Nucleic Acids Res

The structure and function of conserved motifs constituting the apex of Stem I in T-box mRNA leaders are investigated. We point out that this apex shares striking similarities with the L1 stalk (helices 76-78) of the ribosome. A sequence and structure analysis of both elements shows that, similarly to the head of the L1 stalk, the function of the apex of Stem I lies in the docking of tRNA through a stacking interaction with the conserved G19:C56 base pair platform. The inferred structure in the apex of Stem I consists of a module of two T-loops bound together head to tail, a module that is also present in the head of the L1 stalk, but went unnoticed. Supporting the analysis, we show that a highly conserved structure in RNAse P formerly described as the J11/12-J12/11 module, which is precisely known to bind the elbow of tRNA, constitutes a third instance of this T-loop module. A structural analysis explains why six nucleotides constituting the core of this module are highly invariant among all three types of RNA. Our finding that major RNA partners of tRNA bind the elbow with a same RNA structure suggests an explanation for the origin of the tRNA L-shape

Conditioning electrical impedance mammography system

A multi-frequency Electrical Impedance Mammography (EIM) system has been developed to evaluate the conductivity and permittivity spectrums of breast tissues, which aims to improve early detection of breast cancer as a non-invasive, relatively low cost and label-free screening (or pre-screening) method. Multi-frequency EIM systems typically employ current excitations and measure differential potentials from the subject under test. Both the output impedance and system performance (SNR and accuracy) depend on the total output resistance, stray and output capacitances, capacitance at the electrode level, crosstalk at the chip and PCB levels. This makes the system design highly complex due to the impact of the unwanted capacitive effects, which substantially reduce the output impedance of stable current sources and bandwidth of the data that can be acquired. To overcome these difficulties, we present new methods to design a high performance, wide bandwidth EIM system using novel second generation current conveyor operational amplifiers based on a gyrator (OCCII-GIC) combination with different current excitation systems to cancel unwanted capacitive effects from the whole system. We reconstructed tomography images using a planar E-phantom consisting of an RSC circuit model, which represents the resistance of extra-cellular (R), intra-cellular (S) and membrane capacitance (C) of the breast tissues to validate the performance of the system. The experimental results demonstrated that an EIM system with the new design achieved a high output impedance of 10MΩ at 1MHz to at least 3MΩ at 3MHz frequency, with an average SNR and modelling accuracy of over 80dB and 99%, respectively

Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy

The initial identification of breast cancer and the prediction of its category have become a requirement in cancer research because they can simplify the subsequent clinical management of patients. The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. In addition, the ranked order of the variables based on their importance differed across the ML algorithms. The results demonstrated that the three bagging ensemble ML algorithms, namely, RF ERT and DT, yielded better classification accuracies (78–86%) compared with the two boosting algorithms, GBT and ADB (60–75%). We hope that these our results would help improve the classification of breast tissue to allow the early prediction of cancer susceptibility

A coarse-grained force field for Protein–RNA docking

The awareness of important biological role played by functional, non coding (nc) RNA has grown tremendously in recent years. To perform their tasks, ncRNA molecules typically unite with protein partners, forming ribonucleoprotein complexes. Structural insight into their architectures can be greatly supplemented by computational docking techniques, as they provide means for the integration and refinement of experimental data that is often limited to fragments of larger assemblies or represents multiple levels of spatial resolution. Here, we present a coarse-grained force field for protein-RNA docking, implemented within the framework of the ATTRACT program. Complex structure prediction is based on energy minimization in rotational and translational degrees of freedom of binding partners, with possible extension to include structural flexibility. The coarse-grained representation allows for fast and efficient systematic docking search without any prior knowledge about complex geometry

Transient compartmentalization of RNA replicators prevents extinction due to parasites

The appearance of molecular replicators (molecules that can be copied) was probably a critical step in the origin of life. However, parasitic replicators would take over and would have prevented life from taking off unless the replicators were compartmentalized in reproducing protocells. Paradoxically, control of protocell reproduction would seem to require evolved replicators.We show here that a simpler population structure, based on cycles of transient compartmentalization (TC) and mixing of RNA replicators, is sufficient to prevent takeover by parasitic mutants.TC tends to select for ensembles of replicators that replicate at a similar rate, including a diversity of parasites that could serve as a source of opportunistic functionality. Thus,TC in natural, abiological compartments could have allowed life to take hold

Sequence–structure relationships in RNA loops: establishing the basis for loop homology modeling

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence–structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts

A feasibility study of a rotary planar electrode array for electrical impedance mammography using a digital breast phantom

A feasibility study of an electrical impedance mammography (EIM) system with a rotary planar electrode array, named RPEIM, is presented. The RPEIM system is an evolution of the Sussex MK4 system, which is a prototype instrument for breast cancer detection. Comparing it with the other planar electrode EIM systems, the rotation feature enables a dramatic increase in the number of independent measurements. To assist impedance evaluation exploiting electrode array rotation, a synchronous mesh method is proposed. Using the synchronous mesh method, the RPEIM system is shown to have superior performance in image accuracy, spatial resolution and noise tolerance over the MK4 system. To validate the study, we report simulations based on a close-to-realistic 3D digital breast phantom, which comprises of: skin, nipple, ducts, acinus, fat and tumor. A digital breast phantom of a real patient is constructed, whose tumor was detected using the MK4 system. The reconstructed conductivity image of the breast phantom indicates that the breast phantom is a close replica of the patient’s real breast as assessed by the MK4 system in a clinical trial. A comparison between the RPEIM system and the MK4 system is made based on this phantom to assess the advantages of the RPEIM system