Synthesis, characterization and biological screening of various pharmacophoric derivatives of 4-alkylpyrimidine-5-carbonitrile

81-874-Isobutyl-1,6-dihydro-1-methyl-2-(methylthio)-6-oxopyrimidine-5-carbonitrile has been used as a starting material. Reaction of 4-isobutyl-1,6-dihydro-1-methyl-2-(methylthio)-6-oxopyrimidine-5-carbonitrile with hydrazine hydrate and amine gives 2-hydrazino and 2-(alkyl/ substituted aryl amino)-4-isobutyl-1,6-dihydro-1-methyl-6-oxopyrimidine-5- carbonitrile compounds respectively. The hydrazino compounds react with different aromatic aldehydes, substituted benzene sulphonyl chloride and s-triazine derivative to form Schiff base, sulphonamide and s-triazine derivatives respectively. Reaction of Schiff base with mercapto lactic acid and chloroacetyl chloride yield 4-thiazolidinones and 2-azetidinones respectively

New approaches to measuring anthelminthic drug efficacy: parasitological responses of childhood schistosome infections to treatment with praziquantel

By 2020, the global health community aims to control and eliminate human helminthiases, including schistosomiasis in selected African countries, principally by preventive chemotherapy (PCT) through mass drug administration (MDA) of anthelminthics. Quantitative monitoring of anthelminthic responses is crucial for promptly detecting changes in efficacy, potentially indicative of emerging drug resistance. Statistical models offer a powerful means to delineate and compare efficacy among individuals, among groups of individuals and among populations.; We illustrate a variety of statistical frameworks that offer different levels of inference by analysing data from nine previous studies on egg counts collected from African children before and after administration of praziquantel.; We quantify responses to praziquantel as egg reduction rates (ERRs), using different frameworks to estimate ERRs among population strata, as average responses, and within strata, as individual responses. We compare our model-based average ERRs to corresponding model-free estimates, using as reference the World Health Organization (WHO) 90 % threshold of optimal efficacy. We estimate distributions of individual responses and summarize the variation among these responses as the fraction of ERRs falling below the WHO threshold.; Generic models for evaluating responses to anthelminthics deepen our understanding of variation among populations, sub-populations and individuals. We discuss the future application of statistical modelling approaches for monitoring and evaluation of PCT programmes targeting human helminthiases in the context of the WHO 2020 control and elimination goals

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain

A survey on feature weighting based K-Means algorithms

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of Classification [de Amorim, R. C., 'A survey on feature weighting based K-Means algorithms', Journal of Classification, Vol. 33(2): 210-242, August 25, 2016]. Subject to embargo. Embargo end date: 25 August 2017. The final publication is available at Springer via http://dx.doi.org/10.1007/s00357-016-9208-4 © Classification Society of North America 2016In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means.Peer reviewedFinal Accepted Versio

Concurrence of form and function in developing networks and its role in synaptic pruning

A fundamental question in neuroscience is how structure and function of neural systems are related. We study this interplay by combining a familiar auto-associative neural network with an evolving mechanism for the birth and death of synapses. A feedback loop then arises leading to two qualitatively different types of behaviour. In one, the network structure becomes heterogeneous and dissasortative, and the system displays good memory performance; furthermore, the structure is optimised for the particular memory patterns stored during the process. In the other, the structure remains homogeneous and incapable of pattern retrieval. These findings provide an inspiring picture of brain structure and dynamics that is compatible with experimental results on early brain development, and may help to explain synaptic pruning. Other evolving networks—such as those of protein interactions—might share the basic ingredients for this feedback loop and other questions, and indeed many of their structural features are as predicted by our model.We are grateful for financial support from the Spanish MINECO (project of Excellence: FIS2017-84256-P) and from “Obra Social La Caixa”

Rh-POP Pincer Xantphos Complexes for C-S and C-H Activation. Implications for Carbothiolation Catalysis

The neutral Rh­(I)–Xantphos complex [Rh­(κ³-_P,O,P-Xantphos)­Cl]_<i>n</i>, <b>4</b>, and cationic Rh­(III) [Rh­(κ³-_P,O,P-Xantphos)­(H)₂]­[BAr^F₄], <b>2a</b>, and [Rh­(κ³-_P,O,P-Xantphos-3,5-C₆H₃(CF₃)₂)­(H)₂]­[BAr^F₄], <b>2b</b>, are described [Ar^F = 3,5-(CF₃)₂C₆H₃; Xantphos = 4,5-bis­(diphenylphosphino)-9,9-dimethylxanthene; Xantphos-3,5-C₆H₃(CF₃)₂ = 9,9-dimethylxanthene-4,5-bis­(bis­(3,5-bis­(trifluoromethyl)­phenyl)­phosphine]. A solid-state structure of <b>2b</b> isolated from C₆H₅Cl solution shows a κ¹-chlorobenzene adduct, [Rh­(κ³-_P,O,P-Xantphos-3,5-C₆H₃(CF₃)₂)­(H)₂(κ¹-ClC₆H₅)]­[BAr^F₄], <b>3</b>. Addition of H₂ to <b>4</b> affords, crystallographically characterized, [Rh­(κ³-_P,O,P-Xantphos)­(H)₂Cl], <b>5</b>. Addition of diphenyl acetylene to <b>2a</b> results in the formation of the C–H activated metallacyclopentadiene [Rh­(κ³-_P,O,P-Xantphos)­(ClCH₂Cl)­(σ,σ-(C₆H₄)­C­(H)CPh)]­[BAr^F₄], <b>7</b>, a rare example of a crystallographically characterized Rh–dichloromethane complex, alongside the Rh­(I) complex <i>mer</i>-[Rh­(κ³-_P,O,P-Xantphos)­(η²-PhCCPh)]­[BAr^F₄], <b>6</b>. Halide abstraction from [Rh­(κ³-_P,O,P-Xantphos)­Cl]_<i>n</i> in the presence of diphenylacetylene affords <b>6</b> as the only product, which in the solid state shows that the alkyne binds perpendicular to the κ³-POP Xantphos ligand plane. This complex acts as a latent source of the [Rh­(κ³-_P,O,P-Xantphos)]⁺ fragment and facilitates <i>ortho</i>-directed C–S activation in a number of 2-arylsulfides to give <i>mer</i>-[Rh­(κ³-_P,O,P-Xantphos)­(σ,κ¹-Ar)­(SMe)]­[BAr^F₄] (Ar = C₆H₄COMe, <b>8</b>; C₆H₄(CO)­OMe, <b>9</b>; C₆H₄NO₂, <b>10</b>; C₆H₄CNCH₂CH₂O, <b>11</b>; C₆H₄C₅H₄N, <b>12</b>). Similar C–S bond cleavage is observed with allyl sulfide, to give <i>fac</i>-[Rh­(κ³-_P,O,P-Xantphos)­(η³-C₃H₅)­(SPh)]­[BAr^F₄], <b>13</b>. These products of C–S activation have been crystallographically characterized. For <b>8</b> in situ monitoring of the reaction by NMR spectroscopy reveals the initial formation of <i>fac</i>-κ³-<b>8</b>, which then proceeds to isomerize to the <i>mer</i>-isomer. With the <i>para</i>-ketone aryl sulfide, 4-SMeC ₆H₄COMe, C–H activation <i>ortho</i> to the ketone occurs to give <i>mer</i>-[Rh­(κ³-_P,O,P-Xantphos)­(σ,κ¹-4-(COMe)­C₆H₃SMe)­(H)]­[BAr^F₄], <b>14</b>. The temporal evolution of carbothiolation catalysis using <i>mer</i>-κ³-<b>8</b>, and phenyl acetylene and 2-(methylthio)­acetophenone substrates shows initial fast catalysis and then a considerably slower evolution of the product. We suggest that the initially formed <i>fac</i>-isomer of the C–S activation product is considerably more active than the <i>mer</i>-isomer (i.e., <i>mer</i>-<b>8</b>), the latter of which is formed rapidly by isomerization, and this accounts for the observed difference in rates. A likely mechanism is proposed based upon these data

Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications

A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”

Network Structure Implied by Initial Axon Outgrowth in Rodent Cortex: Empirical Measurement and Models

The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means