Cardiotrophin-like cytokine/cytokine-like factor 1 is an essential trophic factor for lumbar and facial motoneurons in vivo

The ciliary neurotrophic factor alpha-receptor(CNTFRalpha) is required for motoneuron survival during development, but the relevant ligand(s) has not been determined. One candidate is the heterodimer formed by cardiotrophin-like cytokine (CLC) and cytokine-like factor 1 (CLF). CLC/CLF binds to CNTFRalpha and enhances the survival of developing motoneurons in vitro; whether this novel trophic factor plays a role in neural development in vivo has not been tested. We examined motor and sensory neurons in embryonic chicks treated with CLC and in mice with a targeted deletion of the clf gene. Treatment with CLC increased the number of lumbar spinal cord motoneurons that survived the cell death period in chicks. However, this effect was regionally specific, because brachial and thoracic motoneurons were unaffected. Similarly, newborn clf -/- mice exhibited a significant reduction in lumbar motoneurons, with no change in the brachial or thoracic cord. Clf deletion also affected brainstem motor nuclei in a regionally specific manner; the number of motoneurons in the facial but not hypoglossal nucleus was significantly reduced. Sensory neurons of the dorsal root ganglia were not affected by either CLC treatment or clf gene deletion. Finally, mRNA for both clc and clf was found in skeletal muscle fibers of embryonic mice during the motoneuron cell death period. These findings support the view that CLC/CLF is a target-derived factor required for the survival of specific pools of motoneurons. The in vivo actions of CLC and CLF can account for many of the effects of CNTFRalpha on developing motoneurons.

Beyond the sphere of the English facial approximation literature: Ramifications of German papers on western method concepts

In the English literature, facial approximation methods have been commonly classified into three types: Russian, American, or Combination. These categorizations are based on the protocols used, for example, whether methods use average soft-tissue depths (American methods) or require face muscle construction (Russian methods). However, literature searches outside the usual realm of English publications reveal key papers that demonstrate that the Russian category above has been founded on distorted views. In reality, Russian methods are based on limited face muscle construction, with heavy reliance on modified average soft-tissue depths. A closer inspection of the American method also reveals inconsistencies with the recognized classification scheme. This investigation thus demonstrates that all major methods of facial approximation depend on both face anatomy and average soft-tissue depths, rendering common method classification schemes redundant. The best way forward appears to be for practitioners to describe the methods they use (including the weight each one gives to average soft-tissue depths and deep face tissue construction) without placing them in any categorical classificatory group or giving them an ambiguous name. The state of this situation may need to be reviewed in the future in light of new research results and paradigms.

Assessing facial approximation accuracy: How do resemblance ratings of disparate faces compare to recognition tests?

In the past, the accuracy of facial approximations has been assessed by resemblance ratings (i.e., the comparison of a facial approximation directly to a target individual) and recognition tests (e.g., the comparison of a facial approximation to a photo array of faces including foils and a target individual). Recently, several research studies have indicated that recognition tests hold major strengths in contrast to resemblance ratings. However, resemblance ratings remain popularly employed and/or are given weighting when judging facial approximations, thus indicating that no consensus has been reached. This study aims to further investigate the matter by comparing the results of resemblance ratings and recognition tests for two facial approximations which clearly differed in their morphological appearance. One facial approximation was constructed by an experienced practitioner privy to the appearance of the target individual (practitioner had direct access to an antemortem frontal photograph during face construction), while the other facial approximation was constructed by a novice under blind conditions. Both facial approximations, whilst clearly morphologically different, were given similar resemblance scores even though recognition test results produced vastly different results. One facial approximation was correctly recognized almost without exception while the other was not correctly recognized above chance rates. These results suggest that resemblance ratings are insensitive measures of the accuracy of facial approximations and lend further weight to the use of recognition tests in facial approximation assessment. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Identification and analysis of novel genes expressed in the mouse embryonic facial primordia

Craniofacial anomalies are a common feature of human congenital dysmorphology syndromes, suggesting that genes expressed in the developing face are likely to play a wider role in embryonic development. To facilitate the identification of genes involved in embryogenesis, we previously constructed an enriched cDNA library by subtracting adult mouse liver cDNA from that of embryonic day (E)10.5 mouse pharyngeal arch cDNA. From this library, 273 unique clones were sequenced and known proteins binned into functional categories in order to assess enrichment of the library (1). We have now selected 31 novel and poorly characterised genes from this library and present bioinformatic analysis to predict proteins encoded by these genes, and to detect evolutionary conservation. Of these genes 61% (19/31) showed restricted expression in the developing embryo, and a subset of these was chosen for further in silico characterisation as well as experimental determination of subcellular localisation based on transient transfection of predicted full-length coding sequences into mammalian cell lines. Where a human orthologue of these genes was detected, chromosomal localisation was determined relative to known loci for human congenital disease.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P