Open-source automated insulin delivery (OS-AID) systems combine commercially available insulin pumps and continuous glucose monitors with open-source algorithms to automate insulin dosing for people ...with insulin-requiring diabetes. Two data sets (OPEN and the OpenAPS Data Commons) contain anonymized OS-AID user data.
We assessed glycemic variability (GV) outcomes in the OPEN data set and characterized it alongside a comparison to the n = 122 version of the OpenAPS Data Commons. Glucose data are analyzed using an unsupervised machine learning algorithm for clustering, and GV metrics are quantified using statistical tests for distribution comparison. Demographic data are also analyzed quantitatively.
The n = 75 OPEN data set contains 36 827 days worth of data. Mean TIR is 82.08% (TOR < 70: 3.66%; TOR > 180: 14.3%). LBGI (
< .05) differs by gender whereas HBGI distributions are similar (
> .05). GV metrics (except TOR < 70, LBGI) show a statistically significant difference (
< .05) between data sets.
Both the OPEN and OpenAPS Data Commons data sets show TOR < 70, TIR, and TOR > 180 within recommended goals, adding additional evidence of real-world efficacy of OS-AID. Future research should evaluate in more detail potential data set differences and relationships between individual patterns of user behaviors and GV outcomes.
Origin-destination (OD) data collection methods are steadily attempting to move from conventional survey techniques (roadside interview, license plate, etc.) toward using passively collected big data ...sources such as those based on global positioning system (GPS) and cell phone call detail records (CDR). In this study, a new passive data source, Google’s Aggregated and Anonymized Trips (AAT), was used to derive hourly OD demand matrices for the San Francisco Bay Area. Since the AAT dataset contains relative flows or weights as opposed to absolute trips, machine learning techniques were applied to convert them with the help of observed OD flows from expanded household travel survey. Several machine learning models were trained to perform quite well for both training and test data. However, it was found that the multi-layer perceptron (MLP), a neural networks approach, resulted in the best performing model for the conversion. Additionally, all models were used for predictions in a hypothetical application context where input AAT data were scaled by different growth factors. This exercise showed that, even though the trip predictions of all models were close to each other initially, they varied widely for different magnitudes of OD markets and growth factors.
•OS AID has been shown to improve clinical outcomes and quality of life.•This is the first study to identify the most common barriers to uptake of OS AID among those currently not using such a ...system.•The findings highlight the implications of inequalities in access to OS AID and how they might be addressed.
Social and technical trends are empowering people with diabetes to co-create or self-develop medical devices and treatments to address their unmet healthcare needs, for example, open-source automated insulin delivery (AID) systems. This study aims to investigate the perceived barriers towards adoption and maintaining of open-source AID systems.
This is a multinational study based on a cross-sectional, retrospective web-based survey of non-users of open-source AID. Participants (n = 129) with type 1 diabetes from 31 countries were recruited online to elicit their perceived barriers towards building and maintaining of an open-source AID system.
Sourcing the necessary components, lack of confidence in one's own technology knowledge and skills, perceived time and energy required to build a system, and fear of losing healthcare provider support appear to be major barriers towards the uptake of open-source AID.
This study identified a range of structural and individual-level barriers to uptake of open-source AID. Some of these individual-level barriers may be overcome over time through the peer support of the DIY online community as well as greater acceptance of open-source innovation among healthcare professionals. The findings have important implications for understanding the possible wider diffusion of open-source diabetes technology solutions in the future.
With rising urban freeway congestion and limited funds available for highway expansion, it may be essential to manage traffic growth by using high-occupancy toll lanes and other travel demand ...management (TDM) measures. To prepare for and help guide freeway corridor management planning in the US-101 and I-280 corridors in San Francisco, California, information describing trip origins and destinations by time of day was desired. Observed roadway facility-specific origin–destination (O-D) flows can help researchers to understand spatial distribution of demand and impute willingness to pay, actions that are useful in evaluating various TDM strategies. This paper describes a new passively collected O-D data source—Google’s aggregated and anonymized trip (AAT) data—obtained under Google’s Better Cities program. Aggregate hourly flow matrices for 85 districts covering California’s nine-county Bay Area specific to four freeway segments in San Francisco were obtained. Because AAT data account for only a sample of travelers, Google provides relative flows rather than absolute counts. Linear regression models were estimated to relate relative flows in the AAT data set and observed traffic volumes from the California Department of Transportation’s Performance Measurement System. The models were applied to convert relative flows to trips and derive facility-specific, time-dependent O-D matrices. Comparison of these facility-specific O-D matrices to select link O-D matrices from a regional travel demand model show that there is a higher correlation in terms of productions at origin districts and attractions at destination districts than at the O-D flow level. Some opportunities and limitations of the new data source are discussed, along with recommendations for future research.
Late-night transit service provides an important connection to jobs, entertainment venues, and other destinations in San Francisco, California, and other major cities. In 2016, the San Francisco ...County Transportation Authority led a comprehensive reexamination of the region’s late-night bus network, which provided service between about midnight and 5:00 a.m., while the region’s rail services were closed for maintenance. Previous literature established the general characteristics of late-night transit users and trip generators but did not develop and validate the use of a specific tool to plan service. Other researchers also developed transit propensity indexes (TPIs) with the use of demographic data for transit service in general but not specifically for the late-night period. A new approach was used to assess transit demand for late-night work trips by using Census Transportation Planning Package data to identify late-night work trips and combining those trip volumes with additional demographic factors associated with reliance on public transit to develop a late-night TPI. The hypothesis was that high TPI scores were an indicator of areas where late-night transit would attract strong ridership. The research team compared the index results with ridership on existing routes by using a stop-level regression analysis to validate that the TPI is predictive of ridership at a statistically significant level. It was concluded that the TPI together with productivity analysis of existing routes supported identification of potential late-night transit network changes to improve coverage in areas where riders would most need and use the service.
This study was undertaken to determine if crosstalk among the transient receptor potential (TRP) melastatin 8 (TRPM8), TRP vanilloid 1 (TRPV1), and vascular endothelial growth factor (VEGF) receptor ...triad modulates VEGF-induced Ca2+ signaling in human corneal keratocytes. Using RT-PCR, qPCR and immunohistochemistry, we determined TRPV1 and TRPM8 gene and protein coexpression in a human corneal keratocyte cell line (HCK) and human corneal cross sections. Fluorescence Ca2+ imaging using both a photomultiplier and a single cell digital imaging system as well as planar patch-clamping measured relative intracellular Ca2+ levels and underlying whole-cell currents. The TRPV1 agonist capsaicin increased both intracellular Ca2+ levels and whole-cell currents, while the antagonist capsazepine (CPZ) inhibited them. VEGF-induced Ca2+ transients and rises in whole-cell currents were suppressed by CPZ, whereas a selective TRPM8 antagonist, AMTB, increased VEGF signaling. In contrast, an endogenous thyroid hormone-derived metabolite 3-lodothyronamine (3-T(1)AM) suppressed increases in the VEGF-induced current. The TRPM8 agonist menthol increased the currents, while AMTB suppressed this response. The VEGF-induced increases in Ca2+ influx and their underlying ionic currents stem from crosstalk between VEGFR and TRPV1, which can be impeded by 3-T(1)AM-induced TRPM8 activation. Such suppression in turn blocks VEGF-induced TRPV1 activation. Therefore, crosstalk between TRPM8 and TRPV1 inhibits VEGFR-induced activation of TRPV1.
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