Lifeboat Foundation

The crystal structure the scientists developed can enable computational-based drug discovery to be used to target the i-motifs from the insulin gene, because when scientists know the specific 3D shape, they can design molecules digitally and model them to see whether they will fit.

Scientists can then develop new drugs using particular chemicals when they know which ones will fit the drug target best—a process called rational design.

As the first crystal structure of this type, the researchers say it will also be useful as a model for other targets in the genome, besides the insulin gene, which form this shape of DNA.

Researchers at the Department of Instrumentation and Applied Physics (IAP), Indian Institute of Science (IISc) and collaborators have designed a new supercapacitor that can be charged by light shining on it. Such supercapacitors can be used in various devices, including streetlights and self-powered electronic devices such as sensors.

Capacitors are electrostatic devices that store energy as charges on two metal plates called electrodes. Supercapacitors are upgraded versions of capacitors—they exploit electrochemical phenomena to store more energy, explains Abha Misra, Professor at IAP and corresponding author of the study published in the Journal of Materials Chemistry A.

The electrodes of the new supercapacitor were made of zinc oxide (ZnO) nanorods grown directly on fluorine-doped tin oxide (FTO), which is transparent. It was synthesized by Pankaj Singh Chauhan, first author and CV Raman postdoctoral fellow in Misra’s group at IISc.

Self-assembled molecules are responsible for important cellular processes. Self-assembled structures such as microtubules or actin filaments are key to cell motility: change of shape, division or extension of membranes. These self-assembled entities have the peculiarity of being formed temporarily, since they require energy consumption. Inspired by nature, there is currently an active area of research that attempts to replicate this process of self-assembly artificially, using the so-called chemical reaction networks.

The control of self-assembly by means of chemical reaction networks is based on the activation of a monomer prone to self-assembly, which is then deactivated. In this way, the self-assembled structure requires a continuous energy consumption to perpetuate itself. From a chemical point of view, this energy is provided by a “fuel”, a chemical reagent. Depending on the availability of that energy source, the self-assembly process occurs or not.

Traditionally, highly reactive fuels have been used to carry out the activation, with little control over the deactivation process. This also implies that the activation and deactivation fuels tend to react with each other, making artificial dissipative self-assembly processes ineffective. In nature, these two processes are controlled by catalysts, which increases their efficiency. Thus, the introduction of catalysts in these processes and the control of their activity by external stimuli such as light are highly desirable, since they can limit part of these problems.

Coherent X-ray imaging has emerged as a powerful tool for studying both nanoscale structures and dynamics in condensed matter and biological systems. The nanometric resolution together with chemical sensitivity and spectral information render X-ray imaging a powerful tool to understand processes such as catalysis, light harvesting or mechanics.

Unfortunately these processes might be random or stochastic in nature. In order to obtain freeze-frame images to study stochastic dynamics, the X-ray fluxes must be very high, potentially heating or even destroying the samples.

Also, detectors acquisition rates are insufficient to capture the fast nanoscale processes. Stroboscopic techniques allow imaging ultrafast repeated processes. But only mean dynamics can be extracted, ruling out measurement of stochastic processes, where the system evolves through a different path in phase space during each measurement. These two obstacles prevent coherent imaging from being applied to complex systems.

The observation of quantum modifications to a well-known chemical law could lead to performance improvements for quantum information storage.

The Arrhenius law says that the rate of a chemical reaction should decrease steadily as you increase the energy barrier between initial and final states. Now researchers have found a system that obeys a quantum version of the Arrhenius law, where the rate does not drop smoothly but instead decreases in a staircase pattern [1]. The system is a type of quantum bit (qubit) that is particularly robust against environmental disturbances. The researchers demonstrated that they can take advantage of this quantum effect to improve the qubit’s performance.

Technologies such as quantum computers and quantum cryptography use qubits to store information, and one of the continuing challenges is that uncontrolled environmental effects can change the state of a qubit. The most common solutions require large amounts of hardware, but an alternative method is to use qubits that are more error resistant, such as so-called cat qubits. The information in these qubits is stored in robust combinations of quantum states that resemble the states in Schrödinger’s famous feline thought experiment (see Synopsis: Quantum-ness Put on the Scale).

In a paper published in the Journal of the American Chemical Society, researchers have documented for the first time the unique chemistry dynamics and structure of high-temperature liquid uranium trichloride (UCl3) salt, a potential nuclear fuel source for next-generation reactors.

Nowadays, there’s lots of buzz about spectacular new medical treatments, such as personalized cancer therapy with modified immune cells or antibodies. Such treatments, however, are very complex and expensive and so find only limited application. Most medical therapies are still based on small chemical compounds that can be produced in large quantities and thus at low cost.

Widely utilized across various industries such as chemistry, agriculture, and military, this technology relies on strategies like dispersive optics and narrow-band light filters.

However, limitations exist in these approaches. Additionally, the fabrication of large-scale InGaAs detector arrays poses challenges, necessitating the development of new experimental methods and algorithms to advance infrared hyperspectral imaging technology in terms of miniaturization and cost-effectiveness.

In a paper published in Light Science & Applications, a team led by Professor Baoqing Sun and Yuan Gao from Shandong University introduce a novel method for encoding near-infrared spectral and spatial data.

A nanoparticle formulation, using oligonucleotide chemistry, able to release a gene editing system with single cell resolution after near infrared laser activation. The full potential of the formulation was demonstrated in the brain after intracerebral and intranasal administrations. The spot of the laser defined the region of gene editing.