To capitalize on this deep knowledge base, we have chosen to use CAR-CD19 T cells as a unique platform solution that will allow us to target and kill any tumor. We recently described the development of bridging proteins which contain the extracellular domain (ECD) of CD19 linked to an antigen binding domain, eg. an antibody fragment, that binds to a tumor-expressed antigen [18]. The wild-type CD19 ECD was difficult to express, therefore we developed novel CD19 ECD mutants that can be linked N- or C-terminally to any protein, generating modular CD19 bridging proteins with enhanced secretion and a predicted lack of immunogenicity [18]. These rationally designed CD19 bridging proteins are capable of binding to any tumor antigen, thereby coating CD19-negative tumor cells with CD19. CD19-coated tumor cells representing diverse indications were thereby made susceptible to potent CAR-CD19 T cell-mediated cytotoxicity [18]. Of note, the CAR-CD19 domain on the T cell remains the same regardless of the antigens targeted by the bridging protein, and this minimizes complexity in CAR T cell manufacturing across our diverse programs. This technology therefore has the potential to broaden the reach of CAR-CD19 T cells beyond B cell malignancies to any tumor without the need to build many different CAR and combination CAR constructs. Given the emerging knowledge regarding the need for multi-antigen targeting in order to ensure durable responses to CAR-T therapy the need for such a simple, pragmatic and modular technology is evident.
Results on how sample processing parameters from centrifugation to freezing, such as the temperature and time to freezing, affect VEGF levels are inconclusive. VEGF levels seem stable for several days at +4C and months at -80C, however, this needs further empirical evidence. Furthermore, repeated freeze-thaw cycles of serum samples seem to have little or no effect on VEGF levels (very low grade of evidence). For plasma samples, the impact of freeze-thaw cycles needs further investigation for recommendation on standardization. Half of the publications indicated no differences in VEGF levels after freeze-thaw cycles, while the other half found a significant impact of the treatment. However, this might also depend on the anticoagulants used, as different studies used different sample systems. Stable VEGF levels after freeze-thaw cycles have been shown for cerebrospinal fluid [88] and urine samples [89].
Anti Deep Freeze 5.epub
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Storage of biological specimens is crucial in the life and medical sciences. Storage conditions for samples can be different for a number of reasons, and it is unclear what effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer, -80C; freezer, -20C; refrigerator, 5C; room temperature, 22C) and storage times (immediate sample processing, 0 h; next day, 16 h; over weekend, 64 h; longer term, 4, 8, and 12 months) as well as repeated sample freezing and thawing (2 to 4 freeze-thaw cycles). We examined two different pig feces and sewage samples, unspiked and spiked with a mock community, in triplicate, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were, in some situations, similarly affected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We provide recommendations for sample storage and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and found significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a data set that could also be used for benchmarking algorithms to identify and correct for unwanted batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing be published together with DNA sequencing data at the International Nucleotide Sequence Database Collaboration (ENA/EBI, NCBI, DDBJ) or other repositories.
Blood samples obtained either from tail vein (before treatments) or cardiac puncture (after the treatment) were centrifuged and serum samples were stored in a deep freezer until they could be analyzed. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) activities and the levels of serum albumin, serum total protein, and serum total bilirubin were determined by Hitachi-917 auto-analyzer using kits manufactured by Roche Diagnostic Division.
Preparation of plants extracts: The air-dried powdered of flaxseed, sesame seeds, safflower seeds and soybean seeds were extracted successively in a continuous extraction apparatus (Soxhlet) until exhaustion with petroleum ether (40-60C), then ethanol. The solvent of each extract was completely removed by evaporation under reduced pressure at a temperature not exceeding 40C. All extracts were kept in deep-freeze till used. 2ff7e9595c
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