Loss of the mammal-specific tectorial membrane component CEA cell adhesion molecule 16 (CEACAM16) leads to hearing impairment at low and high frequencies

The vertebrate-restricted carcinoembryonic antigen gene family evolves extremely rapidly. Among their widely expressed members, the mammal-specific, secreted CEACAM16 is exceptionally well conserved and specifically expressed in the inner ear. To elucidate a potential auditory function we inactivated murine Ceacam16 by homologous recombination. In young Ceacam16-/- mice the hearing threshold for frequencies below 10 kHz and above 22 kHz was raised. This hearing impairment progressed with age. A similar phenotype is observed in hearing-impaired members of Family 1070 with non-syndromic autosomal dominant hearing loss (DFNA4) who carry a missense mutation in CEACAM16. CEACAM16 was found in interdental and Deiters cells and was deposited in the tectorial membrane of the cochlea between postnatal day 12 and 15, when hearing starts in mice. In cochlear sections of Ceacam16-/- mice tectorial membranes were significantly more often stretched out as compared to wild-type mice where they were mostly contracted and detached from the outer hair cells. Homotypic cell sorting observed after ectopic cell surface expression of the carboxy-terminal immunoglobulin variable-like N2 domain of CEACAM16 indicated that CEACAM16 can interact in trans. Furthermore, Western blot analyses of membrane-bound CEACAM16 under reducing and non-reducing conditions demonstrated oligomerization via unpaired cysteines. Taken together, CEACAM16 probably can form higher order structures with other tectorial membrane proteins such as α-tectorin and β-tectorin and influences the physical properties of the tectorial membrane. Evolution of CEACAM16 might have been an important step for the specialization of the mammalian cochlea allowing hearing over an extended frequency range

Query Selectivity Estimation Based on Improved V-optimal Histogram by Introducing Information about Distribution of Boundaries of Range Query Conditions

Part 4: Data Analysis and Information RetrievalInternational audienceSelectivity estimation is a parameter used by a query optimizer for early estimation of the size of data that satisfies query condition. Selectivity is calculated using an estimator of distribution of attribute values of attribute involved in a processed query condition. Histograms built on attributes values from a database may be such representation of the distribution. The paper introduces a new query-distribution-aware V-optimal histogram which is useful in selectivity estimation for a range query. It takes into account either a 1-D distribution of attribute values or a 2-D distribution of boundaries of already processed queries. The advantages of qda-V-optimal histogram appears when it is applied for selectivity estimation of range query conditions that form so-called hot regions. To obtain the proposed error-optimal histogram we use dynamic programming method, Fuzzy C-Means clustering of a set of range boundaries

Efficient Window Aggregation with General Stream Slicing

Window aggregation is a core operation in data stream processing. Existing aggregation techniques focus on reducing latency, eliminating redundant computations, and minimizing memory usage. However, each technique operates under different assumptions with respect to workload characteristics such as properties of aggregation functions (e.g., invertible, associative), window types (e.g., sliding, sessions), windowing measures (e.g., time- or count-based), and stream (dis)order. Violating the assumptions of a technique can deem it unusable or drastically reduce its performance. In this paper, we present the first general stream slicing technique for window aggregation. General stream slicing automatically adapts to workload characteristics to improve performance without sacrificing its general applicability. As a prerequisite, we identify workload characteristics which affect the performance and applicability of aggregation techniques. Our experiments show that general stream slicing outperforms alternative concepts by up to one order of magnitude.Web Information System