Autonomous learning of generative models with chemical reaction network ensembles.

Can a micron-sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory and statistical physics to develop a general architecture whereby a broad class of chemical systems can autonomously learn complex distributions. Our construction takes the form of a chemical implementation of machine learning's optimization workhorse: gradient descent on the relative entropy cost function, which we demonstrate can be viewed as a form of integral feedback control. We show how this method can be applied to optimize any detailed balanced chemical reaction network and that the construction is capable of using hidden units to learn complex distributions.

Conformational Analysis of 1,3-Difluorinated Alkanes.

Fluorine substitution can have a profound impact on molecular conformation. Here, we present a detailed conformational analysis of how the 1,3-difluoropropylene motif (-CHF-CH-CHF-) determines the conformational profiles of 1,3-difluoropropane, - and -2,4-difluoropentane, and - and -3,5-difluoroheptane. It is shown that the 1,3-difluoropropylene motif strongly influences alkane chain conformation, with a significant dependence on the polarity of the medium.

Characterization of Integrase and Excisionase Activity in a Cell-Free Protein Expression System Using a Modeling and Analysis Pipeline.

We present a full-stack modeling, analysis, and parameter identification pipeline to guide the modeling and design of biological systems starting from specifications to circuit implementations and parametrizations. We demonstrate this pipeline by characterizing the integrase and excisionase activity in a cell-free protein expression system. We build on existing Python tools─BioCRNpyler, AutoReduce, and Bioscrape─to create this pipeline.

Telehealth in cancer care during the COVID-19 pandemic.

Introduction: The Victorian COVID-19 Cancer Network (VCCN) Telehealth Expert Working Group aimed to evaluate the telehealth (TH) experience for cancer patients, carers and clinicians with the rapid uptake of TH in early 2020 during the COVID-19 pandemic.

Methods: We conducted a prospective multi-centre cross-sectional survey involving eight Victorian regional and metropolitan cancer services and three consumer advocacy groups. Patients or their carers and clinicians who had TH consultations between 1 July 2020 and 31 December 2020 were invited to participate in patient and clinician surveys, respectively.

The Accuracy of Percutaneous Sacro-Iliac Screw Fixation for Pelvic Ring Injuries using the Lateral view as the Corner Stone for Screw Placement: A Prospective Cohort Study.

This paper has been temporarily removed by the publisher, Wolters-Kluwer, as it may have been published in error. We regret any confusion this may have caused.