Highly-automated, high-throughput replication of yeast-based logic circuit design assessments.

We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of Saccharomyces cerevisiae by Gander et al. Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency's Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned. Graphical Abstract.

Designing supply chains to meet the growing need of vaccines: evidence from four countries.

BACKGROUND: Immunization supply chains (iSCs) move vaccines from manufacturer to point of use with the added complexities of requiring cold chain and an increasing need for agility and efficiency to ensure vaccine quality and availability. Underperforming iSCs have been widely acknowledged as a key constraint to achieving high immunization coverage rates in low- and middle-income countries. This paper details the system design approach used to analyze the iSC network in Sierra Leone, Madagascar, Niger and Guinea and documents six lessons. METHODOLOGY: Between 2018 and 2020, these countries implemented the system design approach, involving four key steps: (1) advocate and introduce to engage stakeholders and prioritize identification of modeling scenarios; (2) collect data and plan analysis through document review and key informant interviews; (3) analyze system design scenarios using computer software modeling tools (LLamasoft's Supply Chain Guru and AnyLogic's AnyLogistix) for optimization and simulation modeling as well as further analysis with Excel, Google maps, and OpenStreetMap; and (4) build consensus on optimized model and implementation roadmap using the Traffic Light Analysis tool and building on stakeholder input. FINDINGS: Key lessons include the following: (1) define system design objectives based on country priorities; (2) establish consensus with stakeholders on scenarios to model; (3) modeling provides the evidence but not the answer; (4) costs should not be weighted above other decision criteria; (5) data collection-work smarter, not harder; (6) not all questions can be answered with a computer model. DISCUSSION: A system design approach can identify changes to the design of the supply chain that can introduce efficiencies and improve reliability. This approach can be more effective when these lessons and principles are applied at the country level. The lessons from these four countries contribute to global thinking and best practices related to system design. The modeling and system design approach provides illustrative results to guide decision-makers. It does not give a "final answer", but compares and contrasts.

VisBOL2-Improving Web-Based Visualization for Synthetic Biology Designs.

VisBOL is a web-based visualization tool used to depict genetic circuit designs. This tool depicts simple DNA circuits adequately, but it has become increasingly outdated as new versions of SBOL Visual were released. This paper introduces VisBOL2, a heavily redesigned version of VisBOL that makes a number of improvements to the original VisBOL, including proper functional interaction rendering, dynamic viewing, a more maintainable code base, and modularity that facilitates compatibility with other software tools. This modularity is demonstrated by incorporating VisBOL2 into a sequence visualization plugin for SynBioHub.

Redesigning immunization supply chains: Results from three country analyses.

INTRODUCTION: Immunization supply chains (iSC) are essential for ensuring access to vaccines that prevent diseases. Guinea, Madagascar, and Niger initiated iSC system design efforts to conduct analysis of alternative supply chain scenarios to identify areas for improvement. METHODOLOGY: Key stakeholders from Ministries of Health and immunization programs identified bottlenecks in the current iSC and prioritized five general design scenarios to model in each country. Scenarios included aspects of integration, changing supply chain levels and delivery frequency, ignoring administrative boundaries, and direct delivery. Primary and secondary data were collected and cleaned. Analysis was completed using Supply Chain Guru (Madagascar and Niger) and AnyLogistix (Guinea) modeling software to build a virtual representation of the iSC physical components and operating policies. RESULTS: Modeling results were compared using both quantitative and qualitative criteria (total operating costs, cost per dose, cold chain capacity, risk of mishandling, logistics burden on healthcare workers, feasibility to implement, and equity). Using a Stop Light Analysis for user-friendly understanding of positive, negative or minimal impact on scenarios, cost savings were realized in most scenarios in Madagascar (except using autonomous aerial vehicles); proposed scenarios in Guinea increased costs or had minimal impact; in Niger, eliminating regional tiers reduced costs. Facility level cold chain was sufficient in all countries. Effect on qualitative indicators largely depended on the scenario and country context. DISCUSSION: Similarities in scenarios selected were seen across the three countries. Results suggest that efficiencies can be found through changes to the iSC design, but the benefits of each scenario must be considered in the country context. Results of the analysis do not provide "the right answer" but rather options and guidance which then must be grounded in the country context and used as evidence for decision making to ensure reliable availability of vaccines.

One- and two-stage anaerobic co-digestion of cucumber waste and sewage sludge.

The demand for uniformly sized and shaped produce that are aesthetically pleasing results in significant food waste throughout the world. Cucumber waste is a major agricultural waste product in a number of countries, especially areas with high pickle production. Opportunity exists for wastewater treatment plants containing anaerobic digesters to utilize cucumber agricultural and industrial waste for biogas production. The biomethane potential of cucumber waste as a substrate for co-digestion with sewage sludge was assessed. The impact of long-term co-digestion of cucumber was then evaluated using mesophilic continuously stirred tank reactors (CSTRs), in both single- and two-stage anaerobic co-digestion with sewage sludge. Ground cucumber waste was added to sewage sludge at 8% of the volume (4.5-4.6% of the organic load) and CSTRs were maintained for five hydraulic retention times (HRTs). One-stage co-digestion of cucumber waste produced comparable gas levels as CSTRs without cucumbers (averaging 219 and 221 m3/kgVS/h, respectively) after two HRTs. The two-stage cucumber co-digestion CSTR averaged 64% higher specific gas than the control and single-stage digester, although the volumetric gas produced was lower (averaging 152 m3/kgVS/h) likely due to gas loss in the first stage resulting in a lower organic load rate. After four HRTs, relative methanogen content showed dramatic differences in levels of hydrogenotrophic methanogens for the two-stage digester, while the one-stage digester containing cucumber waste showed minor differences relative to the control. Cucumber waste co-digestion with sewage sludge is effective although numerous conditions could be utilized to optimize gas production.

Using Data to Keep Vaccines Cold in Kenya: Remote Temperature Monitoring with Data Review Teams for Vaccine Management.

BACKGROUND: Global vaccination coverage rates have remained around 85% for the past several years. Increasing immunization coverage rates requires an effective cold chain to maintain vaccine potency. Remote temperature monitoring (RTM) technology for vaccine refrigerators has shown promise for improving the ability of supply systems to maintain optimal temperature conditions to ensure potent vaccines reach the end users. METHODS: A pilot study of RTM technology and data use teams was implemented in 36 study sites in Kenya. Data were collected at baseline and endline points over a 3-month baseline and 7-month implementation period. Data included 44 qualitative interviews, process logs, meeting minutes from data use team meetings, and quantitative temperature and power data from the RTM devices. RESULTS: The ability of cold chain equipment to maintain World Health Organization-recommended temperatures in study sites improved markedly between the baseline and implementation periods, resulting in an improvement in total time spent in the correct range from 83.9% in the baseline period to 90.9% in the intervention period and an improvement in time spent in the too cold range from 6.5% to 1.5%. Friedman tests revealed that differences in time spent in the correct range and time spent in the too cold range during the course of the study were statistically significant (P<.001 and P=.04, respectively). Qualitative and quantitative data suggest that this improvement was due to a combination of improved responsiveness to temperature excursions at the facility level, resulting from SMS alarms for temperature excursion periods, and improved ability at the management level to recognize and address recurring problems. CONCLUSION: The combination of using RTM technology with a structured data review process by a management team is a promising approach for improving cold chain outcomes. Future research examining the added value of each of the technological and behavioral components separately is needed.

Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia.

BACKGROUND: While cognitive-behavioral therapy for insomnia constitutes the first-line treatment for chronic insomnia, only few reports have investigated how sleep architecture relates to response to this treatment. In this pilot study, we aimed to determine whether pre-treatment sleep spindle density predicts treatment response to cognitive-behavioral therapy for insomnia. METHODS: Twenty-four participants with chronic primary insomnia participated in a 6-week cognitive-behavioral therapy for insomnia performed in groups of 4-6 participants. Treatment response was assessed using the Pittsburgh Sleep Quality Index and the Insomnia Severity Index measured at pre- and post-treatment, and at 3- and 12-months' follow-up assessments. Secondary outcome measures were extracted from sleep diaries over 7 days and overnight polysomnography, obtained at pre- and post-treatment. Spindle density during stage N2-N3 sleep was extracted from polysomnography at pre-treatment. Hierarchical linear modeling analysis assessed whether sleep spindle density predicted response to cognitive-behavioral therapy. RESULTS: After adjusting for age, sex, and education level, lower spindle density at pre-treatment predicted poorer response over the 12-month follow-up, as reflected by a smaller reduction in Pittsburgh Sleep Quality Index over time. Reduced spindle density also predicted lower improvements in sleep diary sleep efficiency and wake after sleep onset immediately after treatment. There were no significant associations between spindle density and changes in the Insomnia Severity Index or polysomnography variables over time. CONCLUSION: These preliminary results suggest that inter-individual differences in sleep spindle density in insomnia may represent an endogenous biomarker predicting responsiveness to cognitive-behavioral therapy. Insomnia with altered spindle activity might constitute an insomnia subtype characterized by a neurophysiological vulnerability to sleep disruption associated with impaired responsiveness to cognitive-behavioral therapy.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries.

BACKGROUND: Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. METHODS: Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. RESULTS: For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. CONCLUSIONS: Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed.