TOPOLOGICAL MODEL FOR THE PREDICTION OF ALPHA-1 ADRENOCEPTOR ANTAGONISTIC ACTIVITY OF ARYLPIPERAZINES

2004 ◽  
Vol 03 (02) ◽  
pp. 245-255 ◽  
Author(s):  
VIPIN KUMAR ◽  
A. K. MADAN
Keyword(s):  
Antagonistic Activity ◽  
Connectivity Index ◽  
Eccentric Connectivity Index ◽  
Data Set ◽  
Wiener’S Index ◽  
Topological Descriptor ◽  
Group Parameter ◽  
Accuracy Of Prediction ◽  
The Relationship ◽  
Zagreb Group Parameter

The relationship between Wiener's index — a distance-based topological descriptor, Zagreb group parameter — M 1, an adjacency-based topological descriptor, and eccentric connectivity index — an adjacency-cum-distance based topological descriptor, with the alpha-1 adrenoceptor antagonistic activity of arylpiperazines has been investigated. A training set, comprising 30 analogues, of substituted arylpiperazines was selected for the present investigations. The values of the Wiener's index, Zagreb group parameter and eccentric connectivity index and each of 30 analogues comprising the data set were computed. Resulting data was analyzed and suitable models developed after identification of active range. Subsequently, a biological activity was assigned to each analogue involved in the data set using these models, which was then compared with the reported adrenoceptor antagonistic activity. High accuracy of prediction ranging from 90–93% was observed using these models.

The eccentric version of atom-bond connectivity index of tetra sheet networks

2018 ◽  
Vol 10 (05) ◽  
pp. 1850065 ◽  
Author(s):  
Muhammad Imran ◽  
Abdul Qudair Baig ◽  
Muhammad Razwan Azhar
Keyword(s):  
Connected Graph ◽  
Molecular Graph ◽  
Theoretical Chemistry ◽  
Connectivity Index ◽  
Maximum Distance ◽  
Eccentric Connectivity Index ◽  
Topological Descriptor ◽  
Degree Of A Vertex ◽  
Connectivity Indices ◽  
Atom Bond

Among topological descriptor of graphs, the connectivity indices are very important and they have a prominent role in theoretical chemistry. The atom-bond connectivity index of a connected graph [Formula: see text] is represented as [Formula: see text], where [Formula: see text] represents the degree of a vertex [Formula: see text] of [Formula: see text] and the eccentric connectivity index of the molecular graph [Formula: see text] is represented as [Formula: see text], where [Formula: see text] is the maximum distance between the vertex [Formula: see text] and any other vertex [Formula: see text] of the graph [Formula: see text]. The new eccentric atom-bond connectivity index of any connected graph [Formula: see text] is defined as [Formula: see text]. In this paper, we compute the new eccentric atom-bond connectivity index for infinite families of tetra sheets equilateral triangular and rectangular networks.

TOPOLOGICAL MODELS FOR THE PREDICTION OF NEUTRAL ENDOPEPTIDASE AND ANGIOTENSIN-CONVERTING ENZYME INHIBITORY ACTIVITY OF MERCAPTOACYLDIPEPTIDES

2006 ◽  
Vol 05 (03) ◽  
pp. 565-577 ◽  
Author(s):  
VINEY LATHER ◽  
A. K. MADAN
Keyword(s):  
Inhibitory Activity ◽  
Topological Index ◽  
Wiener Index ◽  
Neutral Endopeptidase ◽  
Connectivity Index ◽  
Molecular Connectivity ◽  
Ace Inhibitory Activity ◽  
Eccentric Connectivity Index ◽  
Data Set ◽  
Molecular Connectivity Index

The relationship between the topological indices and the Neutral Endopeptidase (NEP) inhibitory activity and Angiotensin-Converting Enzyme (ACE) inhibitory activity of mercaptoacyldipeptides has been investigated. Three topological indices — the Wiener index (a distance-based topological index), the molecular connectivity index (an adjacency-based topological index), and the eccentric connectivity index (an adjacency-cum-distance-based topological index), were presently used for investigation. A data set comprising 39 differently substituted mercaptoacyldipeptides was selected for the present study. The values of the Wiener index, molecular connectivity index, and eccentric connectivity index for each of the 39 compounds comprising the data set were computed using an in-house computer program. Resultant data were analyzed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each compound using these models, and the biological activity was then compared with the reported NEP and ACE inhibitory activity of each compound. Accuracy of prediction up to a maximum of ~91% was obtained using these models.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Railroad Integration and Uneven Development on the European Periphery, 1870–1910

2021 ◽  
Vol 45 (2) ◽  
pp. 261-289
Author(s):  
Eduard J. Alvarez-Palau ◽  
Alfonso Díez-Minguela ◽  
Jordi Martí-Henneberg
Keyword(s):  
Economic Development ◽  
Positive Impact ◽  
Data Set ◽  
Per Capita Gdp ◽  
Catching Up ◽  
Nation States ◽  
Railroad Network ◽  
Per Capita ◽  
European Periphery ◽  
The Relationship

AbstractThis study explores the relationship between railroad integration and regional development on the European periphery between 1870 and 1910, based on a regional data set including 291 spatial units. Railroad integration is proxied by railroad density, while per capita GDP is used as an indicator of economic development. The period under study is of particular relevance as it has been associated with the second wave of railroad construction in Europe and also coincides with the industrialization of most of the continent. Overall, we found that railroads had a significant and positive impact on the growth of per capita GDP across Europe. The magnitude of this relationship appears to be relatively modest, but the results obtained are robust with respect to a number of different specifications. From a geographical perspective, we found that railroads had a significantly greater influence on regions located in countries on the northern periphery of Europe than in other outlying areas. They also helped the economies of these areas to begin the process of catching up with the continent’s industrialized core. In contrast, the regions on the southern periphery showed lower levels of economic growth, with this exacerbating the preexisting divergence in economic development. The expansion of the railroad network in them was unable to homogenize the diffusion of economic development and tended to further benefit the regions that were already industrialized. In most of the cases, the capital effect was magnified, and this contributed to the consolidation of newly created nation-states.

scholarly journals RESTING HEART RATE MODERATES THE RELATIONSHIP BETWEEN NEUROPSYCHIATRIC SYMPTOMS, MCI, AND ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S641-S641
Author(s):  
Shanna L Burke
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Heart Rate ◽  
Relative Risk ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Resting Heart Rate ◽  
Data Set ◽  
Increased Risk ◽  
The Relationship

Abstract Little is known about how resting heart rate moderates the relationship between neuropsychiatric symptoms and cognitive status. This study examined the relative risk of NPS on increasingly severe cognitive statuses and examined the extent to which resting heart rate moderates this relationship. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform Data Set was undertaken, using observations from participants with normal cognition at baseline (13,470). The relative risk of diagnosis with a more severe cognitive status at a future visit was examined using log-binomial regression for each neuropsychiatric symptom. The moderating effect of resting heart rate among those who are later diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) was assessed. Delusions, hallucinations, agitation, depression, anxiety, elation, apathy, disinhibition, irritability, motor disturbance, nighttime behaviors, and appetite disturbance were all significantly associated (p<.001) with an increased risk of AD, and a reduced risk of MCI. Resting heart rate increased the risk of AD but reduced the relative risk of MCI. Depression significantly interacted with resting heart rate to increase the relative risk of MCI (RR: 1.07 (95% CI: 1.00-1.01), p<.001), but not AD. Neuropsychiatric symptoms increase the relative risk of AD but not MCI, which may mean that the deleterious effect of NPS is delayed until later and more severe stages of the disease course. Resting heart rate increases the relative risk of MCI among those with depression. Practitioners considering early intervention in neuropsychiatric symptomology may consider the downstream benefits of treatment considering the long-term effects of NPS.

scholarly journals Spatial pattern and genetic diversity estimates are linked in stochastic models of population differentiation

2000 ◽  
Vol 23 (3) ◽  
pp. 541-544 ◽  
Author(s):  
José Alexandre Felizola Diniz-Filho ◽  
Mariana Pires de Campos Telles
Keyword(s):  
Genetic Diversity ◽  
Spatial Pattern ◽  
Stochastic Models ◽  
Population Differentiation ◽  
Real Data ◽  
Population Heterogeneity ◽  
Data Set ◽  
Mantel’S Test ◽  
The Relationship ◽  
Diversity Estimates

In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively) is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.

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