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Fulltext A Meta-Analysis on the Performance of Cystatin C- versus Creatinine-based eGFR Equations in Predicting Vancomycin Clearance

Mohd Tahir NA, Mohd Saffian S, Islahudin FH, Abdul Gafor AH, Makmor-Bakry M

J Korean Med Sci, 2020 Sep 21;35(37):e306.
PMID: 32959542 DOI: 10.3346/jkms.2020.35.e306

BACKGROUND: The objective of this study was to compare the performance of cystatin C- and creatinine-based estimated glomerular filtration rate (eGFR) equations in predicting the clearance of vancomycin.
METHODS: MEDLINE and Embase databases were searched from inception up to September 2019 to identify all studies that compared the predictive performance of cystatin C- and/or creatinine-based eGFR in predicting the clearance of vancomycin. The prediction errors (PEs) (the value of eGFR equations minus vancomycin clearance) were quantified for each equation and were pooled using a random-effects model. The root mean squared errors were also quantified to provide a metric for imprecision.
RESULTS: This meta-analysis included evaluations of seven different cystatin C- and creatinine-based eGFR equations in total from 26 studies and 1,234 patients. The mean PE (MPE) for cystatin C-based eGFR was 4.378 mL min-1 (95% confidence interval [CI], -29.425, 38.181), while the creatinine-based eGFR provided an MPE of 27.617 mL min-1 (95% CI, 8.675, 46.560) in predicting clearance of vancomycin. This indicates the presence of unbiased results in vancomycin clearance prediction by the cystatin C-based eGFR equations. Meanwhile, creatinine-based eGFR equations demonstrated a statistically significant positive bias in vancomycin clearance prediction.
CONCLUSION: Cystatin C-based eGFR equations are better than creatinine-based eGFR equations in predicting the clearance of vancomycin. This suggests that utilising cystatin C-based eGFR equations could result in better accuracy and precision to predict vancomycin pharmacokinetic parameters.

Matched MeSH terms: Bayes Theorem
Fulltext Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset

M. Hafiz Fazren Abd Rahman, Wan Wardatul Amani Wan Salim, M. Firdaus Abd-Wahab

Biological and Natural Resources Engineering Journal, 2020;3(1):48-61.
MyJurnal

The steep rise of cases pertaining to Diabetes Mellitus (DM) condition among global population has encouraged extensive researches on DM, which led to exhaustive accumulation of data related to DM. In this case, data mining and machine learning applications prove to be a powerful tool in transforming data into meaningful deductions. Several machine learning tools have shown great promise in diabetes classification. However, challenges remain in obtaining an accurate model suitable for real world application. Most disease risk-prediction modelling are found to be specific to a local population. Moreover, real-world data are likely to be complex, incomplete and unorganized, thus, convoluting efforts to develop models around it. This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using three different machine learning algorithms; Decision Tree, Support Vector Machine and Naïve Bayes. Data pre-processing methods are utilised to the raw data to improve model performance. This study uses datasets obtained from the IIUM Medical Centre for classification and modelling. Ultimately, the performance of each model is validated, evaluated and compared based on several statistical metrics that measures accuracy, precision, sensitivity and efficiency. This study shows that the random forest model provides the best overall prediction performance in terms of accuracy (0.87), sensitivity (0.9), specificity (0.8), precision (0.9), F1-score (0.9) and AUC value (0.93) (Normal).

Matched MeSH terms: Bayes Theorem
Fulltext Ecology of bat flies in Singapore: A study on the diversity, infestation bias and host specificity (Diptera: Nycteribiidae)

Lim ZX, Hitch AT, Lee BPY, Low DHW, Neves ES, Borthwick SA, et al.

Int J Parasitol Parasites Wildl, 2020 Aug;12:29-33.
PMID: 32420022 DOI: 10.1016/j.ijppaw.2020.04.010

Bat flies are highly-specialized, hematophagous arthropods that are globally ubiquitous. There is little published research on bat flies (Diptera: Nycteribiidae) in Singapore and understanding the diversity of nycteribiids, host association and infestation rates can provide insight into this host-ectoparasite relationship. Nycteribiids were collected from bats trapped in Singapore (2011-2016) and identified using morphological keys. Host-ectoparasite relationships were investigated with logistic regression and Bayesian poisson regression. Nycteribiids were found to be monoxenously associated with their host bat species and host age, sex, species, and BBCI appear to contribute to differences in prevalence and intensity. Differences in host specificity between bat fly species in Singapore and their conspecifics in less disturbed habitats with higher bat biodiversity, such as Malaysia, Philippines and Thailand, suggest that the high host specificity in Singapore derives from the paucity of suitable hosts and abundance of single species roosts and not from their coevolved restrictions to them.

Matched MeSH terms: Bayes Theorem
Fulltext ECG-based prediction algorithm for imminent malignant ventricular arrhythmias using decision tree

Mandala S, Cai Di T, Sunar MS, Adiwijaya

PLoS One, 2020;15(5):e0231635.
PMID: 32407335 DOI: 10.1371/journal.pone.0231635

Spontaneous prediction of malignant ventricular arrhythmia (MVA) is useful to avoid delay in rescue operations. Recently, researchers have developed several algorithms to predict MVA using various features derived from electrocardiogram (ECG). However, there are several unresolved issues regarding MVA prediction such as the effect of number of ECG features on a prediction remaining unclear, possibility that an alert for occurring MVA may arrive very late and uncertainty in the performance of the algorithm predicting MVA minutes before onset. To overcome the aforementioned problems, this research conducts an in-depth study on the number and types of ECG features that are implemented in a decision tree classifier. In addition, this research also investigates an algorithm's execution time before the occurrence of MVA to minimize delays in warnings for MVA. Lastly, this research aims to study both the sensitivity and specificity of an algorithm to reveal the performance of MVA prediction algorithms from time to time. To strengthen the results of analysis, several classifiers such as support vector machine and naive Bayes are also examined for the purpose of comparison study. There are three phases required to achieve the objectives. The first phase is literature review on existing relevant studies. The second phase deals with design and development of four modules for predicting MVA. Rigorous experiments are performed in the feature selection and classification modules. The results show that eight ECG features with decision tree classifier achieved good prediction performance in terms of execution time and sensitivity. In addition, the results show that the highest percentage for sensitivity and specificity is 95% and 90% respectively, in the fourth 5-minute interval (15.1 minutes-20 minutes) that preceded the onset of an arrhythmia event. Such results imply that the fourth 5-minute interval would be the best time to perform prediction.

Matched MeSH terms: Bayes Theorem
Phylogenetic comparison between Type IX Secretion System (T9SS) protein components suggests evidence of horizontal gene transfer

Emrizal R, Nor Muhammad NA

PeerJ, 2020;8:e9019.
PMID: 32617187 DOI: 10.7717/peerj.9019

Porphyromonas gingivalis is one of the major bacteria that causes periodontitis. Chronic periodontitis is a severe form of periodontal disease that ultimately leads to tooth loss. Virulence factors that contribute to periodontitis are secreted by Type IX Secretion System (T9SS). There are aspects of T9SS protein components that have yet to be characterised. Thus, the aim of this study is to investigate the phylogenetic relationship between members of 20 T9SS component protein families. The Bayesian Inference (BI) trees for 19 T9SS protein components exhibit monophyletic clades for all major classes under Bacteroidetes with strong support for the monophyletic clades or its subclades that is consistent with phylogeny exhibited by the constructed BI tree of 16S rRNA. The BI tree of PorR is different from the 19 BI trees of T9SS protein components as it does not exhibit monophyletic clades for all major classes under Bacteroidetes. There is strong support for the phylogeny exhibited by the BI tree of PorR which deviates from the phylogeny based on 16S rRNA. Hence, it is possible that the porR gene is subjected to horizontal transfer as it is known that virulence factor genes could be horizontally transferred. Seven genes (porR included) that are involved in the biosynthesis of A-LPS are found to be flanked by insertion sequences (IS5 family transposons). Therefore, the intervening DNA segment that contains the porR gene might be transposed and subjected to conjugative transfer. Thus, the seven genes can be co-transferred via horizontal gene transfer. The BI tree of UgdA does not exhibit monophyletic clades for all major classes under Bacteroidetes which is similar to the BI tree of PorR (both are a part of the seven genes). Both BI trees also exhibit similar topology as the four identified clusters with strong support and have similar relative positions to each other in both BI trees. This reinforces the possibility that porR and the other six genes might be horizontally transferred. Other than the BI tree of PorR, the 19 other BI trees of T9SS protein components also exhibit evidence of horizontal gene transfer. However, their genes might undergo horizontal gene transfer less frequently compared to porR because the intervening DNA segment that contains porR is easily exchanged between bacteria under Bacteroidetes due to the presence of insertion sequences (IS5 family transposons) that flank it. In conclusion, this study can provide a better understanding about the phylogeny of T9SS protein components.

Matched MeSH terms: Bayes Theorem
Gene flow creates a mirage of cryptic species in a Southeast Asian spotted stream frog complex

Chan KO, Hutter CR, Wood PL, Grismer LL, Das I, Brown RM

Mol Ecol, 2020 10;29(20):3970-3987.
PMID: 32808335 DOI: 10.1111/mec.15603

Most new cryptic species are described using conventional tree- and distance-based species delimitation methods (SDMs), which rely on phylogenetic arrangements and measures of genetic divergence. However, although numerous factors such as population structure and gene flow are known to confound phylogenetic inference and species delimitation, the influence of these processes is not frequently evaluated. Using large numbers of exons, introns, and ultraconserved elements obtained using the FrogCap sequence-capture protocol, we compared conventional SDMs with more robust genomic analyses that assess population structure and gene flow to characterize species boundaries in a Southeast Asian frog complex (Pulchrana picturata). Our results showed that gene flow and introgression can produce phylogenetic patterns and levels of divergence that resemble distinct species (up to 10% divergence in mitochondrial DNA). Hybrid populations were inferred as independent (singleton) clades that were highly divergent from adjacent populations (7%-10%) and unusually similar (<3%) to allopatric populations. Such anomalous patterns are not uncommon in Southeast Asian amphibians, which brings into question whether the high levels of cryptic diversity observed in other amphibian groups reflect distinct cryptic species-or, instead, highly admixed and structured metapopulation lineages. Our results also provide an alternative explanation to the conundrum of divergent (sometimes nonsister) sympatric lineages-a pattern that has been celebrated as indicative of true cryptic speciation. Based on these findings, we recommend that species delimitation of continuously distributed "cryptic" groups should not rely solely on conventional SDMs, but should necessarily examine population structure and gene flow to avoid taxonomic inflation.

Matched MeSH terms: Bayes Theorem
Fulltext Multi-stage feature selection (MSFS) algorithm for UWB-based early breast cancer size prediction

Vijayasarveswari V, Andrew AM, Jusoh M, Sabapathy T, Raof RAA, Yasin MNM, et al.

PLoS One, 2020;15(8):e0229367.
PMID: 32790672 DOI: 10.1371/journal.pone.0229367

Breast cancer is the most common cancer among women and it is one of the main causes of death for women worldwide. To attain an optimum medical treatment for breast cancer, an early breast cancer detection is crucial. This paper proposes a multi- stage feature selection method that extracts statistically significant features for breast cancer size detection using proposed data normalization techniques. Ultra-wideband (UWB) signals, controlled using microcontroller are transmitted via an antenna from one end of the breast phantom and are received on the other end. These ultra-wideband analogue signals are represented in both time and frequency domain. The preprocessed digital data is passed to the proposed multi- stage feature selection algorithm. This algorithm has four selection stages. It comprises of data normalization methods, feature extraction, data dimensional reduction and feature fusion. The output data is fused together to form the proposed datasets, namely, 8-HybridFeature, 9-HybridFeature and 10-HybridFeature datasets. The classification performance of these datasets is tested using the Support Vector Machine, Probabilistic Neural Network and Naïve Bayes classifiers for breast cancer size classification. The research findings indicate that the 8-HybridFeature dataset performs better in comparison to the other two datasets. For the 8-HybridFeature dataset, the Naïve Bayes classifier (91.98%) outperformed the Support Vector Machine (90.44%) and Probabilistic Neural Network (80.05%) classifiers in terms of classification accuracy. The finalized method is tested and visualized in the MATLAB based 2D and 3D environment.

Matched MeSH terms: Bayes Theorem
Fulltext Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints

Colwell RK, Gotelli NJ, Ashton LA, Beck J, Brehm G, Fayle TM, et al.

Ecol Lett, 2016 09;19(9):1009-22.
PMID: 27358193 DOI: 10.1111/ele.12640

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.

Matched MeSH terms: Bayes Theorem
Fulltext Research trends in microarray data analysis: modelling gene regulatory network by integrating transcription factors data

Farzana Kabir Ahmad, Siti Sakira Kamaruddin

Scientific Research Journal, 2015;12(1):1-10.
MyJurnal

The invention of microarray technology has enabled expression levels of thousands of genes to be monitored at once. This modernized approach has created large amount of data to be examined. Recently, gene regulatory network has been an interesting topic and generated impressive research goals in computational biology. Better understanding of the genetic regulatory processes would bring significant implications in the biomedical fields and many other pharmaceutical industries. As a result, various mathematical and computational methods have been used to model gene regulatory network from microarray data. Amongst those methods, the Bayesian network model attracts the most attention and has become the prominent technique since it can capture nonlinear and stochastic relationships between variables. However, structure learning of this model is NP-hard and computationally complex as the number of potential edges increase drastically with the number of genes. In addition, most of the studies only focused on the predicted results while neglecting the fact that microarray data is a fragmented information on the whole biological process. Hence this study proposed a network-based inference model that combined biological knowledge in order to verify the constructed gene regulatory relationships. The gene regulatory network is constructed using Bayesian network based on low-order conditional independence approach. This technique aims to identify from the data the dependencies to construct the network structure, while addressing the structure learning problem. In addition, three main toolkits such as Ensembl, TFSearch and TRANSFAC have been used to determine the false positive edges and verify reliability of regulatory relationships. The experimental results show that by integrating biological knowledge it could enhance the precision results and reduce the number of false positive edges in the trained gene regulatory network.

Matched MeSH terms: Bayes Theorem
Genetic Polymorphism of Aedes albopictus Population Inferred From ND5 Gene Variabilities In Subang Jaya, Malaysia

Adilah-Amrannudin N, Hamsidi M, Ismail NA, Ismail R, Dom NC, Ahmad AH, et al.

J Am Mosq Control Assoc, 2016 Dec;32(4):265-272.
PMID: 28206858 DOI: 10.2987/16-6579.1

This study was performed to establish the genetic variability of Aedes albopictus within Subang Jaya, Selangor, Malaysia, by using the nicotinamide adenine dinucleotide dehydrogenase 5 subunit (ND5) mitochondrial DNA (mtDNA) marker. A total of 90 samples were collected from 9 localities within an area of the Subang Jaya Municipality. Genetic variability was determined through the amplification and sequencing of a fragment of the ND5 gene. Eight distinct mtDNA haplotypes were identified. The evolutionary relationship of the local haplotypes alongside 28 reference strains was used to construct a phylogram, the analysis of which revealed low genetic differentiation in terms of both nucleotide and haplotype diversity. Bayesian method was used to infer the phylogenetic tree, revealing a unique relationship between local isolates. The study corroborates the reliability of ND5 to identify distinct lineages for polymorphism-based studies and supplements the existing body of knowledge regarding its genetic diversity. This in turn could potentially aid existing vector control strategies to help mitigate the risk and spread of the dengue virus.

Matched MeSH terms: Bayes Theorem
Fulltext Assessment of genetic diversity and population structure of oil palm (Elaeis guineensis Jacq.) field genebank: A step towards molecular-assisted germplasm conservation

Gan ST, Teo CJ, Manirasa S, Wong WC, Wong CK

PLoS One, 2021;16(7):e0255418.
PMID: 34324602 DOI: 10.1371/journal.pone.0255418

Oil palm (Elaeis guineensis) germplasm is exclusively maintained as ex situ living collections in the field for genetic conservation and evaluation. However, this is not for long term and the maintenance of field genebanks is expensive and challenging. Large area of land is required and the germplasms are exposed to extreme weather conditions and casualty from pests and diseases. By using 107 SSR markers, this study aimed to examine the genetic diversity and relatedness of 186 palms from a Nigerian-based oil palm germplasm and to identify core collection for conservation. On average, 8.67 alleles per SSR locus were scored with average effective number of alleles per population ranging from 1.96 to 3.34 and private alleles were detected in all populations. Mean expected heterozygosity was 0.576 ranging from 0.437 to 0.661 and the Wright's fixation index calculated was -0.110. Overall moderate genetic differentiation among populations was detected (mean pairwise population FST = 0.120, gene flow Nm = 1.117 and Nei's genetic distance = 0.466) and this was further confirmed by AMOVA analysis. UPGMA dendogram and Bayesian structure analysis concomitantly clustered the 12 populations into eight genetic groups. The best core collection assembled by Core Hunter ver. 3.2.1 consisted of 58 palms accounting for 31.2% of the original population, which was a smaller core set than using PowerCore 1.0. This core set attained perfect allelic coverage with good representation, high genetic distance between entries, and maintained genetic diversity and structure of the germplasm. This study reported the first molecular characterization and validation of core collections for oil palm field genebank. The established core collection via molecular approach, which captures maximum genetic diversity with minimum redundancy, would allow effective use of genetic resources for introgression and for sustainable oil palm germplasm conservation. The way forward to efficiently conserve the field genebanks into next generation without losing their diversity was further discussed.

Matched MeSH terms: Bayes Theorem
Fulltext Detection of mumps virus of genotype g in Bangladeshi children suffering from encephalitis

Daisuke, Mori, Wahida Khanam, Kamruddin Ahmed

Borneo Journal of Medical Sciences, 2021;15(1):73-79.
MyJurnal

Although mumps virus (MuVi) is an important agent of encephalitis, however, mumps vaccine has not yet been included in the national immunization programme of Bangladesh. Furthermore, the genotype distribution of this virus in Bangladesh is unknown. Cerebrospinal fluid samples collected from 97 children with encephalitis from April 2009 to March 2010 were subjected to polymerase chain reaction (PCR) test to determine the causative agents. MuVi was detected in two samples, these samples were further subjected to conventional PCR using specific primers, then amplicons were sequenced, and genotype was determined as genotype G. Phylogenetic analysis showed that these strains were clustered with strains from Nepal, India, the UK, Thailand, and the USA. By Bayesian inference, we also determined that the ancestor of Bangladeshi and Indian MuVi were same and segregated only about two decades back. These results will help future surveillance and the detection of invading MuVi strains from other countries.

Matched MeSH terms: Bayes Theorem
Does the location of electrode on tympanic membrane matter when recording electrocochleography?

Zakaria MN, Nik Othman NA, Musa Z

Acta Otolaryngol, 2021 Nov;141(11):984-988.
PMID: 34669557 DOI: 10.1080/00016489.2021.1990996

BACKGROUND: The non-invasive tympanic electrocochleography (TM-ECochG) is useful for clinical diagnoses. Nevertheless, the influence of the electrode location on tympanic membrane (TM) on ECochG results needs to be studied.
OBJECTIVE: The aim of the present study was to compare the TM-ECochG results obtained when the electrode was placed on the superior region versus the inferior region of TM.
MATERIALS AND METHODS: Forty healthy adults (aged 29 to 50 years) participated in this comparative study. The TM-ECochG testing was conducted with the electrode placed on the superior and inferior regions of TM.
RESULTS: SP and AP amplitudes were statistically higher for the inferior region of TM (p < .05). In contrast, SP/AP ratios were comparable between the two regions of TM (p = .417).
CONCLUSIONS AND SIGNIFICANCE: In TM-ECochG recording, when the electrode was placed on the inferior region of TM, SP and AP amplitudes were greater than when the electrode was placed on the superior region of TM. On the other hand, SP/AP amplitude ratio was not affected by the location of electrode on TM. The findings from the present study could be useful to guide clinicians in optimizing TM-ECochG recording when testing their respective patients.

Matched MeSH terms: Bayes Theorem
Fulltext Population Genetic Structure of Ornate Threadfin Bream (Nemipterus hexodon) in Thailand

Supmee V, Songrak A, Suppapan J, Sangthong P

Trop Life Sci Res, 2021 Mar;32(1):63-82.
PMID: 33936551 DOI: 10.21315/tlsr2021.32.1.4

Ornate threadfin bream (Nemipterus hexodon) is an economically important fishery species in Southeast Asia. In Thailand, N. hexodon decreased dramatically due to overexploitation for commercial purposes. To construct an effective sustainable management plan, genetic information is necessary. Thus, in our study, the population genetic structure and demographic history of N. hexodon were investigated using 419 bp of the mitochondrial DNA sequence in cytochrome oxidase subunit I gene (mtDNA COI). A total of 142 samples was collected from nine localities in the Gulf of Thailand (Chonburi, Samut Songkhram, Surat Thani, Nakhon Si Thammarat, Songkhla), and the Andaman Sea (Satun, Trang, Krabi, Phang Nga). Fourteen polymorphic sites defined 18 haplotypes, revealing a high haplotype diversity and low nucleotide diversity among nine localities. The analysis of molecular variance (AMOVA) analysis, pairwise F
ST
, and minimum spanning network result revealed that the genetic structure of N. hexodon was separated into two populations: the Gulf of Thailand and the Andaman Sea population. The genetic structure of N. hexodon can be explained by a disruption of gene flow from the geographic barrier and the Pleistocene isolation of the marine basin hypothesis. Neutrality tests, Bayesian skyline analysis, mismatch distribution, and the estimated values of population growth suggested that N. hexodon had experienced a population expansion. The genetic information would certainly help us gain insight into the population genetic structure of N. hexodon living on the coast of Thailand.

Matched MeSH terms: Bayes Theorem
Fulltext Polygenic risk scores for prediction of breast cancer risk in Asian populations

Ho WK, Tai MC, Dennis J, Shu X, Li J, Ho PJ, et al.

Genet Med, 2022 Mar;24(3):586-600.
PMID: 34906514 DOI: 10.1016/j.gim.2021.11.008

PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.
METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

Matched MeSH terms: Bayes Theorem
Fulltext Phylogenetic relationships of Malaysia's long-tailed macaques, Macaca fascicularis, based on cytochrome b sequences

Abdul-Latiff MA, Ruslin F, Fui VV, Abu MH, Rovie-Ryan JJ, Abdul-Patah P, et al.

Zookeys, 2014.
PMID: 24899832 DOI: 10.3897/zookeys.407.6982

Phylogenetic relationships among Malaysia's long-tailed macaques have yet to be established, despite abundant genetic studies of the species worldwide. The aims of this study are to examine the phylogenetic relationships of Macaca fascicularis in Malaysia and to test its classification as a morphological subspecies. A total of 25 genetic samples of M. fascicularis yielding 383 bp of Cytochrome b (Cyt b) sequences were used in phylogenetic analysis along with one sample each of M. nemestrina and M. arctoides used as outgroups. Sequence character analysis reveals that Cyt b locus is a highly conserved region with only 23% parsimony informative character detected among ingroups. Further analysis indicates a clear separation between populations originating from different regions; the Malay Peninsula versus Borneo Insular, the East Coast versus West Coast of the Malay Peninsula, and the island versus mainland Malay Peninsula populations. Phylogenetic trees (NJ, MP and Bayesian) portray a consistent clustering paradigm as Borneo's population was distinguished from Peninsula's population (99% and 100% bootstrap value in NJ and MP respectively and 1.00 posterior probability in Bayesian trees). The East coast population was separated from other Peninsula populations (64% in NJ, 66% in MP and 0.53 posterior probability in Bayesian). West coast populations were divided into 2 clades: the North-South (47%/54% in NJ, 26/26% in MP and 1.00/0.80 posterior probability in Bayesian) and Island-Mainland (93% in NJ, 90% in MP and 1.00 posterior probability in Bayesian). The results confirm the previous morphological assignment of 2 subspecies, M. f. fascicularis and M. f. argentimembris, in the Malay Peninsula. These populations should be treated as separate genetic entities in order to conserve the genetic diversity of Malaysia's M. fascicularis. These findings are crucial in aiding the conservation management and translocation process of M. fascicularis populations in Malaysia.

Matched MeSH terms: Bayes Theorem
DNA-based characterisation and classification of forensically important flesh flies (Diptera: Sarcophagidae) in Malaysia

Tan SH, Rizman-Idid M, Mohd-Aris E, Kurahashi H, Mohamed Z

Forensic Sci Int, 2010 Jun 15;199(1-3):43-9.
PMID: 20392577 DOI: 10.1016/j.forsciint.2010.02.034

Insect larvae and adult insects found on human corpses provide important clues for the estimation of the postmortem interval (PMI). Among all necrophagous insects, flesh flies (Diptera: Sarcophagidae) are considered as carrion flies of forensic importance. DNA variations of 17 Malaysian, two Indonesian and one Japanese flesh fly species are analysed using the mitochondrial COI and COII. These two DNA regions were useful for identifying most species experimented. However, characterisation of the species was not sufficiently made in the case of Sarcophaga javanica. Seventeen Malaysian species of forensic importance were successfully clustered into distinct clades and grouped into the six species groups: peregrina, albiceps, dux, pattoni, princeps and ruficornis. These groups correspond with generic or subgeneric taxa of the subfamily Sarcophaginae: Boettcherisca, Parasarcophaga, Liosarcophaga, Sarcorohdendorfia-Lioproctia, Harpagophalla-Seniorwhitea and Liopygia. The genetic variations found in COI and COII can be applied not only to identify the species of forensic importance, but also to understand the taxonomic positions, generic or subgeneric status, of the sarcophagine species.

Matched MeSH terms: Bayes Theorem
Fulltext Genetic diversity and differentiation of the orange-spotted grouper (Epinephelus coioides) between and within cultured stocks and wild populations inferred from microsatellite DNA analysis

Wang L, Meng Z, Liu X, Zhang Y, Lin H

Int J Mol Sci, 2011;12(7):4378-94.
PMID: 21845084 DOI: 10.3390/ijms12074378

In the present study, we employed microsatellite DNA markers to analyze the genetic diversity and differentiation between and within cultured stocks and wild populations of the orange-spotted grouper originating from the South China Sea and Southeast Asia. Compared to wild populations, genetic changes including reduced genetic diversity and significant differentiation have taken place in cultured grouper stocks, as shown by allele richness and heterozygosity studies, pairwise F(st), structure, molecular variance analysis, as well as multidimensional scaling analysis. Although two geographically adjacent orange-spotted grouper populations in China showed negligible genetic divergence, significant population differentiation was observed in wild grouper populations distributed in a wide geographical area from China, through Malaysia to Indonesia. However, the Mantel test rejected the isolation-by-distance model of genetic structure, which indicated the genetic differentiation among the populations could result from the co-effects of various factors, such as historical dispersal, local environment, ocean currents, river flows and island blocks. Our results demonstrated that microsatellite markers could be suitable not only for genetic monitoring cultured stocks but also for revealing the population structuring of wild orange-spotted grouper populations. Meanwhile, our study provided important information for breeding programs, management of cultured stocks and conservation of wild populations of the orange-spotted grouper.

Matched MeSH terms: Bayes Theorem
Implementing relevance feedback in ligand-based virtual screening using Bayesian inference network

Abdo A, Salim N, Ahmed A

J Biomol Screen, 2011 Oct;16(9):1081-8.
PMID: 21862688 DOI: 10.1177/1087057111416658

Recently, the use of the Bayesian network as an alternative to existing tools for similarity-based virtual screening has received noticeable attention from researchers in the chemoinformatics field. The main aim of the Bayesian network model is to improve the retrieval effectiveness of similarity-based virtual screening. To this end, different models of the Bayesian network have been developed. In our previous works, the retrieval performance of the Bayesian network was observed to improve significantly when multiple reference structures or fragment weightings were used. In this article, the authors enhance the Bayesian inference network (BIN) using the relevance feedback information. In this approach, a few high-ranking structures of unknown activity were filtered from the outputs of BIN, based on a single active reference structure, to form a set of active reference structures. This set of active reference structures was used in two distinct techniques for carrying out such BIN searching: reweighting the fragments in the reference structures and group fusion techniques. Simulated virtual screening experiments with three MDL Drug Data Report data sets showed that the proposed techniques provide simple ways of enhancing the cost-effectiveness of ligand-based virtual screening searches, especially for higher diversity data sets.

Matched MeSH terms: Bayes Theorem
Phylogeny and phylogeography of Old World fruit bats in the Cynopterus brachyotis complex

Campbell P, Schneider CJ, Adnan AM, Zubaid A, Kunz TH

Mol Phylogenet Evol, 2004 Dec;33(3):764-81.
PMID: 15522802

Taxonomic relationships within the Old World fruit bat genus, Cynopterus, have been equivocal for the better part of a century. While nomenclature has been revised multiple times on the basis of phenotypic characters, evolutionary relationships among taxa representing the entire geographic range of the genus have not been determined. We used mitochondrial DNA sequence data to infer phylogenetic relationships among the three most broadly distributed members of the genus: C. brachyotis, C. horsfieldi, and C. sphinx, and to assess whether C. brachyotis represents a single widespread species, or a complex of distinct lineages. Results clearly indicate that C. brachyotis is a complex of lineages. C. sphinx and C. horsfieldi haplotypes formed monophyletic groups nested within the C. brachyotis species complex. We identified six divergent mitochondrial lineages that are currently referred to C. brachyotis. Lineages from India, Myanmar, Sulawesi, and the Philippines are geographically well-defined, while in Malaysia two lineages, designated Sunda and Forest, are broadly sympatric and may be ecologically distinct. Demographic analyses of the Sunda and Forest lineages suggest strikingly different population histories, including a recent and rapid range expansion in the Sunda lineage, possibly associated with changes in sea levels during the Pleistocene. The resolution of the taxonomic issues raised in this study awaits combined analysis of morphometric characters and molecular data. However, since both the Indian and Malaysian Forest C. brachyotis lineages are apparently ecologically restricted to increasingly fragmented forest habitat, we suggest that reevaluation of the conservation status of populations in these regions should be an immediate goal.

Matched MeSH terms: Bayes Theorem

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