Tandem mass spectrometry and nuclear magnetic resonance spectroscopy studies of Candida bombicola sophorolipids and product formed on hydrolysis by cutinase

Natural mixtures of sophorolipids produced by the yeast Candida bombicola have been analyzed by fast atom bombardment (FAB)-MS and collision-induced dissociation (CID)-MS. Some pure components have been analysed by two-dimensional NMR spectroscopy. The presence of acidic, lactonic, and O-acetylated forms and the position of double bonds in the fatty acid part of these glycolipids can be easily inferred from positive and negative ion FAB-mass spectra. Details about position of O-acetylation can be obtained from CID mass spectra of [M+H]+ and [M-H]- ions and from the NMR spectra. Differences in CID fragmentation between protonated and sodiated molecular ions are discussed in detail. Enzymatic hydrolysis of 6',6"-di-O-acetyl sophorolipid lactone by cutinase from Fusarium solani results specifically in the removal of the 6'-O-acetyl group, whereas the 6"-O-acetyl and lactone group are resistant. This specificity is explained from a three-dimensional model of the sophorolipid generated on the basis of the short 1H,1H distances as inferred from the NMR (ROESY) spectra.     

Arginine 206 of the C5a receptor is critical for ligand recognition and receptor activation by C-terminal hexapeptide analogs

C5a is a 74-amino-acid glycoprotein whose receptor is a member of the rhodopsin superfamily. While antagonists have been generated to many of these receptors, similar efforts directed at family members whose natural ligands are proteins have met with little success. The recent development of hexapeptide analogs of C5a has allowed us to begin elucidation of the molecular events that lead to activation by combining a structure/activity study of the ligand with receptor mutagenesis. Removal of the hexapeptide's C-terminal arginine reduces affinity by 100-fold and eliminates the ability of the ligand to activate the receptor. Both the guanidino side chain and the free carboxyl of the arginine participate in the interaction. The guanidino group makes the energy-yielding contact with the receptor, while the free carboxylate negates "electrostatic" interference with Arg-206 of the receptor. It is the apparent movement Arg-206 induced by this set of interactions that is responsible for activation, since conversion of Arg-206 to alanine eliminates the agonist activity of the hexapeptides. Surprisingly, activation is a nearly energy-neutral event and may reflect the binding process rather than the final resting site of the ligand.     

Incremental value of prognostic testing in patients with known or suspected ischemic heart disease: a basis for optimal utilization of exercise technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography

OBJECTIVES: This study assessed the incremental prognostic implications of normal and equivocal exercise technetium-99m (Tc-99m) sestamibi single-photon emission computed tomography (SPECT) and sought to determine its incremental prognostic value, impact on patient management and cost implications. BACKGROUND: The prognostic implications of Tc-99m sestamibi SPECT are not well defined, and risk stratification using this test has not been explored. METHODS: We studied 1,702 patients referred for exercise Tc-99m sestamibi SPECT who were followed up for a mean (+/- SD) of 20 +/- 5 months. Patients with previous percutaneous transluminal coronary angioplasty or coronary artery bypass surgery were excluded. The SPECT studies were assessed using semiquantitative visual analysis. Cardiac death and myocardial infarction were considered "hard" events, and coronary angioplasty and bypass surgery > 60 days after testing were considered "soft" events. RESULTS: Of the 1,702 patients studied, 1,131 had normal or equivocal scan results. A total of 10 events occurred in this group (1 cardiac death and 1 myocardial infarction [0.2% hard events]; 4 coronary angioplasty and 4 bypass surgery procedures [0.7% soft events]). The rates of hard events and referral to catheterization after SPECT were similarly low in patients with a low (< 0.15), intermediate (0.15 to 0.85) and high (> 0.85) post-exercise treadmill test (ETT) likelihood of coronary artery disease. With respect to scan type, patients with normal, probably normal or equivocal scan results had similarly low hard event rates. In the 571 patients with abnormal scan results, there were 43 hard events (7.5%) and 42 soft events (7.4%) (p < 0.001 vs. 1,131 patients with normal scan results for both). When the complete spectrum of scan responses was considered, SPECT provided incremental prognostic value in all patient subgroups analyzed. However, the nuclear scan was cost-effective only in patients with interpretable exercise ECG responses and an intermediate to high post-ETT likelihood of coronary artery disease and in those with uninterpretable exercise ECG responses and an intermediate to high pre-ETT likelihood of coronary artery disease. CONCLUSIONS: Normal or equivocal exercise Tc-99m sestamibi study results are associated with a benign prognosis, even in patients with a high likelihood of coronary artery disease. Although incremental prognostic value is added by nuclear testing in all patient subgroups, a testing strategy incorporating nuclear testing proved to be cost-effective only in the groups with an intermediate to high likelihood of coronary artery disease before scanning.     

Point Set pattern matching ind-dimensions

In this paper we apply computational geometry techniques to obtain an efficient algorithm for the following point set pattern matching problem. Given a setS ofn points and a setP ofk points in thed-dimensional Euclidean space, determine whetherP matches anyk-subset ofS, where a match can be any similarity, i.e., the setP is allowed to undergo translation, rotation, reflection, and global scaling. Motivated by the need to traverse the sets in an orderly fashion to shun exponential complexity, we circumvent the lack of a total order for points in high-dimensional spaces by using an extension of one-dimensional sorting to higher dimensions (which we call circular sorting). This mechanism enables us to achieve the orderly traversal we sought. An optimal algorithm (in time and space) is described for performing circular sorting in arbitrary dimensions. The time complexity of the resulting algorithm for point set pattern matching is O(n logn+kn) for dimension one and O(kn^d) for dimensiond2.Supported in part by CNPq-Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (Brazil) under Grants 200331/79, 300157/90-8, and 500787/91-3.Supported in part by the National Science Foundation under Grant CCR 8901815.     

Clinical and epidemiological findings during a measles outbreak occurring in a population with a high vaccination coverage

Malignant mesothelioma is caused almost exclusively by occupational exposure to asbestos. During the past few years, however, increasing evidence has mounted that background exposure to asbestos could be sufficient to cause mesothelioma. Treatment of malignant mesothelioma remains a big problem. Some new approaches are on their way, and the most exciting ones are local immunotherapy in very early cases. Some success has been reported with local interferon treatment. As for treatment of metastatic pleural disease, the main purpose is symptomatic relief of dyspnea caused by fluid accumulation. The best way to achieve a lasting palliation is pleurodesis, and the most common way to do this, is by chemical means. The drug of choice in the United States has for many years been tetracycline, but since injectable tetracycline is no longer available, some substitute must be found. The substance that will "win" is not yet clear, but the two leading contestants are talc and doxycycline. Bleomycin also has its supporters, and a dark horse is quinacrine, which although not easily available in the United States, has been used in many European centers for decades.     

Composites of hydroxyapatite and bisphosphonate: properties and alveolar bone response

A composite was made by adsorption of the bisphosphonate [(3-dimethylamino-1-hydroxypropylidene)-1,1-bisphosphonate; dimethyl-APD] into an hydroxyapatite (HA) tube. Adsorbed dimethyl-APD did not change the bulk properties of the HA tube but the surface properties were altered. The amount of 0.1 mmol/L dimethyl-APD adsorbed into the HA tube was 0.78 ( ± 0.20) g after 4 weeks. The composite tube of HA and dimethyl-APD placed after extraction of teeth in the premolar regions of dogs were biocompatible, stable and bonded strongly and intimately to the alveolar bone. Although there was no bone resorption around the composite tubes, no conclusion can be drawn yet from this study as far as local inhibition of alveolar bone resorption is concerned.     

Multiphoton Lithography as a Promising Tool for Biomedical Applications

Multiphoton lithography (MPL) is a powerful and useful structuring tool capable of generating 2D and 3D arbitrary micro- and nanometer features of various materials with high spatial resolution down to nm-scale. This technology has received tremendous interest in tissue engineering and medical device manufacturing, due to its ability to print sophisticated structures, which is difficult to achieve through traditional printing methods. Thorough consideration of two-photon photoinitiators (PIs) and photoreactive biomaterials is key to the fabrication of such complex 3D micro- and nanostructures. In the current review, different types of two-photon PIs are discussed for their use in biomedical applications. Next, an overview of biomaterials (both natural and synthetic polymers) along with their crosslinking mechanisms is provided. Finally, biomedical applications exploiting MPL are presented, including photocleaving and photopatterning strategies, biomedical devices, tissue engineering, organoids, organ-on-chip, and photodynamic therapy. This review offers a helicopter view on the use of MPL technology in the biomedical field and defines the necessary considerations toward selection or design of PIs and photoreactive biomaterials to serve a multitude of biomedical applications.     

Metal Single-Site Molecular Complex–MXene Heteroelectrocatalysts Interspersed Graphene Nanonetwork for Efficient Dual-Task of Water Splitting and Metal–Air Batteries

Development of multifunctional electrocatalysts with high efficiency and stability is of great interest in recent energy conversion technologies. Herein, a novel heteroelectrocatalyst of molecular iron complex (Fe_MC)-carbide MXene (Mo₂TiC₂T_x) uniformly embedded in a 3D graphene-based hierarchical network (GrH) is rationally designed. The coexistence of Fe_MC and MXene with their unique interactions triggers optimum electronic properties, rich multiple active sites, and favorite free adsorption energy for excellent trifunctional catalytic activities. Meanwhile, the highly porous GrH effectively promotes a multichannel architecture for charge transfer and gas/ion diffusion to improve stability. Therefore, the Fe_MC–MXene/GrH results in superb performances towards oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) in alkaline medium. The practical tests indicate that Zn/Al–air batteries derived from Fe_MC–MXene/GrH cathodic electrodes produce high power densities of 165.6 and 172.7 mW cm⁻², respectively. Impressively, the liquid-state Zn–air battery delivers excellent cycling stability of over 1100 h. In addition, the alkaline water electrolyzer induces a low cell voltage of 1.55 V at 10 mA cm⁻² and 1.86 V at 0.4 A cm⁻² in 30 wt.% KOH at 80 °C, surpassing recent reports. The achievements suggest an exciting multifunctional electrocatalyst for electrochemical energy applications.     

Applying Wide & Deep Learning Model for Android Malware Classification

Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model.     

Malicious uses of blockchains by malware: from the analysis to Smart-Zephyrus

The permanent availability and relative obscurity of blockchains is the perfect ground for using them for malicious purposes. However, the use of blockchains by malwares has not been characterized yet. This paper analyses the current state of the art in this area. One of the lessons learned is that covert communications for malware have received little attention. To foster further defence-oriented research, a novel mechanism (dubbed Smart-Zephyrus) is built leveraging smart contracts written in Solidity. Our results show that it is possible to hide 4 Kb of secret in 41 s. While being expensive (around USD 1.82 per bit), the provided stealthiness might be worth the price for attackers.