A clinically applicable integrative molecular classification of meningiomas.

Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified.

Rare germline genetic variation in PAX8 transcription factor binding sites and susceptibility to epithelial ovarian cancer.

Common genetic variation throughout the genome together with rare coding variants identified to date explain about a half of the inherited genetic component of epithelial ovarian cancer risk. It is likely that rare variation in the non-coding genome will explain some of the unexplained heritability, but identifying such variants is challenging. The primary problem is lack of statistical power to identifying individual risk variants by association as power is a function of sample size, effect size and allele frequency. Power can be increased by using burden tests which test for association of carriers of any variant in a specified genomic region. This has the effect of increasing the putative effect allele frequency. PAX8 is a transcription factor that plays a critical role in tumour progression, migration and invasion. Furthermore, regulatory elements proximal to target genes of PAX8 are enriched for common ovarian cancer risk variants. We hypothesised that rare variation in PAX8 binding sites are also associated with ovarian cancer risk, but unlikely to be associated with risk of breast, colorectal or endometrial cancer. We have used publicly available, whole-genome sequencing data from the UK 100,000 Genomes Project to evaluate the burden of rare variation in PAX8 binding sites across the genome. Data were available for 522 ovarian cancers, 2,984 breast cancers, 2,696 colorectal cancers, 836 endometrial cancers and 2253 non-cancer controls. Active binding sites were defined using data from multiple PAX8 and H3K27 ChIPseq experiments. We found no association between the burden of rare variation in PAX8 binding sites (defined in several ways) and risk of ovarian, breast or endometrial cancer. An apparent association with colorectal cancer was likely to be a technical artefact as a similar association was also detected for rare variation in random regions of the genome. Despite the null result this study provides a proof-of -principle for using burden testing to identify rare, non-coding germline genetic variation associated with disease. Larger sample sizes available from large-scale sequencing projects together with improved understanding of the function of the non-coding genome will increase the potential of similar studies in the future.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Nanoconfined Water in Pillared Zeolites Probed by 1H Nuclear Magnetic Resonance.

Here, we report the results of our 1H nuclear magnetic resonance study of the dynamics of water molecules confined in zeolites (mordenite and ZSM-5 structures) with hierarchical porosity (micropores in zeolite lamella and mesopores formed by amorphous SiO2 in the inter-lamellar space). 1H nuclear magnetic resonance (NMR) spectra show that water experiences complex behavior within the temperature range from 173 to 298 K. The temperature dependence of 1H spin-lattice relaxation evidences the presence of three processes with different activation energies: freezing (about 30 kJ/mol), fast rotation (about 10 kJ/mol), and translational motion of water molecules (23.6 and 26.0 kJ/mol for pillared mordenite and ZSM-5, respectively). For translational motion, the activation energy is markedly lower than for water in mesoporous silica or zeolites with similar mesopore size but with disordered secondary porosity. This indicates that the process of water diffusion in zeolites with hierarchical porosity is governed not only by the presence of mesopores, but also by the mutual arrangement of meso- and micropores. The translational motion of water molecules is determined mainly by zeolite micropores.

In vivo discovery of RNA proximal proteins via proximity-dependent biotinylation.

RNA molecules function as messenger RNAs (mRNAs) that encode proteins and noncoding transcripts that serve as adaptor molecules, structural components, and regulators of genome organization and gene expression. Their function and regulation are largely mediated by RNA binding proteins (RBPs). Here we present RNA proximity labelling (RPL), an RNA-centric method comprising the endonuclease-deficient Type VI CRISPR-Cas protein dCas13b fused to engineered ascorbate peroxidase APEX2. RPL discovers target RNA proximal proteins in vivo via proximity-based biotinylation. RPL applied to U1 identified proteins involved in both U1 canonical and noncanonical functions. Profiling of poly(A) tail proximal proteins uncovered expected categories of RBPs and provided additional evidence for 5'-3' proximity and unexplored subcellular localizations of poly(A)+ RNA. Our results suggest that RPL allows rapid identification of target RNA binding proteins in native cellular contexts, and is expected to pave the way for discovery of novel RNA-protein interactions important for health and disease.

Local Structures of Two-Dimensional Zeolites-Mordenite and ZSM-5-Probed by Multinuclear NMR.

Mesostructured pillared zeolite materials in the form of lamellar phases with a crystal structure of mordenite (MOR) and ZSM-5 (MFI) were grown using CTAB as an agent that creates mesopores, in a one-pot synthesis; then into the CTAB layers separating the 2D zeolite plates were introduced by diffusion the TEOS molecules which were further hydrolyzed, and finally the material was annealed to remove the organic phase, leaving the 2D zeolite plates separated by pillars of silicon dioxide. To monitor the successive structural changes and the state of the atoms of the zeolite framework and organic compounds at all the steps of the synthesis of pillared MOR and MFI zeolites, the nuclear magnetic resonance method (NMR) with magic angle spinning (MAS) was applied. The 27Al and 29Si MAS NMR spectra confirm the regularity of the zeolite frameworks of the as synthetized materials. Analysis of the 1H and 13C MAS NMR spectra and an experiment with variable contact time evidence a strong interaction between the charged "heads" -[N(CH3)3]+ of CTAB and the zeolite framework at the place of [AlO4]- location. According to 27Al and 29Si MAS NMR the evacuation of organic cations leads to a partial but not critical collapse of the local zeolite structure.

Protein side-chain packing problem: is there still room for improvement?

The protein side-chain packing problem (PSCPP) is an important subproblem of both protein structure prediction and protein design. During the past two decades, a large number of methods have been proposed to tackle this problem. These methods consist of three main components: a rotamer library, a scoring function and a search strategy. The average overall accuracy level obtained by these methods is approximately 87%. Whether a better accuracy level could be achieved remains to be answered. To address this question, we calculated the maximum accuracy level attainable using a simple rotamer library, independently of the energy function or the search method. Using 2883 different structures from the Protein Data Bank, we compared this accuracy level with the accuracy level of five state-of-the-art methods. These comparisons indicated that, for buried residues in the protein, we are already close to the best possible accuracy results. In addition, for exposed residues, we found that a significant gap exists between the possible improvement and the maximum accuracy level achievable with current methods. After determining that an improvement is possible, the next step is to understand what limitations are preventing us from obtaining such an improvement. Previous works on protein structure prediction and protein design have shown that scoring function inaccuracies may represent the main obstacle to achieving better results for these problems. To show that the same is true for the PSCPP, we evaluated the quality of two scoring functions used by some state-of-the-art algorithms. Our results indicate that neither of these scoring functions can guide the search method correctly, thereby reinforcing the idea that efforts to solve the PSCPP must also focus on developing better scoring functions.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women.

OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7). CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

An SVM-based method for assessment of transcription factor-DNA complex models.

BACKGROUND: Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models. RESULTS: We present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models. CONCLUSIONS: A learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models.

Statistical analysis of structural determinants for protein-DNA-binding specificity.

DNA-binding proteins play critical roles in biological processes including gene expression, DNA packaging and DNA repair. They bind to DNA target sequences with different degrees of binding specificity, ranging from highly specific (HS) to nonspecific (NS). Alterations of DNA-binding specificity, due to either genetic variation or somatic mutations, can lead to various diseases. In this study, a comparative analysis of protein-DNA complex structures was carried out to investigate the structural features that contribute to binding specificity. Protein-DNA complexes were grouped into three general classes based on degrees of binding specificity: HS, multispecific (MS), and NS. Our results show a clear trend of structural features among the three classes, including amino acid binding propensities, simple and complex hydrogen bonds, major/minor groove and base contacts, and DNA shape. We found that aspartate is enriched in HS DNA binding proteins and predominately binds to a cytosine through a single hydrogen bond or two consecutive cytosines through bidentate hydrogen bonds. Aromatic residues, histidine and tyrosine, are highly enriched in the HS and MS groups and may contribute to specific binding through different mechanisms. To further investigate the role of protein flexibility in specific protein-DNA recognition, we analyzed the conformational changes between the bound and unbound states of DNA-binding proteins and structural variations. The results indicate that HS and MS DNA-binding domains have larger conformational changes upon DNA-binding and larger degree of flexibility in both bound and unbound states. Proteins 2016; 84:1147-1161. © 2016 Wiley Periodicals, Inc.

Influence of different anaesthetic protocols over the sperm quality on the fresh, chilled (4°C) and frozen-thawed epididymal sperm samples in domestic dogs.

This study assessed the influence of three different anaesthetic protocols on semen quality obtained from the epididymis. Sixty male dogs undergoing to routine sterilization were assigned to three anaesthetic protocols: thiopental group (TG, n = 20), propofol group (PG, n = 20) and ketamine-dexmedetomidine group (KDG, n = 20). Immediately after orchidectomy, the cauda epididymides and vas deferent ducts were isolated and then a retrograde flushing was performed to collect spermatozoa. In experiment 1, after the initial evaluation of the semen (sperm concentration, sperm motility and the percentages of live spermatozoa, abnormal spermatozoa and acrosome membrane integrity), semen samples were diluted in Tris-glucose-egg yolk extender and chilled for 48 hr, and the sperm motility was assessed at 6, 24 and 48 hr. In experiment 2, semen samples were diluted in Tris-glucose-egg yolk extender and chilled for 24 hr, and then samples were frozen in two extenders with different glycerol concentrations, to reach a final concentration of 50-100 × 10(6) spermatozoa ml(-1) , 20% egg yolk, 0.5% Equex and 4% and 5% glycerol, respectively. Mean values of total sperm concentration, sperm viability and the percentages of intact acrosome and abnormal spermatozoa were not significantly different between experimental groups, and therefore, the anaesthetic protocols assessed did not affect sperm parameters mentioned above. However, our study confirmed a detrimental effect of the use of thiopental (TG) over the total sperm motility (p < 0.05) and progressive sperm motility (p < 0.05) of the fresh and chilled epididymal sperm samples. The anaesthetic protocols including the application of propofol or ketamine-dexmedetomidine can be used to recover sperm in domestic canids without significant changes in sperm quality compared when semen is collected routinely and these techniques could be applicable to endangered wild canids.

Immunization of sea bream (Sparus aurata) juveniles against Photobacterium damselae subsp. piscicida by short bath: Effect on some pro-inflammatory molecules and the Mx gene expression.

Cytokines are a family of proteins derived from macrophages, lymphocytes, granulocytes, mast cells and epithelial cells and can be divided into interferons (IFNs), Interleukins (ILs) and Tumor Necrosis factors (TNFs) among others. The presence of cytokines in a wide number of fish species has been proved and several molecules types have been already cloned and sequenced. In this work some proinflamatory molecules and Mx gene were detected in the liver of vaccinated sea bream juveniles with an average body weight of 5 g. The method of immunization was by short bath and three different bacterins against the marine pathogen Photobacterium damselae subsp. piscicida were designed and used to immunize fish. Five genes encoding for five different molecules were analyzed by real time PCR: IL-1ß, IL Ir-2, Cox-2, Mx and TNFα. Gene expression was quantified along four days after fish immunization and results were compared among groups. Results show that the heat-inactivated vaccine stimulates the up-regulation of IL-1ß, IL Ir-2, Cox-2 and TNFα genes whereas the UV-light inactivated vaccine was the unique vaccine which stimulates the expression of Mx gene. The present is a novel study that shows by the first time the effect of the inactivation process of vaccines on the expression levels of genes involved in the defense against Photobacterium damselae subsp piscicida.

A knowledge-based orientation potential for transcription factor-DNA docking.

MOTIVATION: Computational modeling of protein-DNA complexes remains a challenging problem in structural bioinformatics. One of the key factors for a successful protein-DNA docking is a potential function that can accurately discriminate the near-native structures from decoy complexes and at the same time make conformational sampling more efficient. Here, we developed a novel orientation-dependent, knowledge-based, residue-level potential for improving transcription factor (TF)-DNA docking. RESULTS: We demonstrated the performance of this new potential in TF-DNA binding affinity prediction, discrimination of native protein-DNA complex from decoy structures, and most importantly in rigid TF-DNA docking. The rigid TF-DNA docking with the new orientation potential, on a benchmark of 38 complexes, successfully predicts 42% of the cases with root mean square deviations lower than 1 Å and 55% of the cases with root mean square deviations lower than 3 Å. The results suggest that docking with this new orientation-dependent, coarse-grained statistical potential can achieve high-docking accuracy and can serve as a crucial first step in multi-stage flexible protein-DNA docking. AVAILABILITY AND IMPLEMENTATION: The new potential is available at http://bioinfozen.uncc.edu/Protein_DNA_orientation_potential.tar.

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Impact of genetic diversity and antibiotic-resistance of Salmonella isolated from feral cats: One Health approach.

Free-living cats usually live in colonies in urban areas, especially close to parks and neighbourhoods where people feed them without any sanitary control. This can pose a human, animal and environmental health concern due to the close contact between uncontrolled colonies, the population and other domestic and/or wild animals. Thus, this study aimed to assess the genetic diversity and antimicrobial resistance (AMR) among Salmonella enterica subsp. enterica strains isolated from feral cats in a previous epidemiological study in the Gran Canaria island (Spain). A total of nineteen Salmonella isolates were obtained from November 2018 to January 2019 in a Salmonella epidemiological study in feral cats. All isolates obtained were genotyped by pulsed-field gel electrophoresis (PGFE) and were tested for antimicrobial susceptibility, in accordance with Decision 2013/652/EU. PFGE analysis revealed isolates clustering by serovar, with identical clones for serovars Bredeney and Grancanaria, while differing pulsotypes were observed for serovars Florida (88.89 % similarity) and Nima (83.23 % similarity). All but two isolates were resistant to at least one antimicrobial. The results obtained demonstrate that feral cats in the region investigated are a reservoir of Salmonella strains resistant to gentamicin (94.1 %) and of the critically important antimicrobial tigecycline (23.5 %). Hence, they could excrete AMR strains through their faeces and contaminate the environment, favoring the spread of such bacteria to cohabiting pets. Moreover, this widespread presence of AMR Salmonella clones across various serovars highlights the urgent need to implement efficient antimicrobial stewardship and control programs by the local governments due to the ongoing need to protect human and animal health under a One Health concept.

Rewiring of master transcription factor cistromes during high-grade serous ovarian cancer development.

The transcription factors MECOM, PAX8, SOX17 and WT1 are candidate master regulators of high-grade serous 'ovarian' cancer (HGSC), yet their cooperative role in the hypothesized tissue of origin, the fallopian tube secretory epithelium (FTSEC) is unknown. We generated 26 epigenome (CUT&TAG, CUT&RUN, ATAC-seq and HiC) data sets and 24 profiles of RNA-seq transcription factor knock-down followed by RNA sequencing in FTSEC and HGSC models to define binding sites and gene sets regulated by these factors in cis and trans. This revealed that MECOM, PAX8, SOX17 and WT1 are lineage-enriched, super-enhancer associated master regulators whose cooperative DNA-binding patterns and target genes are re-wired during tumor development. All four TFs were indispensable for HGSC clonogenicity and survival but only depletion of PAX8 and WT1 impaired FTSEC cell survival. These four TFs were pharmacologically inhibited by transcriptional inhibitors only in HGSCs but not in FTSECs. Collectively, our data highlights that tumor-specific epigenetic remodeling is tightly related to MECOM, PAX8, SOX17 and WT1 activity and these transcription factors are targetable in a tumor-specific manner through transcriptional inhibitors.

Epigenomic charting and functional annotation of risk loci in renal cell carcinoma.

While the mutational and transcriptional landscapes of renal cell carcinoma (RCC) are well-known, the epigenome is poorly understood. We characterize the epigenome of clear cell (ccRCC), papillary (pRCC), and chromophobe RCC (chRCC) by using ChIP-seq, ATAC-Seq, RNA-seq, and SNP arrays. We integrate 153 individual data sets from 42 patients and nominate 50 histology-specific master transcription factors (MTF) to define RCC histologic subtypes, including EPAS1 and ETS-1 in ccRCC, HNF1B in pRCC, and FOXI1 in chRCC. We confirm histology-specific MTFs via immunohistochemistry including a ccRCC-specific TF, BHLHE41. FOXI1 overexpression with knock-down of EPAS1 in the 786-O ccRCC cell line induces transcriptional upregulation of chRCC-specific genes, TFCP2L1, ATP6V0D2, KIT, and INSRR, implicating FOXI1 as a MTF for chRCC. Integrating RCC GWAS risk SNPs with H3K27ac ChIP-seq and ATAC-seq data reveals that risk-variants are significantly enriched in allelically-imbalanced peaks. This epigenomic atlas in primary human samples provides a resource for future investigation.

Learning from the challenges of undertaking an evaluation of a multi-partner housing support initiative delivered within a hospital setting.

Objectives: We present learning from a mixed-methods evaluation of a housing support initiative for hospital inpatients. Study design: A mixed-methods process evaluation. Methods: A social housing provider delivered a housing support service in two hospitals (mental health unit and general hospital). Healthcare providers, the social housing provider and academic researchers designed and undertook a co-produced, mixed-methods process evaluation of the intervention. The evaluation included questionnaires, semi-structured interviews, analysis of routinely collected data and economic analysis. Despite commitment from the partners, the evaluation faced challenges. We reflect on the lessons learnt within our discussion paper. Results: Despite the commitment of the partners, we faced several challenges.We took an iterative approach to the design and processes of the evaluation to respond to arising challenges. Recruitment of service-users was more difficult than anticipated, requiring additional staff resources. Given the small-scale nature of the intervention, and the quality of data recorded in hospital records, the planned economic analysis was not feasible. Positive factors facilitating evaluation included involvement of staff delivering the intervention, as well as managers. Being able to offer payment to partner organisations for staff time also facilitated ongoing engagement. Conclusions: Multi-partner evaluations are useful, however, researchers and partners need to be prepared to take an iterative, resource intensive approach. Both availability and quality of routine data, and the resources required to support data collection, may limit feasibility of specific methods when evaluating small-scale cross-sector initiatives. Thus, this necessitates a flexible approach to design and analysis.

Textile Functionalization Using LTA and FAU Zeolitic Materials.

COVID-19 has drawn worldwide attention to the need for personal protective equipment. Face masks can be transformed from passive filters into active protection. For this purpose, it is sufficient to apply materials with oligodynamic effect to the fabric of the masks, which makes it possible to destroy infectious agents that have fallen on the mask with aerosol droplets from the air stream. Zeolites themselves are not oligodynamic materials, but can serve as carriers for nanoparticles of metals and/or compounds of silver, zinc, copper, and other materials with biocidal properties. Such a method, when the particles are immobilized on the surface of the substrate, will increase the lifetime of the active oligodynamic material. In this work, we present the functionalization of textile materials with zeolites to obtain active personal protective equipment with an extended service life. This is done with the aim to extend the synthesis of zeolitic materials to polymeric fabrics beyond cotton. The samples were characterized using XRD, SEM, and UV-Vis spectroscopy. Data of physicochemical studies of the obtained hybrid materials (fabrics with crystals grown on fibers) will be presented, with a focus on the effect of fabrics in the growth process of zeolites.