The Guideline Elements Model (GEM) uses XML to represent the heterogeneous knowledge contained in clinical practice guidelines. GEM has important applications in computer aided guideline authoring and clinical decision support systems. However, its XML representation format could limit its potential impact, as semantic web ontology languages, such as OWL, are becoming major knowledge representation frameworks in medical informatics. In this work, we present a faithful translation of GEM from XML into OWL. This translation is intended to keep the knowledge model of GEM intact, as this knowledge model has been carefully designed and has become a recognized standard. An OWL representation would make GEM more applicable in medical informatics systems that rely on semantic web. This work will also be the initial step in making GEM a guideline recommendation ontology.
The machineable representation and execution of clinical guidelines has been the focus of research efforts for some time, however there is less examination of whether the methods and techniques for guidelines are sufficient for clinical protocols. The objective of this study was to test the feasibility of using the Guideline Elements Model II (GEM II) and GEM Cutter for the representation of clinical protocols, specifically clinical protocols commonly used by nurses. After downloading the GEM Cutter 2.5, we decomposed a set of clinical protocols and analyzed the completeness in which elemental protocol data was represented. One of the most complicated of these protocols (extravasations of infused medication) is presented as an example. While GEM II adequately represents core elements of clinical protocols at the high level, it was not possible to adequately represent sequence and associated role based permissions via use of conditional criteria at branching and procedural levels. Functionality of the tool would also be enhanced with more robust terminology management and support for multi-authoring.
Access to timely decision support information is critical for delivery of high-quality medical care. Transformation of clinical knowledge that is originally expressed in the form of a guideline to a computable format is one of the main obstacles to the integration of knowledge sharing functionality into computerized clinical systems. The Guideline Element Model (GEM) provides a methodology for such a transformation. Although the model has been used to store heterogeneous guideline knowledge, it is important to demonstrate that GEM markup facilitates guideline implementation. This report demonstrates the feasibility of implementation of GEM-encoded guideline recommendations using Apache Group s Cocoon Web Publishing Framework. We further demonstrate how XML-based programming allows for maintaining the separation of guideline content from processing logic and from presentation format. Finally, we analyze whether the guideline authors original intent has been sufficiently captured and conveyed to the end user.
Among the most effective strategies for changing the process and outcomes of clinical care are those that make use of computer-mediated decision support. A variety of representation models that facilitate computer-based implementation of medical knowledge have been published, including the Guideline Elements Model (GEM) and the Arden Syntax for Medical Logic Modules (MLMs). We describe an XML-based application that facilitates automated generation of partially populated MLMs from GEM-encoded guidelines. These MLMs can be further edited and shared among Arden-compliant information systems to provide decision support. Our work required three steps: (a) Knowledge extraction from published guideline documents using GEM, (b) Mapping GEM elements to the MLM slots, and (c) XSL transformation of the GEM-encoded guideline. Processing of a sample guideline generated 15 MLMs, each corresponding to a conditional or imperative element in the GEM structure. Mechanisms for linking various MLMs are necessary to represent the complexity of logic typical of a guideline.
The Digital Electronic Guideline Library (DeGeL) is a Web-based framework and a set of distributed tools that facilitate gradual conversion of clinical guidelines from free text, through semi-structured text, to a fully structured, executable representation. Thus, guidelines exist in a hybrid, multiple-format representation The three formats support increasingly sophisticated computational tasks. The tools perform semantic markup, classification, search, and browsing, and support computational modules that we are developing, for run-time application and retrospective quality assessment. We describe the DeGeL architecture and its collaborative-authoring authorization model, which is based on (1) multiple medical-specialty authoring groups, each including a group manager who controls group authorizations, and (2) a hierarchical authorization model based on the different functions involved in the hybrid guideline-specification process. We have implemented the core modules of the DeGeL architecture and demonstrated distributed markup and retrieval using the knowledge roles of two guidelines ontologies (Asbru and GEM). We are currently evaluating several of the DeGeL tools.
Objective: A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems.
Design: This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification.
Results: The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system.
Conclusion: Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.
The aim of this work was to determine whether the GEM-encoding step could improve the representation of clinical practice guidelines as formalized knowledge bases. We used the 1999 Canadian recommendations for the management of hypertension, chosen as the knowledge source in the ASTI project. We first clarified semantic ambiguities of therapeutic sequences recommended in the guideline by proposing an interpretative framework of therapeutic strategies. Then, after a formalization step to standardize the terms used to characterize clinical situations, we created the GEM-encoded instance of the guideline. We developed a module for the automatic derivation of a rule base, BR-GEM, from the instance. BR-GEM was then compared to the rule base, BR-ASTI, embedded within the critic mode of ASTI, and manually built by two physicians from the same Canadian guideline. As compared to BR-ASTI, BR-GEM is more specific and covers more clinical situations. When evaluated on 10 patient cases, the GEM-based approach led to promising results.
Objective: To develop a guideline document model
that includes a sufficiently broad set of concepts to be useful throughout the
guideline life cycle.
Design: Current guideline document models are limited in that they
reflect the specific orientation of the stakeholder who created them; thus,
developers and disseminators often provide few constructs for conceptualizing
recommendations, while implementers de-emphasize concepts related to
establishing guideline validity. The authors developed the Guideline Elements
Model (GEM) using XML to better represent the heterogeneous knowledge
contained in practice guidelines. Core constructs were derived from the
Institute of Medicine's Guideline Appraisal Instrument, the National Guideline
Clearinghouse, and the augmented decision table guideline representation.
These were supplemented by additional concepts from a literature review.
Results: The GEM hierarchy includes more than 100 elements. Major
concepts relate to a guideline's identity, developer, purpose, intended
audience, method of development, target population, knowledge components,
testing, and review plan. Knowledge components in guideline documents include
recommendations (which in turn comprise conditionals and imperatives),
definitions, and algorithms.
Conclusion: GEM is more comprehensive than existing models and is
expressively adequate to represent the heterogeneous information contained in
guidelines. Use of XML contributes to a flexible, comprehensible, shareable,
and reusable knowledge representation that is both readable by human beings
and processible by computers.
Through this collaboration, we were able to integrate a proposed expansion of the National Guideline Clearinghouse (NGC) guideline classification into the XML based Guideline Elements Model (GEM).1 2 We conclude that GEM, through its utilization of XML is flexible enough to accommodate externally developed concepts. We hope to use this result to expand upon a preliminary evaluation of the guideline classification using GEM tools.
To determine whether a high prevalence (55%) of Aβ deposition in a cohort of individuals remaining dementia-free into their 9th and 10th decades is associated with cognitive decline prior to imaging.
A total of 194 participants (mean age 85.5 years, range 82–95) who completed the Ginkgo Evaluation of Memory Study (GEMS) and remained dementia-free subsequently completed Pittsburgh compound B–PET imaging. We examined cross-sectional associations between Aβ status and performance on a broad neuropsychological test battery completed at GEMS entry 7–9 years prior to neuroimaging. We also longitudinally examined cognition over annual evaluations using linear mixed models.
At GEMS screening (2000–2002), participants who were Aβ-positive in 2009 had lower performance on the Stroop test (p < 0.01) and Raven's Progressive Matrices (p = 0.05), with trend level difference for Block Design (p = 0.07). Longitudinal analyses showed significant slope differences for immediate and delayed recall of the Rey-Osterrieth figure, semantic fluency, and Trail-Making Test parts A and B, indicating greater performance decline prior to neuroimaging for Aβ-positive relative to Aβ-negative participants (ps < 0.05).
Highly prevalent Aβ deposition in oldest-older adults is associated with cognitive decline in visual memory, semantic fluency, and psychomotor speed beginning 7–9 years prior to neuroimaging. Mean differences in nonmemory domains, primarily executive functions, between Aβ-status groups may be detectable 7–9 years before neuroimaging.
Capecitabine (CAP) is a 5-FU pro-drug approved for the treatment of several cancers and it is used in combination with gemcitabine (GEM) in the treatment of patients with pancreatic adenocarcinoma (PDAC). However, limited pre-clinical data of the effects of CAP in PDAC are available to support the use of the GEMCAP combination in clinic. Therefore, we investigated the pharmacokinetics and the efficacy of CAP as a single agent first and then in combination with GEM to assess the utility of the GEMCAP therapy in clinic. Using a model of spontaneous PDAC occurring in KrasG12D; p53R172H; Pdx1-Cre (KPC) mice and subcutaneous allografts of a KPC PDAC-derived cell line (K8484), we showed that CAP achieved tumour concentrations (∼25 µM) of 5-FU in both models, as a single agent, and induced survival similar to GEM in KPC mice, suggesting similar efficacy. In vitro studies performed in K8484 cells as well as in human pancreatic cell lines showed an additive effect of the GEMCAP combination however, it increased toxicity in vivo and no benefit of a tolerable GEMCAP combination was identified in the allograft model when compared to GEM alone. Our work provides pre-clinical evidence of 5-FU delivery to tumours and anti-tumour efficacy following oral CAP administration that was similar to effects of GEM. Nevertheless, the GEMCAP combination does not improve the therapeutic index compared to GEM alone. These data suggest that CAP could be considered as an alternative to GEM in future, rationally designed, combination treatment strategies for advanced pancreatic cancer.
Human pancreatic cancer is one of the most common clinical malignancies. The effect of comprehensive treatment based on surgery is general. The effects of chemotherapy were not obvious mainly because of lack of targeting and chemoresistance in pancreatic cancer. This study aimed to investigate the effects of folate receptor (FR)-mediated gemcitabine FA-Chi-Gem nanoparticles with a core-shell structure by electrostatic spray on pancreatic cancer.
In this study, the levels of expression of FR in six human pancreatic cancer cell lines were studied by immunohistochemical analysis. The uptake rate of isothiocyanate-labeled FA-Chi nanoparticles in FR high expression cell line COLO357 was assessed by fluorescence microscope and the inhibition rate of FA-Chi-Gem nanoparticles on COLO357 cells was evaluated by MTT assay. Moreover, the biodistribution of PEG-FA-ICGDER02-Chi in the orthotopic pancreatic tumor model was observed using near-infrared imaging and the human pancreatic cancer orthotopic xenografts were treated with different nanoparticles and normal saline control.
The expression of FR in COLO357 was the highest among the six pancreatic cancer cell lines. The FR mainly distributed on cell membrane and fewer in the cytoplasm in pancreatic cancer. Moreover, the absorption rate of the FA-Chi-Gem nanoparticles was more than the Chi nanoparticles without FA modified. The proliferation of COLO357 was significantly inhibited by FA-Chi-Gem nanoparticles. The PEG-FA-ICGDER02-Chi nanoparticles were enriched in tumor tissue in human pancreatic cancer xenografts, while non-targeted nanoparticles were mainly in normal liver tissue. PEG-FA-Gem-Chi significantly inhibited the growth of human pancreatic cancer xenografts (PEG-FA-Gem-Chi vs. Gem, t=22.950, P=0.000).
PEG-FA-FITC-Chi nanoparticles might be an effective targeted drug for treating human FR-positive pancreatic cancer.
Pancreatic cancer; folate receptor; targeted nanoparticle; gemcitabine
Efficient HTLV-1 viral transmission occurs through cell-to-cell contacts. The Tax viral transcriptional activator protein facilitates this process. Using a comparative transcriptomic analysis, we recently identified a series of genes up-regulated in HTLV-1 Tax expressing T-lymphocytes. We focused our attention towards genes that are important for cytoskeleton dynamic and thus may possibly modulate cell-to-cell contacts. We first demonstrate that Gem, a member of the small GTP-binding proteins within the Ras superfamily, is expressed both at the RNA and protein levels in Tax-expressing cells and in HTLV-1-infected cell lines. Using a series of ChIP assays, we show that Tax recruits CREB and CREB Binding Protein (CBP) onto a c-AMP Responsive Element (CRE) present in the gem promoter. This CRE sequence is required to drive Tax-activated gem transcription. Since Gem is involved in cytoskeleton remodeling, we investigated its role in infected cells motility. We show that Gem co-localizes with F-actin and is involved both in T-cell spontaneous cell migration as well as chemotaxis in the presence of SDF-1/CXCL12. Importantly, gem knock-down in HTLV-1-infected cells decreases cell migration and conjugate formation. Finally, we demonstrate that Gem plays an important role in cell-to-cell viral transmission.
HTLV-1 was the first human oncoretrovirus to be discovered. Five to ten million people are infected, and 1–6% will develop either Adult T-cell Leukemia, or Tropical Spastic Paraparesis/HTLV-1 Associated Myelopathy (TSP/HAM). HTLV-1 infects primarily T-cells, but dendritic cells were also found to carry proviruses. Contrary to HIV-1, cell-free HTLV-1 viral particles are poorly infectious. Thus, efficient viral transmission relies on formation of virological synapses or formation and transfer of viral biofilm-like structures. The Tax viral transactivator plays a key role in both modes of transmission. Using transcriptomic analyses, we recently identified cellular genes that are deregulated following Tax expression in T-cells. We focused our attention on genes that are important for cell architecture and are thus likely to modulate cell-to-cell contacts and motility. We found that Gem was highly upregulated both at the RNA and protein levels in Tax-expressing cells and HTLV-1-infected cell lines. We further show that Tax binds cellular co-activators and transcription factor and activates transcription from the gem promoter. We demonstrated that Gem is involved in cellular migration of HTLV-1-infected cells. Importantly, gem knockdown decreases the rate of HTLV-1-infected cell migration and cell-to-cell conjugate formation. We also show that Gem plays an important role in HTLV-1 transmission through cell-to-cell contacts, the most efficient mode of viral infection.
Gemcitabine (GEM) is currently the standard first line treatment for pancreatic cancer; however, the overall survival of patients with this disease remains poor. Imexon is a pro-oxidant small molecule which produced a high response rate in combination with GEM in a phase I trial in pancreatic cancer. In this study, we investigate the combination of GEM with a novel redox-active agent, imexon, in vitro and in vivo.
Median effect analysis was used for in vitro combination cytotoxicity. The effect of imexon on GEM metabolism and uptake into cells and into DNA and effects on ribonucleotide reductase (RNR) were examined in vitro. The pharmacokinetics and antitumor efficacy of the imexon/GEM combination was evaluated in mouse models.
In three human pancreatic cancer lines, there was additivity for the imexon/GEM combination. There was significantly greater efficacy for the drug combination in Panc-1 xenograft tumors. A pharmacokinetic study in mice showed a near doubling in the AUC of imexon when GEM was co-administered, with no effect of imexon on GEM's pharmacokinetic disposition. In vitro, imexon did not alter GEM's metabolism or uptake into DNA, but significantly inhibited RNR, and this effect was greater when combined with GEM.
These results suggest that the interaction between imexon and GEM may be due to complimentary inhibition of RNR plus an enhanced exposure to imexon when the GEM is administered in vivo. This combination is currently being tested in a randomized phase II trial in pancreatic cancer.
Imexon; Gemcitabine; Ribonucleotide reductase; Synergy; Pancreatic cancer
OBJECTIVE: To describe application of GEM to analysis and categorization of guideline content. METHOD: We examined the application of GEM constructs to the AAP guideline on neurodiagnostic evaluation of febrile seizures. Subjects at 4 sites marked-up the guideline content using a hierarchical template that includes branches for identity, developer, purpose, intended audience, method of development, knowledge components, testing, and review. The types of elements used were tabulated. Subjects were surveyed regarding the usability of the model. RESULTS: Eight subjects analyzed the guideline, using between 46 and 149 elements to model its content. There was considerable variation in the application of elements. The number of elements used correlated with time to complete the task. Subjects found application of GEM to be straightforward in 6 of 8 categories and sufficiently comprehensive to model the guideline's information content. CONCLUSIONS: Subjects found GEM constructs were able to model the content of the guideline. Improved editing tools will facilitate translation.
XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups.
Biomedical Data Management; XML Database; Data Integration; Semantic Interoperability
Conventional development of multi-gene expression models (GEMs) predicting therapeutic response of cancer patients are based on analysis of patients treated with specific regimens, which limits generalization to different or novel drug combinations. We overcome this limitation by developing GEMs based on in vitro drug sensitivities and microarray analyses of the NCI-60 cancer cell line panel. These GEMs were evaluated in blind fashion as predictors of tumor response and/or patient survival in seven independent cohorts of patients with breast (N=275), bladder (N=59), and ovarian (N=143) cancer treated with multi-agent chemotherapy, of which 233 patients were from prospectively-enrolled clinical trials. In all studies, GEMs effectively stratified tumor response and patient survival independent of established clinical and pathologic tumor variables. In bladder cancer patients treated with neoadjuvant MVAC (Methotrexate, Vinblastine, Doxorubicin, Cisplatin), the 3-year overall survival for those with favorable GEM scores was 81% vs. 33% for those with less favorable scores (p=0.002). GEMs for breast cancer patients treated with FAC (Fluorouracil, Doxorubicin, Cyclophosphamide) and ovarian cancer patients treated with platinum-containing regimens also stratified patient survival (5-year overall survival 100% vs. 74% (p=0.05) and 3-year overall survival 68% vs. 43% (p=0.008), respectively. Importantly, clinical prediction using our in vitro GEM was superior to that of conventionally-derived GEMs. We demonstrate a facile yet effective approach to GEM derivation that identifies patients most likely to benefit from selected multi-agent therapy. Use of such in vitro-based GEMs may provide a robust and generalizable approach to personalized cancer therapy.
Combination Chemotherapy; Co-expression Extrapolation; Gene Expression-based Prediction Models
Background and Aims
Cholangiocarcinoma (CCA) is highly resistant to chemotherapy, including gemcitabine (Gem) treatment. MicroRNAs (miRNAs) are endogenous, non-coding, short RNAs that can regulate multiple genes expression. Some miRNAs play important roles in the chemosensitivity of tumors. Here, we examined the relationship between miRNA expression and the sensitivity of CCA cells to Gem.
Microarray analysis was used to determine the miRNA expression profiles of two CCA cell lines, HuH28 and HuCCT1. To determine the effect of candidate miRNAs on Gem sensitivity, expression of each candidate miRNA was modified via either transfection of a miRNA mimic or transfection of an anti-oligonucleotide. Ontology-based programs were used to identify potential target genes of candidate miRNAs that were confirmed to affect the Gem sensitivity of CCA cells.
HuCCT1 cells were more sensitive to Gem than were HuH28 cells, and 18 miRNAs were differentially expressed whose ratios over ± 2log2 between HuH28 and HuCCT1. Among these 18 miRNAs, ectopic overexpression of each of three downregulated miRNAs in HuH28 (miR-29b, miR-205, miR-221) restored Gem sensitivity to HuH28. Suppression of one upregulated miRNA in HuH28, miR-125a-5p, inhibited HuH28 cell proliferation independently to Gem treatment. Selective siRNA-mediated downregulation of either of two software-predicted targets, PIK3R1 (target of miR-29b and miR-221) or MMP-2 (target of miR-29b), also conferred Gem sensitivity to HuH28.
miRNA expression profiling was used to identify key miRNAs that regulate Gem sensitivity in CCA cells, and software that predicts miRNA targets was used to identify promising target genes for anti-tumor therapies.
The study aims to introduce a hybrid optimization algorithm for anatomy-based intensity modulated radiotherapy (AB-IMRT). Our proposal is that by integrating an exact optimization algorithm with a heuristic optimization algorithm, the advantages of both the algorithms can be combined, which will lead to an efficient global optimizer solving the problem at a very fast rate. Our hybrid approach combines Gaussian elimination algorithm (exact optimizer) with fast simulated annealing algorithm (a heuristic global optimizer) for the optimization of beam weights in AB-IMRT. The algorithm has been implemented using MATLAB software. The optimization efficiency of the hybrid algorithm is clarified by (i) analysis of the numerical characteristics of the algorithm and (ii) analysis of the clinical capabilities of the algorithm. The numerical and clinical characteristics of the hybrid algorithm are compared with Gaussian elimination method (GEM) and fast simulated annealing (FSA). The numerical characteristics include convergence, consistency, number of iterations and overall optimization speed, which were analyzed for the respective cases of 8 patients. The clinical capabilities of the hybrid algorithm are demonstrated in cases of (a) prostate and (b) brain. The analyses reveal that (i) the convergence speed of the hybrid algorithm is approximately three times higher than that of FSA algorithm; (ii) the convergence (percentage reduction in the cost function) in hybrid algorithm is about 20% improved as compared to that in GEM algorithm; (iii) the hybrid algorithm is capable of producing relatively better treatment plans in terms of Conformity Index (CI) [~ 2% - 5% improvement] and Homogeneity Index (HI) [~ 4% - 10% improvement] as compared to GEM and FSA algorithms; (iv) the sparing of organs at risk in hybrid algorithm-based plans is better than that in GEM-based plans and comparable to that in FSA-based plans; and (v) the beam weights resulting from the hybrid algorithm are about 20% smoother than those obtained in GEM and FSA algorithms. In summary, the study demonstrates that hybrid algorithms can be effectively used for fast optimization of beam weights in AB-IMRT.
Anatomy-based IMRT; hybrid algorithm; intensity modulated radiotherapy; optimization; fast simulated annealing
The past decade has witnessed the unveiling of a powerful new generation of genetically-engineered mouse (GEM) models of human cancer, which are proving to be highly effective for elucidating cancer mechanisms and interrogating novel experimental therapeutics. This new generation of GEM models are well-suited for chemoprevention research, particularly for investigating progressive stages of carcinogenesis, identifying biomarkers for early detection and intervention, and pre-clinical assessment of novel agents or combinations of agents. Here we discuss opportunities and challenges for the application of GEM models in prevention research, as well as strategies to maximize their relevance for human cancer.
Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran’s Affairs (VA) system initiated interprofessional practice (IPP) models with their Geriatric Evaluation and Management (GEM) programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.
Three strategies were used: 1) a national GEM program survey; 2) a veteran/family satisfaction survey; and 3) an absentee assessment.
Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.
Maintaining the sustainability of IPP programs is crucial for the health of our veterans. This project uncovered tools to improve the GEM IPP model for our veterans that can be incorporated nationally. Despite the lengthy nature of IPP models, patients and families appreciated the thoroughness, requested transportation and food, and responded well to reminder phone calls. A keen eye on these issues and concomitant medical complexity needs to be observed when planning IPP models to ensure sustainability.
interprofessional practice; veterans; geriatric evaluation and management
Mathematical models and simulations are important tools in discovering key causal relationships governing physiological processes. Simulations guide and improve outcomes of medical interventions involving complex physiology. We developed HumMod, a Windows-based model of integrative human physiology. HumMod consists of 5000 variables describing cardiovascular, respiratory, renal, neural, endocrine, skeletal muscle, and metabolic physiology. The model is constructed from empirical data obtained from peer-reviewed physiological literature. All model details, including variables, parameters, and quantitative relationships, are described in Extensible Markup Language (XML) files. The executable (HumMod.exe) parses the XML and displays the results of the physiological simulations. The XML description of physiology in HumMod's modeling environment allows investigators to add detailed descriptions of human physiology to test new concepts. Additional or revised XML content is parsed and incorporated into the model. The model accurately predicts both qualitative and quantitative changes in clinical and experimental responses. The model is useful in understanding proposed physiological mechanisms and physiological interactions that are not evident, allowing one to observe higher level emergent properties of the complex physiological systems. HumMod has many uses, for instance, analysis of renal control of blood pressure, central role of the liver in creating and maintaining insulin resistance, and mechanisms causing orthostatic hypotension in astronauts. Users simulate different physiological and pathophysiological situations by interactively altering numerical parameters and viewing time-dependent responses. HumMod provides a modeling environment to understand the complex interactions of integrative physiology. HumMod can be downloaded at http://hummod.org
integrative physiology; HumMod; physiome; model
With the sequence of the Plasmodium falciparum genome and several global mRNA and protein life cycle expression profiling projects now completed, elucidating the underlying networks of transcriptional control important for the progression of the parasite life cycle is highly pertinent to the development of new anti-malarials. To date, relatively little is known regarding the specific mechanisms the parasite employs to regulate gene expression at the mRNA level, with studies of the P. falciparum genome sequence having revealed few cis-regulatory elements and associated transcription factors. Although it is possible the parasite may evoke mechanisms of transcriptional control drastically different from those used by other eukaryotic organisms, the extreme AT-rich nature of P. falciparum intergenic regions (~90% AT) presents significant challenges to in silico cis-regulatory element discovery.
We have developed an algorithm called Gene Enrichment Motif Searching (GEMS) that uses a hypergeometric-based scoring function and a position-weight matrix optimization routine to identify with high-confidence regulatory elements in the nucleotide-biased and repeat sequence-rich P. falciparum genome. When applied to promoter regions of genes contained within 21 co-expression gene clusters generated from P. falciparum life cycle microarray data using the semi-supervised clustering algorithm Ontology-based Pattern Identification, GEMS identified 34 putative cis-regulatory elements associated with a variety of parasite processes including sexual development, cell invasion, antigenic variation and protein biosynthesis. Among these candidates were novel motifs, as well as many of the elements for which biological experimental evidence already exists in the Plasmodium literature. To provide evidence for the biological relevance of a cell invasion-related element predicted by GEMS, reporter gene and electrophoretic mobility shift assays were conducted.
This GEMS analysis demonstrates that in silico regulatory element discovery can be successfully applied to challenging repeat-sequence-rich, base-biased genomes such as that of P. falciparum. The fact that regulatory elements were predicted from a diverse range of functional gene clusters supports the hypothesis that cis-regulatory elements play a role in the transcriptional control of many P. falciparum biological processes. The putative regulatory elements described represent promising candidates for future biological investigation into the underlying transcriptional control mechanisms of gene regulation in malaria parasites.
Physician-staffed helicopter emergency medical services (HEMS) are a well-established component of prehospital trauma care in Germany. Reduced rescue times and increased catchment area represent presumable specific advantages of HEMS. In contrast, the availability of HEMS is connected to a high financial burden and depends on the weather, day time and controlled visual flight rules. To date, clear evidence regarding the beneficial effects of HEMS in terms of improved clinical outcome has remained elusive.
Traumatized patients (Injury Severity Score; ISS ≥9) primarily treated by HEMS or ground emergency medical services (GEMS) between 2007 and 2009 were analyzed using the TraumaRegister DGU® of the German Society for Trauma Surgery. Only patients treated in German level I and II trauma centers with complete data referring to the transportation mode were included. Complications during hospital treatment included sepsis and organ failure according to the criteria of the American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) consensus conference committee and the Sequential Organ Failure Assessment (SOFA) score.
A total of 13,220 patients with traumatic injuries were included in the present study. Of these, 62.3% (n = 8,231) were transported by GEMS and 37.7% (n = 4,989) by HEMS. Patients treated by HEMS were more seriously injured compared to GEMS (ISS 26.0 vs. 23.7, P < 0.001) with more severe chest and abdominal injuries. The extent of medical treatment on-scene, which involved intubation, chest and treatment with vasopressors, was more extensive in HEMS (P < 0.001) resulting in prolonged on-scene time (39.5 vs. 28.9 minutes, P < 0.001). During their clinical course, HEMS patients more frequently developed multiple organ dysfunction syndrome (MODS) (HEMS: 33.4% vs. GEMS: 25.0%; P < 0.001) and sepsis (HEMS: 8.9% vs. GEMS: 6.6%, P < 0.001) resulting in an increased length of ICU treatment and in-hospital time (P < 0.001). Multivariate logistic regression analysis found that after adjustment by 11 other variables the odds ratio for mortality in HEMS was 0.75 (95% CI: 0.636 to 862).
Afterwards, a subgroup analysis was performed on patients transported to level I trauma centers during daytime with the intent of investigating a possible correlation between the level of the treating trauma center and posttraumatic outcome. According to this analysis, the Standardized Mortality Ratio, SMR, was significantly decreased following the Trauma Score and the Injury Severity Score (TRISS) method (HEMS: 0.647 vs. GEMS: 0.815; P = 0.002) as well as the Revised Injury Severity Classification (RISC) score (HEMS: 0.772 vs. GEMS: 0.864; P = 0.045) in the HEMS group.
Although HEMS patients were more seriously injured and had a significantly higher incidence of MODS and sepsis, these patients demonstrated a survival benefit compared to GEMS.
Hematopoietic stem cell transplantation (HSCT) is an established treatment for multiple myeloma (MM), a plasma cell malignancy. To identify an improved pretransplant conditioning regimen, we investigated the cytotoxicity of gemcitabine (Gem) and clofarabine (Clo) combinations toward MM cell lines and patient cell samples. A strong synergism of the two nucleoside analogs, when combined at their approximate IC10 concentrations, was observed. This synergism could be partly due to the observed Gem-mediated phosphorylation and activation of deoxycytidine kinase, resulting in enhanced phosphorylation of Gem and Clo. Their cytotoxicity correlated with a robust activation of the DNA damage response pathway. [Gem+Clo] decreased the mitochondrial membrane potential with a concomitant release of proapoptotic factors into the cytoplasm and nucleus and the activation of apoptosis. Exposure of MM cells to [Gem+Clo] also decreased the level of ribosomal RNA (rRNA), which might have resulted in nucleolar stress, as reported previously, and caused a p53-dependent cell death. A reduction by approximately 50% in the cytotoxicity of Gem and Clo was observed in the presence of pifithrin α, a p53 inhibitor. Furthermore, MM cell lines with mutant p53 exhibited greater resistance to Gem and Clo, supporting a role for the p53 protein in these cytotoxic responses. Our results provide a rationale for clinical trials incorporating [Gem+Clo] combinations as part of conditioning therapy for high-risk patients with MM undergoing HSCT.