UTJECAJ UVJETA POSTUPKA DOBIVANJA MLJEVENE TROSKE TALJENJEM UGLJENA U VISOKOJ PEĆI UZ UPORABU GEOPOLIMERA

In this study, the material characterization of Vietnamese ground coal slag and ground granulated blast furnace slag (GGBFS), such as particle size distribution, chemical composition, bulk density and particle density are shown. The geopolymer specimens were prepared by mixing an 80 m/m% mass of solid materials (ground coal slag and GGBFS in a different ratio) with 20 m/m % of a 10M NaOH alkaline activator. A systematic experimental series was carried out in order to optimize the preparation process. In that series, the heat curing temperature was 60°C for 6 hours, and then selected specimens were heat treated at a high temperature (1000 °C) for 1 hour. After 7 days of ageing, the physical properties of the geopolymer (compressive strength, specimen density) were measured. Also, after 180 days of ageing, the pH values of water in the geopolymer leaching preparation were determined. The results show that the geopolymer can be used for refractory applications due to its good heat resistance properties. However, geopolymers that were heated at 1000 °C had lower compressive strength, specimen density and pH values of water containing the geopolymer than those that were cured at 60 °C.U ovome istraživanju donose se obilježja vijetnamskih granulata ugljene troske i troske željezne rude na osnovi njihove veličine, kemijskoga sastava i gustoće. Uzorci geopolimera pripremljeni su miješanjem 80 % m/m (mase otopljenoga / masa otopine) ugljene i željezne troske (u različitim omjerima) s 20 % m/m 10M NaOH kao alkalnoga aktivatora. Sustavnim serijama eksperimenata optimiziran je postupak pripreme, pri čemu je temperatura iznosila 60 °C tijekom 6 sati, nakon čega su odabrani uzorci zagrijavani 1 sat na 1000 °C. Nakon sljedećih 7 dana izmjerena su fizička svojstva geopolimera (tlačna čvrstoća, gustoća). Zatim je poslije 180 dana određena pH-vrijednost vode korištene u postupku ispiranja geopolimera. Rezultati su pokazali kako geopolimeri mogu biti korišteni za namjene u vatrostalnim uvjetima zahvaljujući toplinskim svojstvima. Također, geopolimeri koji su zagrijavani na 1000 °C imaju niže vrijednosti tlačne čvrstoće, gustoće i pH-vrijednosti vode u njima od onih koji su grijani na 60 °C

Sources of Multidrug Resistance in Patients With Previous Isoniazid-Resistant Tuberculosis Identified Using Whole Genome Sequencing: A Longitudinal Cohort Study

Background Meta-analysis of patients with isoniazid-resistant tuberculosis given standard first-line anti-tuberculosis treatment indicated an increased risk of multi-drug resistant tuberculosis (MDR-TB) emerging (8%), compared to drug-sensitive tuberculosis (0.3%). Here we use whole genome sequencing (WGS) to investigate whether treatment of patients with pre-existing isoniazid resistant disease with first-line anti-tuberculosis therapy risks selecting for rifampicin resistance, and hence MDR-TB. Methods Patients with isoniazid-resistant pulmonary TB were recruited and followed up for 24 months. Drug-susceptibility testing was performed by Microscopic observation drug-susceptibility assay (MODS), Mycobacterial Growth Indicator Tube (MGIT) and by WGS on isolates at first presentation and in the case of re-presentation. Where MDR-TB was diagnosed, WGS was used to determine the genomic relatedness between initial and subsequent isolates. De novo emergence of MDR-TB was assumed where the genomic distance was five or fewer single nucleotide polymorphisms (SNPs) whereas reinfection with a different MDR-TB strain was assumed where the distance was 10 or more SNPs. Results 239 patients with isoniazid-resistant pulmonary tuberculosis were recruited. Fourteen (14/239, 5.9%) patients were diagnosed with a second episode of tuberculosis that was multi-drug resistant. Six (6/239, 2.5%) were identified as having evolved MDR-TB de novo and six as having been re-infected with a different strain. In two cases the genomic distance was between 5-10 SNPs and therefore indeterminate. Conclusions In isoniazid-resistant TB, de novo emergence and reinfection of MDR-TB strains equally contributed to MDR development. Early diagnosis and optimal treatment of isoniazid resistant TB are urgently needed to avert the de novo emergence of MDR-TB during treatment

Logging intensity drives variability in carbon stocks in lowland forests in Vietnam

Forest degradation in the tropics is generating large carbon (C) emissions. In tropical Asia, logging is the main driver of forest degradation. For effective implementation of REDD+ projects in logged forests in Southeast Asia, the impacts of logging on forest C stocks need to be assessed. Here, we assess C stocks in logged lowland forests in central Vietnam and explore correlations between logging intensity, soil, topography and living aboveground carbon (AGC) stocks. We present an approach to estimate historical logging intensities for the prevalent situation when complete records on logging history are unavailable. Landsat analysis and participatory mapping were used to quantify the density of historical disturbances, used as a proxy of logging intensities in the area. Carbon in AGC, dead wood, belowground carbon (BGC) and soil (SOC) was measured in twenty-four 0.25 ha plots that vary in logging intensity, and data on recent logging, soil properties, elevation and slope were also collected. Heavily logged forests stored only half the amount of AGC of stems ≥10 cm dbh as lightly logged forests, mainly due to a reduction in the number of large (≥60 cm dbh) trees. Carbon in AGC of small trees (5–10 cm dbh), dead wood and BGC comprised only small fractions of total C stocks, while SOC in the topsoil of 0–30 cm depth stored ~50% of total C stocks. Combining logging intensities with soil and topographic data showed that logging intensity was the main factor explaining the variability in AGC. Our research shows large reductions in AGC in medium and heavily logged forests. It highlights the critical importance of conserving big trees to maintain high forest C stocks and accounting for SOC in total C stock estimates

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis.

Background: Molecular diagnostics are considered the most promising route to achievement of rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO-endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: In this systematic analysis, we used a candidate gene approach to identify mutations associated with resistance or consistent with susceptibility for 13 WHO-endorsed antituberculosis drugs. We collected existing worldwide MTBC whole-genome sequencing data and phenotypic data from academic groups and consortia, reference laboratories, public health organisations, and published literature. We categorised phenotypes as follows: methods and critical concentrations currently endorsed by WHO (category 1); critical concentrations previously endorsed by WHO for those methods (category 2); methods or critical concentrations not currently endorsed by WHO (category 3). For each mutation, we used a contingency table of binary phenotypes and presence or absence of the mutation to compute positive predictive value, and we used Fisher's exact tests to generate odds ratios and Benjamini-Hochberg corrected p values. Mutations were graded as associated with resistance if present in at least five isolates, if the odds ratio was more than 1 with a statistically significant corrected p value, and if the lower bound of the 95% CI on the positive predictive value for phenotypic resistance was greater than 25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: We analysed 41 137 MTBC isolates with phenotypic and whole-genome sequencing data from 45 countries. 38 215 MTBC isolates passed quality control steps and were included in the final analysis. 15 667 associations were computed for 13 211 unique mutations linked to one or more drugs. 1149 (7·3%) of 15 667 mutations were classified as associated with phenotypic resistance and 107 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was more than 80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were identified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: We present the first WHO-endorsed catalogue of molecular targets for MTBC drug susceptibility testing, which is intended to provide a global standard for resistance interpretation. The existence of this catalogue should encourage the implementation of molecular diagnostics by national tuberculosis programmes. Funding: Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Policy uncertainty and seasoned equity offerings methods

Based on a sample of U.S. seasoned equity offering (SEO) during the period 2002–2017, we examine how the choice of equity issuance method changes in response to policy uncertainty. We find that firms subject to high policy uncertainty are less likely to use accelerated offerings rather than other types of traditional seasoned equity offerings. Our results are robust to alternative variable specifications, propensity score matching method, IV approach, and the inclusion of additional controls. Also, the effect of policy uncertainty on accelerated offering decision is weaker for firms with better information environment, earnings quality, and governance structures. Further, policy uncertainty increases the cost of funds and lowers long-run abnormal returns after SEOs for firms subject to high levels of policy uncertainty