Cluster of differentiation 47 (CD47) is a transmembrane protein highly expressed in tumor cells that interacts with signal regulatory protein alpha (SIRPα) and triggers a "don't eat me" signal to the macrophage, inhibiting phagocytosis and enabling tumor escape from immunosurveillance. The CD47-SIRPα axis has become an important target for cancer immunotherapy. To date, the advancement of CD47-targeted modalities is hindered by the ubiquitous expression of the target, often leading to rapid drug elimination and hematologic toxicity including anemia. To overcome those challenges a bispecific approach was taken. CC-96673, a humanized IgG1 bispecific antibody co-targeting CD47 and CD20, is designed to bind CD20 with high affinity and CD47 with optimally lowered affinity. As a result of the detuned CD47 affinity, CC-96673 selectively binds to CD20-expressing cells, blocking the interaction of CD47 with SIRPα. This increased selectivity of CC-96673 over monospecific anti-CD47 approaches allows for the use of wild-type IgG1 Fc, which engages activating crystallizable fragment gamma receptors (FcγRs) to fully potentiate macrophages to engulf and destroy CD20+ cells, while sparing CD47+CD20- normal cells. The combined targeting of anti-CD20 and anti-CD47 results in enhanced anti- tumor activity compared to anti-CD20 targeting antibodies alone. Furthermore, preclinical studies have demonstrated that CC-96673 exhibits acceptable pharmacokinetic properties with a favorable toxicity profile in non-human primates. Collectively, these findings define CC-96673 as a promising CD47 × CD20 bispecific antibody that selectively destroys CD20+ cancer cells via enhanced phagocytosis and other effector functions.

Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height.Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement.Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches.Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change.