Systematic exploration of accessible topologies of cage molecules minimalistic models.

Cages are macrocyclic structures with an intrinsic internal cavity that support applications in separations, sensing and catalysis. These materials can be synthesised self-assembly of organic or metal-organic building blocks. Their bottom-up synthesis and the diversity in building block chemistry allows for fine-tuning of their shape and properties towards a target property.

Clickable polyethyleneimine incorporated into triblock copolymeric micelles as an efficient platform in the delivery of siRNA to NSCLC cells.

The efficacy of transfection vectors to cross the endosomal membrane into the cytosol is a central aspect in the development of nucleic acid-based therapeutics. The challenge remains the same: Delivery, Delivery, Delivery. Despite a rational and appropriate construct of triblock polymeric micelles, which could serve as an ideal platform for the co-delivery of siRNAs and hydrophobic anticancer drugs, we show here its inability to properly convey oligonucleotides to their final destination.

Influence of dexamethasone on the interaction between glucocorticoid receptor and SOX9: A molecular dynamics study.

The glucocorticoid receptor (GR) is a nuclear receptor that controls critical biological processes by regulating the transcription of specific genes. GR transcriptional activity is modulated by a series of ligands and coenzymes, where a ligand can act as an agonist or antagonist. GR agonists, such as the glucocorticoids dexamethasone (DEX) and prednisolone, are widely prescribed to patients with inflammatory and autoimmune diseases.

Hazards&Robots: A dataset for visual anomaly detection in robotics.

We propose Hazards&Robots, a dataset for Visual Anomaly Detection in Robotics. The dataset is composed of 324,408 RGB frames, and corresponding feature vectors; it contains 145,470 normal frames and 178,938 anomalous ones categorized in 20 different anomaly classes. The dataset can be used to train and test current and novel visual anomaly detection methods such as those based on deep learning vision models.

Into the dynamics of rotaxanes at atomistic resolution.

Mechanically-interlocked molecules (MIMs) are at the basis of artificial molecular machines and are attracting increasing interest for various applications, from catalysis to drug delivery and nanoelectronics. MIMs are composed of mechanically-interconnected molecular sub-parts that can move with respect to each other, imparting these systems innately dynamical behaviors and interesting stimuli-responsive properties. The rational design of MIMs with desired functionalities requires studying their dynamics at sub-molecular resolution and on relevant timescales, which is challenging experimentally and computationally.

Reconstructing reactivity in dynamic host-guest systems at atomistic resolution: amide hydrolysis under confinement in the cavity of a coordination cage.

Spatial confinement is widely employed by nature to attain unique efficiency in controlling chemical reactions. Notable examples are enzymes, which selectively bind reactants and exquisitely regulate their conversion into products. In an attempt to mimic natural catalytic systems, supramolecular metal-organic cages capable of encapsulating guests in their cavity and of controlling/accelerating chemical reactions under confinement are attracting increasing interest.

Characterization of the Interaction of Polymeric Micelles with siRNA: A Combined Experimental and Molecular Dynamics Study.

The simulation of large molecular systems remains a daunting challenge, which justifies the exploration of novel methodologies to keep computers as an ideal companion tool for everyday laboratory work. Whole micelles, bigger than 20 nm in size, formed by the self-assembly of hundreds of copolymers containing more than 50 repeating units, have until now rarely been simulated, due to a lack of computational power. Therefore, a flexible amphiphilic triblock copolymer (mPEG-α-PLL-PLA) containing a total of 80 repeating units, has been emulated and synthesized to embody compactified nanoconstructs of over 900 assembled copolymers, sized between 80 and 100 nm, for siRNA complexing purposes.

Artificial Intelligence in Thyroid Field-A Comprehensive Review.

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g.

Improving classification of low-resource COVID-19 literature by using Named Entity Recognition.

Automatic document classification for highly interrelated classes is a demanding task that becomes more challenging when there is little labeled data for training. Such is the case of the coronavirus disease 2019 (COVID-19) Clinical repository-a repository of classified and translated academic articles related to COVID-19 and relevant to the clinical practice-where a 3-way classification scheme is being applied to COVID-19 literature. During the 7th Biomedical Linked Annotation Hackathon (BLAH7) hackathon, we performed experiments to explore the use of named-entity-recognition (NER) to improve the classification.

Lisen&Curate: A platform to facilitate gathering textual evidence for curation of regulation of transcription initiation in bacteria.

The number of published papers in biomedical research makes it rather impossible for a researcher to keep up to date. This is where manually curated databases contribute facilitating the access to knowledge. However, the structure required by databases strongly limits the type of valuable information that can be incorporated.