Primary outcomes from Partner2Lose: A randomized controlled trial to evaluate partner involvement on long-term weight loss.

Background: Partner support is associated with better weight loss outcomes in observational studies, but randomized trials show mixed results for including partners. Unclear is whether teaching communication skills to couples will improve weight loss in index participants. Purpose: To compare the efficacy of a partner-assisted intervention versus participant-only weight management program on long-term weight loss. Methods: This community-based study took place in Madison, WI. Index participants were eligible if they met obesity guideline criteria to receive weight loss counseling, were aged 74 years or younger, lived with a partner, and had no medical contraindications to weight loss; partners were aged 74 years or younger and not underweight. Couples were randomized 1:1 to a partner-assisted or participant-only intervention. Index participants in both arms received an evidence-based weight management program. In the partner-assisted arm, partners attended half of the intervention sessions, and couples were trained in communication skills. The primary outcome was index participant weight at 24 months, assessed by masked personnel; secondary outcomes were 24-month self-reported caloric intake and average daily steps assessed by an activity tracker. General linear mixed models were used to compare group differences in these outcomes following intent-to-treat principles. Results: Among couples assigned to partner-assisted (n=115) or participant-only intervention (n=116), most index participants identified as female (67%) and non-Hispanic White (87%). Average baseline age was 47.27 years (SD 11.51 years) and weight was 106.55 kg (SD 19.41 kg). The estimated mean 24-month weight loss was similar in the partner-assisted (2.66 kg) and participant-only arms (2.89 kg) (estimated mean difference, 0.23 kg [95% CI, -1.58, 2.04 kg]). There were no differences in 24-month average daily caloric intake (50 cal [95% CI: -233, 132 cal]) or steps (806 steps [95% CI: -1675, 64 steps]). The percentage of participants reporting an adverse event with at least possible attribution to the intervention did not differ by arm (partner-assisted: 9%, participant-only, 3%, p=0.11). Conclusions: Partner-assisted and individual weight management interventions led to similar outcomes in index participants. Trial registration: Clinicaltrials.gov NCT03801174.

Neurocysticercosis Presenting as Migraine in the United States.

BACKGROUND Cysticercosis is a condition caused by infection with the larval form of Taenia solium, a pork tapeworm that uses pigs as an intermediate host. Humans become infected when they ingest water or food contaminated with tapeworm cysts. Cysticercosis is increasing in frequency in developed countries due to increased access to travel. Neurocysticercosis occurs when Taenia solium cysts embed within the nervous system. The clinical presentation of neurocysticercosis ranges from asymptomatic to life-threatening, largely depending on the brain parenchymal involvement. The diagnosis is typically made with a combination of clinical evaluation, serology, and neuroimaging. Treatment for parenchymal neurocysticercosis may involve anthelmintic agents, symptomatic agents, surgery, or a combination of methods. CASE REPORT A 52-year-old man with a medical history of migraine headaches, complicated type 2 diabetes mellitus, and obesity presented with a 4-month change in his migraines becoming severe, worse over his occiput bilaterally, and unresponsive to abortive therapy. His exposure history was unremarkable except for a habit of eating undercooked bacon, by which he would have developed neurocysticercosis via autoinfection. Neuroimaging and serology confirmed a diagnosis of neurocysticercosis and he was treated accordingly with antiparasitic and anti-inflammatory medications. CONCLUSIONS This presentation is nonspecific and can easily be overlooked, especially if there is an underlying known neurological condition such as migraine. This case illustrates that neurocysticercosis should be considered when an existing neuropathological condition displays a change in presentation or requires a change in therapeutic management, even without obvious risk factors.

Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach.

BACKGROUND: Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research. OBJECTIVE: To introduce functional principal component analysis (fPCA) and demonstrate its potential applicability in estimating trends in ILD collected by mobile heath devices, assessing longitudinal association between ILD and health outcomes, and predicting health outcomes. METHODS: fPCA and scalar-to-function regression models were reviewed. A case study was used to illustrate the process of abstracting trends in intensively self-measured blood glucose using functional principal component analysis and then predicting future HbA1c values in patients with type 2 diabetes using a scalar-to-function regression model. RESULTS: Based on the scalar-to-function regression model results, there was a slightly increasing trend between daily blood glucose measures and HbA1c. 61% of variation in HbA1c could be predicted by the three preceding months' blood glucose values measured before breakfast (P < 0.0001, [Formula: see text]). CONCLUSIONS: Functional data analysis, specifically fPCA, offers a unique tool to capture patterns in ILD collected by mobile health devices. It is particularly useful in assessing longitudinal dynamic association between repeated measures and outcomes, and can be easily integrated in prediction models to improve prediction precision.

Expanding Technology-Enabled Nurse-Delivered Chronic Disease Care: EXTEND.

Mobile monitoring-enabled technologies could enhance telehealth for chronic illness care. EXTEND is an active comparator randomized trial (N=220) of two 24-month interventions: 1) mobile monitoring as a self-management tool (EXTEND); and 2) a 12-month nurse and pharmacist-delivered telehealth intervention incorporating mobile monitoring, self-management support, and medication management that is followed by a 12-month self-management period (EXTEND Plus). EXTEND Plus is a pragmatic approach to integrating mobile monitoring-enabled telehealth for patients uncontrolled diabetes and hypertension into existing clinical infrastructure.

Mobile Monitoring-Enabled Telehealth for Patients with Complex Chronic Illnesses.

Telehealth has the potential to improve management of poorly controlled chronic diseases relative to clinic-based care alone. Mobile monitoring-enabled technologies could enhance telehealth for chronic illness care. Implementation in practice settings would rely on automated integration of data into the electronic health record (EHR). We describe the integration and visualization of data from four remote monitoring devices into the EHR that is coupled with the evaluation of an evidence-based nurse and pharmacist-led telehealth care model for patients with uncontrolled diabetes and hypertension. Using this new pragmatic infrastructure, clinicians use the EHR to prescribe for patients a suite of devices. Alerts are placed upon the data that notify a clinician when values go above or below set thresholds. These data are visualized in the clinical record and clinicians use the EHR as a tool for efficiently delivering and documenting patient telehealth encounters.

Small Monetary Incentives Lead to Greater Adherence in a Weight Loss Program.

PURPOSE: Understand how weekly monetary incentives for dietary tracking and/or weight loss impact 6-month weight loss behavioral adherence. DESIGN: Secondary analysis of participants randomized to one of four conditions in a behavioral weight loss intervention: incentives for dietary tracking, incentives for weight loss, both, or none. SETTING: Participants were asked to self-weigh at least twice weekly, log food and drink in a mobile application five days weekly, and attend bi-weekly, group-based classes. SAMPLE: Data from (n = 91) adults with obesity who completed a 24-week behavioral weight loss intervention of whom 88% were female and 74% Non-Hispanic White, were analyzed. MEASURES: Non-adherence to weight and dietary self-monitoring was defined as the second week of not meeting criteria. Class attendance was also tracked. ANALYSIS: Kaplan-Meier analyses were used to examine differences across the four conditions. RESULTS: Participants incentivized for dietary self-monitoring had an average 15.8 weeks (SE:1.2) until the first non-adherent week compared to 5.9 weeks (SE:0.8) for those not incentivized for dietary self-monitoring (P < .01). Those incentivized for weight loss had an average 18.0 weeks (SE:1.02) of self-weighing until the first non-adherent week compared to 13.5 weeks (SE:1.3) for those not incentivized for weight loss (P = .02). No difference in class attendance was observed. CONCLUSIONS: Incentivizing behaviors associated with weight loss improved adherence to those behaviors and does not appear to spill over to non-incentivized behaviors.

Access to Technology and Digital Literacy as Determinants of Health and Health Care.

Access to and the skills to use technology provide the digital equity necessary for civic and cultural participation, employment, lifelong learning, and access to essential services. However, existing digital disparities and the resultant 'digital divide' risk exacerbating health and health-care inequalities. The COVID-19 pandemic amplified these disparities and accelerated the adoption of technology-driven health care such as telehealth, electronic health records, and digital health technologies. Unfortunately, pre-existing disparities influence the adoption and utilization of these technologies, often leaving disadvantaged groups further behind. Efforts toward digital inclusion, access to technology, and digital literacy are necessary to ensure universal access to and meaningful engagement with digital resources. Nurses play a vital role in promoting digital equity, serving as educators, advocates, and digital navigators, guiding patients through the complexities of the digital health landscape.

Comparison of weight captured via electronic health record and cellular scales to the gold-standard clinical method.

Introduction: Obtaining body weights remotely could improve feasibility of pragmatic trials. This investigation examined whether weights collected via cellular scale or electronic health record (EHR) correspond to gold standard in-person study weights. Methods: The agreement of paired weight measurements from cellular scales were compared to study scales from a weight loss intervention and EHR-collected weights were compared to study scales from a weight loss maintenance intervention. Differential weight change estimates between intervention and control groups using both pragmatic methods were compared to study collected weight. In the Log2Lose feasibility weight loss trial, in-person weights were collected bi-weekly and compared to weights collected via cellular scales throughout the study period. In the MAINTAIN weight loss maintenance trial, in-person weights were collected at baseline, 14, 26, 42 and 56 weeks. All available weights from the EHR during the study period were obtained. Results: On average, in Log2Lose cellular scale weights were 0.6 kg (95% CI: -2.9, 2.2) lower than in-person weights; in MAINTAIN, EHR weights were 2.8 kg (SE: -0.5, 6.0) higher than in-person weights. Estimated weight change using pragmatic methods and study scales in both studies were in the same direction and of similar magnitude. Conclusion: Both methods can be used as cost-effective and real-world surrogates within a tolerable variability for the gold-standard. Trial registration: NCT02691260; NCT01357551.

Utility of Urine Cultures During Febrile Neutropenia Workup in Hematopoietic Stem Cell Transplantation Recipients Without Urinary Symptoms.

The utility of obtaining screening urine cultures for febrile neutropenia (FN) during hematopoietic stem cell transplant (HCT) is unknown. In 667 adult HCT patients with FN, only 40 (6%) were found with bacteriuria. Antibiotics were modified in 3 patients (0.4%) based on urine cultures and none developed urinary-associated infectious complications.

Synthetic Biology Pathway to Nucleoside Triphosphates for Expanded Genetic Alphabets.

One horizon in synthetic biology seeks alternative forms of DNA that store, transcribe, and support the evolution of biological information. Here, hydrogen bond donor and acceptor groups are rearranged within a Watson-Crick geometry to get 12 nucleotides that form 6 independently replicating pairs. Such artificially expanded genetic information systems (AEGIS) support Darwinian evolution in vitro. To move AEGIS into living cells, metabolic pathways are next required to make AEGIS triphosphates economically from their nucleosides, eliminating the need to feed these expensive compounds in growth media. We report that "polyphosphate kinases" can be recruited for such pathways, working with natural diphosphate kinases and engineered nucleoside kinases. This pathway in vitro makes AEGIS triphosphates, including third-generation triphosphates having improved ability to survive in living bacterial cells. In α-32P-labeled forms, produced here for the first time, they were used to study DNA polymerases, finding cases where third-generation AEGIS triphosphates perform better with natural enzymes than second-generation AEGIS triphosphates.

Evaluating the Feasibility and Usability of the Disposable Intubation Drape (I-Drape).

In response to the COVID-19 pandemic, several protective barrier enclosures were developed to protect healthcare providers during airway manipulation. A certified registered nurse anesthetist (CRNA) created a barrier, the disposable intubation drape (I-Drape), that addressed limitations in range of motion. A nonrandomized, quasi-experimental design with repeated measures was used to evaluate I-Drape usability. CRNAs implemented I-Drape up to three times. Multilevel modeling was used to analyze the primary outcome: time (in seconds) to successful intubation. An online survey was used to evaluate secondary outcomes of interest: users' perceptions of features such as usability, visibility, and durability. We recruited 23 CRNAs as participants for 59 trials. Overall successful intubation and first-pass success rates were 96.6% and 93.2%, respectively. Time to successful intubation did not significantly decrease (ß = -9.16, P = 0.323) or differ significantly among types of laryngoscopy device and years of experience was not a significant factor. Overall, users favorably rated I-Drape with respect to usability, visibility, durability, and feature utility. This study demonstrated the functionality, success rate, and acceptability of I-Drape. I-Drape can be used safely and efficiently with any type of laryngoscopy device by providers with various experience levels.

A Tailored SMS Text Message-Based Intervention to Facilitate Patient Access to Referred Community-Based Social Needs Resources: Protocol for a Pilot Feasibility and Acceptability Study.

BACKGROUND: Health care providers are increasingly screening patients for unmet social needs (eg, food, housing, transportation, and social isolation) and referring patients to relevant community-based resources and social services. Patients' connection to referred services is often low, however, suggesting the need for additional support to facilitate engagement with resources. SMS text messaging presents an opportunity to address barriers related to contacting resources in an accessible, scalable, and low-cost manner. OBJECTIVE: In this multi-methods pilot study, we aim to develop an automated SMS text message-based intervention to promote patient connection to referred social needs resources within 2 weeks of the initial referral and to evaluate its feasibility and patient acceptability. This protocol describes the intervention, conceptual underpinnings, study design, and evaluation plan to provide a detailed illustration of how SMS technology can complement current social needs screening and referral practice patterns without disrupting care. METHODS: For this pilot prospective cohort study, this SMS text message-based intervention augments an existing social needs screening, referral, and navigation program at a federally qualified health center. Patients who received at least one referral for any identified unmet social need are sent 2 rounds of SMS messages over 2 weeks. The first round consists of 5-10 messages that deliver descriptions of and contact information for the referred resources. The second round consists of 2 messages that offer a brief reminder to contact the resources. Participants will evaluate the intervention via a survey and a semistructured interview, informed by an adapted technology acceptance model. Rapid qualitative and thematic analysis will be used to extract themes from the responses. Primary outcomes are implementation feasibility and patient acceptability. Secondary outcomes relate to intervention effectiveness: self-reported attempt to connect and successful connection to referred resources 2 weeks after the initial referral encounter. RESULTS: The study received regulatory approval in May 2021, and we anticipate enrolling 15-20 participants for this initial pilot. CONCLUSIONS: This protocol presents detailed implementation methods about a novel automated SMS intervention for social care integration within primary care. By sharing the study protocol early, we intend to facilitate the development and adoption of similar tools across different clinical settings, as more health care providers seek to address the unmet social needs of patients. Study findings will provide practical insights into the design and implementation of SMS text message-based interventions to improve social and medical care coordination. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37316.

A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19.

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants and emerging diseases like monkeypox, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing toward individuals who are most likely to be infected and, thus, increasing the testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6765 participants) and the MyPHD study (8580 participants), including smartwatch data from 1265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate (RHR) features distinguished between COVID-19-positive and -negative cases earlier in the course of the infection than steps features, as early as 10 and 5 days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7-11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38-50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 4.5-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve the allocation of diagnostic testing resources and reduce the burden of test shortages.

The Role of Patient and Parent Education in Pediatric Cast Complications.

Cast immobilization remains the standard of care in managing pediatric fractures. Cast complications often result in emergency department visits, office calls and visits, or lasting patient morbidities that burden the healthcare institution from a time and economic standpoint. The purpose of this quality improvement project was to create a multimodal cast care education protocol with an aim of decreasing cast complications over a 6-week period. Qualified patients (0-18) placed in cast immobilization received a quick response (QR) code sticker on their casts linked to a custom cast care website with text, pictures, and video instructions. Incidence of cast complications, complication type, effect(s) on workflow, and patient demographics were recorded. The complication rate declined 7.6%, but it was not statistically significant. Continuous access to clinic-specific cast instructions demonstrates decreased cast complications in pediatric populations, and this approach to patient education can be easily utilized across all medical specialties.

A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial.

BACKGROUND: The use of digital technologies and software allows for new opportunities to communicate and engage with research participants over time. When software is coupled with automation, we can engage with research participants in a reliable and affordable manner. Research Electronic Data Capture (REDCap), a browser-based software, has the capability to send automated text messages. This feature can be used to automate delivery of tailored intervention content to research participants in interventions, offering the potential to reduce costs and improve accessibility and scalability. OBJECTIVE: This study aimed to describe the development and use of 2 REDCap databases to deliver automated intervention content and communication to index participants and their partners (dyads) in a 2-arm, 24-month weight management trial, Partner2Lose. METHODS: Partner2Lose randomized individuals with overweight or obesity and cohabitating with a partner to a weight management intervention alone or with their partner. Two databases were developed to correspond to 2 study phases: one for weight loss initiation and one for weight loss maintenance and reminders. The weight loss initiation database was programmed to send participants (in both arms) and their partners (partner-assisted arm) tailored text messages during months 1-6 of the intervention to reinforce class content and support goal achievement. The weight maintenance and reminder database was programmed to send maintenance-related text messages to each participant (both arms) and their partners (partner-assisted arm) during months 7-18. It was also programmed to send text messages to all participants and partners over the course of the 24-month trial to remind them of group classes, dietary recall and physical activity tracking for assessments, and measurement visits. All text messages were delivered via Twilio and were unidirectional. RESULTS: Five cohorts, comprising 231 couples, were consented and randomized in the Partner2Lose trial. The databases will send 53,518 automated, tailored text messages during the trial, significantly reducing the need for staff to send and manage intervention content over 24 months. The cost of text messaging will be approximately US $450. Thus far, there is a 0.004% known error rate in text message delivery. CONCLUSIONS: Our trial automated the delivery of tailored intervention content and communication using REDCap. The approach described provides a framework that can be used in future behavioral health interventions to create an accessible, reliable, and affordable method for intervention delivery and engagement that requires minimal trial-specific resources and personnel time. TRIAL REGISTRATION: ClinicalTrials.gov NCT03801174; https://clinicaltrials.gov/ct2/show/NCT03801174?term=NCT03801174.

Bile Acids-A Peek Into Their History and Signaling.

Bile acids wear many hats, including those of an emulsifier to facilitate nutrient absorption, a cholesterol metabolite, and a signaling molecule in various tissues modulating itching to metabolism and cellular functions. Bile acids are synthesized in the liver but exhibit wide-ranging effects indicating their ability to mediate organ-organ crosstalk. So, how does a steroid metabolite orchestrate such diverse functions? Despite the inherent chemical similarity, the side chain decorations alter the chemistry and biology of the different bile acid species and their preferences to bind downstream receptors distinctly. Identification of new modifications in bile acids is burgeoning, and some of it is associated with the microbiota within the intestine. Here, we provide a brief overview of the history and the various receptors that mediate bile acid signaling in addition to its crosstalk with the gut microbiota.

Telehealth for the Longitudinal Management of Chronic Conditions: Systematic Review.

BACKGROUND: Extensive literature support telehealth as a supplement or adjunct to in-person care for the management of chronic conditions such as congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM). Evidence is needed to support the use of telehealth as an equivalent and equitable replacement for in-person care and to assess potential adverse effects. OBJECTIVE: We conducted a systematic review to address the following question: among adults, what is the effect of synchronous telehealth (real-time response among individuals via phone or phone and video) compared with in-person care (or compared with phone, if synchronous video care) for chronic management of CHF, chronic obstructive pulmonary disease, and T2DM on key disease-specific clinical outcomes and health care use? METHODS: We followed systematic review methodologies and searched two databases (MEDLINE and Embase). We included randomized or quasi-experimental studies that evaluated the effect of synchronously delivered telehealth for relevant chronic conditions that occurred over ≥2 encounters and in which some or all in-person care was supplanted by care delivered via phone or video. We assessed the bias using the Cochrane Effective Practice and Organization of Care risk of bias (ROB) tool and the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation. We described the findings narratively and did not conduct meta-analysis owing to the small number of studies and the conceptual heterogeneity of the identified interventions. RESULTS: We identified 8662 studies, and 129 (1.49%) were reviewed at the full-text stage. In total, 3.9% (5/129) of the articles were retained for data extraction, all of which (5/5, 100%) were randomized controlled trials. The CHF study (1/5, 20%) was found to have high ROB and randomized patients (n=210) to receive quarterly automated asynchronous web-based review and follow-up of telemetry data versus synchronous personal follow-up (in-person vs phone-based) for 1 year. A 3-way comparison across study arms found no significant differences in clinical outcomes. Overall, 80% (4/5) of the studies (n=466) evaluated synchronous care for patients with T2DM (ROB was judged to be low for 2, 50% of studies and high for 2, 50% of studies). In total, 20% (1/5) of the studies were adequately powered to assess the difference in glycosylated hemoglobin level between groups; however, no significant difference was found. Intervention design varied greatly from remote monitoring of blood glucose combined with video versus in-person visits to an endocrinology clinic to a brief, 3-week remote intervention to stabilize uncontrolled diabetes. No articles were identified for chronic obstructive pulmonary disease. CONCLUSIONS: This review found few studies with a variety of designs and interventions that used telehealth as a replacement for in-person care. Future research should consider including observational studies and studies on additional highly prevalent chronic diseases.

Integrating Patient-generated Digital Health Data into Electronic Health Records (EHRs) in Ambulatory Care Settings: EHR Vendor Survey and Interviews.

Data traditionally collected in a clinic or hospital setting is now collected electronically in everyday environments from patients, known as patient-generated health data (PGHD). We conducted informal interviews and collected survey data from major ambulatory care EHR vendors that serve the majority of the U.S. market to collect information on how their clients are integrating PGHD into EHRs. Of the 9 EHR vendors contacted, 6 completed the survey and 5 participated in a 45-minute interview. Feedback from the vendors included how PGHD use has steadily risen over the past decade and how the COVID-19 pandemic accelerated PGHD use. Pathways for data from devices or surveys to be brought securely into the EHR are increasing. While promising, adoption of health IT systems has its challenges. There are disparities in EHRs, devices, and applications. We concluded that more supportive policies are needed to advance PGHD integration.

Loss of Hepatic Small Heterodimer Partner Elevates Ileal Bile Acids and Alters Cell Cycle-related Genes in Male Mice.

Small heterodimer partner (Shp) regulates several metabolic processes, including bile acid levels, but lacks the conserved DNA binding domain. Phylogenetic analysis revealed conserved genetic evolution of SHP, FXR, CYP7A1, and CYP8B1. Shp, although primarily studied as a downstream target of Farnesoid X Receptor (Fxr), has a distinct hepatic role that is poorly understood. Here, we report that liver-specific Shp knockout (LShpKO) mice have impaired negative feedback of Cyp7a1 and Cyp8b1 on bile acid challenge and demonstrate that a single copy of the Shp gene is sufficient to maintain this response. LShpKO mice also exhibit elevated total bile acid pool with ileal bile acid composition mimicking that of cholic acid-fed control mice. Agonistic activation of Fxr (GW4064) in the LShpKO did not alter the elevated basal expression of Cyp8b1 but lowered Cyp7a1 expression. We found that deletion of Shp led to an enrichment of distinct motifs and pathways associated with circadian rhythm, copper ion transport, and DNA synthesis. We confirmed increased expression of metallothionein genes that can regulate copper levels in the absence of SHP. LShpKO livers also displayed a higher basal proliferation that was exacerbated specifically with bile acid challenge either with cholic acid or 3,5-diethoxycarbonyl-1,4-dihydrocollidine but not with another liver mitogen, 1,4-bis[2-(3,5-dichloropyridyloxy)]benzene. Overall, our data indicate that hepatic SHP uniquely regulates certain proliferative and metabolic cues.

A Method for Intelligent Allocation of Diagnostic Testing by Leveraging Data from Commercial Wearable Devices: A Case Study on COVID-19.

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing towards individuals who are most likely to be infected and, thus, increasing testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6,765 participants) and the MyPHD study (8,580 participants), including smartwatch data from 1,265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate features distinguished between COVID-19 positive and negative cases earlier in the course of the infection than steps features, as early as ten and five days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7-11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38-50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 3-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve allocation of diagnostic testing resources and reduce the burden of test shortages.