X-ray studies of zeolites and MOFs

This thesis is largely a study of the ADOR process (assembly-disassembly-organisation-reassembly) when applied to zeolite UTL. The final chapter of this thesis deals with the adsorption of the medical gases NO and CO onto the metal organic framework NiNaSIP. Chapter 4 is devoted to the disassembly and organisation steps of the ADOR process. Calcined UTL was hydrolysed using 0.1 – 12 M HCl solutions from 75 – 95 °C run over 10 mins to 72 hrs. A three step mechanism is proposed, which is comprised of an initial rapid hydrolysis that removes the majority of the interlayer constituents of UTL, causing the silica-rich layers to largely collapse. This is followed by a slow, temperature and molarity dependent, deintercalation process that sees the remainder of the interlayer material removed resulting in the full collapse of the layers to form IPC-1P. The third step is a temperature and molarity dependent rebuilding process, whereby the interlayer region is slowly rebuilt, eventually forming a precursor which upon calcination becomes IPC-2 (OKO). Chapter 5 uses the pair distribution function (PDF) technique to structurally confirm the intermediate of the ADORable zeolite UTL. The intermediate, IPC-1P, is a disordered layered compound formed by the hydrolysis of UTL in 0.1 M HCl. Its structure is unsolvable by traditional X-ray diffraction techniques. The PDF technique was first benchmarked against high-quality synchrotron Rietveld refinements of IPC-2 (OKO) and IPC-4 (PCR) – two end products of IPC-1P condensation that share very similar structural features. An IPC-1P starting model derived from density functional theory was used for the PDF refinement, which yielded a final fit of Rw = 18% and a geometrically reasonable structure. This confirms that the layers do stay intact throughout the ADOR process, and shows that PDF is a viable technique for layered zeolite structure determination. Chapter 6 examines the reassembly stage by following the in-situ calcination of a variety of hydrolysed intermediates into their three-dimensional counterparts. Beamline I11 at Diamond Light Source provided high-quality PXRD patterns as a function of temperature, which were refined against using sequential Pawley refinements to track the unit cell changes. 0.1, 1.75, 2.5 and 12 M hydrolysed lamellar precursor phases were calcined. The largest unit cell changes were observed for 0.1 M, and the smallest for 12 M. This shows that increasing the molarity must prebuild most of the interlayer connections, such that upon calcination, only minimal condensation occurs to fully connect the layers. Chapter 7 probes the uptake of the medical gases CO and NO into the metal organic framework NiNaSIP. An in-situ single-crystal XRD study was undertaken using an environmental gas cell at beamline 11.3.1 at the Advanced Light Source. NiNaSIP was first dehydrated to reveal an open nickel site, which acted as the main site of adsorption for the inputted gases. NO was observed in a bent geometry at an occupancy of 40 % and a Ni – N bond length of 2.166(16) Å. The oxygen was modelled to be disordered over two sites. CO was not fully observed, as only the carbon was able to be modelled with an occupancy of 31.2 % and a Ni – C bond length of 2.27(3) Å

Similarity Regression predicts evolution of transcription factor sequence specificity

Transcription factor (TF) binding specificities (motifs) are essential to the analysis of noncoding DNA and gene regulation. Accurate prediction of the sequence specificities of TFs is critical, because the hundreds of sequenced eukaryotic genomes encompass hundreds of thousands of TFs, and assaying each is currently infeasible. There is ongoing controversy regarding the efficacy of motif prediction methods, as well as the degree of motif diversification among related species. Here, we describe Similarity Regression (SR), a significantly improved method for predicting motifs. We have updated and expanded the Cis-BP database using SR, and validate its predictive capacity with new data from diverse eukaryotic TFs. SR inherently quantifies TF motif evolution, and we show that previous claims of near-complete conservation of motifs between human and Drosophila are grossly inflated, with nearly half the motifs in each species absent from the other. We conclude that diversification in DNA binding motifs is pervasive, and present a new tool and updated resource to study TF diversity and gene regulation across eukaryotes

Ferroelastic-switching-driven colossal shear strain and piezoelectricity in a hybrid ferroelectric

Materials that can produce large controllable strains are widely used in shape memory devices, actuators and sensors. Great efforts have been made to improve the strain outputs of various material systems. Among them, ferroelastic transitions underpin giant reversible strains in electrically-driven ferro/piezoelectrics and thermally- or magneticallydriven shape memory alloys. However, large-strain ferroelastic switching in conventional ferroelectrics is very challenging while magnetic and thermal controls are not desirable for applications. Here, we demonstrate an unprecedentedly large shear strain up to 21.5 % in a hybrid ferroelectric, C6H5N(CH3)3CdCl3. The strain response is about two orders of magnitude higher than those of top-performing conventional ferroelectric polymers and oxides. It is achieved via inorganic bond switching and facilitated by the structural confinement of the large organic moieties, which prevents the undesired 180-degree polarization switching. Furthermore, Br substitution can effectively soften the bonds and result in giant shear piezoelectric coefficient (d35 ~ 4800 pm/V) in Br-rich end of the solid solution, C6H5N(CH3)3CdBr3xCl3(1-x). The superior electromechanical properties of the compounds promise their potential in lightweight and high energy density devices, and the strategy described here should inspire the development of next-generation piezoelectrics and electroactive materials based on hybrid ferroelectrics.Comment: 32 pages, 14 figures, 5 table

Potreba - temeljni parametar čovjekovih aktivnosti

Dosad zanemaren kompleksni fenomen potreba, kako u teorijskim, tako i u praktičnim razmatranjima, zahtjeva nužno promjenu. Jer potreba, predstavlja i početnu i završnu točku i proizvodnje i potrošnje. Relativno je prirodom neograničen i beskonačan broj potreba koji čovjek posjeduje. Razvojem proizvodnje i humanizacijom potrošnje on se geometrijskom progresijom povećava. Ne sagledavanje ovog fenomena u svoj svojoj kompleksnosti, važnosti i dinamičnosti uzrokuje višestruke gubitke čije dimenzije su u svim svojim granicama teško sagledive. Stoga se pred ekonomsku politiku (makro i mikro) postavlja staro-novi problem čije dubinsko sagledavanje je temeljna pretpostavka ostvarivanja željenih pravaca i dinamike razvoja

Toward a fully implantable ecosystem for adaptive neuromodulation in humans: Preliminary experience with the CorTec BrainInterchange device in a canine model

This article describes initial work toward an ecosystem for adaptive neuromodulation in humans by documenting the experience of implanting CorTec\u27s BrainInterchange (BIC) device in a beagle canine and using the BCI2000 environment to interact with the BIC device. It begins with laying out the substantial opportunity presented by a useful, easy-to-use, and widely available hardware/software ecosystem in the current landscape of the field of adaptive neuromodulation, and then describes experience with implantation, software integration, and post-surgical validation of recording of brain signals and implant parameters. Initial experience suggests that the hardware capabilities of the BIC device are fully supported by BCI2000, and that the BIC/BCI2000 device can record and process brain signals during free behavior. With further development and validation, the BIC/BCI2000 ecosystem could become an important tool for research into new adaptive neuromodulation protocols in humans

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN