In this task, you are given a abstract of article and corresponding title of an article. Your task is to generate label "yes" if title is right for article, otherwise generate "no".

[Q]: Abstract: A mechanistic understanding of fracture in human bone is critical to predicting fracture risk associated with age and disease. Despite extensive work, a mechanistic framework for describing how the microstructure affects the failure of bone is lacking. Although micromechanical models incorporating local failure criteria have been developed for metallic and ceramic materials, few such models exist for biological materials. In fact, there is no proof to support the widely held belief that fracture in bone is locally strain-controlled, as for example has been shown for ductile fracture in metallic materials. In the present study, we provide such evidence through a novel series of experiments involving a double-notch-bend geometry, designed to shed light on the nature of the critical failure events in bone. We examine how the propagating crack interacts with the bone microstructure to provide some mechanistic understanding of fracture and to define how properties vary with orientation. It was found that fracture in human cortical bone is consistent with strain-controlled failure, and the influence of microstructure can be described in terms of several toughening mechanisms. We provide estimates of the relative importance of these mechanisms, such as uncracked-ligament bridging.. Title: Mechanistic Fracture Criteria For The Failure Of Human Cortical Bone
[A]: yes

[Q]: Abstract: The transient receptor potential (TRP) channels TRPML1, TRPML2, and TRPML3 (also called mucolipins 1-3 or MCOLN1-3) are nonselective cation channels. Mutations in the Trpml1 gene cause mucolipidosis type IV in humans with clinical features including psychomotor retardation, corneal clouding, and retinal degeneration, whereas mutations in the Trpml3 gene cause deafness, circling behavior, and coat color dilution in mice. No disease-causing mutations are reported for the Trpml2 gene. Like TRPML channels, which are expressed in the endolysosomal pathway, two-pore channels (TPCs), namely TPC1, TPC2, and TPC3, are found in intracellular organelles, in particular in endosomes and lysosomes. Both TRPML channels and TPCs may function as calcium/cation release channels in endosomes, lysosomes, and lysosome-related organelles with TRPMLs being activated by phosphatidylinositol 3,5-bisphosphate and regulated by pH and TPCs being activated by nicotinic acid adenine dinucleotide phosphate in a calcium- and pH-dependent manner. They may also be involved in endolysosomal transport and fusion processes, e.g., as intracellular calcium sources. Currently, however, the exact physiological roles of TRPML channels and TPCs remain quite elusive, and whether TRPML channels are purely endolysosomal ion channels or whether they may also be functionally active at the plasma membrane in vivo remains to be determined.. Title: Tet1 and Tet2 regulate 5-hydroxymethylcytosine production and cell lineage specification in mouse embryonic stem cells.
[A]: no

[Q]: Abstract: BACKGROUND MicroRNAs (miRNAs) are produced by the sequential processing of a long hairpin RNA transcript by Drosha and Dicer, an RNase III enzymes, and form transitory small RNA duplexes. One strand of the duplex, which incorporates into RNA-induced silencing complex (RISC) and silences the gene expression is called guide strand, or miRNA; while the other strand of duplex is degraded and called the passenger strand, or miRNA*. Predicting the guide strand of miRNA is important for better understanding the RNA interference pathways.
RESULTS This paper describes support vector machine (SVM) models developed for predicting the guide strands of miRNAs. All models were trained and tested on a dataset consisting of 329 miRNA and 329 miRNA* pairs using five fold cross validation technique. Firstly, models were developed using mono-, di-, and tri-nucleotide composition of miRNA strands and achieved the highest accuracies of 0.588, 0.638 and 0.596 respectively. Secondly, models were developed using split nucleotide composition and achieved maximum accuracies of 0.553, 0.641 and 0.602 for mono-, di-, and tri-nucleotide respectively. Thirdly, models were developed using binary pattern and achieved the highest accuracy of 0.708. Furthermore, when integrating the secondary structure features with binary pattern, an accuracy of 0.719 was seen. Finally, hybrid models were developed by combining various features and achieved maximum accuracy of 0.799 with sensitivity 0.781 and specificity 0.818. Moreover, the performance of this model was tested on an independent dataset that achieved an accuracy of 0.80. In addition, we also compared the performance of our method with various siRNA-designing methods on miRNA and siRNA datasets.
CONCLUSION In this study, first time a method has been developed to predict guide miRNA strands, of miRNA duplex. This study demonstrates that guide and passenger strand of miRNA precursors can be distinguished using their nucleotide sequence and secondary structure. This method will be useful in understanding microRNA processing and can be implemented in RNA silencing technology to improve the biological and clinical research. A web server has been developed based on SVM models described in this study (http://crdd.osdd.net:8081/RISCbinder/).. Title: ROR- drives androgen receptor expression and represents a therapeutic target in castration-resistant prostate cancer
[A]:
no