A numerical analysis of phonation using a two-dimensional flexible channel model of the vocal folds.

A two-dimensional flexible channel model of the vocal folds coupled with an unsteady one-dimensional flow model is presented for an analysis of the mechanism of phonation. The vocal fold is approximated by springs and dampers distributed in the main flow direction that are enveloped with an elastic cover. In order to approximate three-dimensional collision of the vocal folds using the two-dimensional model, threshold values for the glottal width are introduced. The numerical results show that the collision plays an important role in speech sound, especially for higher resonant frequency components, because it causes the source sound to include high-frequency components.     

VISTAL--a new 2D visualization tool of protein 3D structural alignments

We offer a tool, denoted VISTAL, for two-dimensional visualization of protein structural alignments. VISTAL describes aligned structures as a series of matched secondary structure elements, colored according to the three-dimensional distance of their Calpha atoms. AVAILABILITY: VISTAL can be downloaded from http://trantor.bioc.columbia.edu/~kolodny/software.html.     

TFF peptides in the human false vocal folds of the larynx

TFF peptides (formerly P domain peptides, trefoil factors) are typical secretory products of mucin-producing cells and are thought to influence the rheological properties of mucous gels. We investigated the localization of these peptides in the human false vocal folds of the larynx, also known as the ventricular folds or vestibular folds. An analysis of TFF peptide mRNA by RT-PCR and TFF protein by Western blot detected TFF1 and TFF3, but not TFF2. Immunohistochemistry revealed TFF1 to be associated with the secretory product of goblet cells and mucous parts of subepithelial seromucous glands. TFF3 occurred in columnar epithelial cells of the mucosa and in serous cells and excretory duct cells of seromucous glands. These peptides may play a role in the rheological function of mucus secreted onto the true vocal folds and are thus important constituents of vocal production.     

A hybrid genetic-neural model for predicting protein structural classes

A genetic algorithm (GA) for feature selection in conjunction with neural network was applied to predict protein structural classes based on single amino acid and all dipeptide composition frequencies. These sequence parameters were encoded as input features for a GA in feature selection procedure and classified with a three-layered neural network to predict protein structural classes. The system was established through optimization of the classification performance of neural network which was used as evaluation function. In this study, self-consistency and jackknife tests on a database containing 498 proteins were used to verify the performance of this hybrid method, and were compared with some of prior works. The adoption of a hybrid model, which encompasses genetic and neural technologies, demonstrated to be a promising approach in the task of protein structural class prediction.     

Adapted to roar: functional morphology of tiger and lion vocal folds

Vocal production requires active control of the respiratory system, larynx and vocal tract. Vocal sounds in mammals are produced by flow-induced vocal fold oscillation, which requires vocal fold tissue that can sustain the mechanical stress during phonation. Our understanding of the relationship between morphology and vocal function of vocal folds is very limited. Here we tested the hypothesis that vocal fold morphology and viscoelastic properties allow a prediction of fundamental frequency range of sounds that can be produced, and minimal lung pressure necessary to initiate phonation. We tested the hypothesis in lions and tigers who are well-known for producing low frequency and very loud roaring sounds that expose vocal folds to large stresses. In histological sections, we found that the Panthera vocal fold lamina propria consists of a lateral region with adipocytes embedded in a network of collagen and elastin fibers and hyaluronan. There is also a medial region that contains only fibrous proteins and hyaluronan but no fat cells. Young's moduli range between 10 and 2000 kPa for strains up to 60%. Shear moduli ranged between 0.1 and 2 kPa and differed between layers. Biomechanical and morphological data were used to make predictions of fundamental frequency and subglottal pressure ranges. Such predictions agreed well with measurements from natural phonation and phonation of excised larynges, respectively. We assume that fat shapes Panthera vocal folds into an advantageous geometry for phonation and it protects vocal folds. Its primary function is probably not to increase vocal fold mass as suggested previously. The large square-shaped Panthera vocal fold eases phonation onset and thereby extends the dynamic range of the voice.     

A secondary structural model of the 28S rRNA expansion segments D2 and D3 for Chalcidoid wasps (Hymenoptera: Chalcidoidea)

We analyze the secondary structure of two expansion segments (D2, D3) of the 28S ribosomal (rRNA)-encoding gene region from 527 chalcidoid wasp taxa (Hymenoptera: Chalcidoidea) representing 18 of the 19 extant families. The sequences are compared in a multiple sequence alignment, with secondary structure inferred primarily from the evidence of compensatory base changes in conserved helices of the rRNA molecules. This covariation analysis yielded 36 helices that are composed of base pairs exhibiting positional covariation. Several additional regions are also involved in hydrogen bonding, and they form highly variable base-pairing patterns across the alignment. These are identified as regions of expansion and contraction or regions of slipped-strand compensation. Additionally, 31 single-stranded locales are characterized as regions of ambiguous alignment based on the difficulty in assigning positional homology in the presence of multiple adjacent indels. Based on comparative analysis of these sequences, the largest genetic study on any hymenopteran group to date, we report an annotated secondary structural model for the D2, D3 expansion segments that will prove useful in assigning positional nucleotide homology for phylogeny reconstruction in these and closely related apocritan taxa.     

STAR3D: a stack-based RNA 3D structural alignment tool

The various roles of versatile non-coding RNAs typically require the attainment of complex high-order structures. Therefore, comparing the 3D structures of RNA molecules can yield in-depth understanding of their functional conservation and evolutionary history. Recently, many powerful tools have been developed to align RNA 3D structures. Although some methods rely on both backbone conformations and base pairing interactions, none of them consider the entire hierarchical formation of the RNA secondary structure. One of the major issues is that directly applying the algorithms of matching 2D structures to the 3D coordinates is particularly time-consuming. In this article, we propose a novel RNA 3D structural alignment tool, STAR3D, to take into full account the 2D relations between stacks without the complicated comparison of secondary structures. First, the 3D conserved stacks in the inputs are identified and then combined into a tree-like consensus. Afterward, the loop regions are compared one-to-one in accordance with their relative positions in the consensus tree. The experimental results show that the prediction of STAR3D is more accurate for both non-homologous and homologous RNAs than other state-of-the-art tools with shorter running time.     

A physiologically-based flow network model for hepatic drug elimination III: 2D/3D DLA lobule models

Background

One of the major issues in current pharmaceutical development is potential hepatotoxicity and drug-induced liver damage. This is due to the unique metabolic processes performed in the liver to prevent accumulation of a wide range of chemicals in the blood. Recently, we developed a physiologically-based lattice model to address the transport and metabolism of drugs in the liver lobule (liver functional unit).

Method

In this paper, we extend our idealized model to consider structural and spatial variability in two and three dimensions. We introduce a hexagonal-based model with one input (portal vein) and six outputs (hepatic veins) to represent a typical liver lobule. To capture even more realistic structures, we implement a novel sequential diffusion-limited aggregation (DLA) method to construct a morphological sinusoid network in the lobule. A 3D model constructed with stacks of multiple 2D sinusoid realizations is explored to study the effects of 3D structural variations. The role of liver zonation on drug metabolism in the lobule is also addressed, based on flow-based predicted steady-state O₂ profiles used as a zonation indicator.

Results

With this model, we analyze predicted drug concentration levels observed exiting the lobule with their detailed distribution inside the lobule, and compare with our earlier idealized models. In 2D, due to randomness of the sinusoidal structure, individual hepatic veins respond differently (i.e. at different times) to injected drug. In 3D, however, the variation of response to the injected drug is observed to be less extreme. Also, the production curves show more diffusive behavior in 3D than in 2D.

Conclusion

Although, the individual producing ports respond differently, the average lobule production summed over all hepatic veins is more diffuse. Thus the net effect of all these variations makes the overall response smoother. We also show that, in 3D, the effect of zonation on drug production characteristics appears quite small. Our new biophysical structural analysis of a physiologically-based 3D lobule can therefore form the basis for a quantitative assessment of liver function and performance both in health and disease

     

A hybrid blob-slice model for accurate and efficient detection of fluorescence labeled nuclei in 3D

Background  

To exploit the flood of data from advances in high throughput imaging of optically sectioned nuclei, image analysis methods need to correctly detect thousands of nuclei, ideally in real time. Variability in nuclear appearance and undersampled volumetric data make this a challenge.     

Novel two-stage hybrid neural discriminant model for predicting proteins structural classes

In order to establish novel hybrid neural discriminant model, linear discriminant analysis (LDA) was used at the first stage to evaluate the contribution of sequence parameters in determining the protein structural class. An in-house program generated parameters including single amino acid and all dipeptide composition frequencies for 498 proteins came from Zhou [An intriguing controversy over protein structural class prediction, J. Protein Chem. 17(8) (1998) 729-738]. Then, 127 statistically effective parameters were selected by stepwise LDA and were used as inputs of the artificial neural networks (ANNs) to build a two-stage hybrid predictor. In this study, self-consistency and jackknife tests were used to verify the performance of this hybrid model, and were compared with some of prior works. The results showed that our two-stage hybrid neural discriminant model approach is very promising and may play a complementary role to the existing powerful approaches.     

Considering 3D topography of endothelial folds to improve cell count of organ cultured corneas

The posterior side of the cornea is covered by the endothelial monolayer, which governs corneal transparency but cannot proliferate. Determination of endothelial cell density (ECD) is therefore the minimal and mandatory quality control in all eye banks. It avoids primary graft failures caused by endothelial insufficiency, and allows allocation of corneas to surgical techniques requiring different numbers of endothelial cells (ECs). Corneas stored in organ culture (17% of grafts worldwide), are characterized by heavy stromal swelling and numerous deep endothelial folds, up to 200 µm high. During microscopic en face observation, flat surfaces are thus exceptional and EC counting is biased by parallax errors, resulting in overestimated eye bank ECD (ebECD). We used a motorized transmitted light microscope to acquire Z-stacks of images every 10 µm, and processed them to reconstruct the 3D surface of the folded endothelium. This method (3D-ECD) takes into account the local point-by-point slope in order to correct ECD. On a set of 30 corneas, we compared 3D-ECD and ebECD determined on five identical zones at the center of the cornea. 3D reconstruction allowed us to visualize twice as many cells, and ebECD was 8.1 ± 4.5% (95%CI 6.4–9.7) higher than 3D-ECD, with 1744 ± 488 versus 1606 ± 473 cells/mm². 3D counting makes it possible to increase cell sampling and to correct overestimation by the conventional en face counting still routinely performed in eye banks.