An open-source framework for fast-yet-accurate calculation of quantum mechanical features.

We present the open-source framework kallisto that enables the efficient and robust calculation of quantum mechanical features for atoms and molecules. For a benchmark set of 49 experimental molecular polarizabilities, the predictive power of the presented method competes against second-order perturbation theory in a converged atomic-orbital basis set at a fraction of its computational costs. The calculation of isotropic molecular polarizabilities is robust for a data set of more than 80 000 molecules. We present furthermore a generally applicable van der Waals radius model that is rooted on atomic static polarizabilites. Efficiency tests show that such radii can even be calculated for small- to medium-size proteins where the largest system (SARS-CoV-2 spike protein) has 42 539 atoms. Following the work of Domingo-Alemenara et al. [Domingo-Alemenara et al., Nat. Commun., 2019, 10, 5811], we present computational predictions for retention times for different chromatographic methods and describe how physicochemical features improve the predictive power of machine-learning models that otherwise only rely on two-dimensional features like molecular fingerprints. Additionally, we developed an internal benchmark set of experimental super-critical fluid chromatography retention times. For those methods, improvements of up to 10.6% are obtained when combining molecular fingerprints with physicochemical descriptors. Shapley additive explanation values show furthermore that the physical nature of the applied features can be retained within the final machine-learning models. We generally recommend the kallisto framework as a robust, low-cost, and physically motivated featurizer for upcoming state-of-the-art machine-learning studies.

Consensus on Virtual Management of Vestibular Disorders: Urgent Versus Expedited Care.

The virtual practice has made major advances in the way that we care for patients in the modern era. The culture of virtual practice, consulting, and telemedicine, which had started several years ago, took an accelerated leap as humankind was challenged by the novel coronavirus pandemic (COVID19). The social distancing measures and lockdowns imposed in many countries left medical care providers with limited options in evaluating ambulatory patients, pushing the rapid transition to assessments via virtual platforms. In this novel arena of medical practice, which may form new norms beyond the current pandemic crisis, we found it critical to define guidelines on the recommended practice in neurotology, including remote methods in examining the vestibular and eye movement function. The proposed remote examination methods aim to reliably diagnose acute and subacute diseases of the inner-ear, brainstem, and the cerebellum. A key aim was to triage patients into those requiring urgent emergency room assessment versus non-urgent but expedited outpatient management. Physicians who had expertise in managing patients with vestibular disorders were invited to participate in the taskforce. The focus was on two topics: (1) an adequate eye movement and vestibular examination strategy using virtual platforms and (2) a decision pathway providing guidance about which patient should seek urgent medical care and which patient should have non-urgent but expedited outpatient management.