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English language copyediting poses significant barriers to global health authors in academic publishing. Editing is too expensive for most researchers in low-income countries, and large language models (LLMs) like ChatGPT may offer a cost-effective alternative. The technology, however, has been criticized for its biases and inaccuracies. In a preliminary, in-depth case comparison, we compared the number and quality of corrections made by U-M GPT, a secure, University of Michigan-hosted generative AI tool, to those from Grammarly and a human editor to text from two draft papers written by Ugandan sexual and reproductive health researchers. Overall, U-M GPT made about three times as many corrections compared to the human editor and about ten times more than Grammarly. U-M GPT was the least discriminating in terms of quality: only 61% (51/83) of its corrections were judged as improvements. Despite this, U-M GPT has advantages, such as a broad scope of correction types, fast turnaround, and no cost. Its disadvantages, which reflect shortcomings of LLMs more broadly, include the need for prompt engineering skill, careful review of corrections, and high environmental costs due to energy consumption. Additional concerns involve data privacy and content moderation policies that restrict discussions on topics deemed as sensitive; these included words related to sexual and reproductive health. Although LLMs could improve equity, efficiency, and productivity, several important issues should be considered when using the technology. Larger follow-up investigations are needed to confirm our findings. Authors using LLMs should consult journal guidelines and disclose their use.

HIV infection dysregulates the B cell compartment, affecting memory B cell formation and the antibody response to infection and vaccination. Understanding the B cell response to SARS-CoV-2 in people living with HIV (PLWH) may explain the increased morbidity, reduced vaccine efficacy, reduced clearance, and intra-host evolution of SARS-CoV-2 observed in some HIV-1 coinfections. We compared B cell responses to COVID-19 in PLWH and HIV negative (HIV-ve) patients in a cohort recruited in Durban, South Africa, during the first pandemic wave in July 2020 using detailed flow cytometry phenotyping of longitudinal samples with markers of B cell maturation, homing, and regulatory features. This revealed a coordinated B cell response to COVID-19 that differed significantly between HIV-ve and PLWH. Memory B cells in PLWH displayed evidence of reduced germinal centre (GC) activity, homing capacity, and class-switching responses, with increased PD-L1 expression, and decreased Tfh frequency. This was mirrored by increased extrafollicular (EF) activity, with dynamic changes in activated double negative (DN2) and activated naïve B cells, which correlated with anti-RBD-titres in these individuals. An elevated SARS-CoV-2-specific EF response in PLWH was confirmed using viral spike and RBD bait proteins. Despite similar disease severity, these trends were highest in participants with uncontrolled HIV, implicating HIV in driving these changes. EF B cell responses are rapid but give rise to lower affinity antibodies, less durable long-term memory, and reduced capacity to adapt to new variants. Further work is needed to determine the long-term effects of HIV on SARS-CoV-2 immunity, particularly as new variants emerge. This work was supported by a grant from the Wellcome Trust to the Africa Health Research Institute (Wellcome Trust Strategic Core Award [grant number 201433/Z/16/Z]). Additional funding was received from the South African Department of Science and Innovation through the National Research Foundation (South African Research Chairs Initiative [grant number 64809]), and the Victor Daitz Foundation.

High hypoxia-inducible factor-2α (HIF-2α) protein levels predict poor outcome in neuroblastoma, and hypoxia dedifferentiates cultured neuroblastoma cells toward a neural crest-like phenotype. Here, we identify HIF-2α as a marker of normoxic neural crest-like neuroblastoma tumor-initiating/stem cells (TICs) isolated from patient bone marrows. Knockdown of HIF-2α reduced VEGF expression and induced partial sympathetic neuronal differentiation when these TICs were grown in vitro under stem cell-promoting conditions. Xenograft tumors of HIF-2α-silenced cells were widely necrotic, poorly vascularized, and resembled the bulk of tumor cells in clinical neuroblastomas by expressing additional sympathetic neuronal markers, whereas control tumors were immature, well-vascularized, and stroma-rich. Thus, HIF-2α maintains an undifferentiated state of neuroblastoma TICs. Because low differentiation is associated with poor outcome and angiogenesis is crucial for tumor growth, HIF-2α is an attractive target for neuroblastoma therapy.