EV content correlates with measures of hemolysis and other RBC quality indicators and could be implemented as a routine screening tool for nondestructive QC testing of RCCs.
Platelet inventory management based on screening microparticle content in platelet concentrates is a new quality improvement initiative for hospital blood banks. Cells fragment off microparticles (MP) when they are stressed. Blood and blood components may contain cellular fragments from a variety of cells, most notably from activated platelets. When performing their roles as innate immune cells and major players in coagulation and hemostasis, platelets change shape and generate microparticles. With dynamic light scattering (DLS)-based microparticle detection, it is possible to differentiate activated (high microparticle) from non-activated (low microparticle) platelets in transfusions, and optimize the use of this scarce blood product. Previous research suggests that providing non-activated platelets for prophylactic use in hematology-oncology patients could reduce their risk of becoming refractory and improve patient care. The goal of this screening method is to routinely differentiate activated from non-activated platelets. The method described here outlines the steps to be performed for routine platelet inventory management in a hospital blood bank: obtaining a sample from a platelet transfusion, loading the sample into the capillary for DLS measurement, performing the DLS test to identify microparticles, and using the reported microparticle content to identify activated platelets.
Background The microparticle content (MP%) of apheresis platelets—a marker of platelet activation—is influenced by donor factors and by external stressors during collection and storage. This study assessed the impact of apheresis technology and other factors on the activation status (MP%) of single‐donor apheresis platelets. Study Design and Methods Data from six US hospitals that screened platelets by measuring MP% through dynamic light scattering (ThromboLUX) were retrospectively analyzed. Relative risks (RRs) were derived from univariate and multivariable regression models, with activation rate (MP% ≥15% for plasma‐stored platelets; ≥10% for platelet additive solution [PAS]‐stored platelets) and MP% as outcomes. Apheresis platform (Trima Accel vs Amicus), storage medium (plasma vs PAS), pathogen reduction, storage time, and testing location were used as predictors. Results Data were obtained from 7511 platelet units collected using Trima (from 16 suppliers, all stored in plasma, 20.0% were pathogen‐reduced) and 2456 collected using Amicus (from four different collection facilities of one supplier, 65.0% plasma‐stored, 35.0% PAS‐stored, none pathogen‐reduced). Overall, 30.0% of Trima platelets were activated compared to 45.6% of Amicus platelets (P < .0001). Multivariable analysis identified apheresis platform as significantly associated with platelet activation, with a lower activation rate for Trima than Amicus (RR: 0.641, 95% confidence interval [CI]: 0.578; 0.711, P < .0001) and a 6.901% (95% CI: 5.926; 7.876, P < .0001) absolute reduction in MP%, when adjusting for the other variables. Conclusion Trima‐collected platelets were significantly less likely to be activated than Amicus‐collected platelets, irrespective of the storage medium, the use of pathogen reduction, storage time, and testing site.
The Macaulay Land Use Research I n s t i t u t e Creigiehtickler ABFRllt-t N AB9 2Q3 UK ABS1 RAC1 Becausc o f ground r e s o l u t i o n e f f e c t s i t is o f t e n impossible t o map vegetation types d i r e c t l y from satellite imagcry. Howcvor, such imagery is o f t e n t h e only e v e i l a b l e source of v e g e t a t i o n information over l a r g e a r m 9 . I n order t o l l t i l i s e imagery i n l a r g e area vegetation s u r v e y s i t is therefore necessary t o develop i n d i r e c t mapping techniques which rely upon known associations belween plan1 d i s t r i b u t i o n and environmental factors, end only portly depend upon image-der ived i n rorniat ion. In t h i s paper t h e devalopmerk o f such an i n d i r e c t vegetst ion mapping procvc-lure is dcocribcd w i t h respect t o a n a t i o n a l s u r v e y o f bracken ( P t e r i d i t m s u i 1 inum,) i n Scotland. The f i r s t p a r t describes how direct rrtappiry techniqucs using supervised imagp classification methods on LANDSAT MSS imagery f e i l e d , and explains why i n tlie curltext or t h e i n t e r p l a y between t a r g e t si7e/stioye arid image r e s o l u t i o n . The second part d e a l s w i t h t h e development of an i n d i r e c t mapping procedure whj ch utilises stepwise image masking, based upon both e c o l o g i c a l and non-ecological decision rules, and msximum-likelihood classification o f t h e remaining image area, In the f i n a l section t h e results are presented and discussed i n t h e wider context o f e c o l n g i c a l p r o a b i l i t y mapping.
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