Interchange of callosal and association projections in the developing visual cortex.

Neurons projecting transitorily into the corpus callosum from area 17 of the cat were retrogradely labeled by the fluorescent tracer Fast Blue (FB) injected into contralateral areas 17 and 18 on postnatal days 1-5. During the second postnatal month these neurons were still labeled by the early injection, although they had eliminated their callosal axon. At this time, 15-20% of these neurons could be retrogradely relabeled by injections of Diamidino Yellow (DY) into ipsilateral areas 17 and 18, but few or none by similar injections in the other areas that receive from area 17 (19, 21a, PMLS, 20a, 20b, DLS). Similarly, area 17 neurons projecting transitorily to contralateral area PMLS during the first postnatal week could be relabeled by DY injections in ipsilateral areas 17 and 18 but not in PMLS. Already around birth, many transitorily callosal neurons in area 17 send bifurcating axons both to contralateral areas 17 and 18 and ipsilateral area 18. It is probable that during postnatal development some of these neurons selectively eliminate their callosal axon collaterals and maintain the projection to ipsilateral area 18. In fact, some transitorily callosal neurons in area 17 can be double-labeled by simultaneous perinatal injections of FB in contralateral areas 17 and 18 and of a new long-lasting retrograde tracer, rhodamine-conjugated latex microspheres, in ipsilateral area 18. The same neurons can then be relabeled by reinjecting ipsilateral area 18 with DY during the second postnatal month. This finding, however, does not exclude the possibility that some transitorily callosal neurons send an axon to ipsilateral area 18 after eliminating their callosal axon. In conclusion, area 17 neurons that project transitorily through the corpus callosum later participate, probably permanently, in ipsilateral corticocortical projections but selectively to areas 17-18. The mechanism responsible for this selectivity is unknown, but it may be related to the differential radial distribution (i.e., to birth date) of area 17 neurons engaged in the various corticocortical projections. The problems raised by the use of long-lasting retrograde fluorescent tracers in neurodevelopmental studies and by the quantification of results of double- and triple-labeling paradigms are also discussed.

Respiratory variability in mechanically ventilated patients. Critical Care 2011

Introduction: Increased respiratory pattern variability is associated with improved oxygenation. Pressure support (PS) is a widely used partial-assist mechanical ventilation (MV) mode, in which each breathing cycle is initiated by flow or pressure variation at the airway due to patient inspiratory effort. Neurally adjusted ventilatory assist (NAVA) is relatively new and uses the electrical activity of the diaphragm (Eadi) to deliver ventilatory support proportional to the patient's inspiratory demand. We hypothesize that respiratory variability should be greater with NAVA compared with PS.Methods: Twenty-two patients underwent 20 minutes of PS followed by 20 minutes of NAVA. Flow and Eadi curves were used to obtain tidal volume (Vt) and ∫Eadi for 300 to 400 breaths in each patient. Patient-specific cumulative distribution functions (CDF) show the percentage Vt and ∫Eadi within a clinically defined (±10%) variability band for each patient. Values are normalized to patient-specific medians for direct comparison. Variability in Vt (outcome) is thus expressed in terms of variability in ∫Eadi (demand) on the same plot.Results: Variability in Vt relative to variability in ∫Eadi is significantly greater for NAVA than PS (P = 0.00012). Hence, greater variability in outcome Vt is obtained for a given demand in ∫Eadi, under NAVA, as illustrated in Figure 1 for a typical patient. A Fisher 2 × 2 contingency analysis showed that 45% of patients under NAVA had a Vt variability in equal proportion to ∫Eadi variability, versus 0% for PS (P < 0.05).Conclusions: NAVA yields greater variability in tidal volume, relative to ∫Eadi demand, and a better match between Vt and ∫Eadi. These results indicate that NAVA could achieve improved oxygenation compared with PS when sufficient underlying variability in ∫Eadi is present, due to its ability to achieve higher tidal volume variability from a given variability in ∫Eadi.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

En face optical coherence tomography of foveal microstructure in full-thickness macular hole: a model to study perifoveal müller cells.

PURPOSE: To characterize perifoveal intraretinal cavities observed around full-thickness macular holes (MH) using en face optical coherence tomography and to establish correlations with histology of human and primate maculae. DESIGN: Retrospective nonconsecutive observational case series. METHODS: Macular en face scans of 8 patients with MH were analyzed to quantify the areas of hyporeflective spaces, and were compared with macular flat mounts and sections from 1 normal human donor eye and 2 normal primate eyes (Macaca fascicularis). Immunohistochemistry was used to study the distribution of glutamine synthetase, expressed by Müller cells, and zonula occludens-1, a tight-junction protein. RESULTS: The mean area of hyporeflective spaces was lower in the inner nuclear layer (INL) than in the complex formed by the outer plexiform (OPL) and the Henle fiber layers (HFL): 5.0 × 10(-3) mm(2) vs 15.9 × 10(-3) mm(2), respectively (P < .0001, Kruskal-Wallis test). In the OPL and HFL, cavities were elongated with a stellate pattern, whereas in the INL they were rounded and formed vertical cylinders. Immunohistochemistry confirmed that Müller cells followed a radial distribution around the fovea in the frontal plane and a "Z-shaped" course in the axial plane, running obliquely in the OPL and HFL and vertically in the inner layers. In addition, zonula occludens-1 co-localized with Müller cells within the complex of OPL and HFL, indicating junctions in between Müller cells and cone axons. CONCLUSION: The dual profile of cavities around MHs correlates with Müller cell morphology and is consistent with the hypothesis of intra- or extracellular fluid accumulation along these cells.

A Population-Based Model to Consider the Effect of Seasonal Variation on Serum 25(OH)D and Vitamin D Status.

Background. We elaborated a model that predicts the centiles of the 25(OH)D distribution taking into account seasonal variation. Methods. Data from two Swiss population-based studies were used to generate (CoLaus) and validate (Bus Santé) the model. Serum 25(OH)D was measured by ultra high pressure LC-MS/MS and immunoassay. Linear regression models on square-root transformed 25(OH)D values were used to predict centiles of the 25(OH)D distribution. Distribution functions of the observations from the replication set predicted with the model were inspected to assess replication. Results. Overall, 4,912 and 2,537 Caucasians were included in original and replication sets, respectively. Mean (SD) 25(OH)D, age, BMI, and % of men were 47.5 (22.1) nmol/L, 49.8 (8.5) years, 25.6 (4.1) kg/m(2), and 49.3% in the original study. The best model included gender, BMI, and sin-cos functions of measurement day. Sex- and BMI-specific 25(OH)D centile curves as a function of measurement date were generated. The model estimates any centile of the 25(OH)D distribution for given values of sex, BMI, and date and the quantile corresponding to a 25(OH)D measurement. Conclusions. We generated and validated centile curves of 25(OH)D in the general adult Caucasian population. These curves can help rank vitamin D centile independently of when 25(OH)D is measured.

Geospatial approach for defining the Wildland-Urban Interface in the Alpine environment

Problems related to fire hazard and fire management have become in recent decades one of the most relevant issues in the Wildland-Urban Interface (WUI), that is the area where human infrastructures meet or intermingle with natural vegetation. In this paper we develop a robust geospatial method for defining and mapping the WUI in the Alpine environment, where most interactions between infrastructures and wildland vegetation concern the fire ignition through human activities, whereas no significant threats exist for infrastructures due to contact with burning vegetation. We used the three Alpine Swiss cantons of Ticino, Valais and Grisons as the study area. The features representing anthropogenic infrastructures (urban or infrastructural components of the WUI) as well as forest cover related features (wildland component of the WUI) were selected from the Swiss Topographic Landscape Model (TLM3D). Georeferenced forest fire occurrences derived from the WSL Swissfire database were used to define suitable WUI interface distances. The Random Forest algorithm was applied to estimate the importance of predictor variables to fire ignition occurrence. This revealed that buildings and drivable roads are the most relevant anthropogenic components with respect to fire ignition. We consequently defined the combination of drivable roads and easily accessible (i.e. 100 m from the next drivable road) buildings as the WUI-relevant infrastructural component. For the definition of the interface (buffer) distance between WUI infrastructural and wildland components, we computed the empirical cumulative distribution functions (ECDF) of the percentage of ignition points (observed and simulated) arising at increasing distances from the selected infrastructures. The ECDF facilitates the calculation of both the distance at which a given percentage of ignition points occurred and, in turn, the amount of forest area covered at a given distance. Finally, we developed a GIS ModelBuilder routine to map the WUI for the selected buffer distance. The approach was found to be reproducible, robust (based on statistical analyses for evaluating parameters) and flexible (buffer distances depending on the targeted final area covered) so that fire managers may use it to detect WUI according to their specific priorities.

Distribution of the human intracellular serpin protease inhibitor 8 in human tissues.

Ovalbumin-like serine protease inhibitors are mainly localized intracellularly and their in vivo functions are largely unknown. To elucidate their physiological role(s), we studied the expression of one of these inhibitors, protease inhibitor 8 (PI-8), in normal human tissues by immunohistochemistry using a PI-8-specific monoclonal antibody. PI-8 was strongly expressed in the nuclei of squamous epithelium of mouth, pharynx, esophagus, and epidermis, and by the epithelial layer of skin appendages, particularly by more differentiated epithelial cells. PI-8 was also expressed by monocytes and by neuroendocrine cells in the pituitary gland, pancreas, and digestive tract. Monocytes showed nuclear and cytoplasmic localization of PI-8, whereas neuroendocrine cells showed only cytoplasmic staining. In vitro nuclear localization of PI-8 was confirmed by confocal analysis using serpin-transfected HeLa cells. Furthermore, mutation of the P(1) residue did not affect the subcellular distribution pattern of PI-8, indicating that its nuclear localization is independent of the interaction with its target protease. We conclude that PI-8 has a unique distribution pattern in human tissues compared to the distribution patterns of other intracellular serpins. Additional studies must be performed to elucidate its physiological role.

Differential expression of peroxisome proliferator-activated receptors (PPARs): tissue distribution of PPAR-alpha, -beta, and -gamma in the adult rat.

Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily that can be activated by various xenobiotics and natural fatty acids. These transcription factors primarily regulate genes involved in lipid metabolism and also play a role in adipocyte differentiation. We present the expression patterns of the PPAR subtypes in the adult rat, determined by in situ hybridization using specific probes for PPAR-alpha, -beta and -gamma, and by immunohistochemistry using a polyclonal antibody that recognizes the three rat PPAR subtypes. In numerous cell types from either ectodermal, mesodermal, or endodermal origin, PPARs are coexpressed, with relative levels varying between them from one cell type to the other. PPAR-alpha is highly expressed in hepatocytes, cardiomyocytes, enterocytes, and the proximal tubule cells of kidney. PPAR-beta is expressed ubiquitously and often at higher levels than PPAR-alpha and -gamma. PPAR-gamma is expressed predominantly in adipose tissue and the immune system. Our results suggest new potential directions to investigate the functions of the different PPAR subtypes.

Peroxisome proliferator-activated receptors: insight into multiple cellular functions.

Peroxisome proliferator-activated receptors, PPARs, (NR1C) are nuclear hormone receptors implicated in energy homeostasis. Upon activation, these ligand-inducible transcription factors stimulate gene expression by binding to the promoter of target genes. The different structural domains of PPARs are presented in terms of activation mechanisms, namely ligand binding, phosphorylation, and cofactor interaction. The specificity of ligands, such as fatty acids, eicosanoids, fibrates and thiazolidinediones (TZD), is described for each of the three PPAR isotypes, alpha (NR1C1), beta (NR1C2) and gamma (NR1C3), so as the differential tissue distribution of these isotypes. Finally, general and specific functions of the PPAR isotypes are discussed, namely their implication in the control of inflammatory responses, cell proliferation and differentiation, the roles of PPARalpha in fatty acid catabolism and of PPARgamma in adipogenesis.

Spin-labeling coronary MR angiography with steady-state free precession and radial k-space sampling: initial results in healthy volunteers.

The purpose of this study was to prospectively compare free-breathing navigator-gated cardiac-triggered three-dimensional steady-state free precession (SSFP) spin-labeling coronary magnetic resonance (MR) angiography performed by using Cartesian k-space sampling with that performed by using radial k-space sampling. A new dedicated placement of the two-dimensional selective labeling pulse and an individually adjusted labeling delay time approved by the institutional review board were used. In 14 volunteers (eight men, six women; mean age, 28.8 years) who gave informed consent, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, vessel length, and subjective image quality were investigated. Differences between groups were analyzed with nonparametric tests (Wilcoxon, Pearson chi2). Radial imaging, as compared with Cartesian imaging, resulted in a significant reduction in the severity of motion artifacts, as well as an increase in SNR (26.9 vs 12.0, P < .05) in the coronary arteries and CNR (23.1 vs 8.8, P < .05) between the coronary arteries and the myocardium. A tendency toward improved vessel sharpness and vessel length was also found with radial imaging. Radial SSFP imaging is a promising technique for spin-labeling coronary MR angiography.

Free-breathing renal magnetic resonance angiography with steady-state free-precession and slab-selective spin inversion combined with radial k-space sampling and water-selective excitation.

The impact of radial k-space sampling and water-selective excitation on a novel navigator-gated cardiac-triggered slab-selective inversion prepared 3D steady-state free-precession (SSFP) renal MR angiography (MRA) sequence was investigated. Renal MRA was performed on a 1.5-T MR system using three inversion prepared SSFP approaches: Cartesian (TR/TE: 5.7/2.8 ms, FA: 85 degrees), radial (TR/TE: 5.5/2.7 ms, FA: 85 degrees) SSFP, and radial SSFP combined with water-selective excitation (TR/TE: 9.9/4.9 ms, FA: 85 degrees). Radial data acquisition lead to significantly reduced motion artifacts (P < 0.05). SNR and CNR were best using Cartesian SSFP (P < 0.05). Vessel sharpness and vessel length were comparable in all sequences. The addition of a water-selective excitation could not improve image quality. In conclusion, radial k-space sampling reduces motion artifacts significantly in slab-selective inversion prepared renal MRA, while SNR and CNR are decreased. The addition of water-selective excitation could not improve the lower CNR in radial scanning.

Radial transport of nutrients: the plant root as a polarized epithelium.

In higher plants, roots acquire water and soil nutrients and transport them upward to their aerial parts. These functions are closely related to their anatomical structure; water and nutrients entering the root first move radially through several concentric layers of the epidermis, cortex, and endodermis before entering the central cylinder. The endodermis is the innermost cortical cell layer that features rings of hydrophobic cell wall material called the Casparian strips, which functionally resemble tight junctions in animal epithelia. Nutrient uptake from the soil can occur through three different routes that can be interconnected in various ways: the apoplastic route (through the cell wall), the symplastic route (through cellular connections), and a coupled trans-cellular route (involving polarized influx and efflux carriers). This Update presents recent advances in the radial transport of nutrients highlighting the coupled trans-cellular pathway and the roles played by the endodermis as a barrier.

Differential distribution of MAP1a and aldolase c in adult mouse cerebellum.

MAP1a is a microtubule-associated protein with an apparent molecular weight of 360 kDa that is found in the axonal and dendritic processes of neurons. Two monoclonal anti-MAP1a antibodies anti-A and anti-BW6, revealed different epitope distributions in the adult mouse cerebellum. Anti-A stained Purkinje and granule cells uniformly throughout the cerebellum. In contrast, anti-BW6 selectively stained the dendriites of a subset of Purkinje cells, revealing parasagittal bands of immunoreactivity in the molecular layer. The compartmentation of the BW6 epitope was compared to the Purkine cells as revealed by immunostaining with anti-zebrin II, a well known antigen expressed selectively by bands of Purkinje cells. The anti-BW6 staining pattern was complementary to the zebrin II bands, the zebrin II- Purkinjke cells having BW6+ dendrites. These results demonstrate that MAP1a is present in two forms in the mouse cerebellum, one of which is segregated into parasagittal bands. This may indicate a unique MAP1a isoform or may reflect differences in the metabolic states of Purkinje cell classes, and regional differences in their functions.

The role of gene duplication in the origin and evolution of new biological functions

Abstract : Gene duplication is an essential source of material for the origin of genetic novelty and the evolution of lineage- or species-specific phenotypic traits. The reverse transcription of source gene mRNA followed by the genomic insertion of the resulting cDNA - retroposition - has provided the human genome with a significant number of gene copies during the last ~63 million years (MYA) of primate evolution. We estimated that at least 1 new functional gene (retrogene) per MYA emerged by retroposition in the primate lineage leading to humans. Using a combination of comparative sequencing and evolutionary simulations, we obtained strong evidence of functionality for 7 primate specific retrogenes. Most of these genes are specifically expressed in testis suggesting that retroposition has contributed with genetic raw material necessary for the evolution ofmale-specific functions in primates. We characterized CDC14Bretro (identified in the previous survey) that originated from the retroposition of a cell cycle gene - CDC14B - in the common ancestor of humans and apes. We demonstrate that CDC14Bretro experienced a period of intense positive selection in the African ape ancestor. By virtue of the amino acid substitutions that occurred during this period CDC 14Bretro adapted to a new subcellular compartment in African apes. Further analyses indicate that this subcellular shift reflects the evolution of anew functional role of CDC 14Bretro. Prompted by this result, we used yeast (Saccharomyces cerevisiae) to investigate on a global scale the extent of functional diversification of duplicate genes through the subcellular adaptation of their encoded proteins. We found that duplicate proteins frequently evolved new cellular localization patterns, either by partitioning of ancestral localizations ("sublocalization"), or more frequently by relocalization to previously unoccupied compartments ("neolocalization"). Interestingly, proteins involved in processes with a wider subcellular distribution more frequently evolved new localization patterns suggesting that subcellular localization changes are dependent on progenitor gene functions. Relocated proteins adapted to their new subcellular environments and evolved new functional roles through changes of their physio-chemical properties, expression levels, and interaction partners. Our work suggests an important role of subcellular adaptation for the emergence of new gene functions.

Radial forearm free flap donor site morbidity: ulnar-based transposition flap vs split-thickness skin graft.

OBJECTIVES: To evaluate morbidity associated with the radial forearm free flap donor site and to compare functional and aesthetic outcomes of ulnar-based transposition flap (UBTF) vs split-thickness skin graft (STSG) closure of the donor site.¦DESIGN: Case-control study.¦SETTING: Tertiary care institution.¦PATIENTS: The inclusion criteria were flap size not exceeding 30 cm(2), patient availability for a single follow-up visit, and performance of surgery at least 6 months previously. Forty-four patients were included in the study and were reviewed. Twenty-two patients had UBTF closure, and 22 had STSG closure.¦MAIN OUTCOME MEASURES: Variables analyzed included wrist mobility, Michigan Hand Outcomes Questionnaire scores, pinch and grip strength (using a dynamometer), and hand sensitivity (using monofilament testing over the radial nerve distribution). In analyses of operated arms vs nonoperated arms, variables obtained only for the operated arms included Vancouver Scar Scale scores and visual analog scale scores for Aesthetics and Overall Arm Function.¦RESULTS: The mean (SD) wrist extension was significantly better in the UBTF group (56.0° [10.4°] for nonoperated arms and 62.0° [9.7°] for operated arms) than in the STSG group (59.0° [7.1°] for nonoperated arms and 58.4° [12.1°] for operated arms) (P = .02). The improvement in wrist range of motion for the UBTF group approached statistical significance (P = .07). All other variables (Michigan Hand Outcomes Questionnaire scores, pinch and grip strength, hand sensitivity, and visual analog scale scores) were significantly better for nonoperated arms vs operated arms, but no significant differences were observed between the UBTF and STSG groups.¦CONCLUSIONS: The radial forearm free flap donor site carries significant morbidity. Donor site UBTF closure was associated with improved wrist extension and represents an alternative method of closure for small donor site defects.