited [area under the receiver operating characteristic (AUROC) of 69.18%]. Gradient boosted trees predict self-reported race using grayscale PPI (AUROC 77.24%). Conclusions Within chest x-rays, pixel intensity value counts alone are statistically significant indicators and enough for ML classification tasks of patient self-reported race. 

Academic science is becoming increasingly recognized for fostering a toxic workplace culture. A growing number of studies show that hierarchical structure, intense competition, excessive workload expectations, and lack of adequate financial support create an unhealthy work environment (Stephan, 2012; Callier and Vanderford, 2014; Hall, 2023). Science in academia is flooded with underpaid and underappreciated students and postdocs, and sadly, academic institutions are not adequately addressing the urgent need to fix this unsustainable structure (Stephan, 2012; Callier and Vanderford, 2014). This article is our plea to academic science: it is time to change the culture of our workplace and better support the next generation of scientists. 

Conventionally, the size, shape, and biomechanics of cartilages are determined by their voluminous extracellular matrix. By contrast, we found that multiple murine cartilages consist of lipid-filled cells called lipochondrocytes. Despite resembling adipocytes, lipochondrocytes were molecularly distinct and produced lipids exclusively through de novo lipogenesis. Consequently, lipochondrocytes grew uniform lipid droplets that resisted systemic lipid surges and did not enlarge upon obesity. Lipochondrocytes also lacked lipid mobilization factors, which enabled exceptional vacuole stability and protected cartilage from shrinking upon starvation. Lipid droplets modulated lipocartilage biomechanics by decreasing the tissue’s stiffness, strength, and resilience. Lipochondrocytes were found in multiple mammals, including humans, but not in nonmammalian tetrapods. Thus, analogous to bubble wrap, superstable lipid vacuoles confer skeletal tissue with cartilage-like properties without “packing foam–like” extracellular matrix. 

Photosymbioses, intimate interactions between photosynthetic algal symbionts and heterotrophic hosts, are well known in invertebrate and protist systems. Vertebrate animals are an exception where photosynthetic microorganisms are not often considered part of the normal vertebrate microbiome, with a few exceptions in amphibian eggs. Here, we review the breadth of vertebrate diversity and explore where algae have taken hold in vertebrate fur, on vertebrate surfaces, in vertebrate tissues, and within vertebrate cells. We find that algae have myriad partnerships with vertebrate animals, from fishes to mammals, and that those symbioses range from apparent mutualisms to commensalisms to parasitisms. The exception in vertebrates, compared with other groups of eukaryotes, is that intracellular mutualisms and commensalisms with algae or other microbes are notably rare. We currently have no clear cell-in-cell (endosymbiotic) examples of a trophic mutualism in any vertebrate, while there is a broad diversity of such interactions in invertebrate animals and protists. This functional divergence in vertebrate symbioses may be related to vertebrate physiology or a byproduct of our adaptive immune system. Overall, we see that diverse algae are part of the vertebrate microbiome, broadly, with numerous symbiotic interactions occurring across all vertebrate and many algal clades. These interactions are being studied for their ecological, organismal, and cellular implications. This synthesis of vertebrate–algal associations may prove useful for the development of novel therapeutics: pairing algae with medical devices, tissue cultures, and artificial ecto- and endosymbioses. 

Polar fishes have evolved antifreeze proteins (AFPs) that allow them to survive in subzero temperatures. We performed deep transcriptomic sequencing on a postlarval/juvenile variegated snailfish, Liparis gibbus (Actinopterygii: Scorpaeniformes: Cottoidei: Liparidae), living in an iceberg habitat (−2°C) in Eastern Greenland and report detection of highly expressed transcripts that code for putative AFPs from 2 gene families, Type I and LS-12-like proteins (putative Type IV AFPs). The transcripts encoding both proteins have expression levels among the top <1% of expressed genes in the fish. The Type I AFP sequence is different from a reported Type I AFP from the same species, possibly expressed from a different genetic locus. While prior findings from related adult sculpins suggest that LS-12-like/Type IV AFPs may not have a role in antifreeze protection, our finding of very high relative gene expression of the LS-12-like gene suggests that highly active transcription of the gene is important to the fish in the iceberg habitat and raises the possibility that weak or combinatorial antifreeze activity could be beneficial. These findings highlight the physiological importance of antifreeze proteins to the survival of fishes living in polar habitats.