Optimized Atlas-Based Auto-Segmentation of Bony Structures from Whole-Body Computed Tomography.

Purpose: To develop and test a method for fully automated segmentation of bony structures from whole-body computed tomography (CT) and evaluate its performance compared with manual segmentation.

Methods And Materials: We developed a workflow for automatic whole-body bone segmentation using atlas-based segmentation (ABS) method with a postprocessing module (ABS) in MIM MAESTRO software. Fifty-two CT scans comprised the training set to build the atlas library, and 29 CT scans comprised the test set.

Improved Prognosis of Treatment Failure in Cervical Cancer with Nontumor PET/CT Radiomics.

Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting nontumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating nontumor radiomics, including whole-body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy.

Knowledge-Based Planning for Intact Cervical Cancer.

Cervical cancer radiotherapy is often complicated by significant variability in the quality and consistency of treatment plans. Knowledge-based planning (KBP), which utilizes prior patient data to correlated achievable optimal dosimetry with patient-specific anatomy, has demonstrated promise as a quality control tool for controlling this variability, with consequences for patient outcomes, as well as for the reliability of data from multi-institutional clinical trials. In this article we highlight the application of KBP-based quality control to cervical cancer radiotherapy.

A knowledge-based organ dose prediction tool for brachytherapy treatment planning of patients with cervical cancer.

Purpose: The purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D for tandem and ovoid treatments.

Methods And Materials: A total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed.

Disruption of microbial communication yields a two-dimensional percolation transition.

Bacteria communicate with each other to coordinate macroscale behaviors including pathogenesis, biofilm formation, and antibiotic production. Empirical evidence suggests that bacteria are capable of communicating at length scales far exceeding the size of individual cells. Several mechanisms of signal interference have been observed in nature, and how interference influences macroscale activity within microbial populations is unclear.

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities.

Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to 'cognate' receptors, but also to 'non-cognate' receptors found in other strains, resulting in inter-strain crosstalk.

Spatial dispersal of bacterial colonies induces a dynamical transition from local to global quorum sensing.

Bacteria communicate using external chemical signals called autoinducers (AI) in a process known as quorum sensing (QS). QS efficiency is reduced by both limitations of AI diffusion and potential interference from neighboring strains. There is thus a need for predictive theories of how spatial community structure shapes information processing in complex microbial ecosystems.

Arginine-phosphate salt bridges between histones and DNA: intermolecular actuators that control nucleosome architecture.

Structural bioinformatics and van der Waals density functional theory are combined to investigate the mechanochemical impact of a major class of histone-DNA interactions, namely, the formation of salt bridges between arginine residues in histones and phosphate groups on the DNA backbone. Principal component analysis reveals that the configurational fluctuations of the sugar-phosphate backbone display sequence-specific directionality and variability, and clustering of nucleosome crystal structures identifies two major salt-bridge configurations: a monodentate form in which the arginine end-group guanidinium only forms one hydrogen bond with the phosphate, and a bidentate form in which it forms two. Density functional theory calculations highlight that the combination of sequence, denticity, and salt-bridge positioning enables the histones to apply a tunable mechanochemical stress to the DNA via precise and specific activation of backbone deformations.

5-Methylation of cytosine in CG:CG base-pair steps: a physicochemical mechanism for the epigenetic control of DNA nanomechanics.

van der Waals density functional theory is integrated with analysis of a non-redundant set of protein-DNA crystal structures from the Nucleic Acid Database to study the stacking energetics of CG:CG base-pair steps, specifically the role of cytosine 5-methylation. Principal component analysis of the steps reveals the dominant collective motions to correspond to a tensile "opening" mode and two shear "sliding" and "tearing" modes in the orthogonal plane. The stacking interactions of the methyl groups globally inhibit CG:CG step overtwisting while simultaneously softening the modes locally via potential energy modulations that create metastable states.