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Objectives: Impaired B‐cell reconstitution after allogeneic hematopoietic cell transplantation (allo‐HCT) contributes to the pathogenesis of chronic graft‐versus‐host disease (cGVHD). Therefore, methods to consistently achieve effective B cell lymphogenesis are required. We assessed the long‐term effects of posttransplantation cyclophosphamide (PTCy) use on immune reconstitution in clinical settings, an emerging strategy to suppress allogeneic immunological inflammation early after allo‐HCT and prevent subsequent GVHD. Methods: We comprehensively analyzed peripheral immune cell subsets and measured serum immunoglobulin G (IgG) or cytokine levels in 39 patients who survived for >1 year after allo‐HCT. Results: The absolute counts of B1 and IgM memory B cells were significantly lower in patients with severe cGVHD than in those without. The absolute count and percentage (among total CD19+ B cells) of switched memory B cells and serum IgG levels were significantly higher in patients transplanted with PTCy than in those transplanted with conventional GVHD prophylaxis. Interestingly, increased percentages of switched memory B cells and serum IgG levels were observed only in patients transplanted with PTCy and not in those transplanted with umbilical cord blood. Conclusions: PTCy administration can mediate favorable memory B‐cell reconstitution long after allo‐HCT and may therefore suppress cGVHD. [ABSTRACT FROM AUTHOR]

Aim: Despite extensive studies of phenological shifts in migration by climate change and driving factors of migration, a few issues remain unresolved. In particular, little is known about the complex effects of driving factors on migration with interactions and nonlinearity, and partitioning of the effects of factors into spatial, temporal, and spatio‐temporal effects. Here, we aim to elucidate migration pattern as well as its driving factors under climate change. Location: Western North Pacific. Taxon: North Pacific spiny dogfish Squalus suckleyi. Methods: We first examined long‐term changes in the timing and geographic location of migration by applying the Barrier model, a spatio‐temporal model, to c. 5‐decade time series data (1972–2019) for the presence/absence of spiny dogfish in the western North Pacific. We then evaluated the spatial, temporal and spatio‐temporal effects of driving factors (fish productivity, sea surface temperature [SST], depth and magnetic field) on seasonal occurrence patterns using a machine learning model and an interpretable machine learning technique. Results: The migration area did not change over c. 5‐decades, whereas the migration timing advanced by a month after 2000. The spatial effects of magnetic field and depth were consistently large and the spatial and spatio‐temporal effects of SST increased in the migration season, even though the temporal effect of SST was consistently weak. Main Conclusions: The migration area of spiny dogfish was stable over time because of the effect of magnetic field and a strong preference for submarine topography, whereas the migration timing advanced as a result of tracking a suitable location based on SST, which increased sharply after 2000. Therefore, temperature and other factors simultaneously influence migration under climate change, highlighting the importance of considering both biotic and abiotic factors and understanding the underlying processes in predicting future impacts of climate change on species distribution. [ABSTRACT FROM AUTHOR]

Catchability plays a central role in fisheries stock assessment. Since catchability often varies with time depending on population density, environmental factors, and anthropogenic effects, assuming constant catchability in population models can lead to biased abundance estimates. Here we present a novel way to simultaneously estimate time-varying catchability and abundance by integrating a short-term (month-based) removal method and a long-term (year-based) age-structured population dynamics model. We applied this approach to commercial fishery data for a Japanese pufferfish (Takifugu rubripes) population and found that the models with time-varying catchability greatly outperformed the models with constant catchability in terms of predictive ability and model consistency. The temporal variation in catchability was parsimoniously predicted by fishing effort and population size, indicating the existence of effort- and density-dependent catchability. Our approach, integrating population dynamics at different timescales, will help avoid inadvertent overexploitation and contribute to sustainable harvesting by enhancing the estimation accuracy of time-varying catchability and abundance. La capturabilite joue un role cle dans l'evaluation des stocks de peche. Comme elle varie souvent dans le temps en fonction de la densite de population, de facteurs ambiants et d'effets d'origine humaine, l'hypothese d'une capturabilite constante dans les modeles de populations peut mener a des estimations biaisees de l'abondance. Nous presentons une nouvelle approche pour estimer simultanement la capturabilite variable dans le temps et l'abondance en integrant une methode de retrait a court terme (mensuel) et un modele de dynamique des populations structure par age a long terme (annuel). Nous appliquons cette approche a des donnees de peche commerciale pour une population de poissons-globes japonais (Takifugu rubripes) et constatons que les modeles integrant la capturabilite variable dans le temps donnent de bien meilleurs resultats que les modeles a capturabilite constante en ce qui concerne la valeur predictive et la coherence des modeles. La variation temporelle de la capturabilite est parcimonieusement predite par l'effort de peche et la taille de la population, ce qui indique l'existence d'une capturabilite dependant de l'effort et de la densite. Notre approche, qui integre la dynamique de la population a differentes echelles temporelles, aidera a eviter la surexploitation par inadvertance et favorisera des peches durables en rehaussant l'exactitude des estimations de la capturabilite variable dans le temps et de l'abondance. [Traduit par la Redaction], Introduction Fisheries scientists often must conduct stock assessments of fish populations using only commercial fisheries data. However, such data can be problematic because they are collected without proper sampling design [...]

Standardized catch per unit effort (CPUE) is a fundamental component of fishery stock assessment. In multispecies fisheries, catchability can differ depending on which species is being targeted, and so the yearly trend extracted from the standardized CPUE is likely to be biased. We have, therefore, developed a method for predicting the unobserved variable related to targeted species from among multispecies composition data using a mixture regression model for the transformed residuals. In contrast with traditional methods, the proposed method predicts the target variable in CPUE standardization without removing a subset of the data. Keeping the entire data set avoids information loss, and so CPUE standardization with the predicted target variable should yield an unbiased estimate of the yearly trend. Simple simulation tests demonstrate that our method outperforms traditional methods. We illustrate the use of our method by applying it to CPUE data on arabesque greenling (Pleurogrammus azonus) caught in multispecies trawl fisheries in Hokkaido, Japan. La capture par unite d'effort (CPUE) normalisee est une composante fondamentale de l'evaluation des stocks de poissons. Dans les peches plurispecifiques, la capturabilite peut varier selon l'espece ciblee, de sorte que la tendance annuelle obtenue a partir de la CPUE normalisee est susceptible d'etre biaisee. C'est pourquoi nous avons mis au point une methode de prediction de la variable non observee associee aux especes ciblees a partir de donnees sur la composition specifique en utilisant un modele de regression de melanges pour les residus transformes. Contrairement aux methodes traditionnelles, la methode proposee predit la variable cible dans la normalisation de la CPUE sans retirer un sous-ensemble des donnees. Le fait de conserver l'entierete de l'ensemble de donnees evite une perte d'information, de sorte que la normalisation de la CPUE avec la variable cible predite devrait produire une estimation non biaisee de la tendance annuelle. Des essais de simulation simples demontrent que notre methode donne de meilleurs resultats que les methodes traditionnelles. Nous illustrons l'utilisation de notre methode en l'appliquant a des donnees de CPUE pour des maquereaux atkas (Pleurogrammus azonus) pris dans une peche plurispecifique au chalut a Hokkaido (Japon). [Traduit par la Redaction], Introduction Relative abundance (abundance index) is among the most fundamental pieces of data in fishery stock assessment and management (Hilborn and Walters 1992). The abundance index, which is generally assumed [...]