The CT-based fractal analysis of trabecular bone structure may help in detecting decreased quality of bone prior to urgent spinal procedures

Marcin Czyza, b, Arion Kapinasb, James Holtona, Renata Pyzikc, Bronek M. Boszczykb, Nasir A. Quraishib a Spinal Service, The Royal Orhopaedic Hospital NHS Trust, Birmingham, UK; b The Centre for Spinal Studies and Surgery, Nottingham… More

Sampling Stability And Processing Parameter-Dependent Characteristics Of The 3D Fractal Dimension As A Marker Of Structural Brain Complexity In Magnetic Resonance Images

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Stephan Krohn,1, Martijn Froeling,2, Alexander Leemans,3, Dirk Ostwald,1, Jesús Jiménez,4, Pablo Villoslada,5, Francisco J. Esteban,6
 
1 Computational Cognitive Neuroscience Laboratory, Free University Berlin, Germany; 2 Department of Radiology, University Medical Center Utrecht, Netherlands; 3 Image Sciences Institute, University Medical Center Utrecht, Netherlands; 4 Department of Computer Science, University of Jaén, Spain; 5 Center of Neuroimmunology, IDIBAPS, Barcelona, Spain; 6 Systems Biology Unit, Department of Experimental Biology, University of Jaén, Spain.
 
Fractal analysis, i.e. the estimation of an object’s fractal dimension (FD) as a marker of its morphometric complexity, has attracted increasing interest as a versatile tool for the analysis of structural neuroimaging data in both health and disease. However, a number of important methodological questions regarding fractal analysis in magnetic resonance images have so far remained unaddressed. This includes the stability of the FD over repeated within-subject measurements, i.e. the susceptibility of fractal analysis to noise, a formal assessment of its sampling distribution, and the impact of image acquisition and processing parameters. Importantly, fractal analysis has not yet been explored in detail in T2 contrast images. To address these issues, we analyzed structural images from the recently published MASSIVE data set (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation). We conduct a fine-grained stratification of image parameters, leading to 32 distinct analysis groups as a combination of image contrast, spatial resolution, segmentation procedures, tissue type, and image complexity. We estimate 3D tissue models based on the thus obtained input volumes and compute the FDs as the box-counting regression on these models. Furthermore, we present a detailed deviation analysis including resampling methods, composite normality assessment, outlier detection, and multivariate comparisons to establish the susceptibility of the FD to noise. We find that in both T1 and T2 contrasts, the FD of gray matter (GM) segmentations was generally higher than in white matter volumes (WM). FDs in both image contrasts were sampled in comparable range and showed similar responses to processing parameters, e.g. as regards the effects of binary vs. partial volume segmentation and a decrease in FD by image skeletization. Lower spatial resolution invariably resulted in decreased FDs in unskeletized images, while the response depended on the segmentation procedure in image skeletons. Furthermore, in multiple measurements, the FD can be assumed to be sampled from an underlying normal distribution. We tested different options for a sensible within-group deviation criterion and found that outlier detection by Grubbs testing and a 2 standard-deviation interval around the sample mean performed very well in this regard. Even with the more conservative threshold, the overall robustness of the FD to noise was well above 90 %. Most deviations were found in T1-weighted images, and binarized image skeletons were most susceptible to deviations. Importantly, our analysis was able to detect sample-wise deviation clusters, and we identify image registration as a source of noise in fractal analysis. Interestingly, registration-induced deviations were limited to T1-weighted images, lending even further support for the usefulness of T2 contrast in fractal analysis. In conclusion, we provide detailed evidence for the stability of the FD as a marker of structural brain complexity and its parameter-dependent characteristics in magnetic resonance images and thus contribute to the development of fractal analysis as a scientifically and clinically useful neuroimaging tool.

The role of biophysics and engineering in investigating tumour pH and its regulation

Figure 1.

Arti Sikka1, Emily M E Barnes1, Hector C Keun

1 Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, United Kingdom

DOI: 10.1088/2057-1739/aa5cd9

Solid tumours tend to have a high metabolic rate, inducing the intracellular accumulation of lactic acid and CO2 with a concomitant decrease in pH. Since many intracellular processes are pH-sensitive, tumour progression is therefore dependent on the maintenance of intracellular and extracellular pH within a narrow range. Cancer cells employ a number of functionally redundant regulatory mechanisms to maintain pH homeostasis. Several small molecule inhibitors which target these mechanisms are currently in clinical trials with promising outcomes. In order to investigate tumour pH regulation and to stratify and monitor patient response to these treatments, we need to be able to accurately measure pH in situ. Although pH measurement techniques are continually being developed, they are still limited for example by poor probe targeting and spatio-temporal resolution. In this review, we discuss the important role of biophysics and engineering in tackling the challenges faced when measuring tumour pH.

A new strategy to measure intercellular adhesion forces in mature cell-cell contacts

Figure 5

 

Ana Sancho,1, Ine Vandersmissen,2, Sander Craps,2, Aernout Luttun,2, Jürgen Groll,1

1 Department of Functional Materials in Medicine and Dentistry and Bavarian Polymer Institute (BPI), University of Würzburg, 97070 Würzburg, Germany; 2 Department of Cardiovascular Sciences, Center for Molecular and Vascular Biology, KU Leuven, 3000 Leuven, Belgium.

DOI: 10.1038/srep46152

Intercellular adhesion plays a major role in tissue development and homeostasis. Yet, technologies to measure mature cell-cell contacts are not available. We introduce a methodology based on fluidic probe force microscopy to assess cell-cell adhesion forces after formation of mature intercellular contacts in cell monolayers. With this method we quantify that L929 fibroblasts exhibit negligible cell-cell adhesion in monolayers whereas human endothelial cells from the umbilical artery (HUAECs) exert strong intercellular adhesion forces per cell. We use a new in vitro model based on the overexpression of Muscle Segment Homeobox 1 (MSX1) to induce Endothelial-to-Mesenchymal Transition (EndMT), a process involved in cardiovascular development and disease. We reveal how intercellular adhesion forces in monolayer decrease significantly at an early stage of EndMT and we show that cells undergo stiffening and flattening at this stage. This new biomechanical insight complements and expands the established standard biomolecular analyses. Our study thus introduces a novel tool for the assessment of mature intercellular adhesion forces in a physiological setting that will be of relevance to biological processes in developmental biology, tissue regeneration and diseases like cancer and fibrosis.

 

Interrogating the topological robustness of gene regulatory circuits by randomization

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Bin Huang,1,2, Mingyang Lu,1,3, Dongya Jia,1,4, Eshel Ben-Jacob,1,5, Herbert Levine,1,6,7, Jose N. Onuchic,1,2,6,7

1 Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America; 2 Department of Chemistry, Rice University, Houston, TX, United States of America; 3 The Jackson Laboratory, Bar Harbor, ME, United States of America; 4 Program in Systems, Synthetic and Physical Biology, Rice University, Houston, TX, United States of America; 5 School of Physics and Astronomy, and The Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel; 6 Department of Biosciences, Rice University, Houston, TX, United States of America; 7 Department of Physics and Astronomy, Rice University, Houston, TX, United States of America.

DOI: 10.1371/journal.pcbi.1005456

One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.

 

Synthesizing topological structures containing RNA

Figure 3

 

Di Liu,1, Yaming Shao,2, Gang Chen,1, Yuk-Ching Tse-Dinh,3, Joseph A. Piccirilli,1,2, Yossi Weizmann,1

1 Department of Chemistry, The University of Chicago, Chicago, Illinois 60637, USA; 2 Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois 60637, USA; 3 Department of Chemistry and Biochemistry, Biomolecular Sciences Institute, Florida International University, Miami, Florida 33199, USA.

DOI: 10.1038/ncomms14936

Though knotting and entanglement have been observed in DNA and proteins, their existence in RNA remains an enigma. Synthetic RNA topological structures are significant for understanding the physical and biological properties pertaining to RNA topology, and these properties in turn could facilitate identifying naturally occurring topologically nontrivial RNA molecules. Here we show that topological structures containing single-stranded RNA (ssRNA) free of strong base pairing interactions can be created either by configuring RNA–DNA hybrid four-way junctions or by template-directed synthesis with a single-stranded DNA (ssDNA) topological structure. By using a constructed ssRNA knot as a highly sensitive topological probe, we find that Escherichia coli DNA topoisomerase I has low RNA topoisomerase activity and that the R173A point mutation abolishes the unknotting activity for ssRNA, but not for ssDNA. Furthermore, we discover the topological inhibition of reverse transcription (RT) and obtain different RT–PCR patterns for an ssRNA knot and circle of the same sequence.

 

Traumatic brain injury results in acute rarefication of the vascular network

Figure 3

 

Andre Obenaus,1, Michelle Ng,1, Amanda M. Orantes,2, Eli Kinney-Lang,1, Faisal Rashid,1, Mary Hamer,1, Richard A. DeFazio,3, Jiping Tang,4, John H. Zhang,4,5,6, William J. Pearce,4,7

1 Department of Pediatrics, Loma Linda University School of Medicine, Loma Linda, CA, 92350, USA; 2 Molecular and Integrative Physiology, Loma Linda University, Loma Linda, CA, 92350, USA; 3 University of Michigan, Ann Arbor, MI, 48101, USA; 4 Physiology and Pharmacology, Loma Linda University School of Medicine, Loma Linda, CA, 92350, USA; 5 Anesthesiology, Loma Linda University School of Medicine, Loma Linda, CA, 92350, USA; 6 Neurosurgery, Loma Linda University School of Medicine, Loma Linda, CA, 92350, USA; 7 Center for Perinatal Biology, Loma Linda University, Loma Linda, CA, 92350, USA.

DOI: 10.1038/s41598-017-00161-4

The role of the cerebrovascular network and its acute response to TBI is poorly defined and emerging evidence suggests that cerebrovascular reactivity is altered. We explored how cortical vessels are physically altered following TBI using a newly developed technique, vessel painting. We tested our hypothesis that a focal moderate TBI results in global decrements to structural aspects of the vasculature. Rats (naïve, sham-operated, TBI) underwent a moderate controlled cortical impact. Animals underwent vessel painting perfusion to label the entire cortex at 1 day post TBI followed by whole brain axial and coronal images using a wide-field fluorescence microscope. Cortical vessel network characteristics were analyzed for classical angiographic features (junctions, lengths) wherein we observed significant global (both hemispheres) reductions in vessel junctions and vessel lengths of 33% and 22%, respectively. Biological complexity can be quantified using fractal geometric features where we observed that fractal measures were also reduced significantly by 33%, 16% and 13% for kurtosis, peak value frequency and skewness, respectively. Acutely after TBI there is a reduction in vascular network and vascular complexity that are exacerbated at the lesion site and provide structural evidence for the bilateral hemodynamic alterations that have been reported in patients after TBI.

 

A radiobiological model of metastatic burden reduction for molecular radiotherapy: application to patients with bone metastases

Figure 2.

Ana M Denis-Bacelar1, Sarah J Chittenden1, Iain Murray1, Antigoni Divoli1, V Ralph McCready2, David P Dearnaley3, Joe M O’Sullivan4, Bernadette Johnson3, Glenn D Flux1

1 Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, United Kingdom; 2 Department of Nuclear Medicine, Brighton and Sussex University Hospitals NHS Trust, Brighton, United Kingdom; 3 Division of Radiotherapy and Imaging, The Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, United Kingdom; 4 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, United Kingdom.

DOI: 10.1088/1361-6560/aa5e6f

Skeletal tumour burden is a biomarker of prognosis and survival in cancer patients. This study proposes a novel method based on the linear quadratic model to predict the reduction in metastatic tumour burden as a function of the absorbed doses delivered from molecular radiotherapy treatments.

The range of absorbed doses necessary to eradicate all the bone lesions and to reduce the metastatic burden was investigated in a cohort of 22 patients with bone metastases from castration-resistant prostate cancer. A metastatic burden reduction curve was generated for each patient, which predicts the reduction in metastatic burden as a function of the patient mean absorbed dose, defined as the mean of all the lesion absorbed doses in any given patient. In the patient cohort studied, the median of the patient mean absorbed dose predicted to reduce the metastatic burden by 50% was 89 Gy (interquartile range: 83–105 Gy), whilst a median of 183 Gy (interquartile range: 107–247 Gy) was found necessary to eradicate all metastases in a given patient. The absorbed dose required to eradicate all the lesions was strongly correlated with the variability of the absorbed doses delivered to multiple lesions in a given patient (r  =  0.98, P  <  0.0001). The metastatic burden reduction curves showed a potential large reduction in metastatic burden for a small increase in absorbed dose in 91% of patients.

The results indicate the range of absorbed doses required to potentially obtain a significant survival benefit. The metastatic burden reduction method provides a simple tool that could be used in routine clinical practice for patient selection and to indicate the required administered activity to achieve a predicted patient mean absorbed dose and reduction in metastatic tumour burden.