Computational Optimization of Metal-Organic Framework (MOF) Arrays for Chemical Sensing

Although commercial gas sensors exist for applications such as product quality control, industrial food monitoring, and smoke detection, there are many potential applications for which adequate gas sensing technology is lacking. There is an unmet need for gas sensors to detect natural gas leaks, for disease detection via breath analysis, and for environmental monitoring, to name just a few examples. Current gas sensors do not exhibit the sensitivity and/or selectivity required to detect trace amounts of the required gases in complex gas mixture environments (e.g., ambient air or a patient’s breath). It is known that arrays of sensors, or electronic noses, improve chemical detection when compared to single sensor elements. Although some work has been done to optimize sensor device performance, there are many potential sensing materials that have not yet been extensively explored. Herein, we explore the use of metal-organic framework (MOF) materials in sensor arrays, exploiting their high adsorption capabilities to yield more selective and sensitive electronic noses. As a relatively new class of materials, MOFs have not been thoroughly investigated for gas sensing applications. In particular, prior to our work, there had only been a few investigations of MOF sensor arrays and those were limited to purely experimental work that relied heavily on trial-and-error. We demonstrate that leveraging computational modeling and optimization to rationally design MOF sensor arrays can yield significantly improved sensing performance. Our novel computational method was carried out first by predicting individual MOF sensor responses via molecular simulations. Then, we developed a method to analyze those individual responses and provide output signals for entire sensor arrays to predict unknown gas mixtures. Following this, the prediction ability of each array was evaluated according to the Kullback-Liebler divergence (KLD), where we determined the best arrays for detecting methane-in-air mixtures. Finally, we developed and validated a genetic algorithm that enables the optimization of large MOF arrays

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Computational Design of Metal–Organic Framework Arrays for Gas Sensing: Influence of Array Size and Composition on Sensor Performance

Gas sensors are used widely in applications ranging from food quality assessment to environmental monitoring. When put in arrays, they are called “electronic noses” and have improved capability in distinguishing varied gas mixtures. Metal–organic frameworks (MOFs) are promising materials for use in electronic noses due to their high surface areas, reproducibility, and tunability. However, due to the number of MOFs to choose from and the even larger number of ways they can be combined in arrays, it is a challenge to select the right combination of materials for any given sensing application. In this work, we show how well a wide range of CO₂, N₂, C₂H₆, and CH₄ gas mixtures can be distinguished by combining sensing input from arrays of different types of MOFs. We simulated adsorption of 78 gas mixtures in five MOFs (IRMOF-1, HKUST-1, NU-125, UiO-66, and ZIF-8) at 1 and 10 bar via classical grand canonical Monte Carlo (GCMC) methods. We then defined a scoring metric, the sensor array gas space (SAGS) score, which quantifies the potential of various MOF sensor arrays for distinguishing among the tested gas mixtures assuming only the total mass of the adsorbed mixture could be measured. We found that combining sensing input from multiple types of MOFs can significantly increase the SAGS score, well beyond what could be achieved with only an individual MOF sensor. We also compare different MOF combinations to determine the optimal array at different pressures and find that there is little correlation between the best arrays at 1 bar versus 10 bar

The mitochondrial genome of the pentastome parasite Raillietiella orientalis Hett, 1915 (Raillietiellida; Raillietiellidae) with notes on its phylogenetic position

In this study we sequenced and annotated the complete mitochondrial genome of the invasive reptile parasite Raillietiella orientalis using Illumina DNA sequencing. The length of the mitogenome was 15,320 bp and had a GC content of 33.1%. The mitogenome contained 13 protein-coding genes, two ribosomal RNA genes, and 22 tRNA genes, the order of which was diagnostic of Pancrustacean mitogenomes. A phylogenetic tree constructed from the 13 protein-coding genes of R. orientalis and 26 other Pancrustacean mitogenomes supported the placement of R. orientalis as part of the monophyletic subclass Pentastomida within the Maxillopoda and sister to the subclass Branchiura

Adherence to a five day treatment course of topical fluocinonide 0.1% cream in atopic dermatitis

Background: Adherence in the treatment of chronic inflammatory skin diseases such as atopic dermatitis is poor. Methods to improve adherence have proven difficult.Purpose: To determine whether a short course of treatment with a high-potency corticosteroid will improve adherence compared to longer treatment studies and if improvement in disease and itch continues after treatment.Methods: 10 patients with mild to moderate atopic dermatitis were instructed to apply fluocinonide 0.1% cream twice daily for 5 days. Adherence was self-reported and electronically monitored. Treatment outcomes were assessed in terms of Visual Analog Scale of Itch (VAS), Eczema Area and Severity Index (EASI), and Investigator Global Assessment (IGA) scores.Results: The median adherence rate was 40% (range of 0-100). The median percent change in VAS from baseline measures on days 7 and 14 were 90% (range -13, 100, p=0.02) and 52% (range 0, 100, p=0.004). On days 7 and 14, 20% and 70% patients achieved an EASI-75 and 40% and 60% an IGA of 0 or 1.Limitations: Small sample size limited subgroup analyses.Conclusions: Adherence rates with short-term treatment were similar to previously reported rates in longer term treatment studies. However, even non-adherent patients had significant improvement in itch and disease severity

Adherence to a five day treatment course of topical fluocinonide 0.1% cream in atopic dermatitis

Background: Adherence in the treatment of chronic inflammatory skin diseases such as atopic dermatitis is poor. Methods to improve adherence have proven difficult.Purpose: To determine whether a short course of treatment with a high-potency corticosteroid will improve adherence compared to longer treatment studies and if improvement in disease and itch continues after treatment.Methods: 10 patients with mild to moderate atopic dermatitis were instructed to apply fluocinonide 0.1% cream twice daily for 5 days. Adherence was self-reported and electronically monitored. Treatment outcomes were assessed in terms of Visual Analog Scale of Itch (VAS), Eczema Area and Severity Index (EASI), and Investigator Global Assessment (IGA) scores.Results: The median adherence rate was 40% (range of 0-100). The median percent change in VAS from baseline measures on days 7 and 14 were 90% (range -13, 100, p=0.02) and 52% (range 0, 100, p=0.004). On days 7 and 14, 20% and 70% patients achieved an EASI-75 and 40% and 60% an IGA of 0 or 1.Limitations: Small sample size limited subgroup analyses.Conclusions: Adherence rates with short-term treatment were similar to previously reported rates in longer term treatment studies. However, even non-adherent patients had significant improvement in itch and disease severity