Rapid human T cell expansion using gas-permeable bags in the Eppendorf New BrunswickTM S41i CO2 incubator shaker

Recent advances in cellular therapy have greatly increased the demand for T cell expansion techniques. T cells must be expanded rapidly to achieve high cell densities while maintaining high viability and T cell identity. One of the best cell culture tools for large-scale expansion is stirred-tank bioreactors. However, cell culture in bioreactors requires a relatively large number of cells for inoculation. We developed a -method using gas-permeable bags to produce a sufficient number of T cells for the inoculation of bench-scale bioreactors. Please click Additional Files below to see the full abstract

Cell culture scale-up in BioBLU® c rigid-wall, single-use bioreactors

For cultivation of mammalian cells in biopharmaceutical research and manufacturing, single-use technology possesses several advantages to autoclavable material. Bioreactor scalability is critical to streamlining the adaptation of culture volumes during process development and manufacturing. We analyzed BioBLU Single-Use Vessels of different sizes (maximum working volumes of 0.25 L, 3.75 L, and 40 L) that are of geometrically similar stirred-tank design. We identified a scalable tip speed zone and an overlapping range of kLa values, which cover most mammalian cell culture needs. Using computational fluid dynamics simulations we determined the power numbers of the BioBLU bioreactors. Based on these data we scaled up a mAb production process in CHO cells from 250 mL to 3.75 L to 40 L by keeping constant P/V values (impeller power consumption per liquid volume) among the differently sized vessels. Similar cell growth curves and mAb production profiles were achieved at all three scales. In summary, this study demonstrates the excellent scalability of the single-use bioreactors tested

Evaluation of intra- and interspecific divergence of satellite DNA sequences by nucleotide frequency calculation and pairwise sequence comparison

Satellite DNA sequences are known to be highly variable and to have been subjected to concerted evolution that homogenizes member sequences within species. We have analyzed the mode of evolution of satellite DNA sequences in four fishes from the genus Diplodus by calculating the nucleotide frequency of the sequence array and the phylogenetic distances between member sequences. Calculation of nucleotide frequency and pairwise sequence comparison enabled us to characterize the divergence among member sequences in this satellite DNA family. The results suggest that the evolutionary rate of satellite DNA in D. bellottii is about two-fold greater than the average of the other three fishes, and that the sequence homogenization event occurred in D. puntazzo more recently than in the others. The procedures described here are effective to characterize mode of evolution of satellite DNA

RNA based approaches to profile oncogenic pathways from low quantity samples to drive precision oncology strategies

Precision treatment of cancer requires knowledge on active tumor driving signal transduction pathways to select the optimal effective targeted treatment. Currently only a subset of patients derive clinical benefit from mutation based targeted treatment, due to intrinsic and acquired drug resistance mechanisms. Phenotypic assays to identify the tumor driving pathway based on protein analysis are difficult to multiplex on routine pathology samples. In contrast, the transcriptome contains information on signaling pathway activity and can complement genomic analyses. Here we present the validation and clinical application of a new knowledge-based mRNA-based diagnostic assay platform (OncoSignal) for measuring activity of relevant signaling pathways simultaneously and quantitatively with high resolution in tissue samples and circulating tumor cells, specifically with very small specimen quantities. The approach uses mRNA levels of a pathway\u27s direct target genes, selected based on literature for multiple proof points, and used as evidence that a pathway is functionally activated. Using these validated target genes, a Bayesian network model has been built and calibrated on mRNA measurements of samples with known pathway status, which is used next to calculate a pathway activity score on individual test samples. Translation to RT-qPCR assays enables broad clinical diagnostic applications, including small analytes. A large number of cancer samples have been analyzed across a variety of cancer histologies and benchmarked across normal controls. Assays have been used to characterize cell types in the cancer cell microenvironment, including immune cells in which activated and immunotolerant states can be distinguished. Results support the expectation that the assays provide information on cancer driving signaling pathways which is difficult to derive from next generation DNA sequencing analysis. Current clinical oncology applications have been complementary to genomic mutation analysis to improve precision medicine: (1) prediction of response and resistance to various therapies, especially targeted therapy and immunotherapy; (2) assessment and monitoring of therapy efficacy; (3) prediction of invasive cancer cell behavior and prognosis; (4) measurement of circulating tumor cells. Preclinical oncology applications lie in a better understanding of cancer behavior across cancer types, and in development of a pathophysiology-based cancer classification for development of novel therapies and precision medicine

Selectivities of Potassium-Calcium and Potassium-Lead Exchange in Two Tropical Soils

Measurement of cation selectivity in soils provides important information about the affinity and binding strength of a particular cation on soil surfaces. Gaines-Thomas (KGT) selectivity coefficients were determined for a variety of K/Ca and K/Pb ratios on an Oxisol and Ultisol soil from Puerto Rico. The calculated KGT values indicated a preference for K+ over Ca2+ or Pb2+. The selectivity for Pb2+ was significantly greater than that for Ca2+ due to Pb2+\u27s larger hydrated charge density relative to that of Ca2+. The patterns of selectivity were independent of metal type. The selectivity of the Oxisol for Ca2+ or Pb2+ exhibited no trend and changed little with changes in divalent metal surface coverage. The Ultisol displayed a decrease in selectivity for Ca2+ and Pb2+ with increasing surface coverage of these ions. This was attributed to the presence of smectite in the Ultisol, which was able to partially collapse when K+ saturated. Some of the Pb sorption in the soils was due to chemisorption. The Oxisol chemisorbed 3000 mg Pb kg-1 while that value for the Ultisol was ≈1900 mg kg-1. The differences were due to the greater quantities of Fe/Al oxides and organic matter in the Oxisol relative to the Ultisol. Scanning electron microscopy-energy dispersive X-ray (SEM-EDX) spectroscopy detected discrete Pb-C phase in both soils. The C was from organic matter. Under experimental conditions, any Pb-carbonate phase would not have been stable. It was possible Pb was associated with organic sulfhydral groups. The selectivity exhibited by soil systems for various nutrient and heavy metals is important in elucidating how available these metals will be for plant/animal uptake as well as their mobility and stability in the soil environment

Identification of a better Homo sapiens Class II HDAC inhibitor through binding energy calculations and descriptor analysis

Human papillomaviruses (HPVs) are the most common on sexually transmitted viruses in the world. HPVs are responsible for a large spectrum of deseases, both benign and malignant. The certain types of HPV are involved in the development of cervical cancer. In attemps to find additional drugs in the treatment of cervical cancer, inhibitors of the histone deacetylases (HDAC) have received much attention due to their low cytotoxic profiles and the E6/E7 oncogene function of human papilomavirus can be completely by passed by HDAC inhibition. The histone deacetylase inhibitors can induce growth arrest, differentiation and apoptosis of cancer cells. HDAC class I and class II are considered the main targets for cancer. Therefore, the six HDACs class II was modeled and about two inhibitors (SAHA and TSA) were docked using AutoDock4.2, to each of the inhibitor in order to identify the pharmacological properties. Based on the results of docking, SAHA and TSA were able to bind with zinc ion in HDACs models as a drug target. SAHA was satisfied almost all the properties i.e., binding affinity, the Drug-Likeness value and Drug Score with 70% oral bioavailability and the carbonyl group of these compound fits well into the active site of the target where the zinc is present. Hence, SAHA could be developed as potential inhibitors of class II HDACs and valuable cervical cancer drug candidate

Longest Common Prefixes with kk-Errors and Applications

Although real-world text datasets, such as DNA sequences, are far from being uniformly random, average-case string searching algorithms perform significantly better than worst-case ones in most applications of interest. In this paper, we study the problem of computing the longest prefix of each suffix of a given string of length $n$ over a constant-sized alphabet that occurs elsewhere in the string with $k$-errors. This problem has already been studied under the Hamming distance model. Our first result is an improvement upon the state-of-the-art average-case time complexity for non-constant $k$ and using only linear space under the Hamming distance model. Notably, we show that our technique can be extended to the edit distance model with the same time and space complexities. Specifically, our algorithms run in $\mathcal{O}(n \log^k n \log \log n)$ time on average using $\mathcal{O}(n)$ space. We show that our technique is applicable to several algorithmic problems in computational biology and elsewhere

Semiconductor Quantum Dots in Chemical Sensors and Biosensors

Quantum dots are nanometre-scale semiconductor crystals with unique optical properties that are advantageous for the development of novel chemical sensors and biosensors. The surface chemistry of luminescent quantum dots has encouraged the development of multiple probes based on linked recognition molecules such as peptides, nucleic acids or small-molecule ligands. This review overviews the design of sensitive and selective nanoprobes, ranging from the type of target molecules to the optical transduction scheme. Representative examples of quantum dot-based optical sensors from this fast-moving field have been selected and are discussed towards the most promising directions for future research

Molecular Characterisation of Small Molecule Agonists Effect on the Human Glucagon Like Peptide-1 Receptor Internalisation

The glucagon-like peptide receptor (GLP-1R), which is a G-protein coupled receptor (GPCR), signals through both Gαs and Gαq coupled pathways and ERK phosphorylation to stimulate insulin secretion. The aim of this study was to determine molecular details of the effect of small molecule agonists, compounds 2 and B, on GLP-1R mediated cAMP production, intracellular Ca2+ accumulation, ERK phosphorylation and its internalisation. In human GLP-1R (hGLP-1R) expressing cells, compounds 2 and B induced cAMP production but caused no intracellular Ca2+ accumulation, ERK phosphorylation or hGLP-1R internalisation. GLP-1 antagonists Ex(9-39) and JANT-4 and the orthosteric binding site mutation (V36A) in hGLP-1R failed to inhibit compounds 2 and B induced cAMP production, confirming that their binding site distinct from the GLP-1 binding site on GLP-1R. However, K334A mutation of hGLP-1R, which affects Gαs coupling, inhibited GLP-1 as well as compounds 2 and B induced cAMP production, indicating that GLP-1, compounds 2 and B binding induce similar conformational changes in the GLP-1R for Gαs coupling. Additionally, compound 2 or B binding to the hGLP-1R had significantly reduced GLP-1 induced intracellular Ca2+ accumulation, ERK phosphorylation and hGLP-1R internalisation. This study illustrates pharmacology of differential activation of GLP-1R by GLP-1 and compounds 2 and B