Vegetative Community Development over 30 Years within Mixed Pine-Hardwood Mine Reclamation sites in east Texas

The practice of mine reclamation aims to balance the energy needs of society with proactive environmental restoration of degraded land, and long-term studies of vegetative community development on reclaimed mine land have been invaluable in developing effective reclamation practices. This study investigated vegetative community characteristics (composition, richness, species importance)over a 30 year time frame in planted mixed pine-hardwood areas on reclaimed surface coal mine land in East Texas,United States. Reclaimed sites werecompared vegetatively to unmined reference forests. A chronological pattern wasshown for reclaimedcommunity developmentin both understory and overstorystrata. Understory community development exhibitednatural patterns, while theoverstory community varied with different groups of planted species. The olderreclaimed sites were most similar to unmined reference sites. Dissimilaritiesbetween mined and unmined communities were also apparent; for example, thewoody vine community of reference sites was much more substantial in midstoryand overstory strata as compared to reclaimed sites. Overall, this study providedbaseline ecological information about these plant communities that may assistland managers and researchers in furthering their development of reclamation techniques and attainment of reclamation goals

Quantitative trait locus-specific genotype × alcoholism interaction on linkage for evoked electroencephalogram oscillations

We explored the evidence for a quantitative trait locus (QTL)-specific genotype × alcoholism interaction for an evoked electroencephalogram theta band oscillation (ERP) phenotype on a region of chromosome 7 in participants of the US Collaborative Study on the Genetics of Alcoholism. Among 901 participants with both genotype and phenotype data available, we performed variance component linkage analysis (SOLAR version 2.1.2) in the full sample and stratified by DSM-III-R and Feighner-definite alcoholism categories. The heritability of the ERP phenotype after adjusting for age and sex effects in the combined sample and in the alcoholism classification sub-groups ranged from 40% to 66%. Linkage on chromosome 7 was identified at 158 cM (LOD = 3.8) in the full sample and at 108 in the non-alcoholic subgroup (LOD = 3.1). Further, we detected QTL-specific genotype × alcoholism interaction at these loci. This work demonstrates the importance of considering the complexity of common complex traits in our search for genes that predispose to alcoholism

How many locations do we need per day to reliably describe the habitat use of translocated rhinos in Manas NP?

The Indian Rhino Vision (IRV) 2020 program was designed in 2005 in Assam for maintaining existing rhino populations and to re-introduce rhinos in the earlier distribution ranges of Assam. The programme was launched on 12th April 2008. The government of Assam with donor support translocated two male rhinos from the Pobitora WLS to the Buraburijhar area under Basbari range in Manas National Park. As a follow up to these translocations to understand the adaptation of the rhinos, it was important to assess the monitoring frequencies, habitat use and distribution pattern of rhinos in the new habitat. Monitoring was primarily based on radio-telemetry techniques and direct observation. The monitoring team maintains a vigil on the released rhinos all round the day and the observations were systematically recorded three times a day. During this exercise it was found that the rhinos prefer to use grasslands, swamps and marshy areas (beels and rivulet). Key Words: Indian Rhino Vision (IRV) 2020, Radio-Telemetry, Translocatio

Quantitative trait locus-specific genotype x alcoholism interaction on linkage for evoked electroencephalogram oscillations

Abstract We explored the evidence for a quantitative trait locus (QTL)-specific genotype × alcoholism interaction for an evoked electroencephalogram theta band oscillation (ERP) phenotype on a region of chromosome 7 in participants of the US Collaborative Study on the Genetics of Alcoholism. Among 901 participants with both genotype and phenotype data available, we performed variance component linkage analysis (SOLAR version 2.1.2) in the full sample and stratified by DSM-III-R and Feighner-definite alcoholism categories. The heritability of the ERP phenotype after adjusting for age and sex effects in the combined sample and in the alcoholism classification sub-groups ranged from 40% to 66%. Linkage on chromosome 7 was identified at 158 cM (LOD = 3.8) in the full sample and at 108 in the non-alcoholic subgroup (LOD = 3.1). Further, we detected QTL-specific genotype × alcoholism interaction at these loci. This work demonstrates the importance of considering the complexity of common complex traits in our search for genes that predispose to alcoholism

Accuracy of haplotype estimation in a region of low linkage disequilibrium

Abstract We compared the accuracy of haplotype inferences at a 6 Mb region on chromosome 7 where significant linkage between a brain oscillation phenotype and a cholinergic muscarinic receptor gene was previously reported. Individual haplotype assignments and haplotype frequencies were estimated using 5, 10, and 14 consecutive Illumina single-nucleotide polymorphisms (SNPs) within the 1-LOD unit support interval of the chromosome 7 linkage peak. Initially, haplotypes were constructed incorporating phase information provided by relatives using the pedigree analysis package MERLIN. Population-based haplotypes were inferred using the haplotype estimation software HAPLO.STATS and PHASE, using unrelated individuals. The 14 SNPs within this region exhibited markedly low linkage disequilibrium, and the average D' estimate between SNPs was 0.18 (range: 0.01–0.97). In comparison to the family-based haplotypes calculated in MERLIN, the computational inferences of individual haplotype assignments were most accurate when considering 5 consecutive SNPs, but decayed dramatically when considering 10 or 14 SNPs in both PHASE and HAPLO.STATS. When comparing the two haplotype inference methods, both PHASE and HAPLO.STATS performed poorly. These analyses underscore the difficulties of haplotype estimation in the presence of low linkage disequilibrium and stress the importance of careful consideration of confidence measures when using estimated haplotype frequencies and individual assignments in biomedical research

Accuracy of haplotype estimation in a region of low linkage disequilibrium

We compared the accuracy of haplotype inferences at a 6 Mb region on chromosome 7 where significant linkage between a brain oscillation phenotype and a cholinergic muscarinic receptor gene was previously reported. Individual haplotype assignments and haplotype frequencies were estimated using 5, 10, and 14 consecutive Illumina single-nucleotide polymorphisms (SNPs) within the 1-LOD unit support interval of the chromosome 7 linkage peak. Initially, haplotypes were constructed incorporating phase information provided by relatives using the pedigree analysis package MERLIN. Population-based haplotypes were inferred using the haplotype estimation software HAPLO.STATS and PHASE, using unrelated individuals. The 14 SNPs within this region exhibited markedly low linkage disequilibrium, and the average D' estimate between SNPs was 0.18 (range: 0.01–0.97). In comparison to the family-based haplotypes calculated in MERLIN, the computational inferences of individual haplotype assignments were most accurate when considering 5 consecutive SNPs, but decayed dramatically when considering 10 or 14 SNPs in both PHASE and HAPLO.STATS. When comparing the two haplotype inference methods, both PHASE and HAPLO.STATS performed poorly. These analyses underscore the difficulties of haplotype estimation in the presence of low linkage disequilibrium and stress the importance of careful consideration of confidence measures when using estimated haplotype frequencies and individual assignments in biomedical research

Coulomb displacement energy and the low-energy astrophysical S factor for the Be7(p,gamma)B8 reaction

The relationship between the Coulomb displacement energy for the A=8, J=2+, T=1 state and the low-energy astrophysical S factor for the Be7(p,gamma)B8 reaction is discussed. The displacement energy is interpreted in a particle-hole model. The dependence of the particle displacement energy on the potential well geometry is investigated and is used to relate the particle displacement energy to the rms radius and the asymptotic normalization of the valence proton wave function in B8. The asymptotic normalization is used to calculate the astrophysical S factor for the Be7(p,gamma)B8 reaction. The relationship to the Li7(n,gamma) reaction, the B8 quadrupole moment, radial density, and break-up momentum distribution are also discussed.Comment: Latex with Revtex, 26 pages, 8 figures are added in a uuencoded tar-compressed fil

Artificial intelligence assisted patient blood and urine droplet pattern analysis for non‑invasive and accurate diagnosis of bladder cancer

Bladder cancer is one of the most common cancer types in the urinary system. Yet, current bladder cancer diagnosis and follow-up techniques are time-consuming, expensive, and invasive. In the clinical practice, the gold standard for diagnosis remains invasive biopsy followed by histopathological analysis. In recent years, costly diagnostic tests involving the use of bladder cancer biomarkers have been developed, however these tests have high false-positive and false-negative rates limiting their reliability. Hence, there is an urgent need for the development of cost-effective, and non-invasive novel diagnosis methods. To address this gap, here we propose a quick, cheap, and reliable diagnostic method. Our approach relies on an artificial intelligence (AI) model to analyze droplet patterns of blood and urine samples obtained from patients and comparing them to cancer-free control subjects.The AI-assisted model in this study uses a deep neural network, a ResNet network, pre-trained on ImageNet datasets. Recognition and classification of complex patterns formed by dried urine or blood droplets under different conditions resulted in cancer diagnosis with a high specificity and sensitivity.Our approach can be systematically applied across droplets, enabling comparisons to reveal shared spatial behaviors and underlying morphological patterns. Our results support the fact that AI-based models have a great potential for non-invasive and accurate diagnosis of malignancies, including bladder cancer

Prospectus, November 9, 1990

https://spark.parkland.edu/prospectus_1990/1025/thumbnail.jp