Circadian pacemaker coupling by multi-peptidergic neurons in the cockroach Leucophaea maderae

Lesion and transplantation studies in the cockroach, Leucophaea maderae, have located its bilaterally symmetric circadian pacemakers necessary for driving circadian locomotor activity rhythms to the accessory medulla of the optic lobes. The accessory medulla comprises a network of peptidergic neurons, including pigment-dispersing factor (PDF)-expressing presumptive circadian pacemaker cells. At least three of the PDF-expressing neurons directly connect the two accessory medullae, apparently as a circadian coupling pathway. Here, the PDF-expressing circadian coupling pathways were examined for peptide colocalization by tracer experiments and double-label immunohistochemistry with antisera against PDF, FMRFamide, and Asn13-orcokinin. A fourth group of contralaterally projecting medulla neurons was identified, additional to the three known groups. Group one of the contralaterally projecting medulla neurons contained up to four PDF-expressing cells. Of these, three medium-sized PDF-immunoreactive neurons coexpressed FMRFamide and Asn13-orcokinin immunoreactivity. However, the contralaterally projecting largest PDF neuron showed no further peptide colocalization, as was also the case for the other large PDF-expressing medulla cells, allowing the easy identification of this cell group. Although two-thirds of all PDF-expressing medulla neurons coexpressed FMRFamide and orcokinin immunoreactivity in their somata, colocalization of PDF and FMRFamide immunoreactivity was observed in only a few termination sites. Colocalization of PDF and orcokinin immunoreactivity was never observed in any of the terminals or optic commissures. We suggest that circadian pacemaker cells employ axonal peptide sorting to phase-control physiological processes at specific times of the day

Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study

IntroductionThe use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in large language models. While AI provides widespread benefits, including editing for fluency and clarity, it also has drawbacks, including fabricated content, perpetuation of bias, and lack of accountability. The editorial board of Regional Anesthesia & Pain Medicine (RAPM) therefore sought to develop best practices for AI usage and disclosure. Methods A steering committee from the American Society of Regional Anesthesia and Pain Medicine used a modified Delphi process to address definitions, disclosure requirements, authorship standards, and editorial oversight for AI use in publishing. The committee reviewed existing publication guidelines and identified areas of ambiguity, which were translated into questions and distributed to an expert workgroup of authors, reviewers, editors, and AI researchers. Results Two survey rounds, with 91% and 87% response rates, were followed by focused discussion and clarification to identify consensus recommendations. The workgroup achieved consensus on recommendations to authors about definitions of AI, required items to report, disclosure locations, authorship stipulations, and AI use during manuscript preparation. The workgroup formulated recommendations to reviewers about monitoring and evaluating the responsible use of AI in the review process, including the endorsement of AI-detection software, identification of concerns about undisclosed AI use, situations where AI use may necessitate the rejection of a manuscript, and use of checklists in the review process. Finally, there was consensus about AI-driven work, including required and optional disclosures and the use of checklists for AI-associated research. Discussion Our modified Delphi study identified practical recommendations on AI use during the scientific writing and editorial process. The workgroup highlighted the need for transparency, human accountability, protection of patient confidentiality, editorial oversight, and the need for iterative updates. The proposed framework enables authors and editors to harness AI’s efficiencies while maintaining the fundamental principles of responsible scientific communication and may serve as an example for other journals