Correlation of Foot Bimalleolar Angle and Ultrasonography in Assessing the Severity of Club Foot in Neonates Treated by the Ponseti Method

Introduction: Correlation of Pirani score and foot bimalleolar (FBM) angle has been used in few studies but correlation of FBM angle with ultrasonography has never been evaluated so they are being correlated in assessing the severity of clubfoot in neonates treated by Ponseti method. Material and Methods: Thirty-two feet with congenital talipes equinovarus (CTEV) deformity in neonates were prospectively treated by the Ponseti method. FBM angle and ultrasound parameters were measured three times i.e. at the time of initial presentation, at four weeks of treatment and at completion of treatment. The feet were divided according to the Pirani score in groups: one (0-2.0), two (2.5-4) and three (4.5-6). Correlation between FBM angle and ultrasound parameters were evaluated using Pearson correlation/regression. Results: Correlation between FBM angle and ultrasound parameters were statistically significant (p-value < 0.05). Conclusion: Ultrasound has the potential to accurately depict the pathoanatomy in clubfoot. FBM angle and ultrasound are objective methods to assess the severity of clubfoot. FBM angle and ultrasonography correlated in severity of deformity and correction achieved along the course of treatment

Extending methane profiles from aircraft into the stratosphere for satellite total column validation: A comparative analysis of different data sources

Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9-13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO₂ and CH₄ made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH₄ fields from two different models of atmospheric composition - the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D 20 chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH₄ climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a-priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH₄ as compared to the climatology-based data and the satellite a-priori profiles. Both the C-IFS and TOMCAT models have a bias of about -9 ppb at the locations where tropospheric vertical profiles will be measured 25 by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH₄ retrievals (10 ppb and 34 ppb, respectively). In comparison, the a-priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH₄ retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column

An environmentally benign antimicrobial nanoparticle based on a silver-infused lignin core

Silver nanoparticles have antibacterial properties, but their use has been a cause for concern because they persist in the environment. Here, we show that lignin nanoparticles infused with silver ions and coated with a cationic polyelectrolyte layer form a biodegradable and green alternative to silver nanoparticles. The polyelectrolyte layer promotes the adhesion of the particles to bacterial cell membranes and, together with silver ions, can kill a broad spectrum of bacteria, including Escherichia coli, Pseudomonas aeruginosa and quaternary-amine-resistant Ralstonia sp. Ion depletion studies have shown that the bioactivity of these nanoparticles is time-limited because of the desorption of silver ions. High-throughput bioactivity screening did not reveal increased toxicity of the particles when compared to an equivalent mass of metallic silver nanoparticles or silver nitrate solution. Our results demonstrate that the application of green chemistry principles may allow the synthesis of nanoparticles with biodegradable cores that have higher antimicrobial activity and smaller environmental impact than metallic silver nanoparticles

The XVth World Congress of Psychiatric Genetics, October 7–11, 2007: Rapporteur summaries of oral presentations

The World Congress of Psychiatric Genetics (WCPG) has become an annual event since the early 1990's sponsored by the International Society of Psychiatric Genetics (ISPG). Each year the latest published and unpublished findings are aired for discussion by representatives of the majority of research programs on this topic world-wide. The 2007 congress was held in New York City and attracted over 1000 researchers. The topics emphasized included results from whole genome association studies, the significance of copy number variation and the important contributions of epigenetic events to psychiatric disorders. There were over 20 oral sessions devoted to these and other topics of interest. Young investigator recipients of travel awards served as rapporteurs to summarize sessions and these summaries follow.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58040/1/30711_ftp.pd

The degradation of p53 and its major E3 ligase Mdm2 is differentially dependent on the proteasomal ubiquitin receptor S5a.

p53 and its major E3 ligase Mdm2 are both ubiquitinated and targeted to the proteasome for degradation. Despite the importance of this in regulating the p53 pathway, little is known about the mechanisms of proteasomal recognition of ubiquitinated p53 and Mdm2. In this study, we show that knockdown of the proteasomal ubiquitin receptor S5a/PSMD4/Rpn10 inhibits p53 protein degradation and results in the accumulation of ubiquitinated p53. Overexpression of a dominant-negative deletion of S5a lacking its ubiquitin-interacting motifs (UIM)s, but which can be incorporated into the proteasome, also causes the stabilization of p53. Furthermore, small-interferring RNA (siRNA) rescue experiments confirm that the UIMs of S5a are required for the maintenance of low p53 levels. These observations indicate that S5a participates in the recognition of ubiquitinated p53 by the proteasome. In contrast, targeting S5a has no effect on the rate of degradation of Mdm2, indicating that proteasomal recognition of Mdm2 can be mediated by an S5a-independent pathway. S5a knockdown results in an increase in the transcriptional activity of p53. The selective stabilization of p53 and not Mdm2 provides a mechanism for p53 activation. Depletion of S5a causes a p53-dependent decrease in cell proliferation, demonstrating that p53 can have a dominant role in the response to targeting S5a. This study provides evidence for alternative pathways of proteasomal recognition of p53 and Mdm2. Differences in recognition by the proteasome could provide a means to modulate the relative stability of p53 and Mdm2 in response to cellular signals. In addition, they could be exploited for p53-activating therapies. This work shows that the degradation of proteins by the proteasome can be selectively dependent on S5a in human cells, and that this selectivity can extend to an E3 ubiquitin ligase and its substrate

Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology

The key to success in machine learning is the use of effective data representations. The success of deep neural networks (DNNs) is based on their ability to utilize multiple neural network layers, and big data, to learn how to convert simple input representations into richer internal representations that are effective for learning. However, these internal representations are sub-symbolic and difficult to explain. In many scientific problems explainable models are required, and the input data is semantically complex and unsuitable for DNNs. This is true in the fundamental problem of understanding the mechanism of cancer drugs, which requires complex background knowledge about the functions of genes/proteins, their cells, and the molecular structure of the drugs. This background knowledge cannot be compactly expressed propositionally, and requires at least the expressive power of Datalog. Here we demonstrate the use of relational learning to generate new data descriptors in such semantically complex background knowledge. These new descriptors are effective: adding them to standard propositional learning methods significantly improves prediction accuracy. They are also explainable, and add to our understanding of cancer. Our approach can readily be expanded to include other complex forms of background knowledge, and combines the generality of relational learning with the efficiency of standard propositional learning

Application of isothermal titration calorimetry in evaluation of protein–nanoparticle interactions

Nanoparticles (NPs) offer a number of advantages over small organic molecules for controlling protein behaviour inside the cell. Protein binding to the surface of NPs depends on their surface characteristics, composition and method of preparation (Mandal et al. in J Hazard Mater 248–249:238–245, 2013). It is important to understand the binding affinities, stoichiometries and thermodynamical parameters of NP–protein interactions in order to see which interaction will have toxic and hazardous consequences and thus to prevent it. On the other side, because proteins are on the brink of stability, they may experience interactions with some types of NPs that are strong enough to cause denaturation or significantly change their conformations with concomitant loss of their biological function. Structural changes in the protein may cause exposure of new antigenic sites, “cryptic” peptide epitopes, potentially triggering an immune response which can promote autoimmune disease (Treuel et al. in ACS Nano 8(1):503–513, 2014). Mechanistic details of protein structural changes at NP surface have still remained elusive. Understanding the formation and persistence of the protein corona is critical issue; however, there are no many analytical methods which could provide detailed information about the NP–protein interaction characteristics and about protein structural changes caused by interactions with nanoparticles. The article reviews recent studies in NP–protein interactions research and application of isothermal titration calorimetry (ITC) in this research. The study of protein structural changes upon adsorption on nanoparticle surface and application of ITC in these studies is emphasized. The data illustrate that ITC is a versatile tool for evaluation of interactions between NPs and proteins. When coupled with other analytical methods, it is important analytical tool for monitoring conformational changes in proteins

Guanosine stimulates neurite outgrowth in PC12 cells via activation of heme oxygenase and cyclic GMP

Undifferentiated rat pheochromocytoma (PC12) cells extend neurites when cultured in the presence of nerve growth factor (NGF). Extracellular guanosine synergistically enhances NGF-dependent neurite outgrowth. We investigated the mechanism by which guanosine enhances NGF-dependent neurite outgrowth. Guanosine administration to PC12 cells significantly increased guanosine 3-5-cyclic monophosphate (cGMP) within the first 24 h whereas addition of soluble guanylate cyclase (sGC) inhibitors abolished guanosine-induced enhancement of NGF-dependent neurite outgrowth. sGC may be activated either by nitric oxide (NO) or by carbon monoxide (CO). \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$N^{\omega }$$ \end{document}-Nitro-l-arginine methyl ester (l-NAME), a non-isozyme selective inhibitor of nitric oxide synthase (NOS), had no effect on neurite outgrowth induced by guanosine. Neither nNOS (the constitutive isoform), nor iNOS (the inducible isoform) were expressed in undifferentiated PC12 cells, or under these treatment conditions. These data imply that NO does not mediate the neuritogenic effect of guanosine. Zinc protoporphyrin-IX, an inhibitor of heme oxygenase (HO), reduced guanosine-dependent neurite outgrowth but did not attenuate the effect of NGF. The addition of guanosine plus NGF significantly increased the expression of HO-1, the inducible isozyme of HO, after 12 h. These data demonstrate that guanosine enhances NGF-dependent neurite outgrowth by first activating the constitutive isozyme HO-2, and then by inducing the expression of HO-1, the enzymes responsible for CO synthesis, thus stimulating sGC and increasing intracellular cGMP

Treatment of internuclear ophthalmoparesis in multiple sclerosis with fampridine: A randomized double-blind, placebo-controlled cross-over trial

AIM: To examine whether the velocity of saccadic eye movements in internuclear ophthalmoparesis (INO) improves with fampridine treatment in patients with multiple sclerosis (MS). METHODS: Randomized, double-blind, placebo-controlled, cross-over trial with fampridine in patients with MS and INO. Horizontal saccades were recorded at baseline and at multiple time points post-dose. Main outcome measures were the change of peak velocity versional dysconjugacy index (PV-VDI) and first-pass amplitude VDI (FPA-VDI). Both parameters were compared between fampridine and placebo using a mixed model analysis of variance taking patients as their own control. Pharmacokinetics was determined by serial blood sampling. RESULTS: Thirteen patients had a bilateral and 10 had a unilateral INO. One patient had an INO of abduction (posterior INO of Lutz) and was excluded. Fampridine significantly reduced both PV-VDI (-17.4%, 95% CI: -22.4%, -12.1%; P < 0.0001) and FPA-VDI (-12.5%, 95% CI: -18.9%, -5.5%; P < 0.01). Pharmacokinetics demonstrated that testing coincided with the average tmax at 2.08 hours (SD 45 minutes). The main adverse event reported after administration of fampridine was dizziness (61%). CONCLUSION: Fampridine improves saccadic eye movements due to INO in MS. Treatment response to fampridine may gauge patient selection for inclusion to remyelination strategies in MS using saccadic eye movements as primary outcome measure