Electron density-based GPT for optimization and suggestion of host-guest binders.

Here we present a machine learning model trained on electron density for the production of host-guest binders. These are read out as simplified molecular-input line-entry system (SMILES) format with >98% accuracy, enabling a complete characterization of the molecules in two dimensions. Our model generates three-dimensional representations of the electron density and electrostatic potentials of host-guest systems using a variational autoencoder, and then utilizes these representations to optimize the generation of guests via gradient descent.

A first insight into tuberculosis transmission at the border of Ecuador and Colombia: a retrospective study of the population structure of in Esmeraldas province.

Objective: Tuberculosis (TB) is a major public health concern in Ecuador and Colombia, considering that both countries are high-burden TB settings. Molecular epidemiology is crucial to understand the transmission dynamics of complex (MTBC) and to identify active transmission clusters of regional importance.

Methods: We studied the potential transmission of TB between Colombia and Ecuador through the analysis of the population structure of MTBC lineages circulating in the Ecuadorian province of Esmeraldas at the border with Colombia.

Population structure of Mycobacterium tuberculosis in El Oro: A first insight into Ecuador-Peru tuberculosis transmission.

Background: Tuberculosis (TB) is a major public health concern in Ecuador and Peru, both settings of high burden of drug resistance TB. Molecular epidemiology tools are important to understand the transmission dynamics of Mycobacterium tuberculosis Complex (MTBC) and to track active transmission clusters of regional importance. This study is the first to address the transmission of TB between Peru and Ecuador through the population structure of MTBC lineages circulating in the Ecuadorian border province of "El Oro".

Ebselen derivatives inhibit SARS-CoV-2 replication by inhibition of its essential proteins: PL and M proteases, and nsp14 guanine N7-methyltransferase.

Proteases encoded by SARS-CoV-2 constitute a promising target for new therapies against COVID-19. SARS-CoV-2 main protease (M, 3CL) and papain-like protease (PL) are responsible for viral polyprotein cleavage-a process crucial for viral survival and replication. Recently it was shown that 2-phenylbenzisoselenazol-3(2H)-one (ebselen), an organoselenium anti-inflammatory small-molecule drug, is a potent, covalent inhibitor of both the proteases and its potency was evaluated in enzymatic and antiviral assays.

Performance Analysis of Software-Defined Networks to Mitigate Private VLAN Attacks.

The defence-in-depth (DiD) methodology is a defensive approach usually performed by network administrators to implement secure networks by layering and segmenting them. Typically, segmentation is implemented in the second layer using the standard virtual local area networks (VLANs) or private virtual local area networks (PVLANs). Although defence in depth is usually manageable in small networks, it is not easily scalable to larger environments.