Virtual Post-Intensive-Care Rehabilitation for Survivors of COVID-19: A Service Evaluation.

Aim: The objective of this study is to evaluate the safety, utilisation, and effectiveness of a novel, virtual rehabilitation programme for survivors of SARS‑CoV‑2 infection (COVID-19) and intensive care admission.

Methods: A service evaluation was performed. Adults admitted to a United Kingdom intensive care unit with COVID-19-induced respiratory failure and surviving hospital discharge were invited to an eight-week rehabilitation programme.

High-Level Data Fusion Enables the Chemoinformatically Guided Discovery of Chiral Disulfonimide Catalysts for Atropselective Iodination of 2-Amino-6-arylpyridines.

The atropselective iodination of 2-amino-6-arylpyridines catalyzed by chiral disulfonimides (DSIs) is described. Key to the development of this transformation was the use of a chemoinformatically guided workflow for the curation of a structurally diverse training set of DSI catalysts. Utilization of this catalyst training set in the atropselective iodination across a variety 2-aminopyridine substrates allowed for the recommendation of statistically higher-performing DSIs for this reaction.

A Unified Strategy for the Asymmetric Synthesis of Highly Substituted 1,2-Amino Alcohols Leading to Highly Substituted Bisoxazoline Ligands.

A general procedure for the asymmetric synthesis of highly substituted 1,2-amino alcohols in high yield and diastereoselectivity is described that uses organometallic additions of a wide range of nucleophiles to butylsulfinimines as the key step. The addition of organolithium reagents to these imines follows a modified Davis model. The diastereoselectivity for this reaction depends significantly on both the nucleophile and electrophile.

'The incident triage area': a response to the COVID-19 pandemic in the Bristol Royal Infirmary.

With the onset of the COVID-19 pandemic, hospitals nationwide have been presented with a number of potential challenges, including possible increased volume of patient attendances, acuity of illness and potential for patients to present with an infection that requires isolation. At the Bristol Royal Infirmary, an innercity teaching hospital that manages patients aged 16 and over, we present our response to these projected changes in ED attendances, with the initiation of the incident triage area (ITA). The ITA is a triage station situated outside the ED and staffed by a senior clinician, healthcare assistant and patient flow coordinator.

Development of a Computer-Guided Workflow for Catalyst Optimization. Descriptor Validation, Subset Selection, and Training Set Analysis.

Modern, enantioselective catalyst development is driven largely by empiricism. Although this approach has fostered the introduction of most of the existing synthetic methods, it is inherently limited by the skill, creativity, and chemical intuition of the practitioner. Herein, we present a complementary approach to catalyst optimization in which statistical methods are used at each stage to streamline development.

Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning.

Catalyst design in asymmetric reaction development has traditionally been driven by empiricism, wherein experimentalists attempt to qualitatively recognize structural patterns to improve selectivity. Machine learning algorithms and chemoinformatics can potentially accelerate this process by recognizing otherwise inscrutable patterns in large datasets. Herein we report a computationally guided workflow for chiral catalyst selection using chemoinformatics at every stage of development.