Design and Implementation of an Innovative, Rapid Data-Monitoring Strategy for Public Health Emergencies: Pilot of the United States School COVID-19 Mitigation Strategies Project

During the COVID-19 pandemic, an urgent need existed for near-real-time data collection to better understand how individual beliefs and behaviors, state and local policies, and organizational practices influenced health outcomes. We describe the processes, methods, and lessons learned during the development and pilot testing of an innovative rapid data collection process we developed to inform decision-making during the COVID-19 public health emergency. We used a fully integrated mixed-methods approach to develop a structured process for triangulating quantitative and qualitative data from traditional (cross-sectional surveys, focus groups) and nontraditional (social media listening) sources. Respondents included students, parents, teachers, and key school personnel (eg, nurses, administrators, mental health providers). During the pilot phase (February-June 2021), data from 12 cross-sectional and sector-based surveys (n = 20 302 participants), 28 crowdsourced surveys (n = 26 820 participants), 10 focus groups (n = 64 participants), and 11 social media platforms (n = 432 754 503 responses) were triangulated with other data to support COVID-19 mitigation in schools. We disseminated findings through internal dashboards, triangulation reports, and policy briefs. This pilot demonstrated that triangulating traditional and nontraditional data sources can provide rapid data about barriers and facilitators to mitigation implementation during an evolving public health emergency. Such a rapid feedback and continuous improvement model can be tailored to strengthen response efforts. This approach emphasizes the value of nimble data modernization efforts to respond in real time to public health emergencies.

Machine learning-based prediction of low-value care for hospitalized patients

Objective

Low-value care (i.e., costly health care treatments that provide little or no benefit) is an ongoing problem in United States hospitals. Traditional strategies for reducing low-value care are only moderately successful. Informed by behavioral science principles, we sought to use machine learning to inform a targeted prompting system that suggests preferred alternative treatments at the point of care but before clinicians have made a decision.

Methods

We used intravenous administration of albumin for fluid resuscitation in intensive care unit (ICU) patients as an exemplar of low-value care practice, identified using the electronic health record of a multi-hospital health system. We divided all ICU episodes into 4-h periods and defined a set of relevant clinical features at the period level. We then developed two machine learning models: a single-stage model that directly predicts if a patient will receive albumin in the next period; and a two-stage model that first predicts if any resuscitation fluid will be administered and then predicts albumin only among the patients with a high probability of fluid use.

Results

We examined 87,489 ICU episodes divided into approximately 1.5 million 4-h periods. The area under the receiver operating characteristic curve was 0.86 for both prediction models. The positive predictive value was 0.21 (95% confidence interval: 0.20, 0.23) for the single-stage model and 0.22 (0.20, 0.23) for the two-stage model. Applying either model in a targeted prompting system could prevent 10% of albumin administrations, with an attending physician receiving one prompt every 4.2 days of ICU service.

Conclusion

Prediction of low-value care is feasible and could enable a point-of-care, targeted prompting system that offers suggestions ahead of the moment of need before clinicians have already decided. A two-stage approach does not improve performance but does interject new levers for the calibration of such a system.

Predictors of Atrial Fibrillation in Patients With Stroke Attributed to Large- or Small-Vessel Disease: A Prespecified Secondary Analysis of the STROKE AF Randomized Clinical Trial

Importance

The Stroke of Known Cause and Underlying Atrial Fibrillation (STROKE AF) trial found that approximately 1 in 8 patients with recent ischemic stroke attributed to large- or small-vessel disease had poststroke atrial fibrillation (AF) detected by an insertable cardiac monitor (ICM) at 12 months. Identifying predictors of AF could be useful when considering an ICM in routine poststroke clinical care.

Objective

To determine the association between commonly assessed risk factors and poststroke detection of new AF in the STROKE AF cohort monitored by ICM.

Design, Setting, and Participants

This was a prespecified analysis of a randomized (1:1) clinical trial that enrolled patients between April 1, 2016, and July 12, 2019, with primary follow-up through 2020 and mean (SD) duration of 11.0 (3.0) months. Eligible patients were selected from 33 clinical research sites in the US. Patients had an index stroke attributed to large- or small-vessel disease and were 60 years or older or aged 50 to 59 years with at least 1 additional stroke risk factor. A total of 496 patients were enrolled, and 492 were randomly assigned to study groups (3 did not meet inclusion criteria, and 1 withdrew consent). Patients in the ICM group had the index stroke within 10 days before insertion. Data were analyzed from October 8, 2021, to January 28, 2022.

Interventions

ICM monitoring vs site-specific usual care (short-duration external cardiac monitoring).

Main Outcomes and Measures

The ICM device automatically detects AF episodes 2 or more minutes in length; episodes were adjudicated by an expert committee. Cox regression multivariable modeling included all parameters identified in the univariate analysis having P values <.10. AF detection rates were calculated using Kaplan-Meier survival estimates.

Results

The analysis included the 242 participants randomly assigned to the ICM group in the STROKE AF study. Among 242 patients monitored with ICM, 27 developed AF (mean [SD] age, 66.6 [9.3] years; 144 men [60.0%]; 96 [40.0%] women). Two patients had missing baseline data and exited the study early. Univariate predictors of AF detection included age (per 1-year increments: hazard ratio [HR], 1.05; 95% CI, 1.01-1.09; P = .02), CHA2DS2-VASc score (per point: HR, 1.54; 95% CI, 1.15-2.06; P = .004), chronic obstructive pulmonary disease (HR, 2.49; 95% CI, 0.86-7.20; P = .09), congestive heart failure (CHF; with preserved or reduced ejection fraction: HR, 6.64; 95% CI, 2.29-19.24; P < .001), left atrial enlargement (LAE; HR, 3.63; 95% CI, 1.55-8.47; P = .003), QRS duration (HR, 1.02; 95% CI, 1.00-1.04; P = .04), and kidney dysfunction (HR, 3.58; 95% CI, 1.35-9.46; P = .01). In multivariable modeling (n = 197), only CHF (HR, 5.06; 95% CI, 1.45-17.64; P = .05) and LAE (HR, 3.32; 1.34-8.19; P = .009) remained significant predictors of AF. At 12 months, patients with CHF and/or LAE (40 of 142 patients) had an AF detection rate of 23.4% vs 5.0% for patients with neither (HR, 5.1; 95% CI, 2.0-12.8; P < .001).

Conclusions and Relevance

Among patients with ischemic stroke attributed to large- or small-vessel disease, CHF and LAE were associated with a significantly increased risk of poststroke AF detection. These patients may benefit most from the use of ICMs as part of a secondary stroke prevention strategy. However, the study was not powered for clinical predictors of AF, and therefore, other clinical characteristics may not have reached statistical significance.

Trial Registration

ClinicalTrials.gov Identifier: NCT02700945.

Adapting genetic counseling operations amidst the COVID-19 pandemic

The COVID‐19 pandemic caused significant disruptions to the delivery of genetic counseling services and clinical operations. Understanding how these pivots in practice affected patient care across both a county hospital system and academic medical center can help provide models of clinical operations for other genetic counselors. Programmatic data were analyzed between March 18, 2020 and September 18, 2020, including visit completion rates and genetic testing completion outcomes for genetic counseling services during the COVID‐19 pandemic. In addition to analyzing the effects on patient care, we provide commentary on technological adaptations that aided our operations, billing practices, onboarding and engaging new and existing staff, and coordination of education and outreach opportunities. Through this work, we highlight barriers encountered and successful adaptations that will influence future clinical practices and may guide other providers in the development of strategies to meet their clinical and operational needs.

Observation of Conditions Preceding Peak Indoor Air Volatile Org Compound Concentrations in Vapor Intrusion Studies

Temporal and spatial variability of indoor air volatile organic compound (VOC) concentrations can complicate vapor intrusion (VI) assessment and decision-making. Indicators and tracers (I&T) of VI, such as differential temperature, differential pressure, and indoor radon concentration, are low-cost lines of evidence to support sampling scheduling and interpretation of indoor air VOC sampling results. This study compares peak indoor air chlorinated VOC concentrations and I&T conditions before and during those peak events at five VI sites. The sites differ geographically and in their VI conceptual site models (CSM). Relative to site-specific baseline values, the results show that cold or falling outdoor temperatures, rising cross slab differential pressures, and increasing indoor radon concentrations can predict peak VOC concentrations. However, cold outdoor air temperature was not useful at one site where elevated shallow soil temperature was a better predictor. Correlations of peak VOC concentrations to elevated or rising barometric pressure and low wind speed were also observed with some exceptions. This study shows how the independent variables that control or predict peak indoor air VOC concentrations are specific to building types, climates, and VI CSMs. More I&T measurements at VI sites are needed to identify scenario-specific baseline and peak related I&T conditions to improve decision-making.

Iterative guided machine learning-assisted systematic literature reviews: a diabetes case study

BACKGROUND

Systematic Reviews (SR), studies of studies, use a formal process to evaluate the quality of scientific literature and determine ensuing effectiveness from qualifying articles to establish consensus findings around a hypothesis. Their value is increasing as the conduct and publication of research and evaluation has expanded and the process of identifying key insights becomes more time consuming. Text analytics and machine learning (ML) techniques may help overcome this problem of scale while still maintaining the level of rigor expected of SRs.

METHODS

In this article, we discuss an approach that uses existing examples of SRs to build and test a method for assisting the SR title and abstract pre-screening by reducing the initial pool of potential articles down to articles that meet inclusion criteria. Our approach differs from previous approaches to using ML as a SR tool in that it incorporates ML configurations guided by previously conducted SRs, and human confirmation on ML predictions of relevant articles during multiple iterative reviews on smaller tranches of citations. We applied the tailored method to a new SR review effort to validate performance.

RESULTS

The case study test of the approach proved a sensitivity (recall) in finding relevant articles during down selection that may rival many traditional processes and show ability to overcome most type II errors. The study achieved a sensitivity of 99.5% (213 out of 214) of total relevant articles while only conducting a human review of 31% of total articles available for review.

CONCLUSIONS

We believe this iterative method can help overcome bias in initial ML model training by having humans reinforce ML models with new and relevant information, and is an applied step towards transfer learning for ML in SR.

Exploratory analysis of machine learning approaches for surveillance of Zika-associated birth defects

In 2016, Centers for Disease Control and Prevention (CDC) established surveillance of pregnant women with Zika virus infection and their infants in the U.S. states, territories, and freely associated states. To identify cases of Zika-associated birth defects, subject matter experts review data reported from medical records of completed pregnancies to identify findings that meet surveillance case criteria (manual review). The volume of reported data increased over the course of the Zika virus outbreak in the Americas, challenging the resources of the surveillance system to conduct manual review. Machine learning was explored as a possible method for predicting case status. Ensemble models (using machine learning algorithms including support vector machines, logistic regression, random forests, k-nearest neighbors, gradient boosted trees, and decision trees) were developed and trained using data collected from January 2016-October 2017. Models were developed separately, on data from the U.S. states, non-Puerto Rico territories, and freely associated states (referred to as the U.S. Zika Pregnancy and Infant Registry [USZPIR]) and data from Puerto Rico (referred to as the Zika Active Pregnancy Surveillance System [ZAPSS]) due to differences in data collection and storage methods. The machine learning models demonstrated high sensitivity for identifying cases while potentially reducing volume of data for manual review (USZPIR: 96% sensitivity, 25% reduction in review volume; ZAPSS: 97% sensitivity, 50% reduction in review volume). Machine learning models show potential for identifying cases of Zika-associated birth defects and for reducing volume of data for manual review, a potential benefit in other public health emergency response settings.

Efficacy and Safety of Intravenously Administered Tramadol in Patients with Moderate to Severe Pain Following Bunionectomy: A Randomized, Double-Blind, Placebo-Controlled, Dose-Finding Study

INTRODUCTION

This study is part of the registrational program for intravenously administered (IV) tramadol in the USA and compared the analgesic benefit and tolerability of two doses of IV tramadol (50 mg and 25 mg) to placebo in adult patients undergoing bunionectomy, an orthopedic surgical model.

METHODS

This was a phase 3, multicenter, double-blind, three-arm, randomized, placebo-controlled, multiple-dose, parallel-group trial to evaluate IV tramadol in the management of postoperative pain following bunionectomy. Eligible patients were randomized (1:1:1 ratio) to IV tramadol 50 mg, 25 mg, or placebo. Primary endpoint was summary of pain intensity differences over 48 h (SPID48). Key secondary endpoints included SPID24, total consumption of rescue analgesia, and patient global assessment of efficacy (PGA). Safety assessments included treatment emergent adverse events (TEAEs), clinical laboratory tests, vital signs, and electrocardiograms (ECGs). Assessment of the dose-response was an important objective of the study.

RESULTS

The study established a dose response, with IV tramadol 50 mg demonstrating statistically significant benefit (p < 0.05) over placebo for primary and all key secondary efficacy endpoints, whereas tramadol 25 mg demonstrated intermediate results between the 50 mg and placebo arms. IV tramadol 50 mg was well tolerated; most common TEAEs were nausea and vomiting; and there were no meaningful differences among treatments for vital signs, ECG, and laboratory assessments. The largest proportion of patients completed tramadol 50 mg (98.6%) compared to tramadol 25 mg (91.8%) and placebo (88.2%).

CONCLUSION

IV tramadol 50 mg was effective and well tolerated as treatment for postoperative pain following bunionectomy surgery, while IV tramadol 25 mg, although well tolerated, was judged an ineffective dose for the treatment of pain in this setting. IV tramadol 50 mg was further developed in the registrational program for the USA.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, NCT03290378.

Find and Seek

Web designers use visual cues such as layout and typography to make pages easier to navigate and understand. Yet, screen readers generally ignore these features and present page information in a linear audio stream. We investigate whether transcoding the visual semantics of grid-based layouts to tables supports better navigation. In a controlled experiment, participants navigated re-written pages significantly faster when doing data synthesis tasks and more accurately when looking up information meeting multiple criteria. Participants rated their table navigation experience better in terms of effort, memorization, ease of navigation, understanding of page information, and confidence in submitted answers. Participants attributed these gains to the table structure’s support for (1) predictable audio presentation, (2) adopting an appropriate search strategy, and (3) making sense of page content. Contrary to the established belief that tables are inaccessible, our results show that tables can facilitate navigation when users need to synthesize across page content.

Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

Long-term clinical outcomes of magnetically navigated rotor ablation as an adjunct to conventional pulmonary vein isolation

Aims

The objective of this study is to evaluate the outcomes of magnetically guided ablation of atrial fibrillation (AF) rotors in conjunction with magnetically guided pulmonary vein isolation (PVI) in a large consecutive series of patients.

Methods and results

A total of 110 consecutive patients with drug-refractory AF underwent rotor ablation followed by conventional PVI and ablation of other spontaneous arrhythmias, all of which were performed with remote magnetic navigation (RMN). The patients were followed to assess the recurrence of atrial arrhythmia. Patients had a mean age of 62.5 ± 9.9 years, 64.5% had persistent AF, and 36.4% had a prior failed PVI. All patients had mapped rotors (3.9 ± 1.5 per patient), with right atrial (RA) rotors in 77.3% (85/110) of patients. After a mean follow-up of 17.6 ± 9.5 months, 90.9% (100/110) were in stable sinus rhythm including patients on previously ineffective antiarrhythmic drugs (AADs). 69.1% (76/110) were in stable sinus rhythm without any AADs. Outcome did not differ between patients with persistent or paroxysmal AF (69.2% vs. 69.0%; P = 0.75), failed prior ablation or those undergoing an initial ablation (77.5% vs. 64.3%; P = 0.193), or patients with and without intra-procedural AF termination (67.3% vs. 70.5%; P = 0.723).

Conclusion

Ablation of rotors in combination with PVI using RMN was associated with a high success rate in this large cohort of consecutive patients. Significant proportion of patients exhibited RA rotors, which was associated with persistent AF, obstructive sleep apnoea, and obesity.

Evidence of a sewer vapor transport pathway at the USEPA vapor intrusion research duplex

The role of sewer lines as preferential pathways for vapor intrusion is poorly understood. Although the importance of sewer lines for volatile organic compound (VOC) transport has been documented at a small number of sites with vapor intrusion, sewer lines are not routinely sampled during most vapor intrusion investigations. We have used a tracer study and VOC concentration measurements to evaluate the role of the combined sanitary/storm sewer line in VOC transport at the USEPA vapor intrusion research duplex in Indianapolis, Indiana. The results from the tracer study demonstrated gas migration from the sewer main line into the duplex. The migration pathway appears to be complex and may include leakage from the sewer lateral at a location below the building foundation. Vapor samples collected from the sewer line demonstrated the presence of tetrachloroethene (PCE) and chloroform in the sewer main in front of the duplex and at multiple sample locations within the sewer line upstream of the duplex. These test results combined with results from the prior multi-year study of the duplex indicate that the sewer line plays an important role in transport of VOCs from the subsurface source to the immediate vicinity of the duplex building envelope.

Use of Oral Fluids for Detection of Virus and Antibodies in Pigs Infected with Swine Vesicular Disease Virus

The use of swine oral fluid (OF) for the detection of nucleic acids and antibodies is gaining significant popularity. Assays have been developed for this purpose for endemic and foreign animal diseases of swine. Here, we report the use of OF for the detection of virus and antibodies in pigs experimentally infected with swine vesicular disease virus (SVDV), a virus that causes a disease clinically indistinguishable from the economically devastating foot-and-mouth disease. Viral genome was detected in OF by real-time reverse transcription polymerase chain reaction (RRT-PCR) from 1 day post-infection (DPI) to 21 DPI. Virus isolation from OF was also successful at 1-5 DPI. An adapted competitive ELISA based on the monoclonal antibodies 5B7 detected antibodies to SVDV in OF starting at DPI 6. Additionally, using isotype-specific indirect ELISAs, SVDV-specific IgM and IgA were evaluated in OF. IgM response started at DPI 6, peaking at DPI 7 or 14 and declining sharply at DPI 21, while IgA response started at DPI 7, peaked at DPI 14 and remained high until the end of the experiment. These results confirm the potential use of OF for SVD surveillance using both established and partially validated assays in this study.

Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help

Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients' healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations.

Intrinsic Metastabilities in the Charge Configuration of a Double Quantum Dot

We report a thermally activated metastability in a GaAs double quantum dot exhibiting real-time charge switching in diamond shaped regions of the charge stability diagram. Accidental charge traps and sensor backaction are excluded as the origin of the switching. We present an extension of the canonical double dot theory based on an intrinsic, thermal electron exchange process through the reservoirs, giving excellent agreement with the experiment. The electron spin is randomized by the exchange process, thus facilitating fast, gate-controlled spin initialization. At the same time, this process sets an intrinsic upper limit to the spin relaxation time.

Nanoscale Semiconductor Devices as New Biomaterials

Research on nanoscale semiconductor devices will elicit a novel understanding of biological systems. First, we discuss why it is necessary to build interfaces between cells and semiconductor nanoelectronics. Second, we describe some recent molecular biophysics studies with nanowire field effect transistor sensors. Third, we present the use of nanowire transistors as electrical recording devices that can be integrated into synthetic tissues and targeted intra- or extracellularly to study single cells. Lastly, we discuss future directions and challenges in further developing this area of research, which will advance biology and medicine.

Comparison of specimens for detection of porcine reproductive and respiratory syndrome virus infection in boar studs

Porcine reproductive and respiratory syndrome virus (PRRSV)-contaminated semen from boars is a route of transmission to females, and early detection of PRRSV infection in boars is a key component in sow farm biosecurity. The purpose of this study was to determine the optimum diagnostic specimen(s) for the detection of acute PRRSV infection in boars. Individually housed boars (n = 15) were trained for semen and oral fluid collection and then vaccinated with a commercial PRRSV modified live virus vaccine. Starting on the day of vaccination and for 14 days thereafter, oral fluid specimens were collected daily from all boars. The 15 boars were subdivided into three groups of 5, and serum, blood swabs and 'frothy saliva' were collected at the time of semen collection on a 3-day rotation. Frothy saliva, derived from the submandibular salivary gland, is produced by aroused boars. Semen was centrifuged, and semen supernatant and cell fractions were tested separately. All samples were randomly ordered and then tested by PRRSV real-time quantitative reverse-transcription polymerase chain reaction assay (rRT-PCR) and PRRSV antibody ELISA. In this study, a comparison of serum, blood swab, and oral fluid rRT-PCR results found no statistically significant differences in the onset of detection or proportion of positives, but serum was numerically superior to oral fluids for early detection. Serum and oral fluid provided identical rRT-PCR results at ≥ 5 day post-vaccination. Likewise, the onset of detection of PRRSV antibody in serum, oral fluid and frothy saliva was statistically equivalent, with serum results again showing a numerical advantage. These results showed that the highest assurance of providing PRRSV-negative semen to sow farms should be based on rRT-PCR testing of serum collected at the time of semen collection. This approach can be augmented with oral fluid sampling from a random selection of uncollected boars to provide for statistically valid surveillance of the boar stud.

Discovering medical conditions associated with periodontitis using linked electronic health records

AIM

To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses.

MATERIALS AND METHODS

This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders.

RESULTS

Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30-1.99, p < 0.001) and type II (OR = 1.4, 95% CI 1.22-1.67, p < 0.001), hypertension (OR = 1.2, 95% CI 1.10-1.37, p < 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07-1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06-1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32-7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05-2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse.

CONCLUSIONS

This study contributes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.

Role of Homer proteins in the maintenance of sleep-wake states

Sleep is an evolutionarily conserved process that is linked to diurnal cycles and normal daytime wakefulness. Healthy sleep and wakefulness are integral to a healthy lifestyle; this occurs when an organism is able to maintain long bouts of both sleep and wake. Homer proteins, which function as adaptors for group 1 metabotropic glutamate receptors, have been implicated in genetic studies of sleep in both Drosophila and mouse. Drosophila express a single Homer gene product that is upregulated during sleep. By contrast, vertebrates express Homer as both constitutive and immediate early gene (H1a) forms, and H1a is up-regulated during wakefulness. Genetic deletion of Homer in Drosophila results in fragmented sleep and in failure to sustain long bouts of sleep, even under increased sleep drive. However, deletion of Homer1a in mouse results in failure to sustain long bouts of wakefulness. Further evidence for the role of Homer1a in the maintenance of wake comes from the CREB alpha delta mutant mouse, which displays a reduced wake phenotype similar to the Homer1a knockout and fails to up-regulate Homer1a upon sleep loss. Homer1a is a gene whose expression is induced by CREB. Sustained behaviors of the sleep/wake cycle are created by molecular pathways that are distinct from those for arousal or short bouts, and implicate an evolutionarily-conserved role for Homer in sustaining these behaviors.

Developing an online and in-person HIT workforce training program using a team-based learning approach

Workforce training in health information technology (HIT) is in demand as electronic health record adoption becomes a nationwide priority. Columbia University and Weill Cornell Medical College worked together to develop a 6-month ONC-supported certificate course. To identify relevant skills and knowledge, we conducted a needs assessment that included: interviews and focus groups with potential employers and current HIT employees; an analysis of both published literature on competencies and actual job listings; and the development of a diverse operations-oriented curriculum advisory committee, which help to synthesize the findings into 6 core curriculum modules. We selected a team-based learning approach, allowing us to train a diverse student body and providing opportunities to build collaboration skills. Our novel hybrid adaptation of team-based learning combines online and in-person activities. Lessons learned from the development of this program are likely to have widespread applicability as training programs in the field become more prevalent.

Aortic compression and cross clamping in a case of placenta percreta and amniotic fluid embolism: a case report

Amniotic fluid embolism (AFE, also known as anaphylactoid syndrome of pregnancy) at the time of surgery for placenta percreta has been previously reported. We report here a case in which AFE and associated cardiac arrest occurred following a hysterectomy for placenta percreta. In this case, subhepatic manual aortic compression during the cardiac arrest and chest compressions followed by infrarenal aortic cross-clamping during volume infusion and reversal of the coagulopathy were associated with a successful resuscitation and good maternal outcome.

[Terminology for classifying the porcine reproductive and respiratory syndrome virus (PRRSV) status of swine herds]

Standardized terminology for the porcine reproductive and respiratory syndrome virus (PRRSV) status of swine herds is necessary to facilitate communication between veterinarians, swine producers, genetic companies, and other industry participants. It is also required for implementation of regional and national efforts towards PRRSV control and elimination. The purpose of this paper is to provide a herd classification system for describing the PRRSV status of herds, based upon a set of definitions reflecting the biology and ecology of PRRSV. The herd classification system was developed by a definitions committee formed jointly by the American Association of Swine Veterinarians (AASV) and the United States Department of Agriculture PRRS-Coordinated Agricultural Project, and was approved by the AASV Board of Directors on March 9, 2010. The committee included veterinarians from private practice and industry, researchers, and representatives from AASV and the National Pork Board. Breeding herds, with or without growing pigs on the same premises, are categorized as Positive Unstable (Category I), Positive Stable (Category II), Provisional Negative (Category III), or Negative (Category IV) on the basis of herd shedding and exposure status. Growing-pig herds are categorized as Positive or Negative. Recommended testing procedures and decision rules for herd classification are detailed.

The histone acetyltransferase Elp3 plays in active role in the control of synaptic bouton expansion and sleep in Drosophila

The histone acetyltransferase Elp3 (Elongator Protein 3) is the catalytic subunit of the highly conserved Elongator complex. Elp3 is essential for the complex functions of Elongator in both the nucleus and cytoplasm of neurons, including the epigenetic control of neuronal motility genes and the acetylation of α-tubulin that affects axonal branching and cortical neuron migration. Accordingly, misregulation of Elp3 has been implicated in human disorders that specifically affect neuronal function, including familial dysautonomia, a disease characterized by degeneration of the sensory and autonomic nervous system, and the motor neuron degenerative disorder amyotrophic lateral sclerosis. These studies underscore the importance of Elp3 in neurodevelopment and disease, and the need to further characterize the multiple nuclear and cytoplasmic based roles of ELP3 required for neurogenesis in animal models, in vivo. In this report, we investigate the behavioral and morphological consequences that result from targeted reduction of ELP3 specifically in the developing Drosophila nervous system. We demonstrate that loss of Elp3 during neurodevelopment leads to a hyperactive phenotype and sleep loss in the adult flies, a significant expansion in synaptic bouton number and axonal length and branching in the larval neuromuscular junction as well as the misregulation of certain genes known to be involved in these processes. Our results uncover a novel role for Elp3 in the regulation of synaptic bouton expansion during neurogenesis that may be linked with a requirement for sleep.

Effects of different delay of reinforcement procedures on variable-interval responding

Two experiments studied responding in the rat when the first bar press after a variable period of time produced a cue light that remained on for either 10, 30, or 100 sec and terminated with the delivery of food. In Experiment I, response rate decreased and time to the first response after reinforcement increased as the delay of reinforcement increased. Similar results were obtained whether the delay consisted of retracting the lever during the delay, a fixed delay with no scheduled consequence for responding, or every response during the delay restarted the delay interval. In Experiment II, fixed-delay and fixed-interval schedules of the same duration during the delay period had no differential effect on either response rate or time to the first response after reinforcement, but differentially controlled responding during the delay periods.

Differential effects of token reinforcement on instruction-following behavior in retarded students instructed as a group

This study was addressed to the problem of applying behavior modification techniques on a group basis to a class of retarded students with "attentional deficits". Seven boys, age 8 to 15 yr, characterized as showing severe "attentional" problems or disruptive behavior in their respective classrooms, participated daily for 30-min sessions in a special class over a 1.5-month period. In each session, verbal instructions were given to the class as a whole. In control sessions, each appropriate instruction-following response by a child produced praise for that child. In experimental sessions, appropriate responses also produced tokens exchangeable for tangible reinforcers after the session. Token reinforcement differentially maintained instruction-following behavior in four children while one responded appropriately to most instructions and a second improved continuously during the study. While the data suggest that the present approach can be successfully applied to the alteration of instruction-following behavior in retarded children, its major contribution may be that of providing objective quantitative information about such behavior.

A double-blind, multicentered study comparing the accuracy of diagnostic markers to predict short- and long-term clinical events and their utility in patients presenting with chest pain

BACKGROUND

Millions of patients present annually with chest pain, but only 10% have myocardial infarction (MI). We recently reported comparative sensitivity and specificity of available markers in the diagnosis of MI; however, optimum interpretation of marker results requires prognostic follow-up data.

HYPOTHESIS

The study was undertaken to study the accuracy of CK-MB subforms, troponin I and T, myoglobin, and CK-MB in predicting clinical events at 30 days and 6 months.

METHODS

In all, 955 consecutive patients with chest pain were enrolled in a prospective, multicenter, double-blind study to test the prognostic accuracy of these markers.

RESULTS

Myocardial infarction was diagnosed in 119 by CK-MB mass criteria and unstable angina (UA) in 203 patients by clinical criteria. Follow-up at 30 days and 6 months was available in 824 and 724 patients, respectively, with mortalities of 2.8 and 4.14%, respectively. Cumulative 6-month mortality was 5.6% in MI, 4.4% in UA, and 3.0% in others. Revascularization was reported in 9.3% of patients by 6 months. A positive test on each of the markers except myoglobin was predictive of revascularization. The composite endpoint of death or revascularization occurred in 107 patients by 6 months and a positive result on each of the markers was predictive of this composite endpoint (p < 0.05). The relative risk of death or revascularization for patients who did not have MI but tested positive on each of the markers was > 1.0 but did not reach statistical significance.

CONCLUSIONS

With the possible exception of myoglobin, each of the diagnostic markers displayed similar prognostic performance in patients with chest pain presenting to emergency departments. The most appropriate markers to triage patients with chest pain, which has both adequate early diagnostic sensitivity and prognostic accuracy, are the CK-MB subforms.

Nondigestive symptoms in non-erosive reflux disease: nature, prevalence and relation to acid reflux

BACKGROUND

Nondigestive symptoms are frequent in the irritable bowel syndrome (IBS).

AIM

To characterize nondigestive symptoms in non-erosive gastro-oesophageal reflux disease (NERD) patients, as features of IBS are common in patients with NERD.

METHODS

A prospective, case-control study. NERD was defined in patients with reflux symptoms, a normal oesophageal mucosa and oesophageal pH < 4 for > or = 5% of the time during 24-h pH monitoring. Nondigestive symptoms were scored on validated scales of somatic pain, urinary, sleep and neurasthenia. IBS was defined by the Rome I criteria.

RESULTS

pH-positive NERD patients (n = 326) scored significantly higher than controls (nonpatient hospital visitors; n = 174) on all scales. The scores of pain, sleep and neurasthenia were highly specific in the discrimination of NERD patients from controls. In patients, nondigestive symptoms were independently associated with age, reflux symptoms severity and IBS status, but not with oesophageal acid exposure. NERD patients who met diagnostic criteria for IBS (49%) scored significantly higher on all the nondigestive symptoms scales than those had not met [IBS(-)]. Yet, IBS(-) patients scored significantly higher than controls on all scales.

CONCLUSIONS

Nondigestive symptoms were highly prevalent in NERD patients and were specific in their discrimination from controls. Nondigestive symptoms correlated with reflux symptoms and were predicted by IBS status.

Functional heartburn vs. non-erosive reflux disease: similarities and differences

BACKGROUND

Bowel symptoms have been associated with non-erosive reflux disease (NERD). However, their role in functional heartburn (FH) has not been established.

AIMS

To characterize bowel symptoms in FH and NERD patients, and investigate their role as predictors of severity of reflux symptoms.

METHODS

A prospective study of patients with normal upper endoscopy undergoing a 24-h oesophageal pH monitoring for the evaluation of reflux symptoms. Patients with oesophageal acid exposure <3.1% and a symptom index <50% were classified as FH (n = 60), while those with oesophageal acid exposure >4% were defined as NERD (n = 160). Symptom severity was scored on validated scales.

RESULTS

In FH, a female predominance was noted (P < 0.001). Reflux symptoms were scored higher in NERD patients (P < 0.001) while bowel symptoms were similarly scored in the two groups. In both groups, severity of reflux symptoms was independently associated with a composite score on the bowel scales (P < 0.001) and was not predicted by oesophageal acid exposure. In FH, reflux symptom severity was inversely related to age (P = 0.03), while in NERD, the opposite was true (P = 0.01).

CONCLUSIONS

In both FH and NERD, bowel symptoms were the strongest predictors of reflux symptoms severity. A female preponderance, and an opposite relationship between reflux symptom severity and age, indicate that FH and NERD may be distinct entities.

Potential of information technology in dental education

The use of information technology (IT) in dentistry is far ranging. In order to produce a working document for the dental educator, this paper focuses on those methods where IT can assist in the education and competence development of dental students and dentists (e.g. e-learning, distance learning, simulations and computer-based assessment). Web pages and other information-gathering devices have become an essential part of our daily life, as they provide extensive information on all aspects of our society. This is mirrored in dental education where there are many different tools available, as listed in this report. IT offers added value to traditional teaching methods and examples are provided. In spite of the continuing debate on the learning effectiveness of e-learning applications, students request such approaches as an adjunct to the traditional delivery of learning materials. Faculty require support to enable them to effectively use the technology to the benefit of their students. This support should be provided by the institution and it is suggested that, where possible, institutions should appoint an e-learning champion with good interpersonal skills to support and encourage faculty change. From a global prospective, all students and faculty should have access to e-learning tools. This report encourages open access to e-learning material, platforms and programs. The quality of such learning materials must have well defined learning objectives and involve peer review to ensure content validity, accuracy, currency, the use of evidence-based data and the use of best practices. To ensure that the developers' intellectual rights are protected, the original content needs to be secure from unauthorized changes. Strategies and recommendations on how to improve the quality of e-learning are outlined. In the area of assessment, traditional examination schemes can be enriched by IT, whilst the Internet can provide many innovative approaches. Future trends in IT will evolve around improved uptake and access facilitated by the technology (hardware and software). The use of Web 2.0 shows considerable promise and this may have implications on a global level. For example, the one-laptop-per-child project is the best example of what Web 2.0 can do: minimal use of hardware to maximize use of the Internet structure. In essence, simple technology can overcome many of the barriers to learning. IT will always remain exciting, as it is always changing and the users, whether dental students, educators or patients are like chameleons adapting to the ever-changing landscape.

The μPIVOT: an integrated particle image velocimeter and optical tweezers instrument for microenvironment investigations

A novel instrument to manipulate and characterize the mechanical environment in and around microscale objects in a fluidic environment has been developed by integrating two laser-based techniques: micron-resolution particle image velocimetry (μPIV) and optical tweezers (OT). This instrument, the μPIVOT, enables a new realm of microscale studies, yet still maintains the individual capabilities of each optical technique. This was demonstrated with individual measurements of optical trap stiffness (∼70 pN μm(-1) for a 20 μm polystyrene sphere and a linear relationship between trap stiffness and laser power) and fluid velocities within 436 nm of a microchannel wall. The integrated device was validated by comparing computational flow predictions to the measured velocity profile around a trapped particle in either a uniform flow or an imposed, gravity-driven microchannel flow (R(2) = 0.988, RMS error = 13.04 μm s(-1)). Interaction between both techniques is shown to be negligible for 15 μm to 35 μm diameter trapped particles subjected to fluid velocities from 50 μm s(-1) to 500 μm s(-1) even at the highest laser power (1.45 W). The integrated techniques will provide a unique perspective toward understanding microscale phenomena including single-cell biomechanics, non-Newtonian fluid mechanics and single particle or particle-particle hydrodynamics.

A Role for the Molecular Chaperone Protein BiP/GRP78 in Drosophila Sleep Homeostasis

STUDY OBJECTIVES

Microarray studies have identified numerous genes that change in response to prolonged wakefulness. The challenge is to determine which transcriptional changes translate into protein changes that are critical for recovery following sleep loss. BiP is a protein indicator of endoplasmic reticulum (ER) stress, and BiP mRNA increases in mouse and rat cerebral cortex and in Drosophila heads in response to sleep loss. We first sought to determine whether the expression of BiP protein parallels sleep homeostatic drive and dissipates with recovery sleep. We then sought to establish a key role for BiP in the homeostatic process of sleep by contrasting recovery sleep in models of over- and under-expression of BiP.

SUBJECTS AND INTERVENTIONS

Drosophila melanogaster were used to take advantage of the UAS-Gal4 system to both over express wild-type BiP and express a dominant negative form of BiP.

RESULTS

BiP protein rises two and a half fold across sleep loss and falls in recovery sleep, in parallel with gene changes. BiP over expression in the flies leads to an increase in recovery sleep in response to sleep loss, in parallel with a delay in the unfolded protein response. Flies with the dominant negative mutation and reduced functional BiP show the opposite effect.

CONCLUSIONS

We show directly that BiP protein, a key indicator of ER stress is instrumental in determining the amount of recovery sleep following enforced wakefulness. We have thus identified a novel window into regulation of sleep homeostasis.