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      Laser ablation combined with Nanoimprint Lithography technology as new surface engineering approach to produce novel polymer-based heteronucleants for recalcitrant protein crystallization

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          Mutations in CNNM4 Cause Jalili Syndrome, Consisting of Autosomal-Recessive Cone-Rod Dystrophy and Amelogenesis Imperfecta

          The combination of recessively inherited cone-rod dystrophy (CRD) and amelogenesis imperfecta (AI) was first reported by Jalili and Smith in 1988 in a family subsequently linked to a locus on chromosome 2q11, and it has since been reported in a second small family. We have identified five further ethnically diverse families cosegregating CRD and AI. Phenotypic characterization of teeth and visual function in the published and new families reveals a consistent syndrome in all seven families, and all link or are consistent with linkage to 2q11, confirming the existence of a genetically homogenous condition that we now propose to call Jalili syndrome. Using a positional-candidate approach, we have identified mutations in the CNNM4 gene, encoding a putative metal transporter, accounting for the condition in all seven families. Nine mutations are described in all, three missense, three terminations, two large deletions, and a single base insertion. We confirmed expression of Cnnm4 in the neural retina and in ameloblasts in the developing tooth, suggesting a hitherto unknown connection between tooth biomineralization and retinal function. The identification of CNNM4 as the causative gene for Jalili syndrome, characterized by syndromic CRD with AI, has the potential to provide new insights into the roles of metal transport in visual function and biomineralization.
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            Surface design for controlled crystallization: the role of surface chemistry and nanoscale pores in heterogeneous nucleation.

            Current industrial practice for control of primary nucleation (nucleation from a system without pre-existing crystalline matter) during crystallization from solution involves control of supersaturation generation, impurity levels, and solvent composition. Nucleation behavior remains largely unpredictable, however, due to the presence of container surfaces, dust, dirt, and other impurities that can provide heterogeneous nucleation sites, thus making the control and scale-up of processes that depend on primary nucleation difficult. To develop a basis for the rational design of surfaces to control nucleation during crystallization from solution, we studied the role of surface chemistry and morphology of various polymeric substrates on heterogeneous nucleation using aspirin as a model compound. Nucleation induction time statistics were utilized to investigate and quantify systematically the effectiveness of polymer substrates in inducing nucleation. The nucleation induction time study revealed that poly(4-acryloylmorpholine) and poly(2-carboxyethyl acrylate), each cross-linked by divinylbenzene, significantly lowered the nucleation induction time of aspirin while the other polymers were essentially inactive. In addition, we found the presence of nanoscopic pores on certain polymer surfaces led to order-of-magnitude faster aspirin nucleation rates when compared with surfaces without pores. We studied the preferred orientation of aspirin crystals on polymer films and found the nucleation-active polymer surfaces preferentially nucleated the polar facets of aspirin, guided by hydrogen bonds. A model based on interfacial free energies was also developed which predicted the same trend of polymer surface nucleation activities as indicated by the nucleation induction times.
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              Hydrogen Sulfide and Cancer

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                Author and article information

                Journal
                Applied Surface Science
                Applied Surface Science
                Elsevier BV
                01694332
                January 2023
                January 2023
                : 607
                : 155029
                Article
                10.1016/j.apsusc.2022.155029
                5d8cc290-d904-4067-b552-69e1ec18bff6
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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