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1. Lyophilization of premixed COVID‐19 diagnostic RT‐qPCR reactions enables stable long‐term storage at elevated temperature

   https://doi.org/10.1002/biot.202000572  

   Hammerling, Michael J.; Warfel, Katherine F.; Jewett, Michael C. (May 2021, Biotechnology Journal)

   null (Ed.)

   Background Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) diagnostic tests for SARS-CoV-2 are the cornerstone of the global testing infrastructure. However, these tests require cold-chain shipping to distribute, and the labor of skilled technicians to assemble reactions and interpret the results. Strategies to reduce shipping and labor costs at the point-of-care could aid in diagnostic testing scale-up and response to the COVID-19 outbreak, as well as in future outbreaks. Methods In this study we test both lab-developed and commercial SARS-CoV-2 diagnostic RT-qPCR mixes for the ability to be stabilized against elevated temperature by lyophilization. Fully assembled reactions were lyophilized and stored for up to a month at ambient or elevated temperature and were subsequently assayed for their ability to detect dilutions of synthetic SARS-CoV-2 RNA. Results Of the mixes tested, we show that one commercial mix can maintain activity and sensitivity after storage for at least 30 days at ambient temperature after lyophilization. We also demonstrate that lyoprotectants such as disaccharides can stabilize freeze-dried diagnostic reactions against elevated temperatures (up to 50°C) for at least 30 days. Conclusion We anticipate that the incorporation of these methods into SARS-CoV-2 diagnostic testing will improve testing pipelines by reducing labor at the testing facility and eliminating the need for cold-chain shipping. 

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2. Fisher ratio feature selection by manual peak area calculations on comprehensive two-dimensional gas chromatography data using standard mixtures with variable composition, storage, and interferences

   https://doi.org/10.1007/s00216-022-04484-8  

   Oliva, Danson J.; Cheung, Cynthia; Perrault, Katelynn A. (December 2022, Analytical and Bioanalytical Chemistry)

   Comprehensive two-dimensional gas chromatography (GC×GC) is becoming increasingly more common for non-targeted characterization of complex volatile mixtures. The information gained with higher peak capacity and sensitivity provides additional sample composition information when one-dimensional GC is not adequate. GC×GC generates complex multivariate data sets when using non-targeted analysis to discover analytes. Fisher ratio (FR) analysis is applied to discern class markers, limiting complex GC×GC profiles to the most discriminating compounds between classes. While many approaches for feature selection using FR analysis exist, FR can be calculated relatively easily directly on peak areas after any native software has performed peak detection. This study evaluated the success rates of manual FR calculation and comparison to a critical F-value for samples analyzed by GC×GC with defined concentration differences. Long-term storage of samples and other spiked interferences were also investigated to examine their impact on analyzing mixtures using this FR feature selection strategy. Success rates were generally high with mostly 90-100% success rates and some instances of percentages between 80 and 90%. There were rare cases of false positives present and a low occurrence of false negatives. When errors were made in the selection of a compound, it was typically due to chromatographic artifacts present in chromatograms and not from the FR approach itself. This work provides foundational experimental data on the use of manual FR calculations for feature selection from GC×GC data. 

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3. Tuning cesium–guanidinium in formamidinium tin triiodide perovskites with an ethylenediammonium additive for efficient and stable lead-free perovskite solar cells

   https://doi.org/10.1039/d0ma00520g  

   Tosado, Gabriella A.; Zheng, Erjin; Yu, Qiuming (December 2020, Materials Advances)

   null (Ed.)

   Achieving efficient and stable tin-based perovskite solar cells remains challenging. In this work, we incorporate the ethylenediammonium diiodide (EDAI 2 ) additive into a cesium–guanidinium doped formamidinium tin triiodide perovskite with the composition of (CsGA) x FA 1−2x SnI 3 + y % EDAI 2 . This new perovskite utilizes the strong hydrogen bonding of the guanidinium cation and the lattice strain relaxation of the small cesium cation as well as the hollowing and passivation effects of the EDAI 2 additive. The EDAI 2 additive not only yields pinhole-free cubic phase perovskite films but also decreases both shallow and deep trap states in the perovskite films. These effects are pronounced with the increase of substitution of the pair of GA + and Cs + . The new perovskites are deployed in inverted planar solar cells. A maximum power conversion efficiency (PCE) of 5.01% is achieved with the (CsGA) 0.15 FA 0.70 SnI 3 + 0% EDAI 2 device but the device degrades after storage in a nitrogen-filled glove box for 30 days. Both performance and stability are improved with the addition of EDAI 2 . A maximum PCE of 5.72% is achieved with the (CsGA) 0.15 FA 0.70 SnI 3 + 1.0% EDAI 2 device. The (CsGA) 0.15 FA 0.70 SnI 3 + 1.5% EDAI 2 devices exhibit a maximum PCE of 5.69% and the performance is further increased to 6.39% after storage in a nitrogen-filled glove box for 4 days; 70% of the initial PCE is retained after 45 days. This study demonstrates the benefit of tuning cation sizes and introducing divalent cations to integrate stabilizing factors into pure Sn perovskites, creating new routes for efficient and stable lead-free perovskite solar cells. 

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4. The owl sensor: a ‘fragile’ DNA nanostructure for the analysis of single nucleotide variations

   https://doi.org/10.1039/c8nr01107a  

   Karadeema, Rebekah J.; Stancescu, Maria; Steidl, Tyler P.; Bertot, Sophia C.; Kolpashchikov, Dmitry M. (January 2018, Nanoscale)

   Analysis of single nucleotide variations (SNVs) in DNA and RNA sequences is instrumental in healthcare for the detection of genetic and infectious diseases and drug-resistant pathogens. Here we took advantage of the developments in DNA nanotechnology to design a hybridization sensor, named the ‘owl sensor’, which produces a fluorescence signal only when it complexes with fully complementary DNA or RNA analytes. The novelty of the owl sensor operation is that the selectivity of analyte recognition is, at least in part, determined by the structural rigidity and stability of the entire DNA nanostructure rather than exclusively by the stability of the analyte–probe duplex, as is the case for conventional hybridization probes. Using two DNA and two RNA analytes we demonstrated that owl sensors differentiate SNVs in a wide temperature range of 5 °C–32 °C, a performance unachievable by conventional hybridization probes including the molecular beacon probe. The owl sensor reliably detects cognate analytes even in the presence of 100 times excess of single base mismatched sequences. The approach, therefore, promises to add to the toolbox for the diagnosis of SNVs at ambient temperatures. 

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5. Identifiability and Parameter Estimation of Within-Host Model of HIV with Immune Response

   https://doi.org/10.3390/math12182837  

   Liyanage, Yuganthi R; Mirsaleh_Kohan, Leila; Martcheva, Maia; Tuncer, Necibe (September 2024, Mathematics)

   This study examines the interactions between healthy target cells, infected target cells, virus particles, and immune cells within an HIV model. The model exhibits two equilibrium points: an infection-free equilibrium and an infection equilibrium. Stability analysis shows that the infection-free equilibrium is locally asymptotically stable when R0<1. Further, it is unstable when R0>1. The infection equilibrium is locally asymptotically stable when R0>1. The structural and practical identifiabilities of the within-host model for HIV infection dynamics were investigated using differential algebra techniques and Monte Carlo simulations. The HIV model was structurally identifiable by observing the total uninfected and infected target cells, immune cells, and viral load. Monte Carlo simulations assessed the practical identifiability of parameters. The production rate of target cells (λ), the death rate of healthy target cells (d), the death rate of infected target cells (δ), and the viral production rate by infected cells (π) were practically identifiable. The rate of infection of target cells by the virus (β), the death rate of infected cells by immune cells (Ψ), and antigen-driven proliferation rate of immune cells (b) were not practically identifiable. Practical identifiability was constrained by the noise and sparsity of the data. Analysis shows that increasing the frequency of data collection can significantly improve the identifiability of all parameters. This highlights the importance of optimal data sampling in HIV clinical studies, as it determines the best time points, frequency, and the number of sample points required to accurately capture the dynamics of the HIV infection within a host. 

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