Difference in distribution of microtubule-associated proteins 5a and 5b during the development of cerebral cortex and corpus callosum in cats: dependence on phosphorylation.

MAP5, a microtubule-associated protein characteristic of differentiating neurons, was studied in the developing visual cortex and corpus callosum of the cat. In juvenile cortical tissue, during the first month after birth, MAP5 is present as a protein doublet of molecular weights of 320 and 300 kDa, defined as MAP5a and MAP5b, respectively. MAP5a is the phosphorylated form. MAP5a decreases two weeks after birth and is no longer detectable at the beginning of the second postnatal month; MAP5b also decreases after the second postnatal week but more slowly and it is still present in the adult. In the corpus callosum only MAP5a is present between birth and the end of the first postnatal month. Afterwards only MAP5b is present but decreases in concentration more than 3-fold towards adulthood. Our immunocytochemical studies show MAP5 in somata, dendrites and axonal processes of cortical neurons. In adult tissue it is very prominent in pyramidal cells of layer V. In the corpus callosum MAP5 is present in axons at all ages. There is strong evidence that MAP5a is located in axons while MAP5b seems restricted to somata and dendrites until P28, but is found in callosal axons from P39 onwards. Biochemical experiments indicate that the state of phosphorylation of MAP5 influences its association with structural components. After high speed centrifugation of early postnatal brain tissue, MAP5a remains with pellet fractions while most MAP5b is soluble. In conclusion, phosphorylation of MAP5 may regulate (1) its intracellular distribution within axons and dendrites, and (2) its ability to interact with other subcellular components.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Reconsolidation of the soil surface after tillage discontinuity, with and without cultivation, related to erosion and its prediction with RUSLE

Site-specific regression coefficient values are essential for erosion prediction with empirical models. With the objective to investigate the surface-soilconsolidation factor, Cf, linked to the RUSLE's prior-land-use subfactor, PLU, an erosion experiment using simulated rainfall on a 0.075 m m-1 slope, sandy loam Paleudult soil, was conducted at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul (EEA/UFRGS), in Eldorado do Sul, State of Rio Grande do Sul, Brazil. Firstly, a row-cropped area was excluded from cultivation (March 1995), the existing crop residue removed from the field, and the soil kept clean-tilled the rest of the year (to get a degraded soil condition for the intended purpose of this research). The soil was then conventional-tilled for the last time (except for a standard plot which was kept continuously cleantilled for comparison purposes), in January 1996, and the following treatments were established and evaluated for soil reconsolidation and soil erosion until May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) fresh-tilled soil, continuously in clean-tilled fallow (unit plot); (b) reconsolidating soil without cultivation; and (c) reconsolidating soil with cultivation (a crop sequence of three corn- and two black oats cycles, continuously in no-till, removing the crop residues after each harvest for rainfall application and redistributing them on the site after that). Simulated rainfall was applied with a Swanson's type, rotating-boom rainfall simulator, at 63.5 mm h-1 intensity and 90 min duration, six times during the two-and-half years of experimental period (at the beginning of the study and after each crop harvest, with the soil in the unit plot being retilled before each rainfall test). The soil-surface-consolidation factor, Cf, was calculated by dividing soil loss values from the reconsolidating soil treatments by the average value from the fresh-tilled soil treatment (unit plot). Non-linear regression was used to fit the Cf = e b.t model through the calculated Cf-data, where t is time in days since last tillage. Values for b were -0.0020 for the reconsolidating soil without cultivation and -0.0031 for the one with cultivation, yielding Cf-values equal to 0.16 and 0.06, respectively, after two-and-half years of tillage discontinuation, compared to 1.0 for fresh-tilled soil. These estimated Cf-values correspond, respectively, to soil loss reductions of 84 and 94 %, in relation to soil loss from the fresh-tilled soil, showing that the soil surface reconsolidated intenser with cultivation than without it. Two distinct treatmentinherent soil surface conditions probably influenced the rapid decay-rate of Cf values in this study, but, as a matter of a fact, they were part of the real environmental field conditions. Cf-factor curves presented in this paper are therefore useful for predicting erosion with RUSLE, but their application is restricted to situations where both soil type and particular soil surface condition are similar to the ones investigate in this study.

Surface and subsurface decomposition of a desiccated grass pasture biomass related to erosion and its prediction with RUSLE

Erosion is deleterious because it reduces the soil's productivity capacity for growing crops and causes sedimentation and water pollution problems. Surface and buried crop residue, as well as live and dead plant roots, play an important role in erosion control. An efficient way to assess the effectiveness of such materials in erosion reduction is by means of decomposition constants as used within the Revised Universal Soil Loss Equation - RUSLE's prior-land-use subfactor - PLU. This was investigated using simulated rainfall on a 0.12 m m-1 slope, sandy loam Paleudult soil, at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul, in Eldorado do Sul, State of Rio Grande do Sul, Brazil. The study area had been covered by native grass pasture for about fifteen years. By the middle of March 1996, the sod was mechanically mowed and the crop residue removed from the field. Late in April 1996, the sod was chemically desiccated with herbicide and, about one month later, the following treatments were established and evaluated for sod biomass decomposition and soil erosion, from June 1996 to May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) and (b) soil without tillage, with surface residue and dead roots; (c) soil without tillage, with dead roots only; (d) soil tilled conventionally every two-and-half months, with dead roots plus incorporated residue; and (e) soil tilled conventionally every six months, with dead roots plus incorporated residue. Simulated rainfall was applied with a rotating-boom rainfall simulator, at an intensity of 63.5 mm h-1 for 90 min, eight to nine times during the experimental period (about every two-and-half months). Surface and subsurface sod biomass amounts were measured before each rainfall test along with the erosion measurements of runoff rate, sediment concentration in runoff, soil loss rate, and total soil loss. Non-linear regression analysis was performed using an exponential and a power model. Surface sod biomass decomposition was better depicted by the exponential model, while subsurface sod biomass was by the power model. Subsurface sod biomass decomposed faster and more than surface sod biomass, with dead roots in untilled soil without residue on the surface decomposing more than dead roots in untilled soil with surface residue. Tillage type and frequency did not appreciably influence subsurface sod biomass decomposition. Soil loss rates increased greatly with both surface sod biomass decomposition and decomposition of subsurface sod biomass in the conventionally tilled soil, but they were minimally affected by subsurface sod biomass decomposition in the untilled soil. Runoff rates were little affected by the studied treatments. Dead roots plus incorporated residues were effective in reducing erosion in the conventionally tilled soil, while consolidation of the soil surface was important in no-till. The residual effect of the turned soil on erosion diminished gradually with time and ceased after two years.

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelationbetween variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Chromosomal rearrangement and genetic structure in the shrews of the Sorex araneus group

ABSTRACT The role of chromosomal rearrangements in the speciation process is much debated and many theoretical models have been developed. The shrews of the Sorex araneus group offer extraordinary opportunities to study the relationship between chromosomal variation and speciation. Indeed, this group of morphologically very similar species received a great deal of attention due to its karyotypic variability, which is mainly attributed to Robertsonian fusions. To explore the impact of karyotypic changes on genetic differentiation, we first studied the relationship between genetic and karyotypic structure among Alpine species and among chromosome races of the S. araneus group using Bayesian admixture analyses. The results of these analyses confirmed the taxonomic status of the studied species even though introgression can still be detected between species. Moreover, the strong spatial sub-structure highlighted the role of historical factors (e.g. geographical isolation) on genetic structure. Next, we studied gene flow at the chromosome level to address the question of the impact of chromosomal rearrangements on genetic differentiation. We used flow sorted chromosomes from three different karyotypic taxa of the S. araneus group to map microsatellite markers at the chromosóme arm level. We have been able to map 24 markers and to show that the karyotypic organisation of these taxa is well conserved, which suggests that these markers can be used for further inter-taxa studies. A general prediction of chromosomal speciation models is that genetic differentiation between two taxa should be larger across rearranged chromosomes than across chromosomes common to both taxa. We combined two approaches using mapped microsatellites to test this prediction. First, we studied the genetic differentiation among five shrew taxa placed at different evolutionary levels (i.e. within and among species). In this large scale study, we detected an overall significant difference in genetic structure between rearranged vs. common chromosomes. Moreover, this effect varied among pairwise comparisons, which allowed us to differentiate the role of the karyotypic complexity of hybrids and of the evolutionary divergence between taxa. Secondly, we compared the levels of gene flow measured across common vs. rearranged chromosomes in two karyotypically different hybrid zones (strong vs. low complexity of hybrids), which show similar levels of genetic structure. We detected a significantly stronger genetic structure across rearranged chromosomes in the hybrid zone showing the highest level of hybrid complexity. The large variance observed among loci suggested that other factors, such as the position of markers within the chromosome, also certainly affects genetic structure. In conclusion, our results strongly support the role of chromosomal rearrangements in the reproductive barrier and suggest their importance in speciation process of the S. araneus group. RESUME Le rôle des réarrangements chromosomiques dans les processus de spéciation est fortement débattu et de nombreux modèles théoriques ont été développés sur le sujet. Les musaraignes du groupe Sorex araneus présentent de nombreuses opportunités pour étudier les relations entre les variations chromosomiques et la spéciation. En effet, ce groupe d'espèces morphologiquement très proches a attiré l'attention des chercheurs en raison de sa variabilité caryotypique principalement attribuée à des fusions Robertsoniennes. Pour explorer l'impact des changements caryotypiques sur la différenciation génétique, nous avons tout d'abord étudié les relations entre la structure génétique et caryotypique de races chromosomiques et d'espèces alpine du groupe S. araneus en utilisant des analyses Bayesiennes d' « admixture ». Les résultats de ces analyses ont confirmé le statut taxonomique des espèces étudiées bien que nous ayons détecté de l'introgression entre espèces. L'observation d'une sous structure spatiale relativement forte souligne l'importance des facteurs historiques (telle que l'isolation géographique) sur la structure génétique de ce groupe. Ensuite, nous avons étudié le flux de gène au niveau des chromosomes pour aborder de manière directe la question de l'impact des réarrangements chromosomiques sur la différenciation génétique. En conséquence, nous avons utilisé des tris de chromosomes de trois taxons du groupe S. araneus pour localiser des marqueurs microsatellites au niveau du bras chromosomique. Au cours de cette étude, nous avons pu localiser 24 marqueurs et montrer une forte conservation dans l'organisation du caryotype de ces taxa. Ce résultat suggère que leur utilisation est appropriée pour des études entre taxa. Une prédiction générale à tous les modèles de spéciation chromosomique correspond à la plus grande différenciation génétique des chromosomes réarrangés que des chromosomes communs. Nous avons combiné deux approches utilisant des microsatellites localisés au niveau du bras chromosomique pour tester cette prédiction. Premièrement, nous avons étudié la différenciation génétique entre cinq taxa du groupe S. araneus se trouvant à des niveaux évolutifs différents (i.e. à l'intérieur et entre espèce). Au cours de cette étude, nous avons détecté une différenciation globale significativement plus élevée sur les chromosomes réarrangés. Cet effet varie entre les comparaisons, ce qui nous a permis de souligner le rôle de la complexité caryotypique des hybrides et du niveau de divergence évolutive entre taxa. Deuxièmement, nous avons comparé le flux de gènes des chromosomes communs et réarrangés dans deux zones d'hybridation caryotypiquement différentes (forte vs. Faible complexité des hybrides) mais présentant un niveau de différenciation génétique similaire. Ceci nous a permis de détecter une structure génétique significativement plus élevée sur les chromosomes réarrangés au centre de la zone d'hybridation présentant la plus grande complexité caryotypic. La forte variance observée entre loci souligne en outre le fait que d'autres facteurs, tel que la position du marqueur sur le chromosome, affectent probablement aussi la structure génétique mesurée. En conclusion, nos résultats supportent fortement le rôle des réarrangements chromosomiques dans la barrière reproductive entre espèces ainsi que leur importance dans les processus de spéciation des musaraignes du groupe S. araneus.

Integrated Analysis of High-Resolution Gene Expression and Copy Number Profiling Identified Biallelic Deletion of CDKN2A/2B Tumor Suppressor Locus As the Most Frequent and Unique Genomic Abnormality in Diffuse Large B-Cell Lymphoma (DLBCL) with Strong Prognostic Value in Both GCB and ABC Subtypes and Not Overcome by a Dose-Intensive Immunochemotherapy Regimen Plus Rituximab. Results of a Prospective GELA Clinical Trial Program

Background and aim of the study: Genomic gains and losses play a crucial role in the development and progression of DLBCL and are closely related to gene expression profiles (GEP), including the germinal center B-cell like (GCB) and activated B-cell like (ABC) cell of origin (COO) molecular signatures. To identify new oncogenes or tumor suppressor genes (TSG) involved in DLBCL pathogenesis and to determine their prognostic values, an integrated analysis of high-resolution gene expression and copy number profiling was performed. Patients and methods: Two hundred and eight adult patients with de novo CD20+ DLBCL enrolled in the prospective multicentric randomized LNH-03 GELA trials (LNH03-1B, -2B, -3B, 39B, -5B, -6B, -7B) with available frozen tumour samples, centralized reviewing and adequate DNA/RNA quality were selected. 116 patients were treated by Rituximab(R)-CHOP/R-miniCHOP and 92 patients were treated by the high dose (R)-ACVBP regimen dedicated to patients younger than 60 years (y) in frontline. Tumour samples were simultaneously analysed by high resolution comparative genomic hybridization (CGH, Agilent, 144K) and gene expression arrays (Affymetrix, U133+2). Minimal common regions (MCR), as defined by segments that affect the same chromosomal region in different cases, were delineated. Gene expression and MCR data sets were merged using Gene expression and dosage integrator algorithm (GEDI, Lenz et al. PNAS 2008) to identify new potential driver genes. Results: A total of 1363 recurrent (defined by a penetrance > 5%) MCRs within the DLBCL data set, ranging in size from 386 bp, affecting a single gene, to more than 24 Mb were identified by CGH. Of these MCRs, 756 (55%) showed a significant association with gene expression: 396 (59%) gains, 354 (52%) single-copy deletions, and 6 (67%) homozygous deletions. By this integrated approach, in addition to previously reported genes (CDKN2A/2B, PTEN, DLEU2, TNFAIP3, B2M, CD58, TNFRSF14, FOXP1, REL...), several genes targeted by gene copy abnormalities with a dosage effect and potential physiopathological impact were identified, including genes with TSG activity involved in cell cycle (HACE1, CDKN2C) immune response (CD68, CD177, CD70, TNFSF9, IRAK2), DNA integrity (XRCC2, BRCA1, NCOR1, NF1, FHIT) or oncogenic functions (CD79b, PTPRT, MALT1, AUTS2, MCL1, PTTG1...) with distinct distribution according to COO signature. The CDKN2A/2B tumor suppressor locus (9p21) was deleted homozygously in 27% of cases and hemizygously in 9% of cases. Biallelic loss was observed in 49% of ABC DLBCL and in 10% of GCB DLBCL. This deletion was strongly correlated to age and associated to a limited number of additional genetic abnormalities including trisomy 3, 18 and short gains/losses of Chr. 1, 2, 19 regions (FDR < 0.01), allowing to identify genes that may have synergistic effects with CDKN2A/2B inactivation. With a median follow-up of 42.9 months, only CDKN2A/2B biallelic deletion strongly correlates (FDR p.value < 0.01) to a poor outcome in the entire cohort (4y PFS = 44% [32-61] respectively vs. 74% [66-82] for patients in germline configuration; 4y OS = 53% [39-72] vs 83% [76-90]). In a Cox proportional hazard prediction of the PFS, CDKN2A/2B deletion remains predictive (HR = 1.9 [1.1-3.2], p = 0.02) when combined with IPI (HR = 2.4 [1.4-4.1], p = 0.001) and GCB status (HR = 1.3 [0.8-2.3], p = 0.31). This difference remains predictive in the subgroup of patients treated by R-CHOP (4y PFS = 43% [29-63] vs. 66% [55-78], p=0.02), in patients treated by R-ACVBP (4y PFS = 49% [28-84] vs. 83% [74-92], p=0.003), and in GCB (4y PFS = 50% [27-93] vs. 81% [73-90], p=0.02), or ABC/unclassified (5y PFS = 42% [28-61] vs. 67% [55-82] p = 0.009) molecular subtypes (Figure 1). Conclusion: We report for the first time an integrated genetic analysis of a large cohort of DLBCL patients included in a prospective multicentric clinical trial program allowing identifying new potential driver genes with pathogenic impact. However CDKN2A/2B deletion constitutes the strongest and unique prognostic factor of chemoresistance to R-CHOP, regardless the COO signature, which is not overcome by a more intensified immunochemotherapy. Patients displaying this frequent genomic abnormality warrant new and dedicated therapeutic approaches.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

Comparison of fundus autofluorescence between fundus camera (Topcon) and confocal scanning laser ophthalmoscope (HRA) in various pathologies

Purpose: To investigate the differences between Fundus Camera (Topcon TRC-50X) and Confocal Scanning Laser Ophthalmoscope (Heidelberg retina angiogram (HRA)) on the fundus autofluorescence (FAF) imaging (resolution and FAF characteristics). Methods: 105 eyes of 56 patients with various retinal diseases underwent FAF imaging with HRA (488nm exciter/500nm barrier filter) before fluorescein angiography (FFA) and Topcon Fundus Camera (580nm exciter/695nm barrier filter) before and after FFA. The quality of the FAF images was compared for their resolution and analysed for the influence of fixation stability and cataracts. Hypo-and hyper-FAF behaviour was analysed for the healthy disc, healthy fovea, and a variety of pathological features. Results: HRA images were found to be of superior resolution in 18, while Topcon images were estimated superior in 29 eyes. No difference was found in 58 eyes. Both poor fixation (p=0.009) and more advanced cataract (p=0.013) were found associated with better image quality by Topcon. Images acquired by Topcon before and after FFA were identical (100%). The healthy disc was usually dark on HRA (72%), but showed mild autofluorescence on Topcon (85%). The healthy fovea showed in 100% Hypo-FAF on HRA, while Topcon showed in 53% Iso-FAF, in 43% mild Hypo-FAF, and in 4% Hypo-FAF as on HRA. No difference of FAF was found for geographic atrophy, pigment changes, and drusen, although Topcon images were often more detailed. Hyper-FAF due to serous exudation showed better on HRA. Cystic edema was visible only on HRA in a petaloid hyper-FAF pattern in 83%, while only two eyes (17%) showed similar behavior in both HRA- and Topcon images. Hard exudates caused Hypo-FAF only on HRA, hardly visible on Topcon. Blockage phenomenon by blood however was identical. Conclusions: The filter set of Topcon and the single image acquisition appear to be an advantage for patients with cataract and poor fixation respectively. Preceding FFA does not alter the Topcon FAF image. Regarding the FAF behavior, there are differences between the 2 systems which need to be taken into account when interpreting the images.

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.

Sarcomas are heterogeneous and aggressive mesenchymal tumors. Histological grading has so far been the best predictor for metastasis-free survival, but it has several limitations, such as moderate reproducibility and poor prognostic value for some histological types. To improve patient grading, we performed genomic and expression profiling in a training set of 183 sarcomas and established a prognostic gene expression signature, complexity index in sarcomas (CINSARC), composed of 67 genes related to mitosis and chromosome management. In a multivariate analysis, CINSARC predicts metastasis outcome in the training set and in an independent 127 sarcomas validation set. It is superior to the Fédération Francaise des Centres de Lutte Contre le Cancer grading system in determining metastatic outcome for sarcoma patients. Furthermore, it also predicts outcome for gastrointestinal stromal tumors (GISTs), breast carcinomas and lymphomas. Application of the signature will permit more selective use of adjuvant therapies for people with sarcomas, leading to decreased iatrogenic morbidity and improved outcomes for such individuals.