Observer-Based State Feedback for Enhanced Insulin Control of Type ‘I’ Diabetic Patients

During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type ‘I’ diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink

Phase II study of gemcitabine and vindesine in patients with previously untreated non-resectable non-small-cell lung cancer

Because both vindesine and gemcitabine are active drugs in advanced non-small-cell lung cancer (NSCLC), with different modes of action and only partly overlapping toxicity, a phase II study was performed. Gemcitabine 1000 mg m−2 was given on days 1, 8 and 15 every 4 weeks, while vindesine 3 mg m−2 was administered weekly for 7 weeks, then every 2 weeks. A total of 42 patients with nonresectable NSCLC were included. The median age of patients was 56 years; 57% were men, 52% had adenocarcinoma, 31% squamous cell carcinoma and 17% had large-cell carcinoma. The performance status ranged from 0 to 2 with 83% in performance status 1. The majority (55%) had stage IV disease, while 40% had stage III B and 5% stage III A disease. WHO grade 3–4 leucopenia occurred in five patients (12%) and 9% had grade 4 neutropenia. Thrombocytopenia grade 3–4 was observed in six patients (15%). There were no septic death or bleeding episodes. One patient had a transient WHO grade 4 increase in bilirubin, and four patients had a decrease in glomerular filtration rate below the normal limit; one of these patients developed a non-reversible renal insufficiency. Ten patients (24%) complained of dyspnoea of uncertain mechanism, possibly involving bronchoconstriction. There were one complete and seven partial responses among 40 assessable patients (20%, 95% confidence limits 9–36%). Median response duration was 31 weeks (range 11–83 weeks) and median survival time 31 weeks (range 2–171 weeks). The current combination of gemcitabine and vindesine does not appear to be promising for further examination because of the toxicity and somewhat disappointing activity. © 1999 Cancer Research Campaig

Computer-aided DSM-IV-diagnostics – acceptance, use and perceived usefulness in relation to users' learning styles

BACKGROUND: CDSS (computerized decision support system) for medical diagnostics have been studied for long. This study was undertaken to investigate how different preferences of Learning Styles (LS) of psychiatrists might affect acceptance, use and perceived usefulness of a CDSS for diagnostics in psychiatry. METHODS: 49 psychiatrists (specialists and non-specialists) from 3 different clinics volunteered to participate in this study and to use the CDSS to diagnose a paper-based case (based on a real patient). LS, attitudes to CDSS and complementary data were obtained via questionnaires and interviews. To facilitate the study, a special version of the CDSS was created, which automatically could log interaction details. RESULTS: The LS preferences (according to Kolb) of the 49 physicians turned out as follows: 37% were Assimilating, 31% Converging, 27% Accommodating and 6% Diverging. The CDSS under study seemed to favor psychiatrists with abstract conceptualization information perceiving mode (Assimilating and Converging learning styles). A correlation between learning styles preferences and computer skill was found. Positive attitude to computer-aided diagnostics and learning styles preferences was also found to correlate. Using the CDSS, the specialists produced only 1 correct diagnosis and the non-specialists 2 correct diagnoses (median values) as compared to the three predetermined correct diagnoses of the actual case. Only 10% had all three diagnoses correct, 41 % two correct, 47 % one correct and 2 % had no correct diagnose at all. CONCLUSION: Our results indicate that the use of CDSS does not guarantee correct diagnosis and that LS might influence the results. Future research should focus on the possibility to create systems open to individuals with different LS preferences and possibility to create CDSS adapted to the level of expertise of the user

Spatial quantitation of drugs in tissues using liquid extraction surface analysis mass spectrometry imaging

Liquid extraction surface analysis mass spectrometry imaging (LESA-MSI) has been shown to be an effective tissue profiling and imaging technique, producing robust and reliable qualitative distribution images of an analyte or analytes in tissue sections. Here, we expand the use of LESA-MSI beyond qualitative analysis to a quantitative analytical technique by employing a mimetic tissue model previously shown to be applicable for MALDI-MSI quantitation. Liver homogenate was used to generate a viable and molecularly relevant control matrix for spiked drug standards which can be frozen, sectioned and subsequently analyzed for the generation of calibration curves to quantify unknown tissue section samples. The effects of extraction solvent composition, tissue thickness and solvent/tissue contact time were explored prior to any quantitative studies in order to optimize the LESA-MSI method across several different chemical entities. The use of a internal standard to normalize regional differences in ionization response across tissue sections was also investigated. Data are presented comparing quantitative results generated by LESA-MSI to LC-MS/MS. Subsequent analysis of adjacent tissue sections using DESI-MSI is also reported

Vitamin D supplementation to prevent acute respiratory tract infections: systematic review and meta-analysis of individual participant data

This study was supported by a grant from the National Institute for Health Research (NIHR) under its Health Technology Assessment programme (reference No 13/03/25, to ARM

Early death during chemotherapy in patients with small-cell lung cancer: derivation of a prognostic index for toxic death and progression

Based on an increased frequency of early death (death within the first treatment cycle) in our two latest randomized trials of combination chemotherapy in small-cell lung cancer (SCLC), we wanted to identify patients at risk of early non-toxic death (ENTD) and early toxic death (ETD). Data were stored in a database and logistic regression analyses were performed to identify predictive factors for early death. During the first cycle, 118 out of 937 patients (12.6%) died. In 38 patients (4%), the cause of death was sepsis. Significant risk factors were age, performance status (PS), lactate dehydrogenase (LDH) and treatment with epipodophyllotoxins and platinum in the first cycle (EP). Risk factors for ENTD were age, PS and LDH. Extensive stage had a hazard ratio of 1.9 (P = 0.07). Risk factors for ETD were EP, PS and LDH, whereas age and stage were not. For EP, the hazard ratio was as high as 6.7 (P = 0.0001). We introduced a simple prognostic algorithm including performance status, LDH and age. Using a prognostic algorithm to exclude poor-risk patients from trials, we could minimize early death, improve long-term survival and increase the survival differences between different regimens. We suggest that other groups evaluate our algorithm and exclude poor prognosis patients from trials of dose intensification. © 1999 Cancer Research Campaig

Can we apply the Mendelian randomization methodology without considering epigenetic effects?

<p>Abstract</p> <p>Introduction</p> <p>Instrumental variable (IV) methods have been used in econometrics for several decades now, but have only recently been introduced into the epidemiologic research frameworks. Similarly, Mendelian randomization studies, which use the IV methodology for analysis and inference in epidemiology, were introduced into the epidemiologist's toolbox only in the last decade.</p> <p>Analysis</p> <p>Mendelian randomization studies using instrumental variables (IVs) have the potential to avoid some of the limitations of observational epidemiology (confounding, reverse causality, regression dilution bias) for making causal inferences. Certain limitations of randomized controlled trials, such as problems with generalizability, feasibility and ethics for some exposures, and high costs, also make the use of Mendelian randomization in observational studies attractive. Unlike conventional randomized controlled trials (RCTs), Mendelian randomization studies can be conducted in a representative sample without imposing any exclusion criteria or requiring volunteers to be amenable to random treatment allocation.</p> <p>Within the last decade, epigenetics has gained recognition as an independent field of study, and appears to be the new direction for future research into the genetics of complex diseases. Although previous articles have addressed some of the limitations of Mendelian randomization (such as the lack of suitable genetic variants, unreliable associations, population stratification, linkage disequilibrium (LD), pleiotropy, developmental canalization, the need for large sample sizes and some potential problems with binary outcomes), none has directly characterized the impact of epigenetics on Mendelian randomization. The possibility of epigenetic effects (non-Mendelian, heritable changes in gene expression not accompanied by alterations in DNA sequence) could alter the core instrumental variable assumptions of Mendelian randomization.</p> <p>This paper applies conceptual considerations, algebraic derivations and data simulations to question the appropriateness of Mendelian randomization methods when epigenetic modifications are present.</p> <p>Conclusion</p> <p>Given an inheritance of gene expression from parents, Mendelian randomization studies not only need to assume a random distribution of alleles in the offspring, but also a random distribution of epigenetic changes (e.g. gene expression) at conception, in order for the core assumptions of the Mendelian randomization methodology to remain valid. As an increasing number of epidemiologists employ Mendelian randomization methods in their research, caution is therefore needed in drawing conclusions from these studies if these assumptions are not met.</p

Genome-wide enhancer maps link risk variants to disease genes

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complextraits, each of which could reveal insights into the mechanisms of disease(1). Many ofthe underlying causal variants may affect enhancers(2,3), but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types(4). Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577genesthat appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.Peer reviewe