Time-dependent ARMA modeling of genomic sequences

<p>Abstract</p> <p>Background</p> <p>Over the past decade, many investigators have used sophisticated time series tools for the analysis of genomic sequences. Specifically, the correlation of the nucleotide chain has been studied by examining the properties of the power spectrum. The main limitation of the power spectrum is that it is restricted to stationary time series. However, it has been observed over the past decade that genomic sequences exhibit non-stationary statistical behavior. Standard statistical tests have been used to verify that the genomic sequences are indeed not stationary. More recent analysis of genomic data has relied on time-varying power spectral methods to capture the statistical characteristics of genomic sequences. Techniques such as the evolutionary spectrum and evolutionary periodogram have been successful in extracting the time-varying correlation structure. The main difficulty in using time-varying spectral methods is that they are extremely unstable. Large deviations in the correlation structure results from very minor perturbations in the genomic data and experimental procedure. A fundamental new approach is needed in order to provide a stable platform for the non-stationary statistical analysis of genomic sequences.</p> <p>Results</p> <p>In this paper, we propose to model non-stationary genomic sequences by a time-dependent autoregressive moving average (TD-ARMA) process. The model is based on a classical ARMA process whose coefficients are allowed to vary with time. A series expansion of the time-varying coefficients is used to form a generalized Yule-Walker-type system of equations. A recursive least-squares algorithm is subsequently used to estimate the time-dependent coefficients of the model. The non-stationary parameters estimated are used as a basis for statistical inference and biophysical interpretation of genomic data. In particular, we rely on the TD-ARMA model of genomic sequences to investigate the statistical properties and differentiate between coding and non-coding regions in the nucleotide chain. Specifically, we define a quantitative measure of randomness to assess how far a process deviates from white noise. Our simulation results on various gene sequences show that both the coding and non-coding regions are non-random. However, coding sequences are "whiter" than non-coding sequences as attested by a higher index of randomness.</p> <p>Conclusion</p> <p>We demonstrate that the proposed TD-ARMA model can be used to provide a stable time series tool for the analysis of non-stationary genomic sequences. The estimated time-varying coefficients are used to define an index of randomness, in order to assess the statistical correlations in coding and non-coding DNA sequences. It turns out that the statistical differences between coding and non-coding sequences are more subtle than previously thought using stationary analysis tools: Both coding and non-coding sequences exhibit statistical correlations, with the coding regions being "whiter" than the non-coding regions. These results corroborate the evolutionary periodogram analysis of genomic sequences and revoke the stationary analysis' conclusion that coding DNA behaves like random sequences.</p

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Dendrimers: A Platform For Novel Drug Delivery System

The review majorly based on four areas i.e., architecturing, synthesis, properties &amp; applications of dendrimer. The dendrimers having unique architectural design of high degree of branching, multivalency, globular architecture and well defined molecular weight which distinguishesthis structure is unique and optimum nanocarriersin medical applications such as drug delivery, gene delivery, tumor therapy,diagnostic etc. It has some synthetic approaches lead to a dendritic architecture with properties complaisant to modification of shape, size, polarity,surface properties &amp; internal structure.Nanoparticle drug delivery system is popular once are able to increase the stability and selectivity of therapeutic agents. The reticuloendothelial system (RES) uptake drug leakage, cytotoxicity, immunogenicity, hemolytic toxicity, hydrophobicity restrict the use of these nanostructure.And these problems are overcome by surface engineering the dendrimers such as, polyester dendrimer, citric acid dendrimer, argining dendrimer, glycol dendrimers, PEGlyated dendrimers, etc. The bioactive agents can be easily encapsulated in to the interior of the dendrimers and are chemically attached such as conjugated or physically absorbed onto the dendrimer surface,serving the desired properties of the carrier to the specific needs of active material and its therapeutic applications.In addition to supplying a multivalent backbone for drug attachment, dendrimers also provide access for various new polymer architectures that are potentially relevant to drug delivery applications

Distinct gene expression profile of Xanthomonas retroflexus engaged in synergistic multispecies biofilm formation

It is well known that bacteria often exist in naturally formed multispecies biofilms. Within these biofilms, interspecies interactions seem to have an important role in ecological processes. Little is known about the effects of interspecies interactions on gene expression in these multispecies biofilms. This study presents a comparative gene expression analysis of the Xanthomonas retroflexus transcriptome when grown in a single-species biofilm and in dual- and four-species consortia with Stenotrophomonas rhizophila, Microbacterium oxydans and Paenibacillus amylolyticus. The results revealed complex interdependent interaction patterns in the multispecies biofilms. Many of the regulated functions are related to interactions with the external environment and suggest a high phenotypic plasticity in response to coexistence with other species. Furthermore, the changed expression of genes involved in aromatic and branched-chain amino acid biosynthesis suggests nutrient cross feeding as a contributing factor for the observed synergistic biofilm production when these four species coexists in a biofilm