Effects of Storage Time on Glycolysis in Donated Human Blood Units

Background: Donated blood is typically stored before transfusions. During storage, the metabolism of red blood cells changes, possibly causing storage lesions. The changes are storage time dependent and exhibit donor-specific variations. It is necessary to uncover and characterize the responsible molecular mechanisms accounting for such biochemical changes, qualitatively and quantitatively; Study Design and Methods: Based on the integration of metabolic time series data, kinetic models, and a stoichiometric model of the glycolytic pathway, a customized inference method was developed and used to quantify the dynamic changes in glycolytic fluxes during the storage of donated blood units. The method provides a proof of principle for the feasibility of inferences regarding flux characteristics from metabolomics data; Results: Several glycolytic reaction steps change substantially during storage time and vary among different fluxes and donors. The quantification of these storage time effects, which are possibly irreversible, allows for predictions of the transfusion outcome of individual blood units; Conclusion: The improved mechanistic understanding of blood storage, obtained from this computational study, may aid the identification of blood units that age quickly or more slowly during storage, and may ultimately improve transfusion management in clinics

Posttransplant Thrombopoiesis Predicts Survival in Patients Undergoing Autologous Hematopoietic Progenitor Cell Transplantation

AbstractThe frequency and clinical significance of secondary thrombocytopenia following initial engraftment in autologous hematopoietic progenitor cell transplantation (HPCT) is unknown. An institutional review board approved retrospective study of thrombopoiesis was performed in 359 patients transplanted with autologous blood (97%) or marrow (3%) who achieved platelet engraftment to >50,000/μL. Idiopathic secondary posttransplant thrombocytopenia (ISPT) was defined as >50% decline in blood platelets to <100,000/μL in the absence of relapse or sepsis. ISPT occurred at a median of day +35 posttransplant in 17% of patients. Patients with ISPT had similar initial platelet engraftment (median 17 days) versus non-ISPT patients (18 days; P = NS) and recovered platelet counts (median 123,00 K/μL) by day 110 posttransplant. Four factors were independently associated with post-transplant death in a multivariate model: disease status at transplant; the number of prior chemotherapy regimens, failure to achieve a platelet count of >150,000/μL posttransplant, and the occurrence of ISPT. A prognostic score was developed based upon the occurrence of ISPT and posttransplant platelet counts of <150,000/μL. Survival of patients with both factors (n = 25) was poor (15% alive at 5 years); patients with 1 factor (n = 145) had 49% 5-year survival; patients with 0 factors (n = 189) had 72% 5-year survival. Patients who failed to achieve a platelet count of >150,000/μL received significantly fewer CD34+ cells/kg (P < .001), whereas patients with ISPT received fewer CD34+CD38− cells/kg (P = .0006). The kinetics of posttransplant thrombopoiesis is an independent prognostic factor for long-term survival following autologous HPC. ISPT and lower initial posttransplant platelet counts reflect poor engraftment with long-term and short-term repopulating CD34+ hematopoietic stem cells, respectively, and are associated with an increased risk of death from disease relapse

Robust Meta-Model for Predicting the Need for Blood Transfusion in Non-traumatic ICU Patients

Objective: Blood transfusions, crucial in managing anemia and coagulopathy in ICU settings, require accurate prediction for effective resource allocation and patient risk assessment. However, existing clinical decision support systems have primarily targeted a particular patient demographic with unique medical conditions and focused on a single type of blood transfusion. This study aims to develop an advanced machine learning-based model to predict the probability of transfusion necessity over the next 24 hours for a diverse range of non-traumatic ICU patients. Methods: We conducted a retrospective cohort study on 72,072 adult non-traumatic ICU patients admitted to a high-volume US metropolitan academic hospital between 2016 and 2020. We developed a meta-learner and various machine learning models to serve as predictors, training them annually with four-year data and evaluating on the fifth, unseen year, iteratively over five years. Results: The experimental results revealed that the meta-model surpasses the other models in different development scenarios. It achieved notable performance metrics, including an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.97, an accuracy rate of 0.93, and an F1-score of 0.89 in the best scenario. Conclusion: This study pioneers the use of machine learning models for predicting blood transfusion needs in a diverse cohort of critically ill patients. The findings of this evaluation confirm that our model not only predicts transfusion requirements effectively but also identifies key biomarkers for making transfusion decisions

Interfacing and Verifying ALHAT Safe Precision Landing Systems with the Morpheus Vehicle

The NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project developed a suite of prototype sensors to enable autonomous and safe precision landing of robotic or crewed vehicles under any terrain lighting conditions. Development of the ALHAT sensor suite was a cross-NASA effort, culminating in integration and testing on-board a variety of terrestrial vehicles toward infusion into future spaceflight applications. Terrestrial tests were conducted on specialized test gantries, moving trucks, helicopter flights, and a flight test onboard the NASA Morpheus free-flying, rocket-propulsive flight-test vehicle. To accomplish these tests, a tedious integration process was developed and followed, which included both command and telemetry interfacing, as well as sensor alignment and calibration verification to ensure valid test data to analyze ALHAT and Guidance, Navigation and Control (GNC) performance. This was especially true for the flight test campaign of ALHAT onboard Morpheus. For interfacing of ALHAT sensors to the Morpheus flight system, an adaptable command and telemetry architecture was developed to allow for the evolution of per-sensor Interface Control Design/Documents (ICDs). Additionally, individual-sensor and on-vehicle verification testing was developed to ensure functional operation of the ALHAT sensors onboard the vehicle, as well as precision-measurement validity for each ALHAT sensor when integrated within the Morpheus GNC system. This paper provides some insight into the interface development and the integrated-systems verification that were a part of the build-up toward success of the ALHAT and Morpheus flight test campaigns in 2014. These campaigns provided valuable performance data that is refining the path toward spaceflight infusion of the ALHAT sensor suite

Rapid, High Throughput, Automated Detection of SARS-CoV-2 Neutralizing Antibodies Against Wuhan-Wt, Delta and Omicron BA1, BA2 Spike Trimers

Traditional cellular and live-virus methods for detection of SARS-CoV-2 neutralizing antibodies (nAbs) are labor- and time-intensive, and thus not suited for routine use in the clinical lab to predict vaccine efficacy and natural immune protection. Here, we report the development and validation of a rapid, high throughput method for measuring SARS-CoV-2 nAbs against native-like trimeric spike proteins. This assay uses a blockade of human angiotensin converting enzyme 2 (hACE-2) binding (BoAb) approach in an automated digital immunoassay on the Quanterix HD-X platform. BoAb assays using Wuhan-WT (vaccine strain), delta (B.1.167.2), omicron BA1 and BA2 variant viral strains showed strong correlation with cell-based pseudovirus neutralization activity (PNA) and live-virus neutralization activity. Importantly, we were able to detect similar patterns of delta and omicron variant resistance to neutralization in samples with paired vaccine strain and delta variant BoAb measurements. Finally, we screened clinical samples from patients with or without evidence of SARS-CoV-2 exposure by a single-dilution screening version of our assays, finding significant nAb activity only in exposed individuals. Importantly, this completely automated assay can be performed in 4 h to measure neutralizing antibody titers for 16 samples over 8 serial dilutions or, 128 samples at a single dilution with replicates. In principle, these assays offer a rapid, robust, and scalable alternative to time-, skill-, and cost-intensive standard methods for measuring SARS-CoV-2 nAb levels

Effect of swab pooling on the Accula point-of-care RT-PCR for SARS-CoV-2 detection

IntroductionSwab pooling may allow for more efficient use of point-of-care assays for SARS-CoV-2 detection in settings where widespread testing is warranted, but the effects of pooling on assay performance are not well described.MethodsWe tested the Thermo-Fisher Accula rapid point-of-care RT-PCR platform with contrived pooled nasal swab specimens.ResultsWe observed a higher limit of detection of 3,750 copies/swab in pooled specimens compared to 2,250 copies/swab in individual specimens. Assay performance appeared worse in a specimen with visible nasal mucous and debris, although performance was improved when using a standard laboratory mechanical pipette compared to the transfer pipette included in the assay kit.ConclusionClinicians and public health officials overseeing mass testing efforts must understand limitations and benefits of swab or sample pooling, including reduced assay performance from pooled specimens. We conclude that the Accula RT-PCR platform remains an attractive candidate assay for pooling strategies owing to the superior analytical sensitivity compared to most home use and point-of-care tests despite the inhibitory effects of pooled specimens we characterized

A Tale of Two Visions: Can a New View of Personality Help Integrate Psychology?

Personality psychology studies how psychological systems work together. Consequently, the field can act as a unifying resource for the broader discipline of psychology. Yet personality’s current fieldwide organization promotes a fragmented view of the person, seen through such compet-ing theories as the psychodynamic, trait, and humanistic. There exists an alternative—a systems framework for per-sonality—that focuses on 4 topics: identifying personality, personality’s parts, its organization, and its development. This new framework and its view of personality are de-scribed. The framework is applied to such issues as per-sonality measurement, psychotherapy outcome research, and education. The new framework may better organize the field of personality and help with its mission of addressing how major psychological systems interrelate

Mechanisms by which the cystic fibrosis transmembrane conductance regulator may influence SARS-CoV-2 infection and COVID-19 disease severity

Patients with cystic fibrosis (CF) exhibit pronounced respiratory damage and were initially considered among those at highest risk for serious harm from SARS-CoV-2 infection. Numerous clinical studies have subsequently reported that individuals with CF in North America and Europe—while susceptible to severe COVID-19—are often spared from the highest levels of virus-associated mortality. To understand features that might influence COVID-19 among patients with cystic fibrosis, we studied relationships between SARS-CoV-2 and the gene responsible for CF (i.e., the cystic fibrosis transmembrane conductance regulator, CFTR). In contrast to previous reports, we found no association between CFTR carrier status (mutation heterozygosity) and more severe COVID-19 clinical outcomes. We did observe an unexpected trend toward higher mortality among control individuals compared with silent carriers of the common F508del CFTR variant—a finding that will require further study. We next performed experiments to test the influence of homozygous CFTR deficiency on viral propagation and showed that SARS-CoV-2 production in primary airway cells was not altered by the absence of functional CFTR using two independent protocols. On the contrary, experiments performed in vitro strongly indicated that virus proliferation depended on features of the mucosal fluid layer known to be disrupted by absent CFTR in patients with CF, including both low pH and increased viscosity. These results point to the acidic, viscous, and mucus-obstructed airways in patients with cystic fibrosis as unfavorable for the establishment of coronaviral infection. Our findings provide new and important information concerning relationships between the CF clinical phenotype and severity of COVID-19.This work was supported by the Italian Ministry of Health (Ministero della Salute) [Ricerca Finalizzata RF-2016-02364358]; Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico, Ricerca corrente; Fondazione IRCCS Ca′ Granda core COVID-19 Biobank [RC100017A]; “Liver BIBLE” [PR-0391]; and Innovative Medicines Initiative 2 joint undertaking of the European Union (EU) Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations Programme Horizon 2020 [under grant agreement No. 777377] for the project LITMUS and the European Union, programme “Photonics” [under grant agreement 101016726] to LV. JCH was funded by the Research Council of Norway [grant no 312780] and a philanthropic donation from Vivaldi Invest A/S owned by Jon Stephenson von Tetzchner. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. AF was supported by a grant from the German Federal Ministry of Education and Research [01KI20197]. This work was also funded by a generous philanthropic donation from Banca Intesa San Paolo to RA. This study makes use of data generated by the GCATI Genomes for Life. Cohort study of the Genomes of Catalonia from Institut Germans Trias I Pujol (IGTP); IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya [ADE 10/00026], with additional support by the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) [2017-SGR 529], National Grant [PI18/01512], and VEIS project [001-P-001647], co-funded by European Regional Development Fund (ERDF), “A way to build Europe.” EdW and BNW were supported by the Intramural Research Program, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH). PRT and SGS received funding from NIH NIAID [R01 AI167356].Peer reviewe