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Objectives: To determine whether a program that eliminated pharmacy co-pays, the Blue Cross Blue Shield of Louisiana (BCBSLA) Zero Dollar Co-pay (ZDC) program, decreased health care spending. Previous studies have found that value-based insurance designs like the ZDC program have little or no impact on total health care spending. ZDC included an expansive set of medications related to 4 chronic diseases rather than a limited set of medications for 1 or 2 chronic diseases. Additionally, ZDC focused on the most at-risk patients., Study Design: ZDC began in 2014 and enrolled patients over time based on (1) when a patient answered a call from a nurse care manager and (2) when a patient or their employer changed the benefit structure to meet the program criteria. During 2015 and 2016, 265 patients with at least 1 chronic condition (asthma, diabetes, hypertension, mental illness) enrolled in ZDC., Methods: Observational study using within-patient variation and variation in patient enrollment month to identify the impact of the ZDC program on health spending measures. We used 100% BCBSLA claims data from January 2015 to June 2018. Monthly level event studies were used to test for differential spending patterns prior to ZDC enrollment., Results: We found that total spending decreased by $205.9 (P = .049) per member per month, or approximately 18%. We saw a decrease in medical spending ($195.0; P = .023) but did not detect a change in pharmacy spending ($7.59; P = .752). We found no evidence of changes in spending patterns prior to ZDC enrollment., Conclusions: The ZDC program provides evidence that value-based insurance designs that incorporate a comprehensive set of medications and focus on populations with chronic disease can reduce spending.

The aim of this study was to evaluate the effect of mineral trioxide aggregate (MTA) and Brazilian propolis on the cell viability, mineralization, anti-inflammatory ability, and migration of human dental pulp cells (hDPCs). The cell viability was evaluated with CCK-8 kit after 1, 5, 7, and 9 days. The deposition of calcified matrix and the expression of osteogenesis-related genes were evaluated by Alizarin Red staining and real-time PCR after incubation in osteogenic medium for 21 days. The expression of inflammation-related genes in cells was determined after exposure to 1 μg/mL LPS for 3 h. Finally, the numbers of cells that migrated through the permeable membranes were compared during 15 h. Propolis and MTA significantly increased the viability of hDPCscompared to the control group on days 7 and 9. In the propolis group, significant enhancement of osteogenic potential and suppressed expression of IL-1β and IL-6 was observed after LPS exposure compared to the MTA and control groups. The number of migration cells in the propolis group was similar to that of the control group, while MTA significantly promoted cell migration. Propolis showed comparable cell viability to that of MTA and exhibited significantly higher anti-inflammatory and mineralization promotion effects on hDPCs.

Stimulated by thromboxane A 2 , an endogenous arachidonic acid metabolite, the thromboxane A 2 receptor (TP) plays a pivotal role in cardiovascular homeostasis, and thus is considered as an important drug target for cardiovascular disease. Here, we report crystal structures of the human TP bound to two nonprostanoid antagonists, ramatroban and daltroban, at 2.5 Å and 3.0 Å resolution, respectively. The TP structures reveal a ligand-binding pocket capped by two layers of extracellular loops that are stabilized by two disulfide bonds, limiting ligand access from the extracellular milieu. These structures provide details of interactions between the receptor and antagonists, which help to integrate previous mutagenesis and SAR data. Molecular docking of prostanoid-like ligands, combined with mutagenesis, ligand-binding and functional assays, suggests a prostanoid binding mode that may also be adopted by other prostanoid receptors. These insights into TP deepen our understanding about ligand recognition and selectivity mechanisms of this physiologically important receptor.

While polysaccharide-based nanocarriers have been recognized for their crucial roles in tumor theranostics, the industrial-scale production of nanotherapeutics still remains a significant challenge. Most current approaches adopt a postpolymerization self-assembly strategy that follows a separate synthetic step and thus suffers from subgram scale yields and a limited range of application. In this study, we demonstrate the kilogram-scale formation of polysaccharide-polyacrylate nanocarriers at concentrations of up to 5 wt% through a one-pot approach - starting from various acrylate monomers and polysaccharides - that combines aspects of hydrophobicity-induced self-assembly with the free radical graft copolymerization of acrylate monomers from polysaccharide backbones into a single process that is thus denoted as a graft copolymerization induced self-assembly. We also demonstrate that this novel approach is applicable to a broad range of polysaccharides and acrylates. Notably, by choosing a crosslinker that bears a disulfide group and two vinyl capping groups to structurally lock the nanocarriers, the products are rendered cleavable in the reducing environments encountered at tumor sites and thus provide ideal candidates for the construction of anticancer nanotherapeutic systems. In vitro and in vivo studies demonstrated that the use of this nanocarrier for the delivery of doxorubicin hydrochloride (DOX) significantly decreased the side effects of DOX and improved the bio-safety of the chemotherapy accordingly., Statement of Significance: While polysaccharide-based nanocarriers have been recognized for their crucial roles in tumor theranostics, the industrial-scale production of these nanotherapeutics still remains a significant challenge. Most current approaches adopt a post-polymerization self-assembly strategy which that follows a separate synthetic step, and thus suffers from sub-gram scale yields and a limited range of application. In this study, the hydrophobic effect was combined with free radical polymerization to facilitate the graft copolymerization-induced self-assembly (GISA) of acrylate monomers with various hydrophobicities to construct cleavable polysaccharide-polyacrylate nanocarriers at a high efficiency with excellent potential for industrial-scale production. We envision that these nanocarriers will contribute to the development of tumor nanotheranostics that combine the biological functionalities of polysaccharides with the unmatched application-specific flexibility of nanocarriers., (Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.)

Objectives: This study aimed to investigate the role of the Quality Blue Primary Care (QBPC) program on healthcare utilization and overall cost among the beneficiaries of Blue Cross and Blue Shield of Louisiana (BCBSLA)., Study Design: Retrospective observational cohort study using claims data from adults residing in QBPC-implemented regions continuously enrolled through BCBSLA from June 2012 to December 2014 (N = 89,034)., Methods: Controlling for age, gender, and risk score by propensity score weighting, inpatient, outpatient, and corresponding medical expenditures were each compared between the QBPC group and the control group using a difference-in-differences regression model., Results: Average total cost increased in both the QBPC and control groups in 2014, but the increase was significantly less in the intervention group-a difference of $27.09 per member per month (PMPM) (P ≤.001). Savings in total cost were derived largely from a decrease in hospitalizations-a difference of $18.85 PMPM (P = .0023). Furthermore, savings were associated with shifts in healthcare utilization by the intervention group toward proactive management, including increased primary care physician visits (P = .0106) and higher screening rates for diabetes (P = .0019). Inpatient admissions also decreased in the QBPC group, most significantly among those with chronic conditions (P <.05). Conversely, an unexpected increase was observed in emergency department visits., Conclusions: The QBPC program was associated with a shift in primary care delivery and reductions in overall cost. Savings were achieved largely through reductions in hospitalization costs.

Aims: We aimed to examine the association of gestational hypertension and chronic hypertension at the inter-conception examination with type 2 diabetes risk among women with a history of gestational diabetes., Methods: We conducted a population-based study among 1261 women who had a history of gestational diabetes at 1-5years after delivery in Tianjin, China. Logistic regression or Cox regression was used to assess the associations of gestational hypertension and chronic hypertension at the inter-conception examination with pre-diabetes and type 2 diabetes risks., Results: Gestational diabetic women who had a history of gestational hypertension but did not use antihypertensive drugs during pregnancy had a 3.94-fold higher risk (95% CI: 1.94-8.02) of developing type 2 diabetes compared with those who were normotensive in index pregnancy. Compared with gestational diabetic women who had normal blood pressure at the inter-conception examination, hypertensive women at the inter-conception examination were 3.38 times (95% CI: 1.66-6.87) and 2.97 times (95% CI: 1.75-5.05) more likely to develop diabetes and prediabetes, respectively. The odds ratios of type 2 diabetes and prediabetes associated with each 5mmHg increase in systolic blood pressure were 1.25 (95% CI: 1.03-1.51) and 1.20 (95% CI: 1.06-1.35). Each 5mmHg increase in diastolic blood pressure contributed to a 1.49-fold higher risk (95% CI: 1.18-1.88) for type 2 diabetes and a 1.42-fold higher risk (95% CI: 1.22-1.65) for prediabetes., Conclusions: For women with prior gestational diabetes, gestational hypertension and chronic hypertension at the inter-conception examination were risk factors for type 2 diabetes., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Heme is an essential prosthetic group in proteins that reside in virtually every subcellular compartment performing diverse biological functions. Irrespective of whether heme is synthesized in the mitochondria or imported from the environment, this hydrophobic and potentially toxic metalloporphyrin has to be trafficked across membrane barriers, a concept heretofore poorly understood. Here we show, using subcellular-targeted, genetically encoded hemoprotein peroxidase reporters, that both extracellular and endogenous heme contribute to cellular labile heme and that extracellular heme can be transported and used in toto by hemoproteins in all six subcellular compartments examined. The reporters are robust, show large signal-to-background ratio, and provide sufficient range to detect changes in intracellular labile heme. Restoration of reporter activity by heme is organelle-specific, with the Golgi and endoplasmic reticulum being important sites for both exogenous and endogenous heme trafficking. Expression of peroxidase reporters in Caenorhabditis elegans shows that environmental heme influences labile heme in a tissue-dependent manner; reporter activity in the intestine shows a linear increase compared with muscle or hypodermis, with the lowest heme threshold in neurons. Our results demonstrate that the trafficking pathways for exogenous and endogenous heme are distinct, with intrinsic preference for specific subcellular compartments. We anticipate our results will serve as a heuristic paradigm for more sophisticated studies on heme trafficking in cellular and whole-animal models., Competing Interests: I.H. is the president and founder of Rakta Therapeutics Inc. (College Park, MD), a company involved in the development of heme transporter-related diagnostics. I.H. declares no other competing financial interests.

Heme is an essential cofactor and signaling molecule. Heme acquisition by proteins and heme signaling are ultimately reliant on the ability to mobilize labile heme (LH). However, the properties of LH pools, including concentration, oxidation state, distribution, speciation, and dynamics, are poorly understood. Herein, we elucidate the nature and dynamics of LH using genetically encoded ratiometric fluorescent heme sensors in the unicellular eukaryote Saccharomyces cerevisiae We find that the subcellular distribution of LH is heterogeneous; the cytosol maintains LH at ∼20-40 nM, whereas the mitochondria and nucleus maintain it at concentrations below 2.5 nM. Further, we find that the signaling molecule nitric oxide can initiate the rapid mobilization of heme in the cytosol and nucleus from certain thiol-containing factors. We also find that the glycolytic enzyme glyceraldehyde phosphate dehydrogenase constitutes a major cellular heme buffer, and is responsible for maintaining the activity of the heme-dependent nuclear transcription factor heme activator protein (Hap1p). Altogether, we demonstrate that the heme sensors can be used to reveal fundamental aspects of heme trafficking and dynamics and can be used across multiple organisms, including Escherichia coli, yeast, and human cell lines.

Background: Self-reported diabetes has been found to be valid to evaluate people's diabetes status in the population of several countries. However, no such study has been conducted to assess the validity of self-reported diabetes in the Chinese population, the largest population with the highest rate of diabetes. The aim of our study is to evaluate the validity of self-reported diabetes among the middle-aged and older Chinese population., Methods: Data from 11 601 participants, aged ≥45, of the China Health and Retirement Longitudinal Study (CHARLS) during 2011-2012, were analysed. Prevalent self-reported diabetes was compared with reference definition defined by fasting glucose, glycated haemoglobin and medication use. Sensitivity, specificity, positive predicted value, negative predicted value and κ value were calculated overall, by 5-year age groups, by education levels and by living areas., Results: The sensitivity of prevalent self-reported diabetes was 41.5%, and the specificity was 98.6%. The sensitivity of self-reported diabetes increased with education levels, and was much higher among urban residents than rural residents (58.2% vs 35.0%). The specificity was above 98% among all age groups, in different education levels, and in rural and urban areas. Self-reported diabetes had substantial agreement with reference definition among participants with above vocational school education or those living in urban areas (κ=0.658 and 0.646, respectively)., Conclusions: Although the sensitivity of self-reported diabetes was poor among middle-aged and older Chinese adults, the specificity and positive predictive values were fairly good. Furthermore, self-reported diabetes performed well among those with more than vocational school educations or those living in urban areas., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Smartphones of the latest generation featuring advanced multicore processors, dedicated microchips for graphics, high-resolution cameras, and innovative operating systems provide a portable platform for running sophisticated medical screening software and delivering point-of-care patient diagnostic services at a very low cost. In this chapter, we present a smartphone digital dermoscopy application that can analyze high-resolution images of skin lesions and provide the user with feedback about the likelihood of malignancy. The same basic procedure has been adapted to evaluate other skin lesions, such as the flesh-eating bacterial disease known as Buruli ulcer. When implemented on the iPhone, the accuracy and speed achieved by this application are comparable to that of a desktop computer, demonstrating that smartphone applications can combine portability and low cost with high performance. Thus, smartphone-based systems can be used as assistive devices by primary care physicians during routine office visits, and they can have a significant impact in underserved areas and in developing countries, where health-care infrastructure is limited.

In humans, systemic heme homeostasis is achieved via coordinated regulation of heme synthesis, transport and degradation. Although the heme biosynthesis and degradation pathways have been well characterized, the pathways for heme trafficking and incorporation into hemoproteins remain poorly understood. In the past few years, researchers have exploited genetic, cellular and biochemical tools, to identify heme transporters and, in the process, reveal unexpected functions for this elusive group of proteins. However, given the complexity of heme trafficking pathways, current knowledge of heme transporters is fragmented and sometimes contradictory. This review seeks to focus on recent studies on heme transporters with specific emphasis on their functions during erythropoiesis., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Salvianolic acid A (Sal A) is an effective compound extracted from Salvia miltiorrhiza which has been used in the treatment of various diseases. Preliminary data indicate that Sal A treatment has a specific anti-lung cancer effect. However, the manner in which Sal A regulates cancer growth remains unknown. In this study, the A549 lung cancer cell line and its response to Sal A treatment was examined. Results showed that Sal A treatment significantly decreased A549 cell growth, promoted partial apoptosis and increased mitochondrial membrane permeability. Western blot analysis showed that Sal A upregulated the phosphatase and tensin homolog (PTEN) protein level, while consistently downregulating Akt phosphorylation. These results indicate that Sal A negatively mediates A549 lung cancer cell line growth or apoptosis, most likely by positively regulating PTEN protein level.

Adult humans have about 25 trillion red blood cells (RBCs), and each second we recycle about 5 million RBCs by erythrophagocytosis (EP) in macrophages of the reticuloendothelial system. Despite the central role for EP in mammalian iron metabolism, the molecules and pathways responsible for heme trafficking during EP remain unknown. Here, we show that the mammalian homolog of HRG1, a transmembrane heme permease in C. elegans, is essential for macrophage iron homeostasis and transports heme from the phagolysosome to the cytoplasm during EP. HRG1 is strongly expressed in macrophages of the reticuloendothelial system and specifically localizes to the phagolysosomal membranes during EP. Depletion of Hrg1 in mouse macrophages causes attenuation of heme transport from the phagolysosomal compartment. Importantly, missense polymorphisms in human HRG1 are defective in heme transport. Our results reveal HRG1 as the long-sought heme transporter for heme-iron recycling in macrophages and suggest that genetic variations in HRG1 could be modifiers of human iron metabolism., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Caenorhabditis elegans and human HRG-1-related proteins are conserved, membrane-bound permeases that bind and translocate heme in metazoan cells via a currently uncharacterized mechanism. Here, we show that cellular import of heme by HRG-1-related proteins from worms and humans requires strategically located amino acids that are topologically conserved across species. We exploit a heme synthesis-defective Saccharomyces cerevisiae mutant to model the heme auxotrophy of C. elegans and demonstrate that, under heme-deplete conditions, the endosomal CeHRG-1 requires both a specific histidine in the predicted second transmembrane domain (TMD2) and the FARKY motif in the C terminus tail for heme transport. By contrast, the plasma membrane CeHRG-4 transports heme by utilizing a histidine in the exoplasmic (E2) loop and the FARKY motif. Optimal activity under heme-limiting conditions, however, requires histidine in the E2 loop of CeHRG-1 and tyrosine in TMD2 of CeHRG-4. An analogous system exists in humans, because mutation of the synonymous histidine in TMD2 of hHRG-1 eliminates heme transport activity, implying an evolutionary conserved heme transport mechanism that predates vertebrate origins. Our results support a model in which heme is translocated across membranes facilitated by conserved amino acids positioned on the exoplasmic, cytoplasmic, and transmembrane regions of HRG-1-related proteins. These findings may provide a framework for understanding the structural basis of heme transport in eukaryotes and human parasites, which rely on host heme for survival.

Among the most critical components of a computerized system for automated melanoma detection is image sampling and pooling of the extracted features. In this paper, we propose a new method for sampling and pooling based on a combination of spatial pooling and graph theory features. The performance of the new method is evaluated using a dataset of more than 1,500 images representing pigmented skin lesions of known pathology. In our comparisons, we include several methods ranging from simple and multi-scale sampling on a regular grid to more sophisticated approaches, such as blob and curvilinear structure detectors. Our results show that, despite its simplicity, simple sampling on a regular grid provides highly competitive performance, compared to the more sophisticated approaches, while multi-scale sampling yields only trivial improvements. However, the proposed method provides significant performance improvement in terms of sensitivity and area under the receiver operating characteristic curve (95% t-test), and the best performance in terms of specificity compared to all other methods explored.

We have developed a portable library for automated detection of melanoma termed SkinScan© that can be used on smartphones and other handheld devices. Compared to desktop computers, embedded processors have limited processing speed, memory, and power, but they have the advantage of portability and low cost. In this study we explored the feasibility of running a sophisticated application for automated skin cancer detection on an Apple iPhone 4. Our results demonstrate that the proposed library with the advanced image processing and analysis algorithms has excellent performance on handheld and desktop computers. Therefore, deployment of smartphones as screening devices for skin cancer and other skin diseases can have a significant impact on health care delivery in underserved and remote areas.

In typical classification problems, high level concept features provided by a domain expert are usually available during classifier training but not during its deployment. We address this problem from a multitask learning (MTL) perspective by treating these features as auxiliary learning tasks. Previous efforts in MTL have mostly assumed that all tasks have the same input space. However, auxiliary tasks can have different input spaces, since their learning targets are different. Thus, to handle cases with heterogeneous input, in this paper we present a newly developed model using heterogeneous auxiliary tasks to help main task learning. First, we formulate a convex optimization problem for the proposed model, and then, we analyze its hypothesis class and derive true risk bounds. Finally, we compare the proposed model with other relevant methods when applied to the problem of skin cancer screening and public datasets. Our results show that the performance of the proposed method is highly competitive compared to other relevant methods.

In this paper we implement the 7-point checklist, a set of dermoscopic criteria widely used by clinicians for melanoma detection, on smart handheld devices, such as the Apple iPhone and iPad. The application developed is using sophisticated image processing and pattern recognition algorithms, yet it is light enough to run on a handheld device with limited memory and computational speed. When combined with a commercially available handheld dermoscope that provides proper lesion illumination, this application provides a truly self-contained handheld system for melanoma detection. Such a device can be used in a clinical setting for routine skin screening, or as an assistive diagnostic device in underserved areas and in developing countries with limited healthcare infrastructure.

Early skin cancer detection with the help of dermoscopic images is becoming more and more important. Previous methods generally ignored the spatial relation of the pixels or regions inside the lesion. We propose to employ a graph representation of the skin lesion to model the spatial relation. We then use the graph walk kernel, a similarity measure between two graphs, to build a classifier based on support vector machines for melanoma detection. In experiments, we compare the sensitivities and specificities of models with and without spatial information. Experimental results show that the model with spatial information performs the best in both sensitivity and specificity. Statistical test indicates that the improvement is significant.

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Genetic screens for Drosophila mutants defective in pavlovian olfactory memory have provided unique insight into the molecular basis of memory storage. Occasionally, these singular genetic lesions have been assembled into meaningful molecular pathways and neural circuitries. For the most part, however, these genes and their expression patterns in the CNS remain fragmented, demanding new clues from continued mutant screens. From a behavioral screen for long-term memory (LTM) mutants, we have identified ben (CG32594), which encodes a novel protein. Mutations of ben specifically disrupt LTM, leaving earlier memory phases intact. The role of ben appears physiological rather than developmental, because acutely induced expression of a ben(+) transgene in adults rescues the mutant's LTM defect. More interestingly, induced expression of ben(+) specifically in mushroom bodies (MBs), but not in the ellipsoid body of the central complex, is sufficient to rescue the mutant LTM defect. This suggests a role for ben in the MB during olfactory memory formation. We also provide evidence that BEN interacts genetically in both synaptic transmission and LTM formation with SCAMP, a synaptic protein known to be involved in vesicle recycling.

The escalation of American health care costs compels a new approach to manage chronic diseases. Wireless sensor networks (WSN) have been applied successfully in remote monitoring in military, aerospace, civil structure, and healthcare. However, existing wireless network framework cannot provide required quality of service (QoS) due to communication device failure, message loss caused by link error, collision, and hidden terminal for personalized disease management applications. In this paper, we present scalable network architecture and an operating mechanism that tolerates network structure changes caused by failure, with the application level data aggregation algorithm able to heal from the failure. We provide close form solutions that can achieve optimized network delay. Performance analysis was done to evaluate the significance of different nodes' failure in both homogeneous and heterogeneous sensor network and the effects of sensing and communication speed on failure impact in heterogeneous sensor networks.

A number of revolutionary techniques have been developed for cardiac electrophysiology research to better study the various arrhythmia mechanisms that can enhance ablating strategies for cardiac arrhythmias. Once the three-dimensional high resolution cardiac optical imaging data is acquired, it is time consuming to manually go through them and try to identify the patterns associated with various arrhythmia symptoms. In this paper, we present an interactive computer wizard that helps cardiac electrophysiology researchers to visualize and analyze the high resolution cardiac optical imaging data. The wizard provides a file interface that accommodates different file formats. A series of analysis algorithms output waveforms, activation and action potential maps after spatial and temporal filtering, velocity field and heterogeneity measure. The interactive GUI allows the researcher to identify the region of interest in both the spatial and temporal domain, thus enabling them to study different heart chamber at their choice.

In this paper, we apply a Bag-of-Features approach to malignant melanoma detection based on epiluminescence microscopy imaging. Each skin lesion is represented by a histogram of codewords or clusters identified from a training data set. Classification results using Naive Bayes classification and Support Vector Machines are reported. The best performance obtained is 82.21% on a dataset of 100 skin lesion images. Furthermore, since in melanoma screening false negative errors have a much higher impact and associated cost than false positive ones, we use the Neyman-Pearson score in our model selection scheme.

The integration of wireless networking technologies with medical information systems (telemedicine) have a significant impact on healthcare services provided to our society. Applications of telemedicine range from personalized medicine to affordable healthcare for underserved population. Though wireless technologies and medical informatics are individually progressing rapidly, wireless networking for healthcare systems is still at a very premature stage. In this paper we first present our open architecture for medical information systems that integrates both wired and wireless networked data acquisition systems. We then present the implementation at the physical layer and differential service MAC design that adapts channel provisioning based on the information criticality. Performance evaluation using analytical modeling and simulation shows that our DS-MAC provides differentiated services for emergency, warning, and normal traffic.

Astronaut health monitoring (AHM) during long durations of space missions will play a significant role in mission success. Designing networked healthcare systems for aerospace exploration that will enable continual surveillance and timely notification of astronaut health information to terrestrial healthcare providers at minimal deployment and operation cost is an extremely challenging problem. However, such capabilities will enhance the opportunities for remote medical assistance during space missions. In this paper, we extend our task and data aggregation scheduling from single-hop and multi-hop network to mesh network. The algorithm aims to optimize the network performance with respect to response time and network delay. The upper and lower bounds are derived to provide certain guarantee on data delivery time. The performance of a wireless mesh network with 25 sensor nodes is examined by varying network bandwidth and sensing power of sensor nodes. Basic recursive equations for sensing and data reporting are developed for the case of homogeneous and heterogeneous mesh networks and the performance results of two representative data sensing and reporting strategies are presented.

We have recently developed a decision support system for early skin cancer detection that relies on analysis of the pigmentation characteristics of a skin lesion, detected using crosspolarization imaging, and the increased vasculature associated with malignant lesions that is detected using transillumination imaging. Current system uses size difference based on lesion physiology and achieves great overall accuracy (86.9%). In this paper, we explore texture information, one of the criteria dermatologists use in the diagnosis of skin cancer, but has been found very difficult to utilize in an automatic manner. The overarching goal is to improve the overall decision support capability of the DSS. The objective is to use texture information ONLY to classify the benign and malignancy of the skin lesion. A three-layer mechanism that inherent to the support vector machine (SVM) methodology is employed to improve the generalization error rate and the computational efficiency. The performance of the algorithm is validated with a series of benchmark texture images and then tested on 22 pairs of real clinical skin lesion images. Our experimental results show that a 4th-order polynomial kernel can reach an average accuracy of 70% in determining the malignancy of any pixel within any given skin lesion image. Further study will look at whether multi-channel filtering based feature extraction algorithm will improve the accuracy rate, and the performance comparison between SVM-based texture classification and decision tree-based texture classification in both the spatial and frequency domain.