Tumescent Injections in Subcutaneous Pig Tissue Disperse Fluids Volumetrically and Maintain Elevated Local Concentrations of Additives for Several Hours, Suggesting a Treatment for Drug Resistant Wounds.

PurposeBolus injection of fluid into subcutaneous tissue results in accumulation of fluid at the injection site. The fluid does not form a pool. Rather, the injection pressure forces the interstitial matrix to expand to accommodate the excess fluid in its volume, and the fluid becomes bound similar to that in a hydrogel. We seek to understand the properties and dynamics of externally tumesced (swollen) subcutaneous tissue as a first step in assessing whether tumescent antibiotic injections into wounds may provide a novel method of treatment.MethodsSubcutaneous injections of saline are performed in live and dead pigs and the physical properties (volume, expansion ratio, residence time, apparent diffusion constant) of the resulting fluid deposits are observed with diffusion-weighted magnetic resonance imaging, computed tomography, and 3D scanning.ResultsSubcutaneous tissue can expand to a few times its initial volume to accommodate the injected fluid, which is dispersed thoroughly throughout the tumescent volume. The fluid spreads to peripheral unexpanded regions over the course of a few minutes, after which it remains in place for several hours. Eventually the circulation absorbs the excess fluid and the tissue returns to its original state.ConclusionsGiven the evidence for dense fluid dispersal and several-hour residence time, a procedure is proposed whereby tumescent antibiotic injections are used to treat drug-resistant skin infections and chronic wounds that extend into the subcutaneous tissue. The procedure has the potential to effectively treat otherwise untreatable wounds by keeping drug concentrations above minimum inhibitory levels for extended lengths of time

Coordination of metronidazole to Cu(II): Structural characterization of a mononuclear square-planar compound Joshua H.

The reaction between metronidazole [1-(2-hydroxyethyl)-2-methyl-5-nitroimidazole, MET] and CuCl2•2H2O in methanol solution has allowed isolation of blue crystals of composition Cu(MET)2Cl2•MeOH. These crystals have been shown by X-ray diffraction to consist of mononuclear square-planar trans-Cu(MET)2Cl2 molecules in which the metronidazole ligands are trans to each other, as are the Cl ligands. The structure of this compound is very different from other compounds that have been obtained from the reaction between CuCl2•2H2O and metronidazole, namely [Cu(MET)2(μ-Cl)Cl]2 and [Cu(MET)2(μ-Cl)(OH2)]2[Cl]2, which are dimers featuring bridging chloride ligands

Wave climatology in the Apostle Islands, Lake Superior

The wave climate of the Apostle Islands in Lake Superior for 35 year (1979–2013) was hindcast and examined using a third‐generation spectral wave model. Wave measurements within the Apostle Islands and offshore NOAA buoys were used to validate the model. Statistics of the significant wave height, peak wave period, and mean wave direction were computed to reveal the spatial variability of wave properties within the archipelago for average and extreme events. Extreme value analysis was performed to estimate the significant wave height at the 1, 10, and 100 year return periods. Significant wave heights in the interior areas of the islands vary spatially but are approximately half those immediately offshore of the islands. Due to reduced winter ice cover and a clockwise shift in wind direction over the hindcast period, long‐term trend analysis indicates an increasing trend of significant wave heights statistics by as much as 2% per year, which is approximately an order of magnitude greater than similar analysis performed in the global ocean for areas unaffected by ice. Two scientific questions related to wave climate are addressed. First, the wave climate change due to the relative role of changing wind fields or ice covers over the past 35 years was revealed. Second, potential bluff erosion affected by the change of wave climate and the trend of lower water levels in the Apostle Islands, Lake Superior was examined.Key Points:Wave climate of the Apostle Islands in Lake Superior for 35 year was hindcastStatistics of the wave climate reveal the spatial variability of wave propertiesAn increasing trend of SWH is found due to climate changePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113131/1/jgrc21305.pd

Crystal structure of hexa-μ-chlorido-μ4-oxido-tetrakis{[1-(2-hydroxyethyl)-2- methyl-5-nitro-1H-imidazole-κN3]copper(II)} containing short NO2· · ·NO2 contacts

The title tetranuclear copper complex, [Cu4Cl6O(C6H9N3O3)4] or [Cu4Cl6O- (MET)4][MET is 1-(2-hydroxyethyl)-2-methyl-5-nitro-1Η-imidazole or metronidazole], contains a tetrahedral arrangement of copper(II) ions. Each copper atom is also linked to the other three copper atoms in the tetrahedron via bridging chloride ions. A fifth coordination position on each metal atom is occupied by a nitrogen atom of the monodentate MET ligand. The result is a distorted CuCl3NO trigonal–bipyramidal coordination polyhedron with the axial positions occupied by oxygen and nitrogen atoms. The extended structure displays O− H ⋅ ⋅ ⋅O hydrogen bonding, as well as unusual short O⋅ ⋅ ⋅ N interactions [2.775 (4) A ˚ ] between the nitro groups of adjacent clusters that are oriented perpendicular to each other. The scattering contribution of disordered water and methanol solvent molecules was removed using the SQUEEZE procedure [Spek (2015). Acta Cryst. C71, 9–16] in PLATON [Spek (2009). Acta Cryst. D65, 148–155]

Characterization of pancreatic lesions from MT-tgfα, Ela-myc and MT-tgfα/Ela-myc single and double transgenic mice

In order to identify good animal models for investigating therapeutic and preventive strategies for pancreatic cancer, we analyzed pancreatic lesions from several transgenic models and made a series of novel findings. Female MT-tgfα mice of the MT100 line developed pancreatic proliferation, acinar-ductal metaplasia, multilocular cystic neoplasms, ductal adenocarcinomas and prominent fibrosis, while the lesions in males were less severe. MT-tgfα-ES transgenic lines of both sexes developed slowly progressing lesions that were similar to what was seen in MT100 males. In both MT100 and MT-tgfα-ES lines, TGFα transgene was expressed mainly in proliferating ductal cells. Ela-myc transgenic mice with a mixed C57BL/6, SJL and FVB genetic background developed pancreatic tumors at 2–7 months of age, and half of the tumors were ductal adenocarcinomas, similar to what was reported originally by Sandgren et al [1]. However, in 20% of the mice, the tumors metastasized to the liver. MT100/Ela-myc and MT-tgfα-ES/Ela-myc double transgenic mice developed not only acinar carcinomas and mixed carcinomas as previously reported but also various ductal-originated lesions, including multilocular cystic neoplasms and ductal adenocarcinomas. The double transgenic tumors were more malignant and metastasized to the liver at a higher frequency (33%) compared with the Ela-myc tumors. Sequencing of the coding region of p16ink4, k-ras and Rb cDNA in small numbers of pancreatic tumors did not identify mutations. The short latency for tumor development, the variety of tumor morphology and the liver metastases seen in Ela-myc and MT-tgfα/Ela-myc mice make these animals good models for investigating new therapeutic and preventive strategies for pancreatic cancer

3D Shape Perception from Monocular Vision, Touch, and Shape Priors

Perceiving accurate 3D object shape is important for robots to interact with the physical world. Current research along this direction has been primarily relying on visual observations. Vision, however useful, has inherent limitations due to occlusions and the 2D-3D ambiguities, especially for perception with a monocular camera. In contrast, touch gets precise local shape information, though its efficiency for reconstructing the entire shape could be low. In this paper, we propose a novel paradigm that efficiently perceives accurate 3D object shape by incorporating visual and tactile observations, as well as prior knowledge of common object shapes learned from large-scale shape repositories. We use vision first, applying neural networks with learned shape priors to predict an object's 3D shape from a single-view color image. We then use tactile sensing to refine the shape; the robot actively touches the object regions where the visual prediction has high uncertainty. Our method efficiently builds the 3D shape of common objects from a color image and a small number of tactile explorations (around 10). Our setup is easy to apply and has potentials to help robots better perform grasping or manipulation tasks on real-world objects.Comment: IROS 2018. The first two authors contributed equally to this wor

Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions

OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion-defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods. METHODS: Thirty-eight MS patients were scanned with diffusion-weighted imaging, magnetization transfer imaging, and standard conventional MRI sequences (cMRI). A total of 499 regions of interest were identified on standard MRI and labeled as persistent black holes (PBH), persistent gray holes (PGH), acute black holes (ABH), acute gray holes (AGH), nonblack or gray holes (NBH), and normal appearing white matter (NAWM). DBSI, diffusion tensor imaging (DTI), and magnetization transfer ratio (MTR) were applied to the 43,261 imaging voxels extracted from these ROIs. The optimized DNN with 10 fully connected hidden layers was trained using the imaging metrics of the lesion subtypes and NAWM. RESULTS: Concordance, sensitivity, specificity, and accuracy were determined for the different imaging methods. DBSI-DNN derived lesion classification achieved 93.4% overall concordance with predetermined lesion types, compared with 80.2% for DTI-DNN model, 78.3% for MTR-DNN model, and 74.2% for cMRI-DNN model. DBSI-DNN also produced the highest specificity, sensitivity, and accuracy. CONCLUSIONS: DBSI-DNN improves the classification of different MS lesion subtypes, which could aid clinical decision making. The efficacy and efficiency of DBSI-DNN shows great promise for clinical applications in automatic MS lesion detection and classification

Classes of Multiple Decision Functions Strongly Controlling FWER and FDR

This paper provides two general classes of multiple decision functions where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR). These classes offer the possibility that an optimal multiple decision function with respect to a pre-specified criterion, such as the missed discovery rate (MDR), could be found within these classes. Such multiple decision functions can be utilized in multiple testing, specifically, but not limited to, the analysis of high-dimensional microarray data sets.Comment: 19 page