The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: an innovative concept

The accuracy of three-dimensional (3D) predictions of soft tissue changes in the surgical correction of facial asymmetry was evaluated in this study. Preoperative (T1) and 6–12-month postoperative (T2) cone beam computed tomography scans of 13 patients were studied. All patients underwent surgical correction of facial asymmetry as part of a multidisciplinary treatment protocol. The magnitude of the surgical movement was measured; virtual surgery was performed on the preoperative scans using Maxilim software. The predicted soft tissue changes were compared to the actual postoperative appearance (T2). Mean (signed) distances and mean (absolute) distances between the predicted and actual 3D surface meshes for each region were calculated. The one-sample t-test was applied to test the alternative hypothesis that the mean absolute distances had a value of <2.0 mm. A novel directional analysis was applied to analyse the accuracy of the prediction of soft tissue changes. The results showed that the distances between the predicted and actual postoperative soft tissue changes were less than 2.0 mm in all regions. The predicted facial morphology was narrower than the actual surgical changes in the cheek regions. 3D soft tissue prediction using Maxilim software in patients undergoing the correction of facial asymmetry is clinically acceptable

Nonlinear Discrete Systems with Nonanalytic Dispersion Relations

A discrete system of coupled waves (with nonanalytic dispersion relation) is derived in the context of the spectral transform theory for the Ablowitz Ladik spectral problem (discrete version of the Zakharov-Shabat system). This 3-wave evolution problem is a discrete version of the stimulated Raman scattering equations, and it is shown to be solvable for arbitrary boundary value of the two radiation fields and initial value of the medium state. The spectral transform is constructed on the basis of the D-bar approach.Comment: RevTex file, to appear in Journ. Math. Phy

The adaptor protein CRK is a pro-apoptotic transducer of endoplasmic reticulum stress.

Excessive demands on the protein-folding capacity of the endoplasmic reticulum (ER) cause irremediable ER stress and contribute to cell loss in a number of cell degenerative diseases, including type 2 diabetes and neurodegeneration. The signals communicating catastrophic ER damage to the mitochondrial apoptotic machinery remain poorly understood. We used a biochemical approach to purify a cytosolic activity induced by ER stress that causes release of cytochrome c from isolated mitochondria. We discovered that the principal component of the purified pro-apoptotic activity is the proto-oncoprotein CRK (CT10-regulated kinase), an adaptor protein with no known catalytic activity. Crk(-/-) cells are strongly resistant to ER-stress-induced apoptosis. Moreover, CRK is cleaved in response to ER stress to generate an amino-terminal M(r)~14K fragment with greatly enhanced cytotoxic potential. We identified a putative BH3 (BCL2 homology 3) domain within this N-terminal CRK fragment, which sensitizes isolated mitochondria to cytochrome c release and when mutated significantly reduces the apoptotic activity of CRK in vivo. Together these results identify CRK as a pro-apoptotic protein that signals irremediable ER stress to the mitochondrial execution machinery

Decay of weak solutions to the 2D dissipative quasi-geostrophic equation

We address the decay of the norm of weak solutions to the 2D dissipative quasi-geostrophic equation. When the initial data is in $L^2$ only, we prove that the $L^2$ norm tends to zero but with no uniform rate, that is, there are solutions with arbitrarily slow decay. For the initial data in $L^p \cap L^2$, with $1 \leq p < 2$, we are able to obtain a uniform decay rate in $L^2$. We also prove that when the $L^{\frac{2}{2 \alpha -1}}$ norm of the initial data is small enough, the $L^q$ norms, for $q > \frac{2}{2 \alpha -1}$ have uniform decay rates. This result allows us to prove decay for the $L^q$ norms, for $q \geq \frac{2}{2 \alpha -1}$, when the initial data is in $L^2 \cap L^{\frac{2}{2 \alpha -1}}$.Comment: A paragraph describing work by Carrillo and Ferreira proving results directly related to the ones in this paper is added in the Introduction. Rest of the article remains unchange

Pseudo-gap features of intrinsic tunneling in (HgBr_2)-Bi2212 single crystals

The c-axis tunneling properties of both pristine Bi2212 and its HgBr$_2$ intercalate have been measured in the temperature range 4.2 - 250 K. Lithographically patterned 7-10 unit-cell heigh mesa structures on the surfaces of these single crystals were investigated. Clear SIS-like tunneling curves for current applied in the $\it c$-axis direction have been observed. The dynamic conductance d$I/$d$V(V)$ shows both sharp peaks corresponding to a superconducting gap edge and a dip feature beyond the gap, followed by a wide maximum, which persists up to a room temperature. Shape of the temperature dependence of the {\it c}-axis resistance does not change after the intercalation suggesting that a coupling between $\rm CuO_2$-bilayers has little effect on the pseudogap.Comment: 6 pages, 5 figures; presented at the Second Int Conf. New3Sc-1999 (Las Vegas, NV

Prediction of microbial communities for urban metagenomics using neural network approach.

BACKGROUND:Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious diseases and detect potentially urgent threats. To achieve this goal, the DNA sample collection and analysis have been conducted at subway stations in major cities. However, city-scale sampling with the fine-grained geo-spatial resolution is expensive and laborious. In this paper, we introduce MetaMLAnn, a neural network based approach to infer microbial communities at unsampled locations given information reflecting different factors, including subway line networks, sampling material types, and microbial composition patterns. RESULTS:We evaluate the effectiveness of MetaMLAnn based on the public metagenomics dataset collected from multiple locations in the New York and Boston subway systems. The experimental results suggest that MetaMLAnn consistently performs better than other five conventional classifiers under different taxonomic ranks. At genus level, MetaMLAnn can achieve F1 scores of 0.63 and 0.72 on the New York and the Boston datasets, respectively. CONCLUSIONS:By exploiting heterogeneous features, MetaMLAnn captures the hidden interactions between microbial compositions and the urban environment, which enables precise predictions of microbial communities at unmeasured locations