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Background: The INTERCEPT™ Blood System for Red Blood Cells (RBCs) utilizes amustaline (S‐303) and glutathione (GSH) to inactivate pathogens and leukocytes in transfused RBCs. Treatment‐emergent low titer non‐hemolytic antibodies to amustaline/GSH RBC were detected in clinical trials using a prior version of the process. The amustaline/GSH process was re‐formulated to decrease S‐303 RBC adduct formation.
Study Design and Methods: A standard three‐cell antibody screening panel was modified to include reagent red cells (RRC) with high (S‐303H) or low (S‐303L) S‐303 adduct density as assessed by flow cytometry, representative of the original and current amustaline/GSH treatment processes, respectively. General hospital and RBC transfusion‐dependent patients never exposed, and clinical trial subjects exposed to amustaline/GSH RBC were screened for antibodies to amustaline/GSH RBC using a standardized agglutination assay.
Results: Twelve (0.1%) of 10,721 general hospital and 5 (0.5%) of 998 repeatedly‐transfused patients not previously exposed to amustaline/GSH RBCs expressed natural, low titer (2‐32) IgM and/or IgG (non‐IgG1 or IgG3 isotype) antibodies with acridine (a structural element of amustaline) (n = 14) or non‐acridine (n = 3) specificity. 11 of 17 sera reacted with S‐303L panel RRCs. In clinical studies 81 thalassemia and 25 cardiac surgery patients were transfused with a total of 1085 amustaline/GSH RBCs and no natural or treatment‐emergent S‐303 antibodies were detected.
Conclusion: Standardized RRC screening panels are sensitive for the detection of natural and acquired S‐303‐specific antibodies. Natural low titer antibodies to amustaline/GSH RBC are present in 0.15% of naïve patients. The clinical relevance of these antibodies appears minimal but is under further investigation.
The induction of apoptosis is a direct way to eliminate tumor cells and improve cancer therapy. Apoptosis is tightly controlled by the balance of pro- and antiapoptotic Bcl-2 proteins. BH3 mimetics neutralize the antiapoptotic function of Bcl-2 proteins and are highly promising compounds inducing apoptosis in several cancer entities including pediatric malignancies. However, the clinical application of BH3 mimetics in solid tumors is impeded by the frequent resistance to single BH3 mimetics and the anticipated toxicity of high concentrations or combination treatments. One potential avenue to increase the potency of BH3 mimetics is the development of immune cell-based therapies to counteract the intrinsic apoptosis resistance of tumor cells and sensitize them to immune attack. Here, we describe spheroid cultures of pediatric cancer cells that can serve as models for drug testing. In these 3D models, we were able to demonstrate that activated allogeneic Natural Killer (NK) cells migrated into tumor spheroids and displayed cytotoxicity against a wide range of pediatric cancer spheroids, highlighting their potential as anti-tumor effector cells. Next, we investigated whether treatment of tumor spheroids with subtoxic concentrations of BH3 mimetics can increase the cytotoxicity of NK cells. Notably, the cytotoxic effects of NK cells were enhanced by the addition of BH3 mimetics. Treatment with either the Bcl-XL inhibitor A1331852 or the Mcl-1 inhibitor S63845 increased the cytotoxicity of NK cells and reduced spheroid size, while the Bcl-2 inhibitor ABT-199 had no effect on NK cell-mediated killing. Taken together, this is the first study to describe the combination of BH3 mimetics targeting Bcl-XL or Mcl-1 with NK cell-based immunotherapy, highlighting the potential of BH3 mimetics in immunotherapy.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Introduction and Objective: Identifying patients that benefit from cisplatin-based adjuvant chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC). The purpose of this study is to correlate “luminal” and “basal” type protein expression with histological subtypes, to investigate the prognostic impact on survival after adjuvant chemotherapy and to define molecular consensus subtypes of “double negative” patients (i.e., without expression of CK5/6 or GATA3).
Materials and Methods: We performed immunohistochemical (IHC) analysis of CK5/6 and GATA3 for surrogate molecular subtyping in 181 MIBC samples. The mRNA expression profiles for molecular consensus classification were determined in CK5/6 and GATA3 (double) negative cases using a transcriptome panel with 19.398 mRNA targets (HTG Molecular Diagnostics). Data of 110 patients undergoing radical cystectomy were available for survival analysis.
Results: The expression of CK5/6 correlated with squamous histological subtype (96%) and expression of GATA3 was associated with micropapillary histology (100%). In the multivariate Cox-regression model, patients receiving adjuvant chemotherapy had a significant survival benefit (hazard ratio [HR]: 0.19 95% confidence interval [CI]: 0.1–0.4, p < 0.001) and double-negative cases had decreased OS (HR: 4.07; 95% CI: 1.5–10.9, p = 0.005). Double negative cases were classified as NE-like (30%), stroma-rich (30%), and Ba/Sq (40%) consensus molecular subtypes and displaying different histological subtypes.