Synthesis and structural characterization of hexa-μ₂-chlorido-μ₄-oxido-tetrakis{[4-(phenylethynyl)pyridine-κN]copper(II)} dichloromethane monosolvate

In the crystal structure of the title compound, [Cu4Cl6O(C13H9N)4]·CH2Cl2, the core molecular structure consists of a Cu4 tetrahedron with a central interstitial O atom. Each edge of the Cu4 tetrahedron is bridged by a chlorido ligand. Each copper(II) cation is coordinated to the central O atom, two chlorido ligands and one N atom of the 4-phenylethynylpyridine ligand. In the crystal, the molecules are linked by intermolecular C - H⋯Cl interactions. Furthermore, C - H⋯π and π-π interactions also connect the molecules, forming a three-dimensional network. Hirshfeld surface analysis indicates that the most important contributions for the packing arrangement are from H⋯H and C⋯H/H⋯C interactions.</p

Assessment of Iron(III) chloride as a catalyst for the production of hydrogen from the supercritical water gasification of microalgae

Alkali metal salts and supported transition metals have been the dominant catalysts used to maximise hydrogen production from supercritical water gasification (SCWG). Recently, FeCl3 has emerged as an alternative to these that has been found to be more effective in some cases reported in literature. However, to these authors’ knowledge, few studies exist that study this catalyst with none that involve microalgae as the feedstock. Investigation is reported into the effect of FeCl3 on the SCWG of Chlorella vulgaris for a range of temperatures (400–600°C) and biomass concentrations (1–3wt%), with comparisons made to other catalysts (KOH, Ru/C and their combinations). A significant decrease in hydrogen yield, carbon conversion and energy efficiency was observed with the addition of FeCl3, due to a reduced pH which suppressed the water gas shift reaction and catalysed of char forming reactions. This was in contrary to Ru/C and KOH catalysts, where those outcomes increased. Additionally, when FeCl3 was used with Ru/C, the ruthenium was poisoned, nullifying its positive effects. Consequently, FeCl3 is not a suitable catalyst for hydrogen production from microalgae, either alone or in conjunction with a ruthenium catalyst

Synthesis and structural characterization of hexa-μ₂-chlorido-μ₄-oxido-tetrakis{[4-(phenylethynyl)pyridine-κN]copper(II)} dichloromethane monosolvate

In the crystal structure of the title compound, [Cu4Cl6O(C13H9N)4]·CH2Cl2, the core molecular structure consists of a Cu4 tetrahedron with a central interstitial O atom. Each edge of the Cu4 tetrahedron is bridged by a chlorido ligand. Each copper(II) cation is coordinated to the central O atom, two chlorido ligands and one N atom of the 4-phenylethynylpyridine ligand. In the crystal, the molecules are linked by intermolecular C - H⋯Cl interactions. Furthermore, C - H⋯π and π-π interactions also connect the molecules, forming a three-dimensional network. Hirshfeld surface analysis indicates that the most important contributions for the packing arrangement are from H⋯H and C⋯H/H⋯C interactions.</p

Development of a Selective Inhibitor for Kv1.1 Channels Prevalent in Demyelinated Nerves

Members of the voltage-gated K+ channel subfamily (Kv1), involved in regulating transmission between neurons or to muscles, are associated with human diseases and, thus, putative targets for neurotherapeutics. This applies especially to those containing Kv1.1 α subunits which become prevalent in murine demyelinated axons and appear abnormally at inter-nodes, underlying the perturbed propagation of nerve signals. To overcome this dysfunction, akin to the consequential debilitation in multiple sclerosis (MS), small inhibitors were sought that are selective for the culpable hyper-polarising K+ currents. Herein, we report a new semi-podand – compound 3 – that was designed based on the modelling of its interactions with the extracellular pore region in a deduced Kv1.1 channel structure. After synthesis, purification, and structural characterisation, compound 3 was found to potently (IC50 = 8 µM) and selectively block Kv1.1 and 1.6 channels. The tested compound showed no apparent effect on native Nav and Cav channels expressed in F-11 cells. Compound 3 also extensively and selectively inhibited MS-related Kv1.1 homomer but not the brain native Kv1.1- or 1.6-containing channels. These collective findings highlight the therapeutic potential of compound 3 to block currents mediated by Kv1.1 channels enriched in demyelinated central neurons

A Rational Design of a Selective Inhibitor for Kv1.1 Channels Prevalent in Demyelinated Nerves That Improves Their Impaired Axonal Conduction

K+ channels containing Kv1.1 α subunits, which become prevalent at internodes in demyelinated axons, may underlie their dysfunctional conduction akin to muscle weakness in multiple sclerosis. Small inhibitors were sought with selectivity for the culpable hyper-polarizing K+ currents. Modeling of interactions with the extracellular pore in a Kv1.1-deduced structure identified diaryldi(2-pyrrolyl)methane as a suitable scaffold with optimized alkyl ammonium side chains. The resultant synthesized candidate [2,2′-((5,5′(di-p-topyldiaryldi(2-pyrrolyl)methane)bis(2,2′carbonyl)bis(azanediyl)) diethaneamine·2HCl] (8) selectively blocked Kv1.1 channels (IC50 ≈ 15 μM) recombinantly expressed in mammalian cells, induced a positive shift in the voltage dependency of K+ current activation, and slowed its kinetics. It preferentially inhibited channels containing two or more Kv1.1 subunits regardless of their positioning in concatenated tetramers. In slices of corpus callosum from mice subjected to a demyelination protocol, this novel inhibitor improved neuronal conduction, highlighting its potential for alleviating symptoms in multiple sclerosis

Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection

The detection and monitoring of emotions are important in various applications, e.g. to enable naturalistic and personalised human-robot interaction. Emotion detection often require modelling of various data inputs from multiple modalities, including physiological signals (e.g.EEG and GSR), environmental data (e.g. audio and weather), videos (e.g. for capturing facial expressions and gestures) and more recently motion and location data. Many traditional machine learning algorithms have been utilised to capture the diversity of multimodal data at the sensors and features levels for human emotion classification. While the feature engineering processes often embedded in these algorithms are beneficial for emotion modelling, they inherit some critical limitations which may hinder the development of reliable and accurate models. In this work, we adopt a deep learning approach for emotion classification through an iterative process by adding and removing large number of sensor signals from different modalities. Our dataset was collected in a real-world study from smart-phones and wearable devices. It merges local interaction of three sensor modalities: on-body, environmental and location into global model that represents signal dynamics along with the temporal relationships of each modality. Our approach employs a series of learning algorithms including a hybrid approach using Convolutional Neural Network and Long Short-term Memory Recurrent Neural Network (CNN-LSTM) on the raw sensor data, eliminating the needs for manual feature extraction and engineering. The results show that the adoption of deep-learning approaches is effective in human emotion classification when large number of sensors input is utilised (average accuracy 95% and F-Measure=%95) and the hybrid models outperform traditional fully connected deep neural network (average accuracy 73% and F-Measure=73%). Furthermore, the hybrid models outperform previously developed Ensemble algorithms that utilise feature engineering to train the model average accuracy 83% and F-Measure=82%

The North Atlantic Fish Revolution (ca. AD 1500)

UID/HIS/04666/2013We propose the concept of the “Fish Revolution” to demarcate the dramatic increase in North Atlantic fisheries after AD 1500, which led to a 15-fold increase of cod (Gadus morhua) catch volumes and likely a tripling of fish protein to the European market.We consider three key questions: (1) What were the environmental parameters of the Fish Revolution? (2) What were the globalising effects of the Fish Revolution? (3) What were the consequences of the Fish Revolution for fishing communities? While these questions would have been considered unknowable a decade or two ago, methodological developments in marine environmental history and historical ecology have moved information about both supply and demand into the realm of the discernible. Although much research remains to be done, we conclude that this was a major event in the history of resource extraction from the sea, mediated by forces of climate change and globalisation, and is likely to provide a fruitful agenda for future multidisciplinary research.publishersversionpublishe

Neurofascin as a novel target for autoantibody-mediated axonal injury

Axonal injury is considered the major cause of disability in patients with multiple sclerosis (MS), but the underlying effector mechanisms are poorly understood. Starting with a proteomics-based approach, we identified neurofascin-specific autoantibodies in patients with MS. These autoantibodies recognize the native form of the extracellular domains of both neurofascin 186 (NF186), a neuronal protein concentrated in myelinated fibers at nodes of Ranvier, and NF155, the oligodendrocyte-specific isoform of neurofascin. Our in vitro studies with hippocampal slice cultures indicate that neurofascin antibodies inhibit axonal conduction in a complement-dependent manner. To evaluate whether circulating antineurofascin antibodies mediate a pathogenic effect in vivo, we cotransferred these antibodies with myelin oligodendrocyte glycoprotein–specific encephalitogenic T cells to mimic the inflammatory pathology of MS and breach the blood–brain barrier. In this animal model, antibodies to neurofascin selectively targeted nodes of Ranvier, resulting in deposition of complement, axonal injury, and disease exacerbation. Collectively, these results identify a novel mechanism of immune-mediated axonal injury that can contribute to axonal pathology in MS

The impact of the alkyne substitution pattern and metalation on the photo-isomerization of azobenzene-based platinum(II) diynes and polyynes

Trimethylsilyl-protected dialkynes incorporating azobenzene linker groups, Me₃SiCCRCCSiMe₃ (R = azobenzene-3,3′-diyl, azobenzene-4,4′-diyl, 2,5-dioctylazobenzene-4,4′-diyl), and the corresponding terminal dialkynes, HCCRCCH, have been synthesized and characterized. The CuI-catalyzed dehydrohalogenation reaction between <i>trans</i>-[Ph­(Et₃P)₂PtCl] and the deprotected dialkynes in a 2:1 ratio in ⁱPr₂NH/CH₂Cl₂ gives the platinum­(II) diynes <i>trans</i>-[Ph­(Et₃P)₂PtCCRCCPt­(PEt₃)₂Ph], while the dehydrohalogenation polycondensation reaction between <i>trans</i>-[(ⁿBu₃P)₂PtCl₂] and the dialkynes in a 1:1 molar ratio under similar reaction conditions affords the platinum­(II) polyynes, [−Pt­(PⁿBu₃)₂–CCRCC−]_<i>n</i>. The materials have been characterized spectroscopically, with the diynes also studied using single-crystal X-ray diffraction. The platinum­(II) diynes and polyynes are all soluble in common organic solvents. Optical-absorption measurements show that the compounds incorporating the <i>para</i>-alkynylazobenzene spacers have a higher degree of electronic delocalisation than their <i>meta</i>-alkynylazobenzene counterparts. Reversible photoisomerization in solution was observed spectroscopically for the alkynyl-functionalized azobenzene ligands and, to a lesser extent, for the platinum­(II) complexes. Complementary quantum-chemical modeling was also used to analyze the optical properties and isomerization energetics