Disparities in Access to a Regular Primary Care Physician Among First-Generation Migrants with Early Psychosis in Ontario, Canada.

Disparities in primary care utilization among migrants with early psychosis may be related to lack of access to a regular primary care physician. This study aimed to investigate access to a regular primary care physician among first-generation migrants with early psychosis. People aged 14-35 years with first onset non-affective psychotic disorder in Ontario, Canada were identified in health administrative data (N = 39,440).

Oral cannabinoid for the prophylaxis of chemotherapy-induced nausea and vomiting-a systematic review and meta-analysis.

Introduction: Chemotherapy-induced nausea and vomiting (CINV) is a burdensome adverse event frequently associated with chemotherapy treatment of cancer. Evidence suggests that cannabinoid CB2 receptors are present in brainstem neurons, and thus, there may exist a role for cannabinoids to counter CINV. The aim of this paper is to conduct a systematic review and meta-analysis of the efficacy and safety of oral cannabinoids compared with other treatments as documented in randomized controlled trials (RCTs).

TNER: a novel background error suppression method for mutation detection in circulating tumor DNA.

Background: Ultra-deep next-generation sequencing of circulating tumor DNA (ctDNA) holds great promise as a tool for the early detection of cancer and for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection.

Results: To achieve high accuracy of variant calling via better distinguishing low-frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors.

Predictive methods for computational metalloenzyme redesign - a test case with carboxypeptidase A.

Computational metalloenzyme design is a multi-scale problem. It requires treating the metal coordination quantum mechanically, extensive sampling of the protein backbone, and additionally accounting for the polarization of the active site by both the metal cation and the surrounding protein (a phenomenon called electrostatic preorganization). We bring together a combination of theoretical methods that jointly offer these desired qualities: QM/DMD for mixed quantum-classical dynamic sampling, quantum theory of atoms in molecules (QTAIM) for the assessment of electrostatic preorganization, and Density Functional Theory (DFT) for mechanistic studies.

Computational treatment of metalloproteins.

Metalloproteins present a considerable challenge for modeling, especially when the starting point is far from thermodynamic equilibrium. Examples include formidable problems such as metalloprotein folding and structure prediction upon metal addition, removal, or even just replacement; metalloenzyme design, where stabilization of a transition state of the catalyzed reaction in the specific binding pocket around the metal needs to be achieved; docking to metal-containing sites and design of metalloenzyme inhibitors. Even more conservative computations, such as elucidations of the mechanisms and energetics of the reaction catalyzed by natural metalloenzymes, are often nontrivial.

Mysteries of metals in metalloenzymes.

Natural metalloenzymes are often the most proficient catalysts in terms of their activity, selectivity, and ability to operate at mild conditions. However, metalloenzymes are occasionally surprising in their selection of catalytic metals, and in their responses to metal substitution. Indeed, from the isolated standpoint of producing the best catalyst, a chemist designing from first-principles would likely choose a different metal.

Metal-dependent activity of Fe and Ni acireductone dioxygenases: how two electrons reroute the catalytic pathway.

Two virtually identical acireductone dioxygenases, ARD and ARD', catalyze completely different oxidation reactions of the same substrate, 1,2-dihydroxy-3-keto-5-(methylthio)pentene, depending exclusively on the nature of the bound metal. Fe(2+)-dependent ARD' produces the α-keto acid precursor of methionine and formate and allows for the recycling of methionine in cells. Ni(2+)-dependent ARD instead produces methylthiopropionate, CO, and formate, and exits the methionine salvage cycle.

The Role of the Flexible L43-S54 Protein Loop in the CcrA Metallo-β-lactamase in Binding Structurally Dissimilar β-Lactam Antibiotics.

The CcrA di-Zn β-lactamase is a bacterial enzyme capable of efficiently hydrolyzing and thus disabling a diverse set of β-lactam antibiotics. Understanding the factors that contribute to the efficiency of CcrA is essential for the design of new CcrA-resistant antibiotics and enzyme inhibitors. The efficacy of CcrA has been speculated to be partially attributable to the flexible protein loop located above the active site (L43-S54), which would mold around structurally different substrates, for snag binding.

Why urease is a di-nickel enzyme whereas the CcrA β-lactamase is a di-zinc enzyme.

Ureases and metallo-β-lactamases are amide hydrolases closely related in function and structure. However, one major difference between them is that the former uses two nickel cations, and the latter uses two zinc cations to do similar catalytic jobs. What is the reason for this choice that Nature made for the catalytic metals? Is it dictated by electronic or structural reasons in the two catalyzed reactions, or some other evolutionary factors? Are both enzymes "perfect" catalysts, as far as just catalysis is concerned, and if they are, then why? Here, we address these questions through a joint quantum mechanical/molecular mechanical dynamics approach and ab initio mechanistic investigation.