An automatic glucose monitoring system based on periplasmic binding proteins for online bioprocess monitoring.

Glucose is one of the most vital nutrients in all living organisms, so its monitoring is critical in healthcare and bioprocessing. Enzymatic sensors are more popular as a technology solution to meet the requirement. However, periplasmic binding proteins have been investigated extensively for their high sensitivity, enabling microdialysis sampling to replace existing complex and expensive glucose monitoring solutions based on enzymatic sensors. The binding proteins are used as optical biosensors by introducing an environment-sensitive fluorophore to the protein. The biosensor's construction, characterization, and potential application are well studied, but a complete glucose monitoring system based on it is yet to be reported. This work documents the development of the first glucose sensor prototype based on glucose binding protein (GBP) for automatic and continuous glucose measurements. The development includes immobilizing the protein into reusable chips and a low-cost solution for non-invasive glucose sampling in bioprocesses using microdialysis sampling technique. A program was written in LabVIEW to accompany the prototype for the complete automation of measurement. The sampling technique allowed glucose measurements of a few micromolar to 260 mM glucose levels. A thorough analysis of the sampling mode and the device's performance was conducted. The reported measurement accuracy was 81.78%, with an RSD of 1.83%. The prototype was also used in online glucose monitoring of E. coli cell culture. The mode of glucose sensing can be expanded to the measurement of other analytes by switching the binding proteins.

Antiviral cellular therapy for enhancing T-cell reconstitution before or after hematopoietic stem cell transplantation (ACES): a two-arm, open label phase II interventional trial of pediatric patients with risk factor assessment.

Viral infections remain a major risk in immunocompromised pediatric patients, and virus-specific T cell (VST) therapy has been successful for treatment of refractory viral infections in prior studies. We performed a phase II multicenter study (NCT03475212) for the treatment of pediatric patients with inborn errors of immunity and/or post allogeneic hematopoietic stem cell transplant with refractory viral infections using partially-HLA matched VSTs targeting cytomegalovirus, Epstein-Barr virus, or adenovirus. Primary endpoints were feasibility, safety, and clinical responses (>1 log reduction in viremia at 28 days). Secondary endpoints were reconstitution of antiviral immunity and persistence of the infused VSTs. Suitable VST products were identified for 75 of 77 clinical queries. Clinical responses were achieved in 29 of 47 (62%) of patients post-HSCT including 73% of patients evaluable at 1-month post-infusion, meeting the primary efficacy endpoint (>52%). Secondary graft rejection occurred in one child following VST infusion as described in a companion article. Corticosteroids, graft-versus-host disease, transplant-associated thrombotic microangiopathy, and eculizumab treatment correlated with poor response, while uptrending absolute lymphocyte and CD8 T cell counts correlated with good response. This study highlights key clinical factors that impact response to VSTs and demonstrates the feasibility and efficacy of this therapy in pediatric HSCT.

Dataset on genetic variation and trait association in cheeseweed (Malva parviflora L.) genotypes for agronomic traits.

In order to analyze genetic variability, heritability, genetic advance and trait associations in Malva parviflora genotypes for agronomic traits, this paper presented a dataset. Seven agronomic traits variation and genetic parameters, including phenotypic and genotypic variance, genotypic and phenotypic coefficients of variation, broad-sense heritability, genetic advance, traits association, principal component analysis, and heatmap analysis were performed based on phenotypic data. Excel, PBtools, STAR, and R applications were used to analyze the data. There was substantial variation for the traits as revealed by descriptive statistics and variance analysis. Graphical presentation showed for principal component analysis and heatmap analysis. Researchers can use this dataset as guide to their plan for improvement this crop as leafy vegetables.