Stability-based approaches in chemoproteomics

\ua9 The Author(s), 2024. Published by Cambridge University Press. Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies

Chromosome doubling in Tripsacum : the production of artificial, sexual tetraploid plants

Une collection de cals diploïdes et embryogènes de #Tripsacum$ a été constituée et traitée à la colchicine pour induire des doublements chromosomiques. Des sections de cals présentant des cellules dupliquées ont été identifiées par cytométrie en flux, et le niveau de ploïdie des plantules régénérées à partir de ces sections déterminé. Des plantes tétraploïdes, d'origines différentes, ont ainsi été obtenues. Contrairement aux plantes polyploïdes sauvages qui se reproduisent apomictiquement, les plantes tétraploïdes régénérées ont un mode de reproduction sexué. Différentes populations, issues du croisement de ces plantes avec des génotypes tétraploïdes et apomictiques, ont été produites: celles-ci permettront l'étude du contrôle génétique de l'apomixie. (Résumé d'auteur

Brain Interconnections

The interaction brain-machine is now an indissoluble fact. The repercussions this fact will have in future are presently unimaginable. As mentioned in [1] the nerve axon can now be modeled by a cable or a planar high speed interconnection, no matter what kind of interconnection will be used.  The brain development is clearly shown in a stupendous book of the SOCIETY FOR NEUROSCIENCE treating the brain and the nervous system. An extraction of the brain development chapter is here included to show the relationship among the physiological brain connections [2] and the high speed electrical connections [1]. On the other hand, because of the massive volume of information storage now a day the synchronization clock speeds are all in the range of GHz almost reaching the THz. At these very high frequencies the behavior of the interconnects are more like that of a transmission line, and hence distortion, delay, and phase shift-effects caused by phenomena like cross talk, ringing, and overshoot are present and may be undesirable for the performance of a circuit or system. Thus, the interconnects do not have to be considered like simple conductors or lumped elements. All this gives rise to a new emerging discipline known as signal integrity. This discipline is extremely important to maintain the signal quality on microstrip circuits [3]. In this discipline the correct timing and signal quality preservation preventing transients and false switching are studied in order to avoid excessive delays

Influence Diffusion in Social Networks under Time Window Constraints

We study a combinatorial model of the spread of influence in networks that generalizes existing schemata recently proposed in the literature. In our model, agents change behaviors/opinions on the basis of information collected from their neighbors in a time interval of bounded size whereas agents are assumed to have unbounded memory in previously studied scenarios. In our mathematical framework, one is given a network $G=(V,E)$, an integer value $t(v)$ for each node $v\in V$, and a time window size $\lambda$. The goal is to determine a small set of nodes (target set) that influences the whole graph. The spread of influence proceeds in rounds as follows: initially all nodes in the target set are influenced; subsequently, in each round, any uninfluenced node $v$ becomes influenced if the number of its neighbors that have been influenced in the previous $\lambda$ rounds is greater than or equal to $t(v)$. We prove that the problem of finding a minimum cardinality target set that influences the whole network $G$ is hard to approximate within a polylogarithmic factor. On the positive side, we design exact polynomial time algorithms for paths, rings, trees, and complete graphs.Comment: An extended abstract of a preliminary version of this paper appeared in: Proceedings of 20th International Colloquium on Structural Information and Communication Complexity (Sirocco 2013), Lectures Notes in Computer Science vol. 8179, T. Moscibroda and A.A. Rescigno (Eds.), pp. 141-152, 201

Energy measurement and fragment identification using digital signals from partially depleted Si detectors

A study of identification properties of a Si-Si DE-E telescope exploiting an underdepleted residual-energy detector has been performed. Five different bias voltages have been used, one corresponding to full depletion, the others associated with a depleted layer ranging from 90% to 60% of the detector thickness. Fragment identification has been performed using either the DE-E technique or Pulse Shape Analysis (PSA). Both detectors are reverse mounted: particles enter from the low field side, to enhance the PSA performance. The achieved charge and mass resolution has been quantitatively expressed using a Figure of Merit (FoM). Charge collection efficiency has been evaluated and the possibility of energy calibration corrections has been considered. We find that the DE-E performance is not affected by incomplete depletion even when only 60% of the wafer is depleted. Isotopic separation capability improves at lower bias voltages with respect to full depletion, though charge identification thresholds are higher than at full depletion. Good isotopic identification via PSA has been obtained from a partially depleted detector whose doping uniformity is not good enough for isotopic identification at full depletion.Comment: 13 pages, 10 figures 5 tables; submitted to European Physical Journal