The Src substrate associated in mitosis of 68 kDa (Sam68) is a KH-type RNA binding protein that has been shown to regulate several aspects of RNA metabolism; however, its physiologic role has remained elusive. Herein we report the generation of Sam68-null mice by homologous recombination. Aged Sam68−/− mice preserved their bone mass, in sharp contrast with 12-month-old wild-type littermates in which bone mass was decreased up to approximately 75%. In fact, the bone volume of the 12-month-old Sam68−/− mice was virtually indistinguishable from that of 4-month-old wild-type or Sam68−/− mice. Sam68−/− bone marrow stromal cells had a differentiation advantage for the osteogenic pathway. Moreover, the knockdown of Sam68 using short hairpin RNA in the embryonic mesenchymal multipotential progenitor C3H10T1/2 cells resulted in more pronounced expression of the mature osteoblast marker osteocalcin when differentiation was induced with bone morphogenetic protein-2. Cultures of mouse embryo fibroblasts generated from Sam68+/+ and Sam68−/− littermates were induced to differentiate into adipocytes with culture medium containing pioglitazone and the Sam68−/− mouse embryo fibroblasts shown to have impaired adipocyte differentiation. Furthermore, in vivo it was shown that sections of bone from 12-month-old Sam68−/− mice had few marrow adipocytes compared with their age-matched wild-type littermate controls, which exhibited fatty bone marrow. Our findings identify endogenous Sam68 as a positive regulator of adipocyte differentiation and a negative regulator of osteoblast differentiation, which is consistent with Sam68 being a modulator of bone marrow mesenchymal cell differentiation, and hence bone metabolism, in aged mice.

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Abstract. Service Based Systems, composed of Web Services (WSs), offer promising solutions to software development problems for companies. Like other software artefacts, WSs evolve due to the changed user requirements and execution contexts, which may introduce poor solutions-Antipatterns-may cause (1) degradation of design and quality of service (QoS) and (2) difficult maintenance and evolution. Thus, the automatic detection of antipatterns in WSs, which aims at evaluating their design and QoS requires attention. We propose SODA-W (Service Oriented Detection for Antipatterns in Web services), an approach supported by a framework for specifying and detecting antipatterns in WSs. Using SODA-W, we specify ten antipatterns, including God Object Web Service and Fine Grained Web Service, and perform their detection in two different corpora: (1) 13 weather-related and (2) 109 financial-related WSs. SODA-W can specify and detect antipatterns in WSs with an average precision of more than 75% and a recall of 100%.

Identifier lexicon may have a direct impact on software understandability and reusability and, thus, on the quality of the final software product. Understandability and reusability are two important characteristics of software quality. REpresentational State Transfer (REST) style is becoming a de facto standard adopted by software organizations to build their Web applications. Understandable and reusable Uniform Resource Identifers (URIs) are important to attract client developers of RESTful APIs because good URIs support the client developers to understand and reuse the APIs. Consequently, the use of proper lexicon in RESTful APIs has also a direct impact on the quality of Web applications that integrate these APIs. Linguistic antipatterns represent poor practices in the naming, documentation, and choice of identifiers in the APIs as opposed to linguistic patterns that represent the corresponding best practices. In this paper, we present the Semantic Analysis of RESTful APIs (SARA) approach that employs both syntactic and semantic analyses for the detection of linguistic patterns and antipatterns in RESTful APIs. We provide detailed definitions of 12 linguistic patterns and antipatterns and define and apply their detection algorithms on 18 widely-used RESTful APIs, including Facebook, Twitter, and Dropbox. Our detection results show that linguistic patterns and antipatterns do occur in major RESTful APIs in particular in the form of poor documentation practices. Those results also show that SARA can detect linguistic patterns and antipatterns with higher accuracy compared to its state-of-the-art approach — DOLAR.