Murine MyaK, a member of a family of yeast YAK1-related genes, is highly expressed in hormonally modulated epithelia in the reproductive system and in the embryonic central nervous system

We have cloned a mouse homologue (designated Myak) of the yeast protein kinase YAK1. The 1210 aa open reading frame contains a putative protein kinase domain, nuclear localization sequences and PEST sequences. Myak appears to be a member of a growing family of YAK1-related genes that include Drosophila and human Minibrain as well as a recently identified rat gene ANPK that encode a steroid hormone receptor interacting protein. RNA blot analysis revealed that Myak is expressed at low levels ubiquitously but at high levels in reproductive tissues, including testis, epididymis, ovary, uterus, and mammary gland, as well as in brain and kidney. In situ hybridization analysis on selected tissues revealed that Myak is particularly abundant in the hormonally modulated epithelia of the epididymis, mammary gland, and uterus, in round spermatids in the testis, and in the corpora lutea in the ovary, Myak is also highly expressed in the aqueduct of the adult brain and in the brain and spinal cord of day 12.5 embryos, Mol. Reprod. Dev. 55:372-378, 2000. (C) 2000 Wiley-Liss, Inc.

A family of simple benzene 1,3,5-tricarboxamide (BTA) aromatic carboxylic acid hydrogels.

We present the characterisation of a hydrogel forming family of benzene 1,3,5-tricarboxamide (BTA) aromatic carboxylic acid derivatives. The simple, easy to synthesise compounds presented here exhibit consistent gel formation at low concentrations through the use of a pH trigger.

A single-Stream jet noise prediction model for a family of chevron nozzles

This study develops a single-stream jet noise prediction model for a family of chevron nozzles. An original equation is proposed for the fourth-order space-time cross-correlations. They are expressed in flow parameters such as streamwise circulation and turbulent kinetic energy. The cross-correlations based on a Reynolds Averaged Navier-Stokes (RANS) flowfield showed a good agreement with those based on a Large Eddy Simulation (LES) flowfield. This proves that the proposed equation describes the cross-correlations accurately. With this novel source description, there is an excellent agreement between our model's far-field noise predictions and measurements1 for a wide range of frequencies and radiation angles. Our model captures the spectral shape, amplitude and peak frequency very well. This establishes that our model holds good for a family of chevron nozzles. As our model provides quick and accurate predictions, a parametric study was performed to understand the effects of a chevron nozzle geometry on jet noise and thrust loss. Chevron penetration is the underpinning factor for jet noise reduction. The reduction of jet noise per unit thrust loss decreases linearly with chevron penetration. The number of chevrons also has a considerable effect on jet noise.

A conserved family of doublesex-related genes from fishes

The sex-determining gene Mab-3 of C. elegans and the doublesex gene of Drosophila each contain a common DM domain and share a similar role. Human doublesex-related gene DMRT1 also encodes a conserved DM-related DNA-binding domain. We present here the amplification of a broad range of DM domain sequences from three fish species using degenerate PCR. Our results reveal unexpected complexity of the DM domain gene family in vertebrates. (C) 2002 Wiley-Liss, Inc.

A new family of Ce6MoO15 as fast oxide ion conductor

A novel solid solution Ce6MoO15 was achieved. Their structure and oxide ionic conductivity were studied. Based on Ce6MoO15, rare earth element substitution on cerium site shows that all resulting oxides enhance the conductivity further, and have high oxide-ion conductivity, which may be a kind of promising material for SOFCs.

The Apertospathulidae, a new family of haptorid ciliates (Protozoa, Ciliophora)

We studied the morphology of three rare haptorid ciliates, using live observation and silver impregnation: Apertospathula verruculifera n. sp., Longispatha elegans n. gen., n. sp., and Rhinothrix porculus (Penard, 1922) n. gen., n. comb. Simple ethanol fixation (50-70%, v/v) is recommended to reveal the ciliary pattern of "difficult" ciliates, such as R. porculus, by protargol impregnation. The three genera investigated have a distinct feature in common, viz., a lasso-shaped oral bulge and circumoral kinety, where the right half is slightly to distinctly longer than the left and the circumoral kinety is open ventrally. Thus, they are united in a new spathidiid family, the Apertospathulidae n. fam., which probably evolved from a Bryophyllum-like ancestor by partial reduction of the oral bulge and circumoral kinety. Apertospathula verruculifera has a wart-like process, the palpus dorsalis, at the anterior end of the dorsal brush. The right branch of the circumoral kinety is only slightly longer than the left one. Longispatha elegans has a straight oral bulge and circumoral kinety, the right branch of which extends to the posterior end of the body while the left branch ends in the anterior third of the body. Rhinothrix porculus, a curious ciliate with a snout-like dorsal elongation of the oral bulge, the palpus oralis, has a highly characteristic ciliary pattern: the oral pattern is as in Longispatha, but the bulge and circumoral kinety extend spirally to the posterior end of the body while the somatic kinetics course meridionally. This is achieved by inserting some shortened kinetics in the curves of the oral bulge.

Learning a Family of Detectors

Object detection and recognition are important problems in computer vision. The challenges of these problems come from the presence of noise, background clutter, large within class variations of the object class and limited training data. In addition, the computational complexity in the recognition process is also a concern in practice. In this thesis, we propose one approach to handle the problem of detecting an object class that exhibits large within-class variations, and a second approach to speed up the classification processes. In the first approach, we show that foreground-background classification (detection) and within-class classification of the foreground class (pose estimation) can be jointly solved with using a multiplicative form of two kernel functions. One kernel measures similarity for foreground-background classification. The other kernel accounts for latent factors that control within-class variation and implicitly enables feature sharing among foreground training samples. For applications where explicit parameterization of the within-class states is unavailable, a nonparametric formulation of the kernel can be constructed with a proper foreground distance/similarity measure. Detector training is accomplished via standard Support Vector Machine learning. The resulting detectors are tuned to specific variations in the foreground class. They also serve to evaluate hypotheses of the foreground state. When the image masks for foreground objects are provided in training, the detectors can also produce object segmentation. Methods for generating a representative sample set of detectors are proposed that can enable efficient detection and tracking. In addition, because individual detectors verify hypotheses of foreground state, they can also be incorporated in a tracking-by-detection frame work to recover foreground state in image sequences. To run the detectors efficiently at the online stage, an input-sensitive speedup strategy is proposed to select the most relevant detectors quickly. The proposed approach is tested on data sets of human hands, vehicles and human faces. On all data sets, the proposed approach achieves improved detection accuracy over the best competing approaches. In the second part of the thesis, we formulate a filter-and-refine scheme to speed up recognition processes. The binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the face recognition grand challenge version 2 data set, hand shape detection and parameter estimation on a hand data set, and vehicle detection and estimation of the view angle on a multi-pose vehicle data set. On all data sets, our approach is at least five times faster than simply evaluating all foreground state hypotheses with virtually no loss in classification accuracy.

Investigation of the function of the LNX family of E3 ubiquitin ligases in the nervous system

The Lnx1 (Ligand of Numb protein X 1) and Lnx2 genes belong to a family of PDZ domain-containing RING finger domain E3 ubiquitin ligases. mRNA expression for both genes have been reported in early murine central nervous system. However, there have been limited reports with regards to the expression patterns for both the proteins in vivo. Hence, we have attempted to characterize the significance of these proteins in the context of morphology and physiology of the central nervous system. Through our studies, we have attempted to examine closely the expression of these two genes in the murine central nervous system. We have also looked at novel interacting ligands for both proteins. Interacting partners have been examined with particular relevance to possible roles of their interactions with LNX1 and LNX2 in the functioning of the nervous system. Moreover, we have performed loss-of-function studies by way of creation and characterization of knockout mice.

A C-terminal motif found in the beta2-adrenergic receptor, P2Y1 receptor and cystic fibrosis transmembrane conductance regulator determines binding to the Na+/H+ exchanger regulatory factor family of PDZ proteins.

The Na+/H+ exchanger regulatory factor (NHERF) binds to the tail of the beta2-adrenergic receptor and plays a role in adrenergic regulation of Na+/H+ exchange. NHERF contains two PDZ domains, the first of which is required for its interaction with the beta2 receptor. Mutagenesis studies of the beta2 receptor tail revealed that the optimal C-terminal motif for binding to the first PDZ domain of NHERF is D-S/T-x-L, a motif distinct from those recognized by other PDZ domains. The first PDZ domain of NHERF-2, a protein that is 52% identical to NHERF and also known as E3KARP, SIP-1, and TKA-1, exhibits binding preferences very similar to those of the first PDZ domain of NHERF. The delineation of the preferred binding motif for the first PDZ domain of the NHERF family of proteins allows for predictions for other proteins that may interact with NHERF or NHERF-2. For example, as would be predicted from the beta2 receptor tail mutagenesis studies, NHERF binds to the tail of the purinergic P2Y1 receptor, a seven-transmembrane receptor with an intracellular C-terminal tail ending in D-T-S-L. NHERF also binds to the tail of the cystic fibrosis transmembrane conductance regulator, which ends in D-T-R-L. Because the preferred binding motif of the first PDZ domain of the NHERF family of proteins is found at the C termini of a variety of intracellular proteins, NHERF and NHERF-2 may be multifunctional adaptor proteins involved in many previously unsuspected aspects of intracellular signaling.

The Richit-Richards family of distributions and its use in forestry

Johnson's SB and the logit-logistic are four-parameter distribution models that may be obtained from the standard normal and logistic distributions by a four-parameter transformation. For relatively small data sets, such as diameter at breast height measurements obtained from typical sample plots, distribution models with four or less parameters have been found to be empirically adequate. However, in situations in which the distributions are complex, for example in mixed stands or when the stand has been thinned or when working with aggregated data, then distribution models with more shape parameters may prove to be necessary. By replacing the symmetric standard logistic distribution of the logit-logistic with a one-parameter “standard Richards” distribution and transforming by a five-parameter Richards function, we obtain a new six-parameter distribution model, the “Richit-Richards”. The Richit-Richards includes the “logit-Richards”, the “Richit-logistic”, and the logit-logistic as submodels. Maximum likelihood estimation is used to fit the model, and some problems in the maximum likelihood estimation of bounding parameters are discussed. An empirical case study of the Richit-Richards and its submodels is conducted on pooled diameter at breast height data from 107 sample plots of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). It is found that the new models provide significantly better fits than the four-parameter logit-logistic for large data sets.