N-Substituted 2-(2,6-dinitrophenylamino)propanamides: novel prodrugs that release a primary amine via nitroreduction and intramolecular cyclization

A series of N-dinitrophenylamino acid amides [(4-CONHZ-2, 6-diNO2Ph)N(R)C(X,Y)CONHPhOMe] were prepared as potential bioreductive prodrugs and reduced radiolytically to study their rates of subsequent intramolecular cyclization. Compounds bearing a free NH group (R = H) underwent rapid cyclization in neutral aqueous buffers (t1/2 < 1 min) following 4-electron reduction, with the generation of a N-hydroxydihydroquinoxalinone and concomitant release of 4-methoxyaniline. Amine release from analogous N-methyl analogues (R = Me) was relatively slow. These results are consistent with intramolecular cyclization of a monohydroxylamine intermediate. The high rates of cyclization/extrusion by these very electron-deficient hydroxylamines suggest that the process is greatly accelerated by the presence of an H-bonding "conformational lock" between the anilino NH group and the adjacent o-nitro group (Kirk and Cohen, 1972). Changes in the phenylcarboxamide side chain or in C-methylation in the linking chain had little effect on the rate of cyclization. The model compounds had 1-electron reduction potentials in the range appropriate for cellular reduction (-373 mV for a measured example) and appeared suitable for development as prodrugs that release amine-based effectors following enzymic or radiolytic reduction. Prodrug examples containing 4-aminoaniline mustard and 5-amino-1-(chloromethyl)benz[e]indoline alkylating units were evaluated but were not activated efficiently by cellular nitroreductases. However, cell killing by the radiation-induced reduction of the latter prodrug was demonstrated.     

Metallization and investigation of electrical properties of in vitro recrystallized mSbsC-eGFP assemblies

Surface layer (SL) proteins are self-assembling nanosized arrays which can be recrystallized in solution or on surfaces. In this paper, we investigate the metallization, contact potential difference and conductivity of in vitro recrystallized mSbsC-eGFP tube-like assemblies for possible applications in nanobiotechnology. Treatment of mSbsC-eGFP tube-like structures with 150 mM Pt salt solution resulted in the formation of metallized SL assemblies decorated with Pt nanoparticles (? > 3 nm) which were closely packed and aggregated into metal clusters. Kelvin probe force microscopy (KPFM) measurements revealed that metallized and unmetallized SL templates showed different surface potential behaviours, demonstrating that the metal coating changes the electrostatic surface characteristics of SL assemblies. In situ conductivity measurements showed that unmetallized SL assemblies were not conductive. Metallized samples showed linear I-V dependence between - 1 and + 1 V with a conductivity of ～ 10(3) S m( - 1).     

Sustainability assessment for biodiesel production via fuzzy optimisation during research and development (R&D) stage

Biodiesel is regarded as an important renewable fuel for meeting the global future energy demand and resolving the environmental problems (e.g. global warming). Despite its known advantages, it is still very critical to assess the sustainability of biodiesel production prior to greater expansion for commercialisation. Early hazard assessment when the process is still under development and design is very beneficial as process modifications to eliminate or reduce hazards can be made easier at lower costs. In this paper, inherent safety, health and environment (SHE) and economic performance (EP) analysis is conducted for biodiesel production during the earliest process lifecycle which is named as research and development (R&D) stage. Prior to the assessment, eight biodiesel production pathways via base-catalysed, acid-catalysed, enzymatic and supercritical transesterification using fresh or waste oil are classified. The inherent SHE assessments are conducted using the renowned methods of the Prototype Index of Inherent Safety (PIIS), Inherent Occupational Health Index (IOHI) and Inherent Environmental Toxicity Hazard (IETH) for inherent safety, health and environmental friendliness, respectively. The EP assessment is done using a proposed costing assessment based on operating cost and revenue. A systematic framework for assessing alternative biodiesel production pathways during the R&D stage is presented. Fuzzy optimisation approach is used to assess the pathway candidates based on multiple objectives of inherent SHE and EP. From the assessment result, it is found that biodiesel production based on enzymatic transesterification using waste oil is the most desirable pathway. Following the result of the assessments, several improvement actions for inherent SHE in biodiesel production are proposed and discussed.     

Understanding Parkinsonian handwriting through a computational model of basal ganglia

Handwriting in Parkinson's disease (PD) is typically characterized by micrographia, jagged line contour, and unusual fluctuations in pen tip velocity. Although PD handwriting features have been used for diagnostics, they are not based on a signaling model of basal ganglia (BG). In this letter, we present a computational model of handwriting generation that highlights the role of BG. When PD conditions like reduced dopamine and altered dynamics of the subthalamic nucleus and globus pallidus externa subsystems are simulated, the handwriting produced by the model manifested characteristic PD handwriting distortions like micrographia and velocity fluctuations. Our approach to PD modeling is in tune with the perspective that PD is a dynamic disease.     

Linear Diophantine equation (LDE) decoder: A training-free decoding algorithm for multifrequency SSVEP with reduced computation cost

Multifrequency steady-state visual evoked potentials (SSVEPs) have been developed to extend the capability of SSVEP-based brain-machine interfaces (BMIs) to complex applications that have large numbers of targets. Even though various multifrequency stimulation methods have been introduced, the decoding algorithms for multifrequency SSVEP are still in early development. The recently developed multifrequency canonical correlation analysis (MFCCA) was shown to be a feasible training-free option to use in decoding multifrequency SSVEPs. However, the time complexity of MFCCA is shown to be $O(n^3)$, which will lead to long computation time as $n$ grows, where $n$ represents the input size in decoding. In this paper, a novel decoding algorithm is proposed with the aim to reduce the time complexity. This algorithm is based on linear Diophantine equation solvers and has a reduced computation cost $O(nlogn)$ while remaining training-free. Our simulation results demonstrated that linear Diophantine equation (LDE) decoder run time is only one fifth of MFCCA run time under respective optimal settings on 5-s single-channel data. This reduced computation cost makes it easier to implement multifrequency SSVEP in real-time systems. The effectiveness of this new decoding algorithm is validated with nine healthy participants when using dry electrode scalp electroencephalography (EEG).