ЭФФЕКТИВНОСТЬ НОЧНОЙ ИНТУБАЦИИ ПРИ ОПЕРАЦИЯХ ПО ПОВОДУ РАКА ОРГАНОВ ПОЛОСТИ РТА – РЕТРОСПЕКТИВНОЕ ИССЛЕДОВАНИЕ

In the post-operative period of maxillofacial oncological operations, tracheostomy is the most commonly used method for securing the airway. These untoward complications made practitioners choose alternative modalities like submental intubation, but literature support on alternatives to tracheostomy for oral oncologic cases is limited. The aim of this observational study is to ascertain whether the use of overnight intubation is a safer and cost-effective practice and if it can be considered an alternative to tracheostomy.Material and methods. 30 patients, 23 males and 7 females in the age group of 34–80 years who underwent treatment for head and neck cancer with major intraoral resection and a unilateral or bilateral neck dissection were included in the study. The following variables were recorded: age, sex, site of tumour, type of neck dissection, use of mandibulotomy/ mandibulectomy, type of reconstruction, duration of stay in ICU, mean hospital stay and Mallampati classification. Postoperative complications, associated with the airway, if any, were recorded simultaneously.Results. None of the 30 patients required re-intubation nor did they develop any respiratory distress post extubation.Conclusion. The purpose of this study is to raise the conscience of every surgeon to cogitate his/her choice of procedure for his/her patients and advocate the use of overnight intubation, as it is a virtuous alternative to tracheostomy.В послеоперационном периоде у больных со злокачественными новообразованиями челюстно-лицевой области трахеостомия является самым распространенным методом, обеспечивающим проходимость воздушных путей. Осложнения трахеостомии побуждают врачей выбирать альтернативные методы, такие как субментальная интубация трахеи. Литературные данные об альтернативных трахеостомии методах при операциях по поводу опухолей органов полости рта ограничены.Цель исследования – выяснить, является ли использование ночной интубации более безопасной и рентабельной по цене, можно ли считать её альтернативой трахеостомии.Материал и методы. Исследование включало 30 больных раком органов головы и шеи (23 мужчины и 7 женщин) в возрасте 34–80 лет, которым была произведена внутриротовая резекция органов полости рта в большом объеме и односторонняя или двусторонняя шейная диссекция. Учитывались следующие параметры: возраст, пол, локализация опухоли, тип шейной диссекции, применение мандибулотомии/мандибулэктомии, тип реконструкции, продолжительность пребывания в реанимации, среднее время пребывания в больнице и классификация Маллампати. Также велась регистрация послеоперационных осложнений, связанных с обеспечением проходимости дыхательных путей.Результаты. Ни один из 30 пациентов не нуждался в повторной интубации, и у них не возникало каких-либо респираторных дистрессов после экстубации.Заключение. Цель этого исследования заключалось в том, чтобы каждый хирург мог обдумать и взвесить свой выбор процедуры для конкретного больного и выступить в поддержку ночной интубации как эффективной альтернативы трахеостомии

Promoter analysis by saturation mutagenesis

Gene expression and regulation are mediated by DNA sequences, in most instances, directly upstream to the coding sequences by recruiting transcription factors, regulators, and a RNA polymerase in a spatially defined fashion. Few nucleotides within a promoter make contact with the bound proteins. The minimal set of nucleotides that can recruit a protein factor is called a cis-acting element. This article addresses a powerful mutagenesis strategy that can be employed to define cis-acting elements at a molecular level. Technical details including primer design, saturation mutagenesis, construction of promoter libraries, phenotypic analysis, data analysis, and interpretation are discussed

Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks

BACKGROUND: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the search space by means of clustering genes into putatively co-regulated groups, as opposed to those that are simply co-expressed. Be cause genes may be co-regulated only across a subset of all observed experimental conditions, biclustering (clustering of genes and conditions) is more appropriate than standard clustering. Co-regulated genes are also often functionally (physically, spatially, genetically, and/or evolutionarily) associated, and such a priori known or pre-computed associations can provide support for appropriately grouping genes. One important association is the presence of one or more common cis-regulatory motifs. In organisms where these motifs are not known, their de novo detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions. RESULTS: We have developed an algorithm, cMonkey, that detects putative co-regulated gene groupings by integrating the biclustering of gene expression data and various functional associations with the de novo detection of sequence motifs. CONCLUSION: We have applied this procedure to the archaeon Halobacterium NRC-1, as part of our efforts to decipher its regulatory network. In addition, we used cMonkey on public data for three organisms in the other two domains of life: Helicobacter pylori, Saccharomyces cerevisiae, and Escherichia coli. The biclusters detected by cMonkey both recapitulated known biology and enabled novel predictions (some for Halobacterium were subsequently confirmed in the laboratory). For example, it identified the bacteriorhodopsin regulon, assigned additional genes to this regulon with apparently unrelated function, and detected its known promoter motif. We have performed a thorough comparison of cMonkey results against other clustering methods, and find that cMonkey biclusters are more parsimonious with all available evidence for co-regulation

Gasifier-based power generation: technology and economics

The paper describes a 100 kW power generation system installed at Port Blair, Andaman and Nicobar Islands, under a project sponsored by the Department of Non-Conventional Energy Sources, Government of India. The system consists of a wood gasifier utilising the waste wood from a saw mill and a diesel engine genset. The performance of the total system and its elements are presented along with economics of operation. To bring out the economics of using such renewable energy devices for power generation, some realistic situations are considered for which the effective cost of power and the pay-back period for the investment are evaluated. The economics is compared with that of a similar system of 3.7 kW capacity

Five-kilowatt wood gasifier technology: evolution and field experience

Various elements of an efficient and reliable 5k W wood gasifier system developed over the last ten years are described. The good performance obtained from the system is related to the careful design of its components and sub-systems. Results from extensive testing of gasifier prototypes at two national centres are discussed along with the experience gained in the field from their use at more than one hundred and fifty locations spread over five states in the country. Issues related to acceptance of the technology are also included. Improvements in design to extend the life, to reduce the cost, and to reduce the number of components are also discussed. A few variants of the design to meet the specific requirements of water pumping, power generation and to exploit specific site characteristics are presented

Classifying the Arithmetical Complexity of Teaching Models

This paper classifies the complexity of various teaching models by their position in the arithmetical hierarchy. In particular, we determine the arithmetical complexity of the index sets of the following classes: (1) the class of uniformly r.e. families with finite teaching dimension, and (2) the class of uniformly r.e. families with finite positive recursive teaching dimension witnessed by a uniformly r.e. teaching sequence. We also derive the arithmetical complexity of several other decision problems in teaching, such as the problem of deciding, given an effective coding $\{\mathcal L_0,\mathcal L_1,\mathcal L_2,\ldots\}$ of all uniformly r.e. families, any $e$ such that $\mathcal L_e = \{L^e_0,L^e_1,\ldots,\}$, any $i$ and $d$, whether or not the teaching dimension of $L^e_i$ with respect to $\mathcal L_e$ is upper bounded by $d$.Comment: 15 pages in International Conference on Algorithmic Learning Theory, 201

Molecular Assemblies, Genes and Genomics Integrated Efficiently (MAGGIE)

Final report on MAGGIE. We set ambitious goals to model the functions of individual organisms and their community from molecular to systems scale. These scientific goals are driving the development of sophisticated algorithms to analyze large amounts of experimental measurements made using high throughput technologies to explain and predict how the environment influences biological function at multiple scales and how the microbial systems in turn modify the environment. By experimentally evaluating predictions made using these models we will test the degree to which our quantitative multiscale understanding wilt help to rationally steer individual microbes and their communities towards specific tasks. Towards this end we have made substantial progress towards understanding evolution of gene families, transcriptional structures, detailed structures of keystone molecular assemblies (proteins and complexes), protein interactions, biological networks, microbial interactions, and community structure. Using comparative analysis we have tracked the evolutionary history of gene functions to understand how novel functions evolve. One level up, we have used proteomics data, high-resolution genome tiling microarrays, and 5' RNA sequencing to revise genome annotations, discover new genes including ncRNAs, and map dynamically changing operon structures of five model organisms: For Desulfovibrio vulgaris Hildenborough, Pyrococcus furiosis, Sulfolobus solfataricus, Methanococcus maripaludis and Haiobacterium salinarum NROL We have developed machine learning algorithms to accurately identify protein interactions at a near-zero false positive rate from noisy data generated using tagfess complex purification, TAP purification, and analysis of membrane complexes. Combining other genome-scale datasets produced by ENIGMA (in particular, microarray data) and available from literature we have been able to achieve a true positive rate as high as 65% at almost zero false positives when applied to the manually curated training set. Applying this method to the data representing around a quarter of the fraction space for water soluble proteins in D. vulgaris, we obtained 854 reliable pair wise interactions. Further, we have developed algorithms to analyze and assign significance to protein interaction data from bait pull-down experiments and integrate these data with other systems biology data through associative biclustering in a parallel computing environment. We will 'fill-in' missing information in these interaction data using a 'Transitive Closure' algorithm and subsequently use 'Between Commonality Decomposition' algorithm to discover complexes within these large graphs of protein interactions. To characterize the metabolic activities of proteins and their complexes we are developing algorithms to deconvolute pure mass spectra, estimate chemical formula for m/z values, and fit isotopic fine structure to metabolomics data. We have discovered that in comparison to isotopic pattern fitting methods restricting the chemical formula by these two dimensions actually facilitates unique solutions for chemical formula generators. To understand how microbial functions are regulated we have developed complementary algorithms for reconstructing gene regulatory networks (GRNs). Whereas the network inference algorithms cMonkey and Inferelator developed enable de novo reconstruction of predictive models for GRNs from diverse systems biology data, the RegPrecise and RegPredict framework developed uses evolutionary comparisons of genomes from closely related organisms to reconstruct conserved regulons. We have integrated the two complementary algorithms to rapidly generate comprehensive models for gene regulation of understudied organisms. Our preliminary analyses of these reconstructed GRNs have revealed novel regulatory mechanisms and cis-regulatory motifs, as well asothers that are conserved across species. Finally, we are supporting scientific efforts in ENIGMA with data management solutions and by integrating all of the algorithms, software and data into a Knowledgebase. For instance, we have developed the RegPrecise database (http://regprecise.lbl.gov) which represents manually curated sets of regulons laying the basis for automatic annotation of regulatory interactions in closely related species. We are also in the midst of scaling up MicrobesOnline to handle the growing volume of sequence and functional genomics data. Over the last year our efforts have been focused on providing support for additional genomic and functional genomic data types. Similarly, we have developed several visualization tools to help with the exploration of complex systems biology datasets. A case in point is the Gaggle Genome Browser (GGB), which was enhanced with visualizations for plotting peptide detections and protein-DNA binding alongside transcriptome structure, plus the ability to interactively filter by signal intensity or p-value

A Map of Update Constraints in Inductive Inference

We investigate how different learning restrictions reduce learning power and how the different restrictions relate to one another. We give a complete map for nine different restrictions both for the cases of complete information learning and set-driven learning. This completes the picture for these well-studied \emph{delayable} learning restrictions. A further insight is gained by different characterizations of \emph{conservative} learning in terms of variants of \emph{cautious} learning. Our analyses greatly benefit from general theorems we give, for example showing that learners with exclusively delayable restrictions can always be assumed total.Comment: fixed a mistake in Theorem 21, result is the sam