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Craniosynostosis is a group of disorders of premature calvarial suture fusion. The identity of the calvarial stem cells (CSCs) that produce fusion-driving osteoblasts in craniosynostosis remains poorly understood. Here we show that both physiologic calvarial mineralization and pathologic calvarial fusion in craniosynostosis reflect the interaction of two separate stem cell lineages; a previously identified cathepsin K (CTSK) lineage CSC1 (CTSK+ CSC) and a separate discoidin domain-containing receptor 2 (DDR2) lineage stem cell (DDR2+ CSC) that we identified in this study. Deletion of Twist1, a gene associated with craniosynostosis in humans2,3, solely in CTSK+ CSCs is sufficient to drive craniosynostosis in mice, but the sites that are destined to fuse exhibit an unexpected depletion of CTSK+ CSCs and a corresponding expansion of DDR2+ CSCs, with DDR2+ CSC expansion being a direct maladaptive response to CTSK+ CSC depletion. DDR2+ CSCs display full stemness features, and our results establish the presence of two distinct stem cell lineages in the sutures, with both populations contributing to physiologic calvarial mineralization. DDR2+ CSCs mediate a distinct form of endochondral ossification without the typical haematopoietic marrow formation. Implantation of DDR2+ CSCs into suture sites is sufficient to induce fusion, and this phenotype was prevented by co-transplantation of CTSK+ CSCs. Finally, the human counterparts of DDR2+ CSCs and CTSK+ CSCs display conserved functional properties in xenograft assays. The interaction between these two stem cell populations provides a new biologic interface for the modulation of calvarial mineralization and suture patency.

Large language model (LLM) chatbots possess a remarkable capacity to synthesize complex information into concise, digestible summaries across a wide range of orthopedic subject matter. As LLM chatbots become widely available they will serve as a powerful, accessible resource that patients, clinicians, and researchers may reference to obtain information about orthopedic science and clinical management. Here, we examined the performance of three well‐known and easily accessible chatbots–ChatGPT, Bard, and Bing AI–in responding to inquiries relating to clinical management and orthopedic concepts. Although all three chatbots were found to be capable of generating relevant responses, ChatGPT outperformed Bard and BingAI in each category due to its ability to provide accurate and complete responses to orthopedic queries. Despite their promising applications in clinical management, shortcomings observed included incomplete responses, lack of context, and outdated information. Nonetheless, the ability for these LLM chatbots to address these inquires has largely yet to be evaluated and will be critical for understanding the risks and opportunities of LLM chatbots in orthopedics. [ABSTRACT FROM AUTHOR]

Fecundity seems to stop declining and plateaus at low levels very late in Drosophila melanogaster populations. Here we test whether this apparent cessation of reproductive aging by a population, herein referred to as fecundity plateaus, is robust under various environmental influences: namely, male age and nutrition. The effect of male age on late age fecundity patterns was tested by supplying older females with young males before average population fecundity declined to plateau levels. The second possible environmental influence we tested was nutrition and whether late-life fecundity plateaus arise from a decline in the calories available for reproduction. This hypothesis was tested by comparing average daily female fecundity with both low- and high-lifetime nutrition. Both hypotheses were tested by measuring mid- and late-life fecundity for each cohort under the various environmental influences, and statistically testing whether fecundity stops declining and plateaus at late ages. These experiments demonstrate that mid- and late-life population fecundity patterns are significantly affected by the age of males and nutrition level. However, male age and nutrition level did not affect the existence of late-life fecundity plateaus, which demonstrates the robustness of our earlier findings. These results do not address any issue pertaining to the possible role, if any, of lifelong inter-individual heterogeneity in Drosophila fecundity.