SUMMARY This paper shows how approximate maximum likelihood estimation for fairly general point processes on the line can be performed with GLIM. The approximation is based on a weighted sum approximation to an integral in the likelihood. Various weighting schemes are briefly examined. The methodology is illustrated with an example, and its extension to Poisson processes in higher dimensions is briefly described.

In North America, red blood cells (RBCs) are cryopreserved in a clinical setting using high glycerol concentrations (40% w/v) with slow cooling rates (~1°C/min) prior to storage at −80°C, while European protocols use reduced glycerol concentrations with rapid freezing rates. After thawing and prior to transfusion, glycerol must be removed to avoid intravascular hemolysis. This is a time consuming process requiring specialized equipment. Small molecule ice recrystallization inhibitors (IRIs) such as β-PMP-Glc and β-pBrPh-Glc have the ability to prevent ice recrystallization, a process that contributes to cellular injury and decreased cell viability after cryopreservation. Herein, we report that addition of 110 mM β-PMP-Glc or 30 mM β-pBrPh-Glc to a 15% glycerol solution increases post-thaw RBC integrity by 30-50% using slow cooling rates and emphasize the potential of small molecule IRIs for the preservation of cells.

While overall quality was similar before and after the production method change, the observed differences, although small, indicate a lack of equivalency across RBC products manufactured by different methods.

No abstract

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans’ assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis.

Processing method impacts RCC characteristics throughout storage; better understanding of these differences and reporting of processing method details is critical.

While irradiation of red cell concentrates (RCC) prevents graft-versus-host disease in susceptible transfusion recipients, it also damages red blood cells (RBC). To understand the ability of irradiation regulations to prevent transfusion of inferior units, we irradiated 980 RCC in saline-adenine-glucose-mannitol (SAGM) using various combinations of pre-irradiation age and post-irradiation storage times, and measured hemolysis and extracellular potassium levels. We observed unacceptably high hemolysis (>0·8%) in some RCC and elevated extracellular potassium levels in all gamma-irradiated RCC. This suggests that more restrictive storage times should be considered for RCC in SAGM.

During cryopreservation, ice recrystallization is a major cause of cellular damage. Conventional cryoprotectants such as dimethyl sulfoxide (DMSO) and glycerol function by a number of different mechanisms but do not mitigate or control ice recrystallization at concentrations utilized in cryopreservation procedures. In North America, cryopreservation of human red blood cells (RBCs) utilizes high concentrations of glycerol. RBC units frozen under these conditions must be subjected to a time-consuming deglycerolization process after thawing in order to remove the glycerol to <1% prior to transfusion thus limiting the use of frozen RBC units in emergency situations. We have identified several low molecular mass ice recrystallization inhibitors (IRIs) that are effective cryoprotectants for human RBCs, resulting in 70–80% intact RBCs using only 15% glycerol and slow freezing rates. These compounds are capable of reducing the average ice crystal size of extracellular ice relative to a 15% glycerol control validating the positive correlation between a reduction in ice crystal size and increased post-thaw recovery of RBCs. The most potent IRI from this study is also capable of protecting frozen RBCs against the large temperature fluctuations associated with transient warming.