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Synaptic plasticity is a critical process that regulates neuronal activity by allowing neurons to adjust their synaptic strength in response to changes in activity. Despite the high proximity of excitatory glutamatergic and inhibitory GABAergic postsynaptic zones and their functional integration within dendritic regions, concurrent plasticity has historically been underassessed. Growing evidence for pathological disruptions in the excitation and inhibition (E/I) balance in neurological and neurodevelopmental disorders indicates the need for an improved, more “holistic” understanding of synaptic interplay. There continues to be a long-standing focus on the persistent strengthening of excitation (excitatory long-term potentiation; eLTP) and its role in learning and memory, although the importance of inhibitory long-term potentiation (iLTP) and depression (iLTD) has become increasingly apparent. Emerging evidence further points to a dynamic dialogue between excitatory and inhibitory synapses, but much remains to be understood regarding the mechanisms and extent of this exchange. In this mini-review, we explore the role calcium signaling and synaptic crosstalk play in regulating postsynaptic plasticity and neuronal excitability. We examine current knowledge on GABAergic and glutamatergic synapse responses to perturbances in activity, with a focus on postsynaptic plasticity induced by short-term pharmacological treatments which act to either enhance or reduce neuronal excitability via ionotropic receptor regulation in neuronal culture. To delve deeper into potential mechanisms of synaptic crosstalk, we discuss the influence of synaptic activity on key regulatory proteins, including kinases, phosphatases, and synaptic structural/scaffolding proteins. Finally, we briefly suggest avenues for future research to better understand the crosstalk between glutamatergic and GABAergic synapses.

Ligand-gated ion channel GABA type A receptors (GABA_ARs) mediate the majority of fast inhibition in the central nervous system, while glutamatergic AMPA receptors (AMPARs) and NMDA receptors (NMDARs) collectively mediate fast excitatory neurotransmission. NMDARs particularly play a unique role in synaptic plasticity due to high calcium permeability and voltage-dependent Mg²⁺ block typically relieved by AMPAR-mediated depolarization. Slow inhibition and excitation are generated by G protein-coupled, GABA type B (GABA_BRs) and metabotropic glutamate receptors (mGluRs), respectively. The concerted action of these receptors balances neuronal excitability. A close and coordinated spatial relationship between glutamatergic and GABAergic synapses on dendrites (Megías et al., 2001; Bleckert et al., 2013; Iascone et al., 2020), sometimes as near as on the same spine (Chen et al., 2012), facilitates synaptic input integration, dynamic calcium regulation, synaptic crosstalk, and coregulation.

Synaptic plasticity describes the ability of synapses to adapt their relative strength based on the overall level of activity or specific activity patterns, often by dynamic regulation of receptor-synaptic scaffold interactions or through trafficking. During development, it is heavily involved in dendritic growth, synaptogenesis, and the formation of neural circuits (reviewed in Akgül and McBain, 2016; Ismail et al., 2017; Jenks et al., 2021). In mature neurons, synaptic plasticity is responsible for synapse remodeling during experience. Genetic mutations or pathology leading to altered excitatory or inhibitory neurotransmission or impaired synaptogenesis typically result in deficits in synaptic plasticity, a common feature in neurodevelopmental and neurological disorders (Rudolph and Möhler, 2014; Mele et al., 2019), including autism (Hansel, 2019; Sohal and Rubenstein, 2019), down syndrome (Galdzicki et al., 2001; Schulz et al.

What is antibiotic resistance? What is the global clinical antibacterial pipeline? What is the global preclinical antibacterial pipeline? Institutions associated with preclinical drug development Preclinical projects Trends in the preclinical antibacterial pipeline References Further reading.

The global preclinical antibacterial pipeline refers to innovative antibacterial candidate drugs that are under development with the aim of effectively eliminating newly emerged and pre-existing priority pathogens.

Antibacterial medicines or antibiotics treat bacterial infections in humans, animals, and plants. However, bacteria may eventually develop resistance against antibiotics-mediated killing by acquiring genetic mutations. Although antibiotic resistance occurs naturally, misuse or overuse of antibiotics can significantly escalate the process.

Many cancer therapies do not produce the hoped-for results. A common reason for this is that the tumors develop resistance to the medications. This is the case, for example, with alpelisib, a drug that has been approved for use in Switzerland for the past few years as a treatment for advanced breast cancer.

A research group at the Department of Biomedicine of the University of Basel has now discovered that the loss of the neurofibromin 1 (NF1) gene leads to a reduced response to alpelisib. The researchers also found that the dietary supplement N-acetylcysteine restores the sensitivity of cancer cells to this treatment. The findings have been published in the journal Cell Reports Medicine on April 11.

At the moment, patients with advanced and metastatic breast cancer lack effective treatment options. The PI3K signaling pathway is often overactive in breast cancer due to mutations promoting tumor development. The approval of the PI3K inhibitor Alpelisib was therefore keenly anticipated.

Most Beautiful japanese humanoid Robots | AI SCience |

The world of robots is evolving at an unprecedented rate. We just cannot imagine the kind of innovations the Japanese companies have come up with when it comes to humanoid robots. There are a lot of new technological upgrades in these robots that will prove to be very important as time passes. But what possible capabilities can we reach through it? Stay tuned and you shall find all of the answers.
#WhatisArtificialIntelligence #QuickSupport #Innovation.

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The Oxford Martin Programme on Bio-Inspired Technologies is investigating the possibility of making computers real.

We aim to develop a completely new methodology for overcoming the extreme fragility of memory. By learning how biological molecules shield fragile states from the environment, we hope to create the building blocks of future computers.

The unique power of computers comes from their ability to carry out all possible calculations in parallel.

As quantum advantage has been demonstrated on different quantum computing platforms using Gaussian boson sampling,^1–3 quantum computing is moving to the next stage, namely demonstrating quantum advantage in solving practical problems. Two typical problems of this kind are computational-aided material design and drug discovery, in which quantum chemistry plays a critical role in answering questions such as ∼Which one is the best?∼. Many recent efforts have been devoted to the development of advanced quantum algorithms for solving quantum chemistry problems on noisy intermediate-scale quantum (NISQ) devices,^2,4–14 while implementing these algorithms for complex problems is limited by available qubit counts, coherence time and gate fidelity. Specifically, without error correction, quantum simulations of quantum chemistry are viable only if low-depth quantum algorithms are implemented to suppress the total error rate. Recent advances in error mitigation techniques enable us to model many-electron problems with a dozen qubits and tens of circuit depths on NISQ devices,⁹ while such circuit sizes and depths are still a long way from practical applications.

The difference between the available and actually required quantum resources in practical quantum simulations has renewed the interest in divide and conquer (DC) based methods.^15–19 Realistic material and (bio)chemistry systems often involve complex environments, such as surfaces and interfaces. To model these systems, the Schrödinger equations are much too complicated to be solvable. It therefore becomes desirable that approximate practical methods of applying quantum mechanics be developed.²⁰ One popular scheme is to divide the complex problem under consideration into as many parts as possible until these become simple enough for an adequate solution, namely the philosophy of DC.²¹ The DC method is particularly suitable for NISQ devices since the sub-problem for each part can in principle be solved with fewer computational resources.^{15–18,22–25} One successful application of DC is to estimate the ground-state potential energy surface of a ring containing 10 hydrogen atoms using the density matrix embedding theory (DMET) on a trapped-ion quantum computer, in which a 20-qubit problem is decomposed into ten 2-qubit problems.¹⁸

DC often treats all subsystems at the same computational level and estimates physical observables by summing up the corresponding quantities of subsystems, while in practical simulations of complex systems, the particle–particle interactions may exhibit completely different characteristics in and between subsystems. Long-range Coulomb interactions can be well approximated as quasiclassical electrostatic interactions since empirical methods, such as empirical force filed (EFF) approaches,²⁶ are promising to describe these interactions. As the distance between particles decreases, the repulsive exchange interactions from electrons having the same spin become important so that quantum mean-field approaches, such as Hartree–Fock (HF), are necessary to characterize these electronic interactions.

Quantum networking uses subatomic matter to deliver data in a way that goes beyond today’s fiber-optic systems. Amazon wants to grow diamonds which would be part of a component that lets the data travel farther without breaking down.

Pretty futuristic!

Amazon.com Inc. is teaming up with a unit of De Beers Group to grow artificial diamonds, betting that custom-made gems could could help revolutionize computer networks.

Continue reading “Amazon Looks to Grow Diamonds in Bid to Boost Computer Networks” »

The remarkable physicochemical properties of the natural nucleic acids, DNA and RNA, define modern biology at the molecular level and are widely believed to have been central to life’s origins. However, their ability to form repositories of information as well as functional structures such as ligands (aptamers) and catalysts (ribozymes/DNAzymes) is not unique. A range of nonnatural alternatives, collectively termed xeno nucleic acids (XNAs), are also capable of supporting genetic information storage and propagation as well as evolution. This gives rise to a new field of “synthetic genetics,” which seeks to expand the nucleic acid chemical toolbox for applications in both biotechnology and molecular medicine. In this review, we outline XNA polymerase and reverse transcriptase engineering as a key enabling technology and summarize the application of “synthetic genetics” to the development of aptamers, enzymes, and nanostructures.

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