Real-World Use of Control-IQ Technology Is Associated with a Lower Rate of Severe Hypoglycemia and Diabetic Ketoacidosis Than Historical Data: Results of the Control-IQ Observational (CLIO) Prospective Study

Objective: Severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) remain significant risks with intensive insulin therapy. While these adverse event (AE) rates are generally very low in advanced hybrid closed-loop (AHCL) clinical studies, prospectively collected real-world AE rates are lacking. Research Design and Methods: The Control-IQ Observational (CLIO) study was a single-arm, prospective, longitudinal, postmarket surveillance study of individuals with type 1 diabetes (T1D) age 6 years and older who began the use of t:slim X2 insulin pump with Control-IQ technology in the real-world outpatient setting. AEs were reported monthly over 12 months and were compared to historical data from the T1D Exchange. Patient-reported outcomes were assessed quarterly. All study visits were virtual. Results: Three thousand one hundred fifty-seven participants enrolled from August 2020 through March 2022. Two thousand nine hundred ninety-eight participants completed through 12 months. SH rates were significantly lower than historic rates for children (9.31 vs. 19.31 events/100 patient years, d = 0.29, P < 0.01) and adults (9.77 vs. 29.49 events/100 patient years, d = 0.53, P < 0.01). DKA rates were also significantly lower in both groups. Lower observed rates of AEs occurred independent of baseline hemoglobin A1c or prior insulin delivery method. Time in range 70-180 mg/dL was 70.1% (61.0-78.8) for adults, 61.2% (52.4-70.5) for age 6-13, 60.9% (50.1-71.8) for age 14-17, and 67.3% (57.4-76.9) overall. Reduction in diabetes burden was consistently reported. Conclusions: SH and DKA rates were lower for users of t:slim X2 with Control-IQ technology compared to historical data for both adults and children. Real-world use of this AHCL system proved safe and effective in this virtual study design. The study was registered at clinicaltrials.gov (NCT04503174).

Digital exposure notification tools: A global landscape analysis

BACKGROUND

As the COVID-19 pandemic continues, digital exposure notification systems are increasingly used to support traditional contact tracing and other preventive strategies. Likewise, a plethora of COVID-19 mobile applications have emerged. Objective: To characterize the global landscape of pandemic related mobile applications, including digital exposure notification and contact tracing tools.

DATA SOURCES AND METHODS

The following queries were entered into the Google search engine: "(*country name* COVID app) OR (COVID app *country name*) OR (COVID app *country name*+) OR (*country name*+ COVID app)". The App Store, Google Play, and official government websites were then accessed to collect descriptive data for each application. Descriptive data were qualified and quantified using standard methods. COVID-19 Exposure Notification Systems (ENS) and non-Exposure Notification products were categorized and summarized to provide a global landscape review.

RESULTS

Our search resulted in a global count of 224 COVID-19 mobile applications, in 127 countries. Of these 224 apps, 128 supported exposure notification, with 75 employing the Google Apple Exposure Notification (GAEN) application programming interface (API). Of the 75 apps using the GAEN API, 15 apps were developed using Exposure Notification Express, a GAEN turnkey solution. COVID-19 applications that did not include exposure notifications (n = 96) focused on COVID-19 Self-Assessment (35·4%), COVID-19 Statistics and Information (32·3%), and COVID-19 Health Advice (29·2%).

CONCLUSIONS

The digital response to COVID-19 generated diverse and novel solutions to support non-pharmacologic public health interventions. More research is needed to evaluate the extent to which these services and strategies were useful in reducing viral transmission.

Exposure notification system activity as a leading indicator for SARS-COV-2 caseload forecasting

PURPOSE

Digital methods to augment traditional contact tracing approaches were developed and deployed globally during the COVID-19 pandemic. These "Exposure Notification (EN)" systems present new opportunities to support public health interventions. To date, there have been attempts to model the impact of such systems, yet no reports have explored the value of real-time system data for predictive epidemiological modeling.

METHODS

We investigated the potential to short-term forecast COVID-19 caseloads using data from California's implementation of the Google Apple Exposure Notification (GAEN) platform, branded as CA Notify. CA Notify is a digital public health intervention leveraging resident's smartphones for anonymous EN. We extended a published statistical model that uses prior case counts to investigate the possibility of predicting short-term future case counts and then added EN activity to test for improved forecast performance. Additional predictive value was assessed by comparing the pandemic forecasting models with and without EN activity to the actual reported caseloads from 1-7 days in the future.

RESULTS

Observation of time series presents noticeable evidence for temporal association of system activity and caseloads. Incorporating earlier ENs in our model improved prediction of the caseload counts. Using Bayesian inference, we found nonzero influence of EN terms with probability one. Furthermore, we found a reduction in both the mean absolute percentage error and the mean squared prediction error, the latter of at least 5% and up to 32% when using ENs over the model without.

CONCLUSIONS

This preliminary investigation suggests smartphone based ENs can significantly improve the accuracy of short-term forecasting. These predictive models can be readily deployed as local early warning systems to triage resources and interventions.

Randomized trial evaluating an mHealth intervention for the early community-based detection and follow-up of cutaneous leishmaniasis in rural Colombia

BACKGROUND

In Latin America, cutaneous leishmaniasis primarily affects dispersed rural communities, that have limited access to the public health system and medical attention. Mobile health (mHealth) strategies have shown potential to improve clinical management and epidemiological surveillance of neglected tropical diseases, particularly those of the skin.

METHODS

The Guaral +ST app for Android was designed to monitor cutaneous leishmaniasis treatment and assess therapeutic response. We carried out a randomized trial in the coastal municipality of Tumaco in southwestern Colombia, with parallel arms comparing a) follow-up aided by the app to b) standard institution-based follow-up. Treatment was prescribed according to national guidelines. Follow-up of therapeutic response was scheduled at the end of treatment and at 7, 13 and 26 weeks after the start of treatment. The primary endpoint was the proportion of participants who were monitored at or around week 26, allowing outcome and effectiveness of treatment to be determined.

RESULTS

Follow-up of treatment and outcome assessment was achieved in significantly more patients in the intervention arm than the controls, Of the 75 participants in the two randomized arms, 74 had information on whether or not treatment was followed and outcome determined at or around week 26. Among these, 26/49 (53.1%) were evaluated in the intervention arm, and none (0/25, 0%) in the control arm (difference = 53.1%, 95% confidence interval 39.1-67.0%, p<0.001). Of the 26 participants evaluated at or around week 26 in the intervention arm, 22 (84.6%) had cured. There were no serious adverse events, nor events of severe intensity among patients monitored by CHW using the app.

CONCLUSION

This study provides proof of concept for mHealth to monitor treatment of CL in remote and complex settings, deliver improved care and to provide information to the health system on the effectiveness of treatment as it is delivered to affected populations.

CLINICAL TRIAL REGISTRATION

ISRCTN54865992.

The neurophysiology of intraoperative error: An EEG study of trainee surgeons during robotic-assisted surgery simulations

Surgeons operate in mentally and physically demanding workspaces where the impact of error is highly consequential. Accurately characterizing the neurophysiology of surgeons during intraoperative error will help guide more accurate performance assessment and precision training for surgeons and other teleoperators. To better understand the neurophysiology of intraoperative error, we build and deploy a system for intraoperative error detection and electroencephalography (EEG) signal synchronization during robot-assisted surgery (RAS). We then examine the association between EEG data and detected errors. Our results suggest that there are significant EEG changes during intraoperative error that are detectable irrespective of surgical experience level.

Defining Key Performance Indicators for the California COVID-19 Exposure Notification System (CA Notify)

OBJECTIVES

Toward common methods for system monitoring and evaluation, we proposed a key performance indicator framework and discussed lessons learned while implementing a statewide exposure notification (EN) system in California during the COVID-19 epidemic.

MATERIALS AND METHODS

California deployed the Google Apple Exposure Notification framework, branded CA Notify, on December 10, 2020, to supplement traditional COVID-19 contact tracing programs. For system evaluation, we defined 6 key performance indicators: adoption, retention, sharing of unique codes, identification of potential contacts, behavior change, and impact. We aggregated and analyzed data from December 10, 2020, to July 1, 2021, in compliance with the CA Notify privacy policy.

RESULTS

We estimated CA Notify adoption at nearly 11 million smartphone activations during the study period. Among 1 654 201 CA Notify users who received a positive test result for SARS-CoV-2, 446 634 (27%) shared their unique code, leading to ENs for other CA Notify users who were in close proximity to the SARS-CoV-2-positive individual. We identified at least 122 970 CA Notify users as contacts through this process. Contact identification occurred a median of 4 days after symptom onset or specimen collection date of the user who received a positive test result for SARS-CoV-2.

PRACTICE IMPLICATIONS

Smartphone-based EN systems are promising new tools to supplement traditional contact tracing and public health interventions, particularly when efficient scaling is not feasible for other approaches. Methods to collect and interpret appropriate measures of system performance must be refined while maintaining trust and privacy.

Understanding the needs of people aging with type 1 diabetes: a user-focused research study with prototype diabetes advance directive and setting the stage for future research

Purpose

People living with Type 1 diabetes (T1D) are living longer than ever and facing the new "luxury" of the challenges of aging. While research is slowly expanding and addressing T1D physiology with regards to aging, there is little research addressing specific challenges and barriers to optimal care by those aging with T1D. To address this gap, this study employed human-centered design research to explore the gaps and barriers to care faced by people aging with T1D.

Methods

Researchers employed human-centered design methods of needfinding and user interviews and facilitated participatory workshops. In total, 27 people with T1D (PWT1D), 5 loved ones (partners of PWT1D), and 7 healthcare providers (HCPs) were engaged.

Results

Design artifacts were developed, including user personas that help visually articulate the different experiences of PWT1D and their unique needs as they age, as well as a prototype diabetes-specific advance directive that could be further refined to specifically aid those with Type 1 diabetes who are aging and requiring more interactions with the healthcare system. Initial user testing with people with T1D as well as healthcare providers demonstrated the need for such a diabetes advance directive tool or document.

Conclusion

This work supports the conclusion that additional focus and scientific enquiry should be given to the needs of people aging with Type 1 diabetes, with a goal of improving the experience of all people with T1D when interacting with their care providers or with the healthcare system as a whole.

Designing a Framework for Remote Cancer Care Through Community Co-design: Participatory Development Study

BACKGROUND

Recent shifts to telemedicine and remote patient monitoring demonstrate the potential for new technology to transform health systems; yet, methods to design for inclusion and resilience are lacking.

OBJECTIVE

The aim of this study is to design and implement a participatory framework to produce effective health care solutions through co-design with diverse stakeholders.

METHODS

We developed a design framework to cocreate solutions to locally prioritized health and communication problems focused on cancer care. The framework is premised on the framing and discovery of problems through community engagement and lead-user innovation with the hypothesis that diversity and inclusion in the co-design process generate more innovative and resilient solutions. Discovery, design, and development were implemented through structured phases with design studios at various locations in urban and rural Kentucky, including Appalachia, each building from prior work. In the final design studio, working prototypes were developed and tested. Outputs were assessed using the System Usability Scale as well as semistructured user feedback.

RESULTS

We co-designed, developed, and tested a mobile app (myPath) and service model for distress surveillance and cancer care coordination following the LAUNCH (Linking and Amplifying User-Centered Networks through Connected Health) framework. The problem of awareness, navigation, and communication through cancer care was selected by the community after framing areas for opportunity based on significant geographic disparities in cancer and health burden resource and broadband access. The codeveloped digital myPath app showed the highest perceived combined usability (mean 81.9, SD 15.2) compared with the current gold standard of distress management for patients with cancer, the paper-based National Comprehensive Cancer Network Distress Thermometer (mean 74.2, SD 15.8). Testing of the System Usability Scale subscales showed that the myPath app had significantly better usability than the paper Distress Thermometer (t63=2.611; P=.01), whereas learnability did not differ between the instruments (t63=-0.311; P=.76). Notable differences by patient and provider scoring and feedback were found.

CONCLUSIONS

Participatory problem definition and community-based co-design, design-with methods, may produce more acceptable and effective solutions than traditional design-for approaches.

A Risk-Based Clinical Decision Support System for Patient-Specific Antimicrobial Therapy (iBiogram): Design and Retrospective Analysis

Background

There is a pressing need for digital tools that can leverage big data to help clinicians select effective antibiotic treatments in the absence of timely susceptibility data. Clinical presentation and local epidemiology can inform therapy selection to balance the risk of antimicrobial resistance and patient risk. However, data and clinical expertise must be appropriately integrated into clinical workflows.

Objective

The aim of this study is to leverage available data in electronic health records, to develop a data-driven, user-centered, clinical decision support system to navigate patient safety and population health.

Methods

We analyzed 5 years of susceptibility testing (1,078,510 isolates) and patient data (30,761 patients) across a large academic medical center. After curating the data according to the Clinical and Laboratory Standards Institute guidelines, we analyzed and visualized the impact of risk factors on clinical outcomes. On the basis of this data-driven understanding, we developed a probabilistic algorithm that maps these data to individual cases and implemented iBiogram, a prototype digital empiric antimicrobial clinical decision support system, which we evaluated against actual prescribing outcomes.

Results

We determined patient-specific factors across syndromes and contexts and identified relevant local patterns of antimicrobial resistance by clinical syndrome. Mortality and length of stay differed significantly depending on these factors and could be used to generate heuristic targets for an acceptable risk of underprescription. Combined with the developed remaining risk algorithm, these factors can be used to inform clinicians’ reasoning. A retrospective comparison of the iBiogram-suggested therapies versus the actual prescription by physicians showed similar performance for low-risk diseases such as urinary tract infections, whereas iBiogram recognized risk and recommended more appropriate coverage in high mortality conditions such as sepsis.

Conclusions

The application of such data-driven, patient-centered tools may guide empirical prescription for clinicians to balance morbidity and mortality with antimicrobial stewardship.

Mending Disconnects in Cancer Care: Setting an Agenda for Research, Practice, and Policy

Cancer in the United States accounts for $600 billion in health care costs, lost work time and productivity, reduced quality of life, and premature mortality. The future of oncology delivery must mend disconnects to equitably improve patient outcomes while constraining costs and burden on patients, caregivers, and care teams. Embedding learning health systems into oncology can connect care, engaging patients and providers in fully interoperable data systems that remotely monitor patients; generate predictive and prescriptive analytics to facilitate appropriate, timely referrals; and extend the reach of clinicians beyond clinic walls. Incorporating functional learning systems into the future of oncology and follow-up care requires coordinated national attention to 4 synergistic strategies: (1) galvanize and shape public discourse to develop and adopt these systems, (2) demonstrate their value, (3) test and evaluate their use, and (4) reform policy to incentivize and regulate their use.

COVID-19 vaccine delivery: an opportunity to set up systems for the future

The race to develop safe and effective SARS-COV-2 vaccines has moved with unprecedented speed. There are now multiple vaccines that have received emergency use authorization from the United States Food and Drug Administration and a host of candidates positioned for approval worldwide. Attention has now turned to allocation, distribution and verification of these vaccines, yet this focus exposes that the underlying infrastructure for global delivery and monitoring is threadbare and unevenly distributed. This presents both a barrier and an opportunity to deploy sustainable infrastructure. Major global stakeholders must convene quickly, collaborate, and collectively invest in global standards, legal models, common vocabularies and interoperable biometric-supported digital health technologies. As the COVID-19 vaccine effort scales, governments, private sector, and NGOs have the chance to place lasting resources needed for equitable and effective delivery that can pay dividends into the future.

Recognition and management of community-acquired acute kidney injury in low-resource settings in the ISN 0by25 trial: A multi-country feasibility study

BACKGROUND

Acute kidney injury (AKI) is increasingly encountered in community settings and contributes to morbidity, mortality, and increased resource utilization worldwide. In low-resource settings, lack of awareness of and limited access to diagnostic and therapeutic interventions likely influence patient management. We evaluated the feasibility of the use of point-of-care (POC) serum creatinine and urine dipstick testing with an education and training program to optimize the identification and management of AKI in the community in 3 low-resource countries.

METHODS AND FINDINGS

Patients presenting to healthcare centers (HCCs) from 1 October 2016 to 29 September 2017 in the cities Cochabamba, Bolivia; Dharan, Nepal; and Blantyre, Malawi, were assessed utilizing a symptom-based risk score to identify patients at moderate to high AKI risk. POC testing for serum creatinine and urine dipstick at enrollment were utilized to classify these patients as having chronic kidney disease (CKD), acute kidney disease (AKD), or no kidney disease (NKD). Patients were followed for a maximum of 6 months with repeat POC testing. AKI development was assessed at 7 days, kidney recovery at 1 month, and progression to CKD and mortality at 3 and 6 months. Following an observation phase to establish baseline data, care providers and physicians in the HCCs were trained with a standardized protocol utilizing POC tests to evaluate and manage patients, guided by physicians in referral hospitals connected via mobile digital technology. We evaluated 3,577 patients, and 2,101 were enrolled: 978 in the observation phase and 1,123 in the intervention phase. Due to the high number of patients attending the centers daily, it was not feasible to screen all patients to assess the actual incidence of AKI. Of enrolled patients, 1,825/2,101 (87%) were adults, 1,117/2,101 (53%) were females, 399/2,101 (19%) were from Bolivia, 813/2,101 (39%) were from Malawi, and 889/2,101 (42%) were from Nepal. The age of enrolled patients ranged from 1 month to 96 years, with a mean of 43 years (SD 21) and a median of 43 years (IQR 27-62). Hypertension was the most common comorbidity (418/2,101; 20%). At enrollment, 197/2,101 (9.4%) had CKD, and 1,199/2,101 (57%) had AKD. AKI developed in 30% within 7 days. By 1 month, 268/978 (27%) patients in the observation phase and 203/1,123 (18%) in the intervention phase were lost to follow-up. In the intervention phase, more patients received fluids (observation 714/978 [73%] versus intervention 874/1,123 [78%]; 95% CI 0.63, 0.94; p = 0.012), hospitalization was reduced (observation 578/978 [59%] versus intervention 548/1,123 [49%]; 95% CI 0.55, 0.79; p < 0.001), and admitted patients with severe AKI did not show a significantly lower mortality during follow-up (observation 27/135 [20%] versus intervention 21/178 [11.8%]; 95% CI 0.98, 3.52; p = 0.057). Of 504 patients with kidney function assessed during the 6-month follow-up, de novo CKD arose in 79/484 (16.3%), with no difference between the observation and intervention phase (95% CI 0.91, 2.47; p = 0.101). Overall mortality was 273/2,101 (13%) and was highest in those who had CKD (24/106; 23%), followed by those with AKD (128/760; 17%), AKI (85/628; 14%), and NKD (36/607; 6%). The main limitation of our study was the inability to determine the actual incidence of kidney dysfunction in the health centers as it was not feasible to screen all the patients due to the high numbers seen daily.

CONCLUSIONS

This multicenter, non-randomized feasibility study in low-resource settings demonstrates that it is feasible to implement a comprehensive program utilizing POC testing and protocol-based management to improve the recognition and management of AKI and AKD in high-risk patients in primary care.

COVID-19 vaccine delivery: an opportunity to set up systems for the future

The race to develop safe and effective SARS-COV-2 vaccines has moved with unprecedented speed. There are now multiple promising candidates seeking emergency use authorization from the United States Food and Drug Administration and a host of candidates positioned for approval worldwide. Attention has now turned to allocation, distribution and verification of these vaccines, yet this focus exposes that the underlying infrastructure for global delivery and monitoring is threadbare and unevenly distributed. This presents both a barrier and an opportunity to deploy sustainable infrastructure. Major global stakeholders must convene quickly, collaborate, and collectively invest in global standards, legal models, common vocabularies and interoperable biometric-supported digital health technologies. As the COVID-19 vaccine effort scales, governments, private sector and NGOs have the chance to place lasting resources needed for equitable and effective delivery that can pay dividends into the future.

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Background

Assigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.

Objective

The aim of this study was to develop and clinically validate an adaptable, personalized diagnostic model to assist clinicians in ruling in and ruling out COVID-19 in potential patients. We compared the diagnostic performance of probabilistic, graphical, and machine learning models against a previously published benchmark model.

Methods

We integrated patient symptoms and test data using machine learning and Bayesian inference to quantify individual patient risk of SARS-CoV-2 infection. We trained models with 100,000 simulated patient profiles based on 13 symptoms and estimated local prevalence, imaging, and molecular diagnostic performance from published reports. We tested these models with consecutive patients who presented with a COVID-19–compatible illness at the University of California San Diego Medical Center over the course of 14 days starting in March 2020.

Results

We included 55 consecutive patients with fever (n=43, 78%) or cough (n=42, 77%) presenting for ambulatory (n=11, 20%) or hospital care (n=44, 80%). In total, 51% (n=28) were female and 49% (n=27) were aged <60 years. Common comorbidities included diabetes (n=12, 22%), hypertension (n=15, 27%), cancer (n=9, 16%), and cardiovascular disease (n=7, 13%). Of these, 69% (n=38) were confirmed via reverse transcription-polymerase chain reaction (RT-PCR) to be positive for SARS-CoV-2 infection, and 20% (n=11) had repeated negative nucleic acid testing and an alternate diagnosis. Bayesian inference network, distance metric learning, and ensemble models discriminated between patients with SARS-CoV-2 infection and alternate diagnoses with sensitivities of 81.6%-84.2%, specificities of 58.8%-70.6%, and accuracies of 61.4%-71.8%. After integrating imaging and laboratory test statistics with the predictions of the Bayesian inference network, changes in diagnostic uncertainty at each step in the simulated clinical evaluation process were highly sensitive to location, symptom, and diagnostic test choices.

Conclusions

Decision support models that incorporate symptoms and available test results can help providers diagnose SARS-CoV-2 infection in real-world settings.

The Landscape of Connected Cancer Symptom Management in Rural America: A Narrative Review of Opportunities for Launching Connected Health Interventions

Background

The 2016 President's Cancer Panel called for projects focusing on improving cancer symptom management using connected health technologies (broadband and telecommunications). However, rural communities, like those in Appalachia, may experience a "double burden" of high cancer rates and lower rates of broadband access and adoption necessary for connected health solutions.

Purpose

To better understand the current landscape of connected health in the management of cancer symptoms in rural America.

Methods

A literature search was conducted using four academic databases (PubMed, CINAHL, MEDLINE, and PsycINFO) to locate articles published from 2010 to 2019 relevant to connected cancer symptom management in rural America. Text screening was conducted to identify relevant publications.

Results

Among 17 reviewed studies, four were conducted using a randomized controlled trial; the remainder were formative in design or small pilot projects. Five studies engaged stakeholders from rural communities in designing solutions. Most commonly studied symptoms were psychological/emotional symptoms, followed by physical symptoms, particularly pain. Technologies used were primarily telephone-based; few were Internet-enabled video conferencing or web-based. Advanced mobile and Internet-based approaches were generally in the development phase. Overall, both rural patients and healthcare providers reported high acceptance, usage, and satisfaction of connected health technologies. Ten of the 17 studies reported improved symptom management outcomes. Methodological challenges that limited the interpretation of the findings were summarized.

Implications

The review identified a need to engage rural stakeholders to develop and test connected cancer symptom management solutions that are based on advanced mobile and broadband Internet technologies.

Experiencing Cancer in Appalachian Kentucky

Quilted Appalachian Sunset©2011 Jim Harrisjim-harris.pixels.com Nothing tells the story of people working together better than a community quilt. A diversity of talents, colors, and materials brought together through skill and shared purpose. Perhaps never before have we as Americans needed a stronger reminder that many hands make short work of big problems. The work presented here by the L.A.U.N.C.H. Collaborative offers a new framework for health care that could be compared to a digital quilt, powered by community-based participatory design, with lived expertise and the newest advances in broadband-enabled connected health solutions. This work demonstrates the value and need to engage local communities and what can be learned when beneficiaries and traditional caregivers work together to develop healthcare solutions.

"Global Health": Time to Refocus while We still Have Time

Two decades of growing resource availability from agencies and foundations in wealthy countries has transformed approaches to health in poorly resourced nations. This progress looks increasingly unstable as climate change, social unrest, and, now, disruptive pandemics present threats not only to health but also to the mechanisms that manage it, and to funding itself. The growth in "global health" schools, technology development laboratories, nongovernmental organizations and multilateral institutions in donor countries has delivered not only successes but also disappointment, and reflect a paradigm that is in many ways contrary to the principles of population-based ownership that they espouse. Although the COVID-19 crisis has underlined the importance of health access and health service capacity, we may have a limited window of opportunity in which to rethink the current model and improve both efficiency and effectiveness. With a dose of humility, we may all benefit from studying our own rhetoric on human-centered design and applying these principles across global health to ensure that our approach is effective, efficient, and defensible.

A comprehensive assessment for community-based, person-centered care for older adults

Background

Many health and social needs can be assessed and met in community settings, where lower-cost, person-centered, preventative and proactive services predominate. This study reports on the development and implementation of a person-centered care model integrating dental, social, and health services for low-income older adults at a community dental clinic co-located within a senior wellness center.

Methods

A digital comprehensive geriatric assessment (CGA) and referral system linking medical, dental, and psychosocial needs by real-time CGA-derived metrics for 996 older adults (age ≥ 60) was implemented in 2016–2018 as part of a continuous quality improvement project. This study aims to describe: 1) the development and content of a new CGA; 2) CGA implementation, workflows, triage, referrals; 3) correlations between CGA domains, and adjusted regression models, assessing associations with self-reported recent hospitalizations, emergency department (ED) visits, and clinically-assessed dental urgency.

Results

The multidisciplinary team from the senior wellness and dental centers planned and implemented a CGA that included standard medical history along with validated instruments for functional status, mental health and social determinants, and added oral health. Care navigators employed the CGA with 996 older adults, and made 1139 referrals (dental = 797, care coordination = 163, social work = 90, mental health = 32). CGA dimensions correlated between oral health, medical status, depressive symptoms, isolation, and reduced quality of life (QoL). Pain, medical symptoms, isolation and depressive symptoms were associated with poorer self-reported health, while general health was most strongly correlated with lower depressive symptoms, and higher functional status and QoL. Isolation was the strongest correlate of lower QoL.

Adjusted odds ratios identified social and medical factors associated with recent hospitalization and ED visits. General and oral health were associated with dental urgency. Dental urgency was most strongly associated with general health (AOR = 1.78,95%CI [1.31, 2.43]), dental symptoms (AOR = 2.39,95%CI [1.78, 3.20]), dental pain (AOR = 2.06,95%CI [1.55–2.74]), and difficulty chewing (AOR = 2.80, 95%CI [2.09–3.76]). Dental symptoms were associated with recent ED visits (AOR = 1.61, 95%CI [1.12–2.30]) or hospitalizations (AOR = 1.47, 95%CI [1.04–2.10]).

Conclusion

Community-based inter-professional care is feasible with CGAs that include medical, dental, and social factors. A person-centered care model requires coordination supported by new workflows. Real-time metrics-based triage process provided efficient means for client review and a robust process to surface needs in complex cases.

Longitudinal analysis of cost and dental utilization patterns for older adults in outpatient and long-term care settings in Minnesota

BACKGROUND

Dental utilization patterns and costs of providing comprehensive oral healthcare for older adults in different settings have not been examined.

METHODS

Retrospective longitudinal cohort data from Apple Tree Dental (ATD) were analyzed (N = 1,159 total; 503 outpatients, 656 long-term care residents) to describe oral health status at presentation, service utilization patterns, and care costs. Generalized estimating equation (GEE) repeated measures analysis identified significant contributors to service cost over the three-year study period.

RESULTS

Cohort mean age was 74 years (range = 55-104); the outpatient (OP) group was younger compared to the long-term care (LTC) group. Half (56%) had Medicaid, 22% had other insurance, and 22% self-paid. Most (72%) had functional dentitions (20+ teeth), 15% had impaired dentitions (9-19 teeth), 6% had severe tooth loss (1-8 teeth), and 7% were edentulous (OP = 2%, LTC = 11%). More in the OP group had functional dentition (83% vs. 63% LTC). The number of appointments declined from 5.0 in Year 1 (OP = 5.7, LTC = 4.4) to 3.3 in Year 3 (OP = 3.6, LTC = 3.0). The average cost to provide dental services was $1,375/year for three years (OP = $1,427, LTC = $1,336), and costs declined each year, from an average of $1,959 (OP = $2,068, LTC = $1,876) in Year 1 to $1,016 (OP = $989, LTC = $1,037) by Year 3. Those with functional dentition at presentation were significantly less costly than those with 1-19 teeth, while edentulous patients demonstrated the lowest cost and utilization. Year in treatment, insurance type, dentition type, and problem-focused first exam were significantly associated with year-over-year cost change in both OP and LTC patients.

CONCLUSION

Costs for providing comprehensive dental care in OP and LTC settings were similar, modest, and declined over time. Dentate patients with functional dentition and edentulous patients were less costly to treat. LTC patients had lower utilization than OP patients. Care patterns shifted over time to increased preventive care and decreased restorative care visits.

Barn-Raising on the Digital Frontier: The L.A.U.N.C.H. Collaborative

A meta-analysis of oncology papers from around the world revealed that cancer patients who lived more than 50 miles away from hospital centers routinely presented with more advanced stages of disease at diagnosis, exhibited lower adherence to prescribed treatments, presented with poorer diagnoses, and reported a lower quality of life than patients who lived nearer to care facilities. Connected health approaches-or the use of broadband and telecommunications technologies to evaluate, diagnose, and monitor patients beyond the clinic-are becoming an indispensable tool in medicine to overcome the obstacle of distance.

Bartonella quintana Endocarditis in a Homeless Man with Cat Exposure in San Diego, California

We report a case of Bartonella quintana endocarditis in a homeless man with congenital bicuspid aortic valve and significant cat exposure living in downtown San Diego, California.

Biometric recognition of newborns and infants by non-contact fingerprinting: lessons learned

Despite years of effort, reliable biometric identification of newborns and young children has remained elusive. In this paper, we review the importance of trusted identification methods, the biometric landscape for infants and adults, barriers and success stories, and we discuss specific failure modes particular to young children. We then describe our approach to infant identification using non-contact optical imaging of fingerprints. We detail our technology development history, including Human-Centered Design methods, various iterations of our platform, and how these iterations addressed failure modes in the identification process. We close with a brief description of our clinical trial of newborns and infants at an urban hospital in Mexico and report preliminary results that show high accuracy, with matching rates consistent with acceptable field-performance for reliable biometric identification in large populations.

Reducing Hypoglycemia in the Real World: A Retrospective Analysis of Predictive Low-Glucose Suspend Technology in an Ambulatory Insulin-Dependent Cohort

Objective: Analyze real-world usage and impact of a predictive low-glucose suspend (PLGS) insulin delivery system for maintenance of euglycemia and prevention of hypoglycemic events in people with insulin-dependent diabetes. Methods: Retrospective analysis of Tandem Basal-IQ users who uploaded at least 21 days of PLGS usage data between August 31, 2018, and March 14, 2019 (N = 8132). Insulin delivery and sensor-glucose concentrations were analyzed. The times spent below 70 mg/dL, between 70 and 180 mg/dL, and above 180 mg/dL were assessed. Subgroup analyses were conducted to examine matched pre-/postoutcomes with experienced users (n = 1371) and performance over time for a mixed subgroup with >9 weeks of data (n = 3563). Results: The mean age of patients was 32.4 years, 52% were female, 96% had type 1 diabetes, and 4% had type 2 diabetes. Mean duration on PLGS was 65 days. Algorithm introduction led to a 45% median relative risk reduction in sensor time <70 mg/dL, pre/post (% <70:2.0, 1.1), while the mean glucose remained stable (168 and 168 mg/dL). Mean frequency of hypoglycemic events decreased from one every 9 days to one every 30 days. Total daily insulin dose decreased from 43.4 to 42.3 U in the pre/post subgroup. Manual override of the system was low (4.5%). The number of daily suspensions remained stable (4.9). Conclusions: Introduction of PLGS resulted in effective and sustained prevention of hypoglycemia without a significant increase in mean blood glucose and may be considered for people with type 1 diabetes at risk for hypoglycemia.

Biometric identification of newborns and infants by non-contact fingerprinting: lessons learned

Despite years of effort, reliable biometric identification of newborns and young children has remained elusive. In this paper, we review the importance of trusted identification methods, the biometric landscape for infants and adults, barriers and success stories, and we discuss specific failure modes particular to young children. We then describe our approach to infant identification using non-contact optical imaging of fingerprints. We detail our technology development history, including Human-Centered Design methods, various iterations of our platform, and how these iterations addressed failure modes in the identification process. We close with a brief description of our clinical trial of newborns and infants at an urban hospital in Mexico and report preliminary results that show high accuracy, with matching rates consistent with acceptable field-performance for reliable biometric identification in large populations.

An open access medical knowledge base for community driven diagnostic decision support system development

INTRODUCTION

While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will remain an important component of future diagnostic decision support systems by providing ground truth and facilitating explainable human-computer interaction, but that prototype development is hampered by the lack of freely available computable knowledge bases.

METHODS

We constructed an open access knowledge base and evaluated its potential in the context of a prototype decision support system. We developed a modified set-covering algorithm to benchmark the performance of our knowledge base compared to existing platforms. Testing was based on case reports from selected literature and medical student preparatory material.

RESULTS

The knowledge base contains over 2000 ICD-10 coded diseases and 450 RX-Norm coded medications, with over 8000 unique observations encoded as SNOMED or LOINC semantic terms. Using 117 medical cases, we found the accuracy of the knowledge base and test algorithm to be comparable to established diagnostic tools such as Isabel and DXplain. Our prototype, as well as DXplain, showed the correct answer as "best suggestion" in 33% of the cases. While we identified shortcomings during development and evaluation, we found the knowledge base to be a promising platform for decision support systems.

CONCLUSION

We built and successfully evaluated an open access knowledge base to facilitate the development of new medical diagnostic assistants. This knowledge base can be expanded and curated by users and serve as a starting point to facilitate new technology development and system improvement in many contexts.

Clinical detection of Hepatitis C viral infection by yeast-secreted HCV-core:Gold-binding-peptide

Access to affordable and field deployable diagnostics are key barriers to the control and eradication of many endemic and emerging infectious diseases. While cost, accuracy, and usability have all improved in recent years, there remains a pressing need for even less expensive and more scalable technologies. To that end, we explored new methods to inexpensively produce and couple protein-based biosensing molecules (affinity reagents) with scalable electrochemical sensors. Previous whole-cell constructs resulted in confounding measurements in clinical testing due to significant cross-reactivity when probing for host-immune (antibody) response to infection. To address this, we developed two complimentary strategies based on either the release of surface displayed or secretion of fusion proteins. These dual affinity biosensing elements couple antibody recognition (using antigen) and sensor surface adhesion (using gold-binding peptide-GBP) to allow single-step reagent production, purification, and biosensor assembly. As a proof-of-concept, we developed Hepatitis C virus (HCV)-core antigen-GBP fusion proteins. These constructs were first tested and optimized for consistent surface adhesion then the assembled immunosensors were tested for cross-reactivity and evaluated for performance in vitro. We observed loss of function of the released reagents while secreted constructs performed well in in vitro testing with 2 orders of dynamic range, and a limit of detection of 32 nM. Finally, we validated the secreted platform with clinical isolates (n = 3) with statistically significant differentiation of positive vs. non-infected serum (p < 0.0001) demonstrating the ability to clearly distinguish HCV positive and negative clinical samples.

High-Density Redox Amplified Coulostatic Discharge-Based Biosensor Array

High-density biosensor arrays are essential for many cutting-edge biomedical applications including point-of-care vaccination screening to detect multiple highly-contagious diseases. Typical electrochemical biosensing techniques are based on the measurement of sub-pA currents for micron-sized sensors requiring highly-sensitive readout circuits. Such circuits are often too complex to scale down for high-density arrays. In this paper, a high-density 4,096-pixel electrochemical biosensor array in 180 nm CMOS is presented. It uses a coulostatic discharge sensing technique and interdigitated electrode geometry to reduce both the complexity and size of the readout circuitry. Each biopixel contains an interdigitated microelectrode with a 13 aA low-leakage readout circuit directly underneath. Compared to standard planar electrodes, the implemented interdigitated electrodes achieve a maximum amplification factor of 10.5× from redox cycling. The array's sensor density is comparable to state-of-the-art arrays, all without augmenting the sensors with complex post-processing. The detection of anti-Rubella and anti-Mumps antibodies in human serum is demonstrated.

Lyophilized visually readable loop-mediated isothermal reverse transcriptase nucleic acid amplification test for detection Ebola Zaire RNA

Recent viral outbreaks highlight the need for reliable, yet broadly deployable diagnostics for detection of epidemic and emerging pathogens. In this study we designed and optimized methods to visually detect viral nucleic acid by isothermal amplification and SYBR dye intercalation. We designed and tested loop-mediated isothermal amplification (LAMP) primers and lyophilized reactions to optimize the detection of Zaire Ebola Virus (ZEBOV) and further evolved the LAMP platform to allow room-temperature storage for deployment in resource limited settings. Our results demonstrated excellent sensitivity and specificity for viral nucleic acid sequences with lower limits of detection of less than 100 copies. Moreover, lyophilized reaction mixtures retained activity for prolonged periods under dry conditions at room temperature. This approach offers a way for detection of emerging viruses in resource limited settings.

Recognition and management of acute kidney injury in the International Society of Nephrology 0by25 Global Snapshot: a multinational cross-sectional study

BACKGROUND

Epidemiological data for acute kidney injury are scarce, especially in low-income countries (LICs) and lower-middle-income countries (LMICs). We aimed to assess regional differences in acute kidney injury recognition, management, and outcomes.

METHODS

In this multinational cross-sectional study, 322 physicians from 289 centres in 72 countries collected prospective data for paediatric and adult patients with confirmed acute kidney injury in hospital and non-hospital settings who met criteria for acute kidney injury. Signs and symptoms at presentation, comorbidities, risk factors for acute kidney injury, and process-of-care data were obtained at the start of acute kidney injury, and need for dialysis, renal recovery, and mortality recorded at 7 days, and at hospital discharge or death, whichever came earlier. We classified countries into high-income countries (HICs), upper-middle-income countries (UMICs), and combined LICs and LMICs (LLMICs) according to their 2014 gross national income per person.

FINDINGS

Between Sept 29 and Dec 7, 2014, data were collected from 4018 patients. 2337 (58%) patients developed community-acquired acute kidney injury, with 889 (80%) of 1118 patients in LLMICs, 815 (51%) of 1594 in UMICs, and 663 (51%) of 1241 in HICs (for HICs vs UMICs p=0.33; p<0.0001 for all other comparisons). Hypotension (1615 [40%] patients) and dehydration (1536 [38%] patients) were the most common causes of acute kidney injury. Dehydration was the most frequent cause of acute kidney injury in LLMICs (526 [46%] of 1153 vs 518 [32%] of 1605 in UMICs vs 492 [39%] of 1260 in HICs) and hypotension in HICs (564 [45%] of 1260 vs 611 [38%%] of 1605 in UMICs vs 440 [38%] of 1153 LLMICs). Mortality at 7 days was 423 (11%) of 3855, and was higher in LLMICs (129 [12%] of 1076) than in HICs (125 [10%] of 1230) and UMICs (169 [11%] of 1549).

INTERPRETATION

We identified common aetiological factors across all countries, which might be amenable to a standardised approach for early recognition and treatment of acute kidney injury. Study limitations include a small number of patients from outpatient settings and LICs, potentially under-representing the true burden of acute kidney injury in these areas. Additional strategies are needed to raise awareness of acute kidney injury in community health-care settings, especially in LICs.

FUNDING

International Society of Nephrology.

Yeast dual-affinity biobricks: Progress towards renewable whole-cell biosensors

Point-of-care (POC) diagnostic biosensors offer a promising solution to improve healthcare, not only in developed parts of the world, but also in resource limited areas that lack adequate medical infrastructure and trained technicians. However, in remote and resource limited settings, cost and storage of traditional POC immunoassays often limit actual deployment. Synthetically engineered biological components ("BioBricks") provide an avenue to reduce costs and simplify assay procedures. In this article, the design and development of an ultra-low cost, whole-cell "renewable" capture reagent for use in POC diagnostic applications is described. Yeast cells were genetically modified to display both single chain variable fragment (scFv) antibodies and gold-binding peptide (GBP) on their surfaces for simple one step enrichment and surface functionalization. Electrochemical impedance spectroscopy (EIS) and fluorescent imaging were used to verify and characterize the binding of cells to gold electrodes. A complete electrochemical detection assay was then performed on screen-printed electrodes fixed with yeast displaying scFv directed to Salmonella outer membrane protein D (OmpD). Electrochemical assays were optimized and cross-validated with established fluorescence techniques. Nanomolar detection limits were observed for both formats.

Innovative strategies for transforming internal medicine residency training in resource-limited settings: the Mozambique experience

With approximately 4 physicians per 100,000 inhabitants, Mozambique faces one of the most severe health care provider shortages in Sub-Saharan Africa. The lack of sufficient well-trained medical school faculty is one of Mozambique's major barrier to producing new physicians annually. A partnership between the Universidade Eduardo Mondlane and the University of California, San Diego, has addressed this challenge with support from the Medical Education Partnership Initiative. After an initial needs assessment involving questionnaires and focus groups of residents, and working with key members from the Ministry of Health, the Medical Council, and Maputo Central Hospital, a set of interventions was designed. The hospital's internal medicine residency program was chosen as the focus for the plan. Interventions included curriculum design, new teaching methodologies, investment in an informatics infrastructure for access to digital references, building capacity to support clinical research, and providing financial incentives to retain junior faculty. The number of candidates entering the internal medicine residency program has increased, and detailed monitoring and evaluation is measuring the impact of these changes on the quality of training. These changes are expected to improve the long-term quality of postgraduate training in general through dissemination to other departments. They also have the potential to facilitate equitable distribution of specialists nationwide by expanding postgraduate training to other hospitals and universities.

Strengthening research capacity through the medical education partnership initiative: the Mozambique experience

BACKGROUND

Since Mozambique's independence, the major emphasis of its higher educational institutions has been on didactic education. Because of fiscal and human resource constraints, basic and applied research activities have been relatively modest in scope, and priorities have often been set primarily by external collaborators. These factors have compromised the scope and the relevance of locally conducted research and have limited the impact of Mozambique's universities as major catalysts for national development.

CASE DESCRIPTION

We developed a multi-institutional partnership to undertake a comprehensive analysis of the research environment at Mozambique's major public universities to identify factors that have served as barriers to the development of a robust research enterprise. Based on this analysis, we developed a multifaceted plan to reduce the impact of these barriers and to enhance research capacity within Mozambique.

INTERVENTIONS

On the basis of our needs assessment, we have implemented a number of major initiatives within participating institutions to facilitate basic and applied research activities. These have included specialized training programmes, a reorganization of the research administration infrastructure, the development of multiple collaborative research projects that have emphasized local research priorities and a substantial investment in bioinformatics. We have established a research support centre that provides grant development and management services to Mozambique's public universities and have developed an independent Institutional Review Board for the review of research involving human research subjects. Multiple research projects involving both communicable and non-communicable diseases have been developed and substantial external research support has been obtained to undertake these projects. A sizable investment in biomedical informatics has enhanced both connectivity and access to digital reference material. Active engagement with relevant entities within the Government of Mozambique has aligned institutional development with national priorities.

CONCLUSIONS

Although multiple challenges remain, over the past 3 years significant progress has been made towards establishing conditions within which a broad range of basic, translational and clinical and public health research can be undertaken. Ongoing development of this research enterprise will enhance capacity to address critical locally relevant research questions and will leverage resources to accelerate the development of Mozambique's national universities.

Pictogram evaluation and authoring collaboration environment

Studies showed benefits of using pictograms in health communication such as improved recall and comprehension of health instructions. Pictograms are culturally sensitive thus need to be rigorously validated to ensure they convey the intended meaning correctly to the targeted population. The infeasibility of manually creating pictograms and the lack of robust means to store and validate pictograms are potential barriers to the wider adoption of pictograms in health communication. To address these challenges, we created an open access web-based tool, PEACE (Pictogram Evaluation and Authoring Collaboration Environment) as a part of SHINE (Sustainable Health Informatics and Networking Environment) initiatives. We report the development process and the preliminary evaluation results of PEACE in this paper.

The octarepeat domain of the prion protein binds Cu(II) with three distinct coordination modes at pH 7.4

The prion protein (PrP) binds Cu2+ in its N-terminal octarepeat domain. This unusual domain is comprised of four or more tandem repeats of the fundamental sequence PHGGGWGQ. Previous work from our laboratories demonstrates that at full copper occupancy, each HGGGW segment binds a single Cu2+. However, several recent studies suggest that low copper occupancy favors different coordination modes, possibly involving imidazoles from histidines in adjacent octapeptide segments. This is investigated here using a combination of X-band EPR, S-band EPR, and ESEEM, along with a library of modified peptides designed to favor different coordination interactions. At pH 7.4, three distinct coordination modes are identified. Each mode is fully characterized to reveal a series of copper-dependent octarepeat domain structures. Multiple His coordination is clearly identified at low copper stoichiometry. In addition, EPR detected copper-copper interactions at full occupancy suggest that the octarepeat domain partially collapses, perhaps stabilizing this specific binding mode and facilitating cooperative copper uptake. This work provides the first complete characterization of all dominant copper coordination modes at pH 7.4.

The iSH2 domain of PI 3-kinase is a rigid tether for p110 and not a conformational switch

Class IA PI 3-kinases are heterodimeric proteins with distinct catalytic (p110) and regulatory (p85) subunits. The minimal fragment of p85 capable of regulating p110 activity (p85ni) is the N-terminal SH2 domain linked to the iSH2 coiled-coil domain. We used cysteine mutagenesis and (14)C-NEM-labeling to show that the p110-binding site in the iSH2 domain includes two regions: residues 482-484 and 532-541. These regions are adjacent to each other in the three-dimensional structural model of the iSH2 domain, and define a coherent binding site. We then used spin labeling and EPR spectroscopy to demonstrate that the conformation of the iSH2 domain is unaffected by binding to the N-terminal fragment of p110 (residues 1-108), and/or by phosphopeptide binding to p85ni/p110(1-108) heterodimers. Finally, we show that the cSH2 domain cannot substitute for the nSH2 domain with regard to inhibition of p110. These data support a model in which the iSH2 domain is a rigid tether for p110, and regulation of p85/p110 is mediated by nSH2-p110 contacts.

Crystal structure of the actin binding domain of the cyclase-associated protein

Cyclase-associated protein (CAP or Srv2p) is a modular actin monomer binding protein that directly regulates filament dynamics and has been implicated in a number of complex developmental and morphological processes, including mRNA localization and the establishment of cell polarity. The crystal structure of the C-terminal dimerization and actin monomer binding domain (C-CAP) reveals a highly unusual dimer, composed of monomers possessing six coils of right-handed beta-helix flanked by antiparallel beta-strands. Domain swapping, involving the last two strands of each monomer, results in the formation of an extended dimer with an extensive interface. This structural and biochemical characterization provides new insights into the organization and potential mechanistic properties of the multiprotein assemblies that integrate dynamic actin processes into the overall physiology of the cell. An unanticipated finding is that the unique tertiary structure of the C-CAP monomer provides a structural model for a wide range of molecules, including RP2 and cofactor C, proteins involved in X-linked retinitis pigmentosa and tubulin maturation, respectively, as well as several uncharacterized proteins that exhibit very diverse domain organizations. Thus, the unusual right-handed beta-helical fold present in C-CAP appears to support a wide range of biological functions.

Copper coordination in the full-length, recombinant prion protein

The prion protein (PrP) binds divalent copper at physiologically relevant conditions and is believed to participate in copper regulation or act as a copper-dependent enzyme. Ongoing studies aim at determining the molecular features of the copper binding sites. The emerging consensus is that most copper binds in the octarepeat domain, which is composed of four or more copies of the fundamental sequence PHGGGWGQ. Previous work from our laboratory using PrP-derived peptides, in conjunction with EPR and X-ray crystallography, demonstrated that the HGGGW segment constitutes the fundamental binding unit in the octarepeat domain [Burns et al. (2002) Biochemistry 41, 3991-4001; Aronoff-Spencer et al. (2000) Biochemistry 39, 13760-13771]. Copper coordination arises from the His imidazole and sequential deprotonated glycine amides. In this present work, recombinant, full-length Syrian hamster PrP is investigated using EPR methodologies. Four copper ions are taken up in the octarepeat domain, which supports previous findings. However, quantification studies reveal a fifth binding site in the flexible region between the octarepeats and the PrP globular C-terminal domain. A series of PrP peptide constructs show that this site involves His96 in the PrP(92-96) segment GGGTH. Further examination by X-band EPR, S-band EPR, and electron spin-echo envelope spectroscopy, demonstrates coordination by the His96 imidazole and the glycine preceding the threonine. The copper affinity for this type of binding site is highly pH dependent, and EPR studies here show that recombinant PrP loses its affinity for copper below pH 6.0. These studies seem to provide a complete profile of the copper binding sites in PrP and support the hypothesis that PrP function is related to its ability to bind copper in a pH-dependent fashion.

The structure of the inter-SH2 domain of class IA phosphoinositide 3-kinase determined by site-directed spin labeling EPR and homology modeling

Phosphoinositide (PI) 3-kinases catalyze the phosphorylation of the D3 position of the inositol ring of PI, and its phosphorylated derivatives and play important roles in many intracellular signal transducing pathways. Class IA PI3-kinases contain distinct regulatory (p85) and catalytic (p110) subunits. p110 is stabilized and inhibited by constitutive association with p85, and is disinhibited when the SH2 domains of p85 bind to tyrosyl-phosphorylated proteins. Because the two subunits do not dissociate, disinhibition of p110 presumably occurs by an allosteric mechanism. To explore the means by which p85 regulates the activity of p110, structures of the inter-SH2 domain of p85 were determined with and without phosphopeptide by using a combination of site directed spin labeling EPR and homology modeling and molecular dynamics. The inter-SH2 domain is assigned as a rigid anti-parallel coiled-coil whose primary function is to bind p110, facilitating inhibition of p110 by the N-terminal SH2 domain of p85.

Molecular features of the copper binding sites in the octarepeat domain of the prion protein

Recent evidence suggests that the prion protein (PrP) is a copper binding protein. The N-terminal region of human PrP contains four sequential copies of the highly conserved octarepeat sequence PHGGGWGQ spanning residues 60-91. This region selectively binds Cu2+ in vivo. In a previous study using peptide design, EPR, and CD spectroscopy, we showed that the HGGGW segment within each octarepeat comprises the fundamental Cu2+ binding unit [Aronoff-Spencer et al. (2000) Biochemistry 40, 13760-13771]. Here we present the first atomic resolution view of the copper binding site within an octarepeat. The crystal structure of HGGGW in a complex with Cu2+ reveals equatorial coordination by the histidine imidazole, two deprotonated glycine amides, and a glycine carbonyl, along with an axial water bridging to the Trp indole. Companion S-band EPR, X-band ESEEM, and HYSCORE experiments performed on a library of 15N-labeled peptides indicate that the structure of the copper binding site in HGGGW and PHGGGWGQ in solution is consistent with that of the crystal structure. Moreover, EPR performed on PrP(23-28, 57-91) and an 15N-labeled analogue demonstrates that the identified structure is maintained in the full PrP octarepeat domain. It has been shown that copper stimulates PrP endocytosis. The identified Gly-Cu linkage is unstable below pH approximately 6.5 and thus suggests a pH-dependent molecular mechanism by which PrP detects Cu2+ in the extracellular matrix or releases PrP-bound Cu2+ within the endosome. The structure also reveals an unusual complementary interaction between copper-structured HGGGW units that may facilitate molecular recognition between prion proteins, thereby suggesting a mechanism for transmembrane signaling and perhaps conversion to the pathogenic form.

Identification of the Cu2+ binding sites in the N-terminal domain of the prion protein by EPR and CD spectroscopy

Recent evidence indicates that the prion protein (PrP) plays a role in copper metabolism in the central nervous system. The N-terminal region of human PrP contains four sequential copies of the highly conserved octarepeat sequence PHGGGWGQ spanning residues 60-91. This region selectively binds divalent copper ions (Cu(2+)) in vivo. To elucidate the specific mode and site of binding, we have studied a series of Cu(2+)-peptide complexes composed of 1-, 2-, and 4-octarepeats and several sub-octarepeat peptides, by electron paramagnetic resonance (EPR, conventional X-band and low-frequency S-band) and circular dichroism (CD) spectroscopy. At pH 7.45, two EPR active binding modes are observed where the dominant mode appears to involve coordination of three nitrogens and one oxygen to the copper ion, while in the minor mode two nitrogens and two oxygens coordinate. ESEEM spectra demonstrate that the histidine imidazole contributes one of these nitrogens. The truncated sequence HGGGW gives EPR and CD that are indistinguishable from the dominant binding mode observed for the multi-octarepeat sequences and may therefore comprise the fundamental Cu(2+) binding unit. Both EPR and CD titration experiments demonstrate rigorously a 1:1 Cu(2+)/octarepeat binding stoichiometry regardless of the number of octarepeats in a given peptide sequence. Detailed spin integration of the EPR signals demonstrates that all of the bound Cu(2+) is detected thereby ruling out strong exchange coupling that is often found when there is imidazolate bridging between paramagnetic metal centers. A model consistent with these data is proposed in which Cu(2+) is bound to the nitrogen of the histidine imidazole side chain and to two nitrogens from sequential glycine backbone amides.