Search

Background: The optimal timing of vaccination with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines after cellular therapy is incompletely understood. The objectives of this study are to determine whether humoral and cellular responses after SARS-CoV-2 vaccination differ if initiated <4 months versus 4-12 months after cellular therapy., Methods: We conducted a multicenter, prospective, observational study at 30 cancer centers in the United States. SARS-CoV-2 vaccination was administered as part of routine care. We obtained blood prior to and after vaccinations at up to 5 time points and tested for SARS-CoV-2 spike (anti-S) IgG in all participants and neutralizing antibodies for Wuhan D614G, Delta B.1.617.2, and Omicron B.1.1.529 strains, as well as SARS-CoV-2-specific T-cell receptors, in a subgroup., Results: We enrolled 466 allogeneic hematopoietic cell transplantation (HCT) (n = 231), autologous HCT (n = 170), and chimeric antigen receptor T-cell (CAR-T-cell) therapy (n = 65) recipients between April 2021 and June 2022. Humoral and cellular responses did not significantly differ among participants initiating vaccinations <4 months versus 4-12 months after cellular therapy. Anti-S IgG ≥2500 U/mL was correlated with high neutralizing antibody titers and attained by the last time point in 70%, 69%, and 34% of allogeneic HCT, autologous HCT, and CAR-T-cell recipients, respectively. SARS-CoV-2-specific T-cell responses were attained in 57%, 83%, and 58%, respectively. Pre-cellular therapy SARS-CoV-2 infection or vaccination and baseline B-cell count were key predictors of post-cellular therapy immunity., Conclusions: These data support mRNA SARS-CoV-2 vaccination prior to, and reinitiation 3 to 4 months after, cellular therapies with allogeneic HCT, autologous HCT, and CAR-T-cell therapy., Competing Interests: Potential conflicts of interest . J. A. H—research funding: AlloVir, Geovax, Merck; consulting: Pfizer, Gilead, Moderna, Geovax, AlloVir. J. H. Y.—research funding: AlloVir, Ansun, Cidara, F2G, GSK, NobelPharma, Pulmocide, Scynexis, Shire/Takeda. L. W. L.—employment and equity holder in Adaptive Biotechnologies Corporation. M. V. D.—research funding: Janssen, Roche/Genentech. R. N.—consulting: Ono Pharmaceutical, Jazz Pharmaceuticals, Bluebird Bio, Omeros Pharmaceutical, Sanofi, Pfizer. J. M.—consulting: Evision, Kite, Allovir, Bristol Myers Squibb, Novartis, CRISPR, Nektar, Caribiou Bio, Sana Technologies, Legend Biotech. S. D.—research funding: MSK Leukemia SPORE Career Enhancement Program and MSK Gerstner Physician Scholar program. J. J. A.—employment: National Marrow Donor Program; Advisory Board: AscellaHealth, Takeda. M. H.—research support/funding: Takeda Pharmaceutical Company, ADC Therapeutics, Spectrum Pharmaceuticals, Astellas Pharma; consultancy: Incyte Corporation, MorphoSys, SeaGen, Gamida Cell, Novartis, Legend Biotech, Kadmon, ADC Therapeutics, Omeros, AbbVie, Caribou, CRISPR, Genmab, Kite; Speaker’s Bureau: Sanofi Genzyme, AstraZeneca, BeiGene, ADC Therapeutics, Kite; Data Monitoring Committee: Myeloid Therapeutics, Inc. M. L. R.—research funding from Jazz Pharmaceuticals and Atara Bio-Pharma; employment by IQVIA Biotech and Kura Oncology; stock in Kura Oncology. M. M. H.—research funding from Astellas Pharma, CSL Behring, Incyte, Sanofi; consultancy: Sobi, Inc. M.-A. P.—honoraria from Adicet, Allogene, Allovir, Caribou Biosciences, Celgene, Bristol-Myers Squibb, Equilium, Exevir, ImmPACT Bio, Incyte, Karyopharm, Kite/Gilead, Merck, Miltenyi Biotec, MorphoSys, Nektar Therapeutics, Novartis, Omeros, OrcaBio, Sanofi, Syncopation, VectivBio AG, and Vor Biopharma; he serves on Data and Safety Monitoring Boards (DSMBs) for Cidara Therapeutics and Sellas Life Sciences, and the scientific advisory board of NexImmune; he has ownership interests in NexImmune, Omeros, and OrcaBio; he has received institutional research support for clinical trials from Allogene, Incyte, Kite/Gilead, Miltenyi Biotec, Nektar Therapeutics, and Novartis. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Ultra-low volume (ULV) space sprays aerosolize insecticide formulated products (FP) to contact flying mosquitoes, while barrier sprays expose mosquitoes to FP residue on vegetation and other surfaces. Centers for Disease Control and Prevention bottle bioassays used to assess insecticide resistance are based on residual active ingredient (AI) exposure and do not directly relate to FP efficacy. The current pilot study developed a novel compact wind tunnel for mosquito exposure to FP. Caged Aedes albopictus and Culex pipiens/quinquefasciatus were exposed to undiluted Biomist®3 + 15 FP (permethrin AI) or air (control) within the wind tunnel, transferred to new cages, and held in a 28 °C incubator. Separate mosquitoes were exposed to residual permethrin AI (8 μg mL -1 ) in bottle bioassays. Mortality was monitored 15, 30, 60, and 120 min post-exposure., Results: Chi-square tests (P < 0.05) showed significantly higher mortality in Aedes compared to Culex populations for most time points in both bioassay and wind tunnel exposure groups. As expected, mosquitoes exposed to Biomist®3 + 15 showed higher mortality rates than bottle bioassay exposure to permethrin. Two Culex colonies resistant to permethrin in bottle bioassays were susceptible to Biomist®3 + 15 in the wind tunnel., Conclusion: The novel compact wind tunnel developed here may be an alternative to field trials for testing FP efficacy, avoiding factors such as weather, logistical planning, and extended personnel hours. The wind tunnel could allow programs to conveniently test efficacy of multiple FP. Comparisons of different insecticide exposure methods provide practical information to inform operational decisions. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change.IMPORTANCEMicrobiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development., Competing Interests: The authors declare no conflict of interest.