A semi-supervised approach to unobtrusively predict abnormality in breathing patterns using hydraulic bed sensor data in older adults aging in place.

Shortness of breath is often considered a repercussion of aging in older adults, as respiratory illnesses like COPD1 or respiratory illnesses due to heart-related issues are often misdiagnosed, under-diagnosed or ignored at early stages. Continuous health monitoring using ambient sensors has the potential to ameliorate this problem for older adults at aging-in-place facilities. In this paper, we leverage continuous respiratory health data collected by using ambient hydraulic bed sensors installed in the apartments of older adults in aging-in-place Americare facilities to find data-adaptive indicators related to shortness of breath. We used unlabeled data collected unobtrusively over the span of three years from a COPD-diagnosed individual and used data mining to label the data. These labeled data are then used to train a predictive model to make future predictions in older adults related to shortness of breath abnormality. To pick the continuous changes in respiratory health we make predictions for shorter time windows (60-s). Hence, to summarize each day's predictions we propose an abnormal breathing index (ABI) in this paper. To showcase the trajectory of the shortness of breath abnormality over time (in terms of days), we also propose trend analysis on the ABI quarterly and incrementally. We have evaluated six individual cases retrospectively to highlight the potential and use cases of our approach.

Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery.

Too often, the testing and evaluation of object detection, as well as the classification techniques for high-resolution remote sensing imagery, are confined to clean, discretely partitioned datasets, i.e., the closed-world model. In recent years, the performance on a number of benchmark datasets has exceeded 99% when evaluated using cross-validation techniques. However, real-world remote sensing data are truly big data, which often exceed billions of pixels. Therefore, one of the greatest challenges regarding the evaluation of machine learning models taken out of the clean laboratory setting and into the real world is the difficulty of measuring performance. It is necessary to evaluate these models on a grander scale, namely, tens of thousands of square kilometers, where it is intractable to the ground truth and the ever-changing anthropogenic surface of Earth. The ultimate goal of computer vision model development for automated analysis and broad area search and discovery is to augment and assist humans, specifically human-machine teaming for real-world tasks. In this research, various models have been trained using object classes from benchmark datasets such as UC Merced, PatternNet, RESISC-45, and MDSv2. We detail techniques to scan broad swaths of the Earth with deep convolutional neural networks. We present algorithms for localizing object detection results, as well as a methodology for the evaluation of the results of broad-area scans. Our research explores the challenges of transitioning these models out of the training-validation laboratory setting and into the real-world application domain. We show a scalable approach to leverage state-of-the-art deep convolutional neural networks for the search, detection, and annotation of objects within large swaths of imagery, with the ultimate goal of providing a methodology for evaluating object detection machine learning models in real-world scenarios.

Clinical Outcome of Drug-Eluted Stenting (Zilver PTX) in Patients With Femoropopliteal Occlusive Disease a Single Center Experience.

BACKGROUND: Few industry sponsored trials reported satisfactory outcomes in the use of drug-eluting stents (DES) for treatment of femoropopliteal arterial disease. This study analyzed the early/late clinical outcome from a real world single center. PATIENT POPULATIONS/METHODS: A total of 115 limbs treated with Zilver PTX were analyzed for: major adverse limb event (MALE: above ankle limb amputation/major intervention at 1 year), major adverse events (MAEs; death, amputation, and target lesion thrombosis/reintervention), primary patency (based on duplex ultrasound ± ankle brachial indexes), limb salvage, and amputation free survival rates (AFS) at 1 and 2 years. RESULTS: Indications included claudication in 32% and critical limb threatening ischemia (CLTI) in 68%. Lesions treated included: superficial femoral artery (SFA) 66%, both SFA and popliteal artery (PA) 19% and PA 15%. Mean lesion length was 21 cm and 68% had total occlusion. 45% were Trans-Atlantic Inter-Society Consensus (TASC) TASC II D lesions and 55% A-C lesions. Mean follow-up was 18.4 months (1-76 months). Perioperative major morbidity rate was 8.7% with 0% mortality. MALE rate at 1 year was 17% (13.5% for claudication vs 19.2% for CLTI, p=0.4499). MAE rate was 30% for claudication versus 52% for CLTI (p=0.0392). Overall primary patency rates at 1 and 2 years were 75% and 54% (86% and 71% for claudication vs 70% and 46% for CLTI, respectively, p=0.0213). Primary patency rates at 1 and 2 years were 94% and 88% for TASC A-C lesions versus 50% and 16% for TASC D lesions (p<0.0001). Overall freedom from MALE rate at 1 and 2 years were 85% and 79% (86% and 86% for claudication vs 84% and 74% for CLTI, p=0.2391). These rates were 96% and 93% for TASC A-C lesions versus 70% and 50% for D lesions, respectively (p<0.0001). Limb salvage rates at 1 and 2 years were 93% and 86% (100% and 100% for claudication vs 89% and 78% for CLTI, p=0.012). Overall AFS rates at 1 and 2 years were 79% and 71% (93% and 82% for TASC A-C vs 59% and 59% for D lesions, p=0.001). CONCLUSION: Clinical outcomes after DES (Zilver PTX) in femoropopliteal arterial lesions were satisfactory for TASC A-C lesions but inferior/unsatisfactory for TASC D lesions.

Clinical outcome of drug-coated balloon angioplasty in patients with femoropopliteal disease: A real-world single-center experience.

BACKGROUND: Several multicenter industry-sponsored clinical trials reported satisfactory results in the use of drug-coated balloons (DCBs) for treatment of femoropopliteal occlusive disease. However, few single-center studies have been published to verify the outcome from real-world experience. METHODS: In this study, 228 patients treated with DCB angioplasty (Lutonix 0.35; Bard, Tempe, Arizona) were analyzed. Perioperative major adverse events (death, amputation, target lesion thrombosis or reintervention) were calculated. Kaplan-Meier analysis was used to estimate primary patency rates (based on duplex ultrasound with or without ankle-brachial index) and limb salvage rates. RESULTS: Lesions treated were primarily TransAtlantic Inter-Society Consensus (TASC) type C and D lesions. Indications included claudication (Rutherford classes 2 and 3) in 40% and critical limb ischemia (CLI; Rutherford classes 4 and 5) in 60%. Lesions treated included 61% in the superficial femoral artery, 15% in the popliteal artery, and 24% in both superficial femoral artery and popliteal artery. Mean follow-up was 12.2 months (range, 1-42 months). Overall perioperative morbidity and mortality rates were 13% and 1%. The perioperative major adverse event rate was 3%. Symptom relief (improvement of one Rutherford category or more) was obtained in 64%. Primary patency rates were 56% and 39% at 1 year and 2 years, respectively. Limb salvage rates were 92% and 83% at 1 year and 2 years. Patients with claudication had a lower rate of early perioperative complications (4% vs 19%; P = .001). Symptom improvement was 76% for claudication vs 49% for CLI (P < .001). Overall, major amputation rate was 0% for claudication vs 13% for CLI (P < .001). The primary patency rates at 1 year and 2 years were 59% and 41% for claudication vs 54% and 37% for CLI (P = .307). The assisted primary patency rates at 1 year and 2 years were 72% and 52% for claudication vs 64% and 46% for CLI (P = .223). Primary patency rates at 1 year and 2 years were 82% and 71% for TASC A to C lesions vs 29% and 14% for TASC D lesions (P < .001). Limb salvage rates at 1 year and 2 years were 100% and 100% for claudication vs 85% and 74% for CLI (P < .001). CONCLUSIONS: Clinical outcomes after DCB angioplasty in femoropopliteal lesions were inferior to what has been reported in previous studies, particularly for TASC D lesions. Further investigation from real-world experience with long-term follow-up is needed to confirm these results.

The incidence of carotid in-stent stenosis is underestimated ≥50% or ≥80% and its clinical implications.

BACKGROUND: The incidence of carotid in-stent stenosis has been reported to vary between 1% and 30%. Most published studies have short follow-up, which may lead to underestimation of the incidence of in-stent stenosis. This study analyzed the incidence of ≥50% and ≥80% in-stent stenosis using validated duplex ultrasound criteria and its clinical implications. METHODS: This is a retrospective analysis of prospectively collected data of 450 carotid artery stenting (CAS) procedures (February 6, 2001-December 19, 2016). All patients had postoperative carotid duplex ultrasound examination, which was repeated at 1 month, 6 months, and every 6 to 12 months thereafter. A Kaplan-Meier analysis was used to estimate rates of freedom from ≥50% in-stent stenosis (internal carotid artery peak systolic velocity of ≥224 cm/s) and ≥80% in-stent stenosis (internal carotid artery peak systolic velocity of ≥325 cm/s), freedom from reintervention, and survival. RESULTS: The mean age was 68.3 years, with a mean follow-up of 40.3 months. A total of 201 patients (45% [201/450]) had CAS for symptomatic disease. Primary CAS was done in 291 patients (65%); in the remaining 35%, CAS was done for postcarotid endarterectomy (CEA) stenosis. A total of 101 patients (23%) had ≥50% late carotid in-stent stenosis, and of these, 33 (7.4%) had ≥80% in-stent stenosis. Nineteen patients (4.3%) developed late transient ischemic attack and three (0.7%) late stroke. Twenty-three (5.2%) patients had late reintervention. Rates of freedom from ≥50% in-stent stenosis in the whole series were 85%, 79%, 75%, 72%, and 70% at 1 year, 2 years, 3 years, 4 years, and 5 years, respectively. The rates of freedom from ≥50% in-stent stenosis for primary CAS and CAS for post-CEA stenosis were not statistically significant (P = .540). The rates of freedom from ≥80% in-stent stenosis for the whole series were 96%, 95%, 93%, 90%, and 89% at 1 year, 2 years, 3 years, 4 years, and 5 years, respectively. The rates of freedom from ≥80% in-stent stenosis for primary CAS and CAS for post-CEA stenosis were also not statistically significant (P = .516). Rates of freedom from reintervention were 98%, 96%, 93%, 93%, and 91% at 1 year, 2 years, 3 years, 4 years, and 5 years, respectively, and there were no significant differences between primary CAS and CAS for post-CEA stenosis (P = .939). The overall late survival rates were 99%, 97%, 96%, 94%, and 91% at 1 year, 2 years, 3 years, 4 years, and 5 years. CONCLUSIONS: The incidence of ≥50% in-stent stenosis is relatively high; however, the rates of ≥80% stenosis and late neurologic events are low. Longer follow-up of patients with ≥50% carotid in-stent stenosis may yield higher incidence of ≥80% stenosis.

Exploring the Geospatial Relationship Between COVID-19 Positivity and Income in Mixed Urban-Rural Population.

The COVID-19 pandemic has had a deep influence on American life in general and on the American economy in particular. However, the burden of the pandemic has not been distributed equally among members of a population based on their social-determinants-of-health. The purpose of this study was to investigate whether the median income was associated with COVID-19 total number of tests and positivity rate in Boone County, Missouri during the pandemic. We analyzed the geospatial data using three heat maps showing the Census tract-wise COVID-19 positivity rate, Census tract-wise median income, and Census tract-wise total number of COVID-19 tests to highlight our study findings. Our study results support the hypothesis that individuals with lower median income tend to have a lower total number of COVID-19 tests and higher COVID-19 positivity rates in Boone County, Missouri. The Pearson correlation coefficient between the positivity rate and median income is -0.324.

Stepping Beyond Assessment: Fall Risk Prediction Models Among Older Adults from Cumulative Change in Gait Parameter Estimates.

Falls significantly affect the health of older adults. Injuries sustained through falls have long-term consequences on the ability to live independently and age in place, and are the leading cause of injury death in the United States for seniors. Early fall risk detection provides an important opportunity for prospective intervention by healthcare providers and home caregivers. In-home depth sensor technologies have been developed for real-time fall detection and gait parameter estimation including walking speed, the sixth vital sign, which has been shown to correlate with the risk of falling. This study evaluates the use of supervised classification for estimating fall risk from cumulative changes in gait parameter estimates as captured by 3D depth sensors placed within the homes of older adult participants. Using recall as the primary metric for model success rate due to the severity of fall injuries sustained by false negatives, we demonstrate an enhancement of assessing fall risk with univariate logistic regression using multivariate logistic regression, support vector, and hierarchical tree-based modeling techniques by an improvement of 18.80%, 31.78%, and 33.94%, respectively, in the 14 days preceding a fall event. Random forest and XGBoost models resulted in recall and precision scores of 0.805 compared to the best univariate regression model of Y-Entropy with a recall of 0.639 and precision of 0.527 for the 14-day window leading to a predicted fall event.

Demographic and Time Trend Analysis of COVID-19 Test Results of Boone County, Missouri.

The COVID-19 pandemic has had deep influence on American life. However, the burden of the pandemic has not been distributed equally among members of a population based on their demographic features. The purpose of this study was to investigate whether sex, age, race, and religion were associated with COVID-19 positivity rates in Boone County, Missouri over a 22-month period (March 15, 2020 to December 2, 2021) of the pandemic. We analyzed the data using age distribution histograms, two-way delta tables, and trend analysis graphs to highlight our study findings. We evaluated those graphs with each demographic feature across a collection of defined epochs of key events, such as vaccine release, Delta variant, vaccine boosters, and initial Omicron variant. Our results supported the hypothesis that males and minority races such as Black or African Americans and All-Other are more likely to have a higher COVID-19 positivity rate across our defined epochs.

The Role of Remote Sensing and Geospatial Analysis for Understanding COVID-19 Population Severity: A Systematic Review.

Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.

HTIDB: Hierarchical Time-Indexed Database for Efficient Storage and Access to Irregular Time-series Health Sensor Data.

With the enormous amount of data collected by unobtrusive sensors, the potential of utilizing these data and applying various multi-modal advanced analytics on them is numerous and promising. However, taking advantage of the ever-growing data requires high-performance data-handling systems to enable high data scalability and easy data accessibility. This paper demonstrates robust design, developments, and techniques of a hierarchical time-indexed database for decision support systems leveraging irregular and sporadic time series data from sensor systems, e.g., wearables or environmental. We propose a technique that leverages the flexibility of general purpose, high-scalability database systems, while integrating data analytics focused column stores that leverage hierarchical time indexing, compression, and dense raw numeric data storage. We have evaluated the performance characteristics and tradeoffs of each to understand the data access latencies and storage requirements, which are key elements for capacity planning for scalable systems.

The immunoregulatory enzyme IDO paradoxically drives B cell-mediated autoimmunity.

Rheumatoid arthritis (RA) is a chronic and debilitating inflammatory autoimmune disease of unknown etiology. As with a variety of autoimmune disorders, evidence of elevated tryptophan catabolism has been detected in RA patients indicative of activation of the immunomodulatory enzyme IDO. However, the role that IDO plays in the disease process is not well understood. The conceptualization that IDO acts solely to suppress effector T cell activation has led to the general assumption that inhibition of IDO activity should exacerbate autoimmune disorders. Recent results in cancer models, however, suggest a more complex role for IDO as an integral component of the inflammatory microenvironment necessary for supporting tumor outgrowth. This has led us to investigate the involvement of IDO in the pathological inflammation associated with RA. Using the K/BxN murine RA model and IDO inhibitor 1-methyl-tryptophan, we found that inhibiting IDO activity had the unexpected consequence of ameliorating, rather than exacerbating arthritis symptoms. 1-Methyl tryptophan treatment led to decreased autoantibody titers, reduced levels of inflammatory cytokines, and an attenuated disease course. This alleviation of arthritis was not due to an altered T cell response, but rather resulted from a diminished autoreactive B cell response, thus demonstrating a previously unappreciated role for IDO in stimulating B cell responses. Our findings raise the question of how an immunosuppressive enzyme can paradoxically drive autoimmunity. We suggest that IDO is not simply immunosuppressive, but rather plays a more complex role in modulating inflammatory responses, in particular those that are driven by autoreactive B cells.

Leveraging Unsupervised Machine Learning to Discover Patterns in Linguistic Health Summaries for Eldercare.

The Center for Eldercare and Rehabilitation Technology, at University of Missouri, has researched the use of smart, unobtrusive sensors for older adult residents' health monitoring and alerting in aging-in-place communities for many years. Sensors placed in the apartments of older adult residents generate a deluge of daily data that is automatically aggregated, analyzed, and summarized to aid in health awareness, clinical care, and research for healthy aging. When anomalies or concerning trends are detected within the data, the sensor information is converted into linguistic health messages using fuzzy computational techniques, so as to make it understandable to the clinicians. Sensor data are analyzed at the individual level, therefore, through this study we aim to discover various combinations of patterns of anomalies happening together and recurrently in the older adult's population using these text summaries. Leveraging various computational text data processing techniques, we are able to extract relevant analytical features from the health messages. These features are transformed into a transactional encoding, then processed with frequent pattern mining techniques for association rule discovery. At individual level analysis, resident ID 3027 was considered as an exemplar to describe the analysis. Seven combinations of anomalies/rules/associations were discovered in this resident, out of which rule group three showed an increased recurrence during the COVID lockdown of facility. At the population level, a total of 38 associations were discovered that highlight the health patterns, and we continue to explore the health conditions associated with them. Ultimately, our goal is to correlate the combinations of anomalies with certain health conditions, which can then be leveraged for predictive analytics and preventative care. This will improve the current clinical care systems for older adult residents in smart sensor, aging-in-place communities.

Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks.

While most deep learning architectures are built on convolution, alternative foundations such as morphology are being explored for purposes such as interpretability and its connection to the analysis and processing of geometric structures. The morphological hit-or-miss operation has the advantage that it considers both foreground information and background information when evaluating the target shape in an image. In this article, we identify limitations in the existing hit-or-miss neural definitions and formulate an optimization problem to learn the transform relative to deeper architectures. To this end, we model the semantically important condition that the intersection of the hit and miss structuring elements (SEs) should be empty and present a way to express Don't Care (DNC), which is important for denoting regions of an SE that are not relevant to detecting a target pattern. Our analysis shows that convolution, in fact, acts like a hit-to-miss transform through semantic interpretation of its filter differences. On these premises, we introduce an extension that outperforms conventional convolution on benchmark data. Quantitative experiments are provided on synthetic and benchmark data, showing that the direct encoding hit-or-miss transform provides better interpretability on learned shapes consistent with objects, whereas our morphologically inspired generalized convolution yields higher classification accuracy. Finally, qualitative hit and miss filter visualizations are provided relative to single morphological layer.

GeoIRIS: Geospatial Information Retrieval and Indexing System-Content Mining, Semantics Modeling, and Complex Queries.

Searching for relevant knowledge across heterogeneous geospatial databases requires an extensive knowledge of the semantic meaning of images, a keen eye for visual patterns, and efficient strategies for collecting and analyzing data with minimal human intervention. In this paper, we present our recently developed content-based multimodal Geospatial Information Retrieval and Indexing System (GeoIRIS) which includes automatic feature extraction, visual content mining from large-scale image databases, and high-dimensional database indexing for fast retrieval. Using these underpinnings, we have developed techniques for complex queries that merge information from heterogeneous geospatial databases, retrievals of objects based on shape and visual characteristics, analysis of multiobject relationships for the retrieval of objects in specific spatial configurations, and semantic models to link low-level image features with high-level visual descriptors. GeoIRIS brings this diverse set of technologies together into a coherent system with an aim of allowing image analysts to more rapidly identify relevant imagery. GeoIRIS is able to answer analysts' questions in seconds, such as "given a query image, show me database satellite images that have similar objects and spatial relationship that are within a certain radius of a landmark."

Knowledge-driven multidimensional indexing structure for biomedical media database retrieval.

Today, biomedical media data are being generated at rates unimaginable only years ago. Content-based retrieval of biomedical media from large databases is becoming increasingly important to clinical, research, and educational communities. In this paper, we present the recently developed entropy balanced statistical (EBS) k-d tree and its applications to biomedical media, including a high-resolution computed tomography (HRCT) lung image database and the first real-time protein tertiary structure search engine. Our index utilizes statistical properties inherent in large-scale biomedical media databases for efficient and accurate searches. By applying concepts from pattern recognition and information theory, the EBS k-d tree is built through top-down decision tree induction. Experimentation shows similarity searches against a protein structure database of 53 363 structures consistently execute in less than 8.14 ms for the top 100 most similar structures. Additionally, we have shown improved retrieval precision over adaptive and statistical k-d trees. Retrieval precision of the EBS k-d tree is 81.6% for content-based retrieval of HRCT lung images and 94.9% at 10% recall for protein structure similarity search. The EBS k-d tree has enormous potential for use in biomedical applications embedded with ground-truth knowledge and multidimensional signatures.

Use of Online Health Information by Geriatric and Adult Emergency Department Patients: Access, Understanding, and Trust.

OBJECTIVE: The objective was to characterize geriatric patients' use of online health information (OHI) relative to younger adults and assess their comfort ith OHI compared to health information (HI) from their physician. METHODS: This was a prospective cross-sectional survey study of adult emergency department (ED) patients. The survey assessed patients' self-reported use of OHI in the past year and immediately prior to ED visit and analyzed differences across four age groups: 18-39, 40-64, 65-74, and 75+. Patients' ability to access, understand, and trust OHI was assessed using a 7-point Likert scale and compared to parallel questions regarding HI obtained from their doctor. Patient use of OHI was compared across age groups. Comfort with OHI and HI obtained from a doctor was compared across age groups using the Kruskal-Wallis test. Comparisons between sources of HI were made within age groups using the Wilcoxon signed-rank test. RESULTS: Of 889 patients who were approached for study inclusion, 723 patients (81.3%) completed the survey. The majority of patients had used OHI in the past year in all age groups, but older patients were less likely to have used OHI: age 18-39, 90.3%; 40-64, 85.3%; 65-74, 76.4%; and 75+, 50.7% (p < 0.001). The youngest patients were most likely to have used OHI prior to coming to the ED, 47.1%, 28.3%, 17.1%, and 8.0% (p < 0.001). Older patients were more likely to have an established doctor-18-39, 79.4%; 40-64, 91.1%; 65-74, 97.5%; and 75+ 97.4% (p < 0.001)-and were more likely to have contacted their doctor prior to their ED visit: 36.7, 40.2, 46.7, and 53.5% (p = 0.02). The oldest patients were most likely to find HI more accessible from their doctor than the Internet, while the youngest patients found HI more accessible on the Internet than from their doctor. Regardless of age, patients noted that information from their physician was both easier to understand and more trustworthy than information found on the Internet. CONCLUSION: Although many older patients used OHI, they were less likely than younger adults to use the Internet immediately prior to an ED visit. Despite often using OHI, patients of all age groups found healthcare information from their doctor easier to understand and more trustworthy than information from the Internet. As health systems work to efficiently provide information to patients, addressing these perceived deficiencies may be necessary to build effective OHI programs.

What Did You Google? Describing Online Health Information Search Patterns of ED patients and Their Relationship with Final Diagnoses.

INTRODUCTION: Emergency department (ED) patients' Internet search terms prior to arrival have not been well characterized. The objective of this analysis was to characterize the Internet search terms patients used prior to ED arrival and their relationship to final diagnoses. METHODS: We collected data via survey; participants listed Internet search terms used. Terms were classified into categories: symptom, specific diagnosis, treatment options, anatomy questions, processes of care/physicians, or "other." We categorized each discharge diagnosis as either symptom-based or formal diagnosis. The relationship between the search term and final diagnosis was assigned to one of four categories of search/diagnosis combinations (symptom search/symptom diagnosis, symptom search/formal diagnosis, diagnosis search/symptom diagnosis, diagnosis search/formal diagnosis), representing different "trajectories." RESULTS: We approached 889 patients; 723 (81.3%) participated. Of these, 177 (24.5%) used the Internet prior to ED presentation; however, seven had incomplete data (N=170). Mean age was 47 years (standard deviation 18.2); 58.6% were female and 65.7% white. We found that 61.7% searched symptoms and 40.6% searched a specific diagnosis. Most patients received discharge diagnoses of equal specificity as their search terms (34% flat trajectory-symptoms and 34% flat trajectory-diagnosis). Ten percent searched for a diagnosis by name but received a symptom-based discharge diagnosis with less specificity. In contrast, 22% searched for a symptom and received a detailed diagnosis. Among those who searched for a diagnosis by name (n=69) only 29% received the diagnosis that they had searched. CONCLUSION: The majority of patients used symptoms as the basis of their pre-ED presentation Internet search. When patients did search for specific diagnoses, only a minority searched for the diagnosis they eventually received.

ProteinDBS: a real-time retrieval system for protein structure comparison.

We have developed a web server (ProteinDBS) for the life science community to search for similar protein tertiary structures in real time. This system applies computer visualization techniques to extract the predominant visual patterns encoded in two-dimensional distance matrices generated from the three-dimensional coordinates of protein chains. When meaningful contents, represented in a multi-dimensional feature space, have been extracted from distance matrices, an advanced indexing structure, Entropy Balanced Statistical (EBS) k-d tree, is utilized to index the data. Our system is able to return search results in ranked order from a database with 46 075 chains in seconds, exhibiting a reasonably high degree of precision. To our knowledge, this is the first real-time search engine for protein structure comparison. ProteinDBS provides two types of query method: query by Protein Data Bank protein chain ID and by new structures uploaded by users. The system is hosted at http://ProteinDBS.rnet.missouri.edu.

Arthroscopic findings in horses with subtle radiographic evidence of osteochondral lesions of the medial femoral condyle: 15 cases (1995-2002).

OBJECTIVE: To determine arthroscopic findings in lame horses with subtle radiographic lesions of the medial femoral condyle. DESIGN: Retrospective study. ANIMALS: 15 horses examined because of lameness that had subtle radiographic evidence of osteochondral lesions involving the medial femoral condyle in at least 1 joint. PROCEDURE: Medical records were reviewed, and results of physical examination, radiography, and arthroscopy were recorded. Follow-up information was obtained through reexamination of the horses or telephone conversations with the referring veterinarians, owners, or trainers. RESULTS: Lameness severity ranged from grade 1 to 3 on a scale from 0 to 5. Radiography and arthroscopy were performed on 28 stifle joints. The 4 unaffected joints in 4 horses with unilateral hind limb lameness that underwent bilateral arthroscopy had no radiographic lesions, but 2 of the 4 had arthroscopic lesions. Of the remaining 24 joints, 20 had radiographic evidence of flattening of the apex of the medial femoral condyle and 4 had minimal subchondral lucency. Lesions were identified arthroscopically in 18 of the 20 joints with flattening of the condyle and in all 4 joints with subchondral lucency. Treatment consisted of abrasion arthroplasty or microfracture. Seven of the 9 horses with focal cartilage lesions and 2 of the 6 horses with generalized cartilage lesions were reportedly sound without any evidence of joint effusion at the time of final follow-up. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that horses with hind limb lameness and subtle radiographic lesions of the medial femoral condyle are likely to have arthroscopically apparent cartilage lesions and subchondral bone defects.

Immature CD4+CD8+ thymocytes and mature T cells regulate Nur77 distinctly in response to TCR stimulation.

The orphan steroid receptor, Nur77, is thought to be a central participant in events leading to TCR-mediated clonal deletion of immature thymocytes. Interestingly, although both immature and mature murine T cell populations rapidly up-regulate Nur77 after TCR stimulation, immature CD4+CD8+ thymocytes respond by undergoing apoptosis, whereas their mature descendants respond by dividing. To understand these developmental differences in susceptibility to the proapoptotic potential of Nur77, we compared its regulation and compartmentalization and show that mature, but not immature, T cells hyperphosphorylate Nur77 in response to TCR signals. Nur77 resides in the nucleus of immature CD4+CD8+ thymocytes throughout the course of its expression and is not found in either the organellar or cytoplasmic fractions. However, hyperphosphorylation of Nur77 in mature T cells, which is mediated by both the MAPK and PI3K/Akt pathways, shifts its localization from the nucleus to the cytoplasm. The failure of immature CD4+CD8+ thymocytes to hyperphosphorylate Nur77 in response to TCR stimulation may be due in part to decreased Akt activity at this developmental stage.