Divergence Index Research Articles

Impact of immunocompetence index based selection on health conditions in broiler chicken

Present investigation was carried out to assess the impact of immunocompetence index based selection on the survivability of Synthetic Dam Line of broiler chicken. The base population (G0) was screened for various immunocompetence traits, which were then combined in to an index, called immunocompetence (IC) index and two generations (G1 and G2) were obtained after selection for high and low IC index values. Significant differences in percent mortality patterns were noticed in the base population (P< 0.05) and G1 generation (P<0.01), whereas, in G2 generation, high index line had comparatively higher per cent mortality (2.07) as compared to the low index lines (1.29). However, the overall mortality rate was reduced substantially over the two generations of divergent IC index based selection in broiler chicken. The present investigation revealed that selective breeding for better immunocompetence status using IC index could lead to better health status in terms of reduced mortality in broiler chicken.

Classification and Prediction of Stock Market Index Based on Fuzzy Metagraph

Stock market price forecasting is one of the challenging tasks due to the difficulty in predicting the non-linear and non-stationary time series data. In this paper a Fuzzy Metagraph (FM) based stock market decision making, classification and prediction are proposed for short term investors of Indian stock market. Simple Moving Average (SMA), Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD) and Relative Strength Index (RSI) are some of the Technical Indicators which are used as input to train the system which is integrated with Fuzzy Metagraph. This approach of incorporating FM with SMA, MACD and RSI would be a new attempt in classification and prediction on share market investment. Stocks listed in Bombay Stock Exchange (BSE) in India are used to evaluate the performance of the system. The results obtained from the proposed FM based model are found to be satisfactory with very low risk error.

What is important in being cured from: Does discordance between physicians and patients matter? (2)

AimsThe influence of discordance in what is important in being cured from depression on clinical outcome at 6 months, assessed with a divergence index. Methods304 outpatients treated for depression by general practitioners or by psychiatrists and completing a 6-month treatment period: a divergence index (divergence between physician and patient view on what is important in being cured from depression) was calculated for each physician–patient pair. The relation between this index and outcome at 6 months was analyzed (including depressive, anxious and somatic symptom severity, positive effect, functional impairment and quality of life (psychological and social relations). ResultsResponse rates (50% improvement) were 65.9% for depressive symptomatology and 46.2% for anxious symptomatology. The subgroup with a poor physician–patient agreement (highest quartile) on expectations had a worse clinical outcome than the subgroup with an excellent physician–patient agreement (lowest quartile): differences in response rate between these groups ranged from 9% to 27%; this difference reached statistical significance for 3 outcome variables (anxiety, positive effect and social relationships). ConclusionsThe study shows that outcomes with standard antidepressant drugs are still suboptimal and that discordance between what patients׳ and physicians׳ consider important in the definition of cure from depression significantly influences clinical outcomes at 6 months.

The Extent of Intra-Clonal Genetic Diversity within the Myeloma Clone Is a Predictive Biomarker of Progression and Outcome after Treatment

▪Multiple myeloma (MM) is a disease characterized by the abnormal proliferation of plasma cells in the bone marrow. We and others have recently demonstrated the existence of different myeloma subclones phylogenetically related to the founding clone. This intra-clonal heterogeneity is the basis for disease progression, treatment resistance, and relapse. However, the clinical and biological relevance of the presence and diversity of different myeloma subclones has not been fully established.In this study, we used whole exome sequencing (WES) plus a pull down of the MYC, IGH, IGL and IGK loci as a tool to analyze the largest series of presenting cases of myeloma (463 patients) to date, which were entered into the Myeloma XI trial (NCT01554852). DNA from both tumor and peripheral blood samples were used in the exome capture protocol following the SureSelect Target Enrichment System for Illumina Paired-End Sequencing Library v1.5. Exome reads were used to call single nucleotide variants (SNVs), indels, translocations, and copy number aberrations. The proportion of tumor cells containing an SNV was inferred. The presence and proportion of subclones were defined in a subset of 437 patients using a genetic algorithm based-tool (GAUCHO), which also calculated different indices of clonal diversity: number of clones, mean pairwise genetic divergence, Shannon and Inverse Simpson diversity index and Berger-Parker dominance index. Based on these results, we aimed to determine the clinical implications of the number of mutations and the subclonal diversity of MM at presentation in progression free (PFS) and overall survival (OS).We found that MM patients with t(14;16) and t(14;20) had more exonic mutations (not including Ig variants) than the rest of samples (median 87 versus 43, p<0.001). Additionally, we found that MM patients with an APOBEC signature or with mutations in ATM/ATR had significantly more mutations than patients without these genetic lesions with a median number of 137 mutations (range 20-569) and 84.5 (range 33-319) respectively (p<0.001). Subsequently, we identified patients with high number of mutations (>59 mutations) that had a worse outcome in terms of OS (2-year OS rate of 71% (95% CI, 63-80%) vs. 82% (95% CI, 78-87%), p=0.02), but not progression free survival (median 22.5 (95% CI 18.7-30.2) vs. 27.5 (95% CI, 25.8-30.5) months, p=0.1)We reported recurrent mutated genes in myeloma with mutations being present at both clonal and subclonal levels (IRF4, RB1, DIS3, BRAF, KRAS, and NRAS), whereas other genes were mutated only at clonal (HIST1H1E, LTB, TP53 or EGR1), or subclonal levels (CYLD, TRAF3, MAX). These results give insights about the differences in mutation acquisition times and potential subclonal fitness.We inferred that the median number of clones present in this myeloma series was 5, and determined the prognostic value of the number and diversity of subclones in MM patients. The prognostic impact of having high number of clones was unclear as no significant differences were found. On the contrary, there was a significant difference in terms of outcome when calculating distinct measurements of subclonal diversity. Briefly, MM patients with high values of inverse Simpson diversity index had a significantly poorer PFS (median 13.2 (95% CI, 9.4-∞) vs. 26.9 months (95% CI, 24-30.2) months, p=0.02) and OS (66% (95% CI, 52-82%) vs. 81% (95% CI, 77-85%) alive at 2-years, p=0.01); and, alternatively, MM patients who did not have a dominant subclone accounting for >25% of MM cells (low values of Berger-Parker Dominance index, n=56) had a significantly shorter PFS than those with a dominant clone accounting for more than 25% of cells with a median of 22 (95% CI, 12.3-26.3) vs. 27.5 months (95% CI, 23.9-30.9) respectively, p=0.02.Our results show that mutational load and subclonal diversity are poor prognostic factors in myeloma. Previous studies from massive-parallel sequencing and single cell analyses of myeloma plasma cells already revealed that myeloma had the features of an evolutionary ecosystem, where different tumour subclones coexist and have differential response to treatment. We have demonstrated in this study that measures of tumor diversity have important clinical consequences. To our knowledge, this is the first time that the use of clonal diversity indices as predictive biomarkers of progression is proposed in haematological malignancies, and more specifically, myeloma. DisclosuresWalker:Onyx Pharmaceuticals: Consultancy, Honoraria.

Spatial Information Divergence: Using Global and Local Indices to Compare Geographical Masks Applied to Crime Data

AbstractAdvances in Geographic Information Science (GISc) and the increasing availability of location data have facilitated the dissemination of crime data and the abundance of crime mapping websites. However, data holders acknowledge that when releasing sensitive crime data there is a risk of compromising the victims' privacy. Hence, protection methodologies are primarily applied to the data to ensure that individual privacy is not violated. This article addresses one group of location protection methodologies, namely geographical masks that are applicable for crime data representations. The purpose is to identify which mask is the most appropriate for crime incident visualizations. A global divergence index (GDi) and a local divergence index (LDi) are developed to compare the effects that these masks have on the original crime point pattern. The indices calculate how dissimilar the spatial information of the masked data is from the spatial information of the original data in regards to the information obtained via spatial crime analysis. The results of the analysis show that the variable radius mask and the donut geomask should be primarily used for crime representations as they produce less spatial information divergence of the original crime point pattern than the alternative local random rotation mask and circular mask.

Impact of the central Pacific zonal wind divergence and convergence on the central Pacific El Niño event

The central Pacific (CP) zonal wind divergence and convergence indices are defined, and the forming mechanism of CP El Nino (La Nina) events is discussed preliminarily. The results show that the divergence and convergence of the zonal wind anomaly (ZWA) are the key process in the forming of CP El Nino (La Nina) events. A correlation analysis between the central Pacific zonal wind divergence and convergence indices and central Pacific El Nino indices indicates that there is a remarkable lag correlation between them. The central Pacific zonal wind divergence and convergence indices can be used to predict the CP events. Based on these results, a linear regression equation is obtained to predict the CP El Nino (La Nina) events 5 months ahead.

Thermal refraction defocusing in very-large-core step-index antiguided fiber lasers

Thermal refraction defocusing in very-large-core step-index antiguided fibers is investigated theoretically. Recent analytical methods based on a zero-field approximation for studying the effects of thermal focusing are extended and applied to the defocusing effects that occur in laser media with negative temperature coefficient of refractive index. Intermediate values of thermal defocusing tend to flatten the radial intensity distribution, while strong thermal defocusing is shown to concentrate the intensity near the antiguiding core&#x2013;cladding boundary. The same analysis is also applicable for very-large-core graded-index fibers with a divergent parabolic index profile.

Local Sparsity Divergence for Hyperspectral Anomaly Detection

Anomaly detection (AD) has increasingly become important in hyperspectral imagery (HSI) owing to its high spatial and spectral resolutions. Many anomaly detectors have been proposed, and most of them are based on a Reed–Xiaoli (RX) detector, which assumes that the spectrum signature of HSI pixels can be modeled with Gaussian distributions. However, recent studies show that the Gaussian and other unimodal distributions are not a good fit to the data and often lead to many false alarms. This letter proposes a novel hyperspectral AD algorithm based on local sparsity divergence (LSD) without any distribution hypothesis. Our algorithm exploits the fact that targets and background lie in different low-dimensional subspaces and that targets cannot be effectively represented by their local surrounding background. A sliding dual-window strategy is first adopted to construct local spectral and spatial dictionaries, which enable the extraction of the sparse coefficients of each HSI pixel. Then, a consistent sparsity divergence index is proposed to compute the LSD map at each spectral band separately. Finally, joint segmentation of LSD maps over different bands is performed for AD. Experimental results on both simulated data and recorded data demonstrate the effectiveness of the proposed algorithm.

Predicting hybrid fertility from maker-based genetic divergence index of parental varieties: implications for utilizing inter-subspecies heterosis in hybrid rice breeding

Utilizing inter-subspecies heterosis of indica-japonica rice hybrids is a potential solution to break the yield ceiling for hybrid rice breeding. However, the reduced panicle fertility (PF) of the inter-subspecies hybrids caused by reproductive isolation due to genetic divergence between parental varieties has hampered the effective utilization of the inter-subspecies heterosis. This is because significantly reduced fertility always leads to low yield of the F1 hybrids. To study the association between genetic divergence of indica-japonica parental varieties and panicle fertility of their inter-subspecies hybrids, we developed a method to determine the genetic divergence index (GDI) of the two parents, assisted by the insertion/deletion (InDel) molecular genotyping. Based on parents’ GDI, we produced 103 combinations of F1 hybrids whose parental varieties showed a wide range of indica-japonica genetic divergence. PF of all the F1 hybrids in different combinations was measured to analyze its association with GDI of their corresponding parents. A negative correlation between GDI of indica-japonica parental varieties and PF of their corresponding F1 hybrids was detected based on field experiments conducted in three independent locations. The results suggested that GDI of parental varieties can be used to predict PF of their indica-japonica hybrids before a hybridization experiment is conducted. The molecular-maker-based GDI provides a useful tool to assist in selecting indica and japonica parental varieties for hybrid rice breeding in a more designed manner to achieve reasonable heterosis and panicle fertilities in F1 hybrids.

Explaining the behavior of joint and marginal Monte Carlo estimators in latent variable models with independence assumptions

In latent variable models the parameter estimation can be implemented by using the joint or the marginal likelihood, based on independence or conditional independence assumptions. The same dilemma occurs within the Bayesian framework with respect to the estimation of the Bayesian marginal (or integrated) likelihood, which is the main tool for model comparison and averaging. In most cases, the Bayesian marginal likelihood is a high dimensional integral that cannot be computed analytically and a plethora of methods based on Monte Carlo integration (MCI) are used for its estimation. In this work, it is shown that the joint MCI approach makes subtle use of the properties of the adopted model, leading to increased error and bias in finite settings. The sources and the components of the error associated with estimators under the two approaches are identified here and provided in exact forms. Additionally, the effect of the sample covariation on the Monte Carlo estimators is examined. In particular, even under independence assumptions the sample covariance will be close to (but not exactly) zero which surprisingly has a severe effect on the estimated values and their variability. To address this problem, an index of the sample's divergence from independence is introduced as a multivariate extension of covariance. The implications addressed here are important in the majority of practical problems appearing in Bayesian inference of multi-parameter models with analogous structures.

Balance between a Higher Degree of Heterosis and Increased Reproductive Isolation: A Strategic Design for Breeding Inter-Subspecific Hybrid Rice

The application of heterosis (hybrid vigor) has brought great success to plant breeding, particularly of hybrid rice, achieving significant yield increases. Attempts to explore the heterosis of inter-subspecific hybrids between indica and japonica rice, which result in even greater yield increases, have greatly increased in the past decades. However, because of the reduced seed setting rate in F1 hybrids as a result of increased reproductive isolation, the application of inter-subspecific hybrids in rice has slowed. Understanding the balance between heterosis and the reproductive isolation of inter-subspecific hybrids will facilitate the strategic design of inter-subspecific hybrid breeding. In this study, five indica and seven japonica rice varieties were chosen as the parental lines of a complete diallel mating design. Data from six group traits from all of the hybrids and inbred lines were collected. We found that the grain weight per plant, grain number per panicle, tiller per plant, thousand grain weight and plant height, which reflected increased heterosis, were associated with the genetic divergence index (GDI) of the parents. Meanwhile, owing to the reduced seed setting rate, which was also associated with the parents' GDI, the grain production of the hybrids was negatively affected. After analyzing the relationships between the GDI of indica-japonica parents and the grain weight per plant of the F1 hybrids, an ideal GDI value (0.37) for the two indica-japonica parents that could provide an optimal balance between the inter-subspecific heterosis and reproductive isolation was proposed. Our findings will help in the strategic design of an inter-subspecific hybrid rice breeding program by identifying the ideal indica and japonica parents for a hybrid combination to achieve hybrid rice with an optimal yield. This strategic design of an inter-subspecific hybrid rice breeding program will be time saving and cost effective.

Determinants of species abundance for eastern North American trees

AbstractAimWe aimed to quantify the relative contributions of trait‐based selection and the flow of individuals across space created by differences in species abundance, i.e. mass effects, in determining local‐scale species relative abundance (SRA) at 0.07 ha, 1° grid cell and subregion grains.LocationThe eastern USA.MethodsWe coupled a maximum entropy model (MaxEnt) with nine species‐specific plant traits and a continental‐scale forest inventory dataset to perform our analyses. Mass effects were estimated using the next grain size up as the metacommunity (or the eastern USA at the subregion grain, and also at the 1° grid cell grain in a fourth analysis). Permutation tests were conducted to test the significance of trait constraints. The Kullback–Leibler divergence index was used to decompose the information content in each assemblage SRA.ResultsTrait constraints were significant in predicting community structures at coarse scales, but were largely not significant at fine or medium scales. At the 0.07 ha grain little of the variation in local SRA can be explained by either trait constraints or a regional SRA. At the 1° grain c. 61% of the variation could be accounted for by a regional SRA represented by subregions. At the subregion grain c. 74% of the variation could be accounted for by trait constraints and the SRA of the entire study area.Main conclusionsOur results suggest that the relative importance of community assembly processes is scale dependent. Estimated mass effects predominated at small spatial scales where environmental gradients were weak. Trait‐based selection was hard to detect at small scales and was strongest at large scales where environmental gradients are stronger. The fact that, at all scales, mass effects accounted for more variation in assemblage SRA than trait‐based selection in our analyses suggests that regional processes are important in determining community structures more locally.

Revisiting the Performance of MACD and RSI Oscillators

Chong and Ng (2008) find that the Moving Average Convergence–Divergence (MACD) and Relative Strength Index (RSI) rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD(12,26,0) and RSI(21,50) rules consistently generate significant abnormal returns in the Milan Comit General and the S&amp;P/TSX Composite Index. In addition, the RSI(14,30/70) rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors’ belief in these two technical indicators in different developed markets.

Damage Identification by the Kullback-Leibler Divergence and Hybrid Damage Index

The hybrid damage index (HDI) is presented as a mean for the damage identification in this paper, which is on the basis of the Kullback-Leibler divergence (KLD) and its approximations. The proposed method is suitable for detecting damage in one-dimensional structure and delamination in laminated composite. The first step of analysis includes obtaining the mode data of the structure before and after the damage, and then the KLD and its approximations are obtained. In addition, the HDI is obtained on the basis of the KLD and its approximations, utilizing the natural frequencies and mode shape at the same time. Furthermore, the modal strain energy (MSE) method is employed to verify the efficiency of the proposed method. Finally, to demonstrate the capability of the proposed method, examples of the beam and laminated composite are applied for checking the present approaches numerically, and the final results validate the effective and accurate performance of the present technique.

Mathematical errors, smoke and mirrors in pursuit of an illusion: Comments on Govinder et al. (2013)

The 'Equity Index' (EI) as gratuitously labelled by Govinder and Makgoba in a recent paper is not an equity index. It is actually simply a demographic divergence index (DDI), one of many possible mathematical alternatives which warrant the name DDI. The invocation of the word 'equity' in the original name is a deliberate but implicit claim of moral and ethical authority for the construct. This claim needs to be tested before the label 'equity' is admitted as a meaningful description. A thorn by any other name is not a rose, and proximity is not provenance.

Host conservatism or host specialization? Patterns of fungal diversification are influenced by host plant specificity inOphiognomonia(Gnomoniaceae: Diaporthales)

In this study evolutionary host plant patterns at ranks from order to species were analysed using spatial evolutionary and ecological vicariance analysis (SEEVA), based on a multigene phylogeny of 45 ascomycete fungal species. The objective was to understand speciation events and host associations in Ophiognomonia (Gnomoniaceae). Species of this genus are perithecial fungi that occur as endophytes, pathogens, and latent saprobes on plants in the families of Betulaceae, Fagaceae, Juglandaceae, Lauraceae, Malvaceae, Platanaceae, Rosaceae, Salicaceae, and Sapindaceae. A second objective was to determine whether speciation events are influenced by host conservatism, host specialization, or host switching at different taxonomic host ranks. Host differences between sister clades were interpreted using the divergence index (D) from the SEEVA analysis, ranging from 0 for no divergence to 1 for maximum possible divergence. Several fungal subclades showed clear patterns of host order/family conservatism (D = 1.00) for hosts in Betulaceae, Fagaceae, Juglandaceae, and Rosaceae. Clear trends of host specialization at host genus and species ranks (D = 1.00) were suggested within these host families. Independent host jumps were observed for two species at the family rank and three at the order rank. As a result of this study, host specificity and specialization is hypothesized as a mechanism that can strongly contribute to speciation patterns in fungal pathogens. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 1–16.

Plant functional traits and community assembly along interacting gradients of productivity and fragmentation

Quantifying the association of plant functional traits to environmental gradients is a promising approach for understanding and projecting community responses to land use and climatic changes. Although habitat fragmentation and climate are expected to affect plant communities interactively, there is a lack of empirical studies addressing trait associations to fragmentation in different climatic regimes. In this study, we analyse data on the key functional traits: specific leaf area (SLA), plant height, seed mass and seed number. First, we assess the evidence for the community assembly mechanisms habitat filtering and competition at different spatial scales, using several null-models and a comprehensive set of community-level trait convergence and divergence indices. Second, we analyse the association of community-mean traits with patch area and connectivity along a south–north productivity gradient. We found clear evidence for trait convergence due to habitat filtering. In contrast, the evidence for trait divergence due to competition fundamentally depended on the null-model used. When the null-model controlled for habitat filtering, there was only evidence for trait divergence at the smallest sampling scale (0.25 m × 0.25 m). All traits varied significantly along the S–N productivity gradient. While plant height and SLA were consistently associated with fragmentation, the association of seed mass and seed number with fragmentation changed along the S–N gradient. Our findings indicate trait convergence due to drought stress in the arid sites and due to higher productivity in the mesic sites. The association of plant traits to fragmentation is likely driven by increased colonization ability in small and/or isolated patches (plant height, seed number) or increased persistence ability in isolated patches (seed mass). Our study provides the first empirical test of trait associations with fragmentation along a productivity gradient. We conclude that it is crucial to study the interactive effects of different ecological drivers on plant functional traits.

Robust estimation of distance between sets of points

This paper proposes a new methodology for computing Hausdorff distances between sets of points in a robust way. In a first step, robust nearest neighbor distance distributions between the two sets of points are obtained by considering reliability measures in the computations through a Monte Carlo scheme. In a second step, the computed distributions are operated using random variables algebra in order to obtain probability distributions of the average, minimum or maximum distances. In the last step, different statistics are computed from these distributions. A statistical test of significance, the nearest neighbor index, in addition to the newly proposed divergence and clustering indices are used to compare the computed measurements with respect to values obtained by chance. Results on synthetic and real data show that the proposed method is more robust than the standard Hausdorff distance. In addition, unlike previously proposed methods based on thresholding, it is appropriate for problems that can be modeled through point processes.

Biochemical pathways of amino acids in soil: Assessment by position-specific labeling and 13C-PLFA analysis

Microbial utilization is a key transformation process of soil organic matter (SOM). For the first time, position-specific 13C labeling was combined with compound-specific 13C-PLFA analysis to trace metabolites of two amino acids in microbial groups and to reconstruct detailed biochemical pathways. Short-term transformation was assessed by applying position-specifically 13C labeled alanine and glutamic acid to soil in a field experiment. Microbial utilization of the amino acids' functional groups was quantified by 13C incorporation in total microbial biomass and in distinct microbial groups classified by 13C-PLFA.Loss from PLFAs was fastest for the highly oxidized carboxyl group of both amino acids, whereas the reduced C positions, e.g. C3–5, were preferentially incorporated into microorganisms and their PLFAs. The incorporation of C from alanines' C2 position into the cell membrane of gram negative bacteria was higher by more than one order of magnitude than into all other microbial groups. Whereas C2 of alanine was still bound to C3 at day 3, the C2 and C3 positions were partially split at day 10. In contrast, the C2 of glutamic acid was lost faster from PLFAs of all microbial groups. The divergence index, which reflects relative incorporation of one position to the incorporation of C from all positions in a molecule, revealed that discrimination between positions is highest in the initial reactions and decreases with time.Reconstruction of microbial transformation pathways showed that the C2 position of alanine is lost faster than its C3 position regardless of whether the molecule is used ana- or catabolically. Glutamic acid C2 is incorporated into PLFAs only by two out of eight microbial groups (fungi and part of gram positive prokaryotes). Its incorporation in PLFA can only be explained by either the utilization of the glyoxolate bypass or the transformation of glutamic acid into aspartate prior to being fed into the citric acid cycle. During these pathways, no C is lost as CO2 but neither is energy produced, making them typical C deficiency pathways. Glutamic acid is therefore a promising metabolic tracer in regard to ecophysiology of cells and therefore changing environmental conditions.Analyzing the fate of individual C atoms by position-specific labeling allows insight into the mechanisms and kinetics of microbial utilization by various microbial groups. This approach will strongly improve our understanding of soil C fluxes.

Immunocompetence index selection of broiler chicken lines for disease resistance and their impact on survival rate

Aim: This study was aimed to develop the disease resistance broiler chicken lines over two generations (G , G and G ) of 0 1 2 selection for immunocompetence (IC) index by targeting all the facets of immune response traits viz., humoral response (HR) to Sheep red blood cells (SRBC), cell mediated immune response (CMI) to phytohaeagglutinationP mitogen (PHA-P), levels of serum serum immunoglobinG (IgG) and serum lysozyme (LZM) level. Materials and Methods: The SDL Synthetic Dam Line (SDL) broiler line consisting of 303, 204 and 300 birds in G , G and 0 1 G generations, respectively were screened for immunocompetence traits such as humoral response to SRBCs, cell mediated 2 immune response to PHA-P and levels of serum lysozyme by Lysoplate assay and IgG by SRID method, and ranked based on their IC index values. Results: The percent survival rate up to 6 weeks of age in SDL broiler chicken lines were selected for high immunocompetence index (HIC) and low immunocompetence index values (LIC) over two generations (G , G and G ) of selection 0 1 2 and observed that significant differences (P< 0.05) in percent survival pattern in the base population (n= 303) with the highest survivability of 100.00% was observed in 5-6 weeks of age followed by 99.37% and 97.23% in 4-5 and 0-4 weeks of age respectively. In the G generation, significant differences ( P<0.01) was noticed in the selected high and low index lines up to 6 1 weeks of age with the overall survival rate lower in high index lines (93.10% ) as compared to the low index lines (97.62%). Whereas the reverse trend was observed in the G generation that the high index line had significantly (P<0.05) higher survival 2 percent (98.62%) as compared to the low index lines (97.93%). Moreover, the overall survival rate was better substantially over the two generations of divergent immunocompetent index selection of SDL broiler chicken lines. The present investigation revealed that breeding for better immunocompetence status by selection index could lead to better health status in term of improved survival rate in broiler chicken over the generation of selection and further suggested that index selection for more number of generations coupled with economic traits would seem to be a viable option for development of disease resistant chicken lines. Conclusion: Breeding for overall genetic improvement of immunocompetence status by index selection with all the facets of immune system could lead to better survival rate and development of disease resistant chicken.