Displaying publications 141 - 160 of 264 in total

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  1. Jeffrine J. Rovie-Ryan, Millawati Gani, Norsyamimi Rosli, Han Ming Gan, Gilmoore G. Bolongon, Tan Cheng Cheng, et al.
    Sains Malaysiana, 2018;47:2533-2542.
    Slow lorises (Nycticebus) consist of eight species native to Southeast Asia while three species are recognised in
    Malaysia - N. coucang, N. menagensis and N. kayan. This study reports on the rediscovery of the subspecies N. coucang
    insularis Robinson, 1917 in Tioman Island and the genetic assessment of its mitochondrial DNA variation. Morphological
    measurements conform the specimen as the putative N. coucang but with distinct colour and markings. Two mitochondrial
    DNA segments (cytochrome b and control region) were produced from the subspecies representing their first registered
    sequences in GenBank. Genetically, the subspecies showed 99% of nucleotide similarity to N. coucang species type for
    both the DNA segments and constitute its own unique haplotype. Phylogenetic trees constructed using three methods
    (neighbour joining, maximum likelihood and Bayesian inference) showed two major groups within Nycticebus; the
    basal group was formed by N. pygmaeus while the second group consisted of the remaining Nycticebus species. The
    phylogenetic position of the subspecies, however, remains unresolved due to the observed mixing between N. coucang and
    N. bengalensis. Several reasons could lead to this condition including the lack of well documented voucher specimens and
    the short DNA fragments used. In addition, the possibility of hybridisation event between N. coucang and N. bengalensis
    could not be excluded as a possible explanation since both species occur sympatrically at the Isthmus of Kra region
    until the Thailand-Malaysia border. The rediscovery of this subspecies displays the unique faunal diversity that justifies
    the importance of Tioman Island as a protected area.
    Matched MeSH terms: Bayes Theorem
  2. Alsalem MA, Zaidan AA, Zaidan BB, Albahri OS, Alamoodi AH, Albahri AS, et al.
    J Med Syst, 2019 Jun 01;43(7):212.
    PMID: 31154550 DOI: 10.1007/s10916-019-1338-x
    This paper aims to assist the administration departments of medical organisations in making the right decision on selecting a suitable multiclass classification model for acute leukaemia. In this paper, we proposed a framework that will aid these departments in evaluating, benchmarking and ranking available multiclass classification models for the selection of the best one. Medical organisations have continuously faced evaluation and benchmarking challenges in such endeavour, especially when no single model is superior. Moreover, the improper selection of multiclass classification for acute leukaemia model may be costly for medical organisations. For example, when a patient dies, one such organisation will be legally or financially sued for incidents in which the model fails to fulfil its desired outcome. With regard to evaluation and benchmarking, multiclass classification models are challenging processes due to multiple evaluation and conflicting criteria. This study structured a decision matrix (DM) based on the crossover of 2 groups of multi-evaluation criteria and 22 multiclass classification models. The matrix was then evaluated with datasets comprising 72 samples of acute leukaemia, which include 5327 gens. Subsequently, multi-criteria decision-making (MCDM) techniques are used in the benchmarking and ranking of multiclass classification models. The MCDM used techniques that include the integrated BWM and VIKOR. BWM has been applied for the weight calculations of evaluation criteria, whereas VIKOR has been used to benchmark and rank classification models. VIKOR has also been employed in two decision-making contexts: individual and group decision making and internal and external group aggregation. Results showed the following: (1) the integration of BWM and VIKOR is effective at solving the benchmarking/selection problems of multiclass classification models. (2) The ranks of classification models obtained from internal and external VIKOR group decision making were almost the same, and the best multiclass classification model based on the two was 'Bayes. Naive Byes Updateable' and the worst one was 'Trees.LMT'. (3) Among the scores of groups in the objective validation, significant differences were identified, which indicated that the ranking results of internal and external VIKOR group decision making were valid.
    Matched MeSH terms: Bayes Theorem
  3. Nurul Ashikeen Ab Razak, Mustafa Abdul Rahman, Tuen AA
    Sains Malaysiana, 2016;45:1089-1095.
    Family Scolopacidae includes the sandpipers, shanks, snipes, godwits and curlews. Systematic classifications of shorebirds
    at the higher level have been successfully resolved. Nevertheless, the phylogeny of shorebirds in the familial level is still
    poorly understood. Thus, this phylogenetic study on Scolopacidae was conducted upon the framework provided by the first
    sequence-based species-level phylogeny within the shorebirds to determine the phylogenetic relationships among family
    members of Scolopacidae in West Borneo, Sarawak using combined gene markers, mtDNA Cytochrome Oxidise I (COI)
    and nucDNA Recombinant Activating Gene 1 (RAG1). A total of 1,342 base pair (bp) were inferred from both COI and RAG1
    gene from 45 sequences constituted of 15 species Scolopacidae sampled from Sarawak namely Xenus cinereus, Actitis
    hypoleucos, Tringa totanus, Tringa glareola, Tringa stagnatilis, Heteroscelus brevipes, Calidris alba, Calidris ruficollis,
    Calidris ferruginea, Calidris tenuirostris, Calidris alpina, Gallinago stenura, Gallinago megala, Numenius arquata, and
    Numenius phaeopus. The phylogenetic tree was constructed with Charadrius mongulus derived as an outgroup. The
    Bayesian Inference (BI) tree constructed supported grouping of species into several lineages of Numeniinae, Calidrinae,
    Scolopacinae and Tringinae. The groupings of species into several lineages correlate with morphological features that
    contribute to their adaptation and ability of the species to fit to their ecosystems.
    Matched MeSH terms: Bayes Theorem
  4. Walters K, Cox A, Yaacob H
    Genet Epidemiol, 2019 Sep;43(6):675-689.
    PMID: 31286571 DOI: 10.1002/gepi.22212
    The default causal single-nucleotide polymorphism (SNP) effect size prior in Bayesian fine-mapping studies is usually the Normal distribution. This choice is often based on computational convenience, rather than evidence that it is the most suitable prior distribution. The choice of prior is important because previous studies have shown considerable sensitivity of causal SNP Bayes factors to the form of the prior. In some well-studied diseases there are now considerable numbers of genome-wide association study (GWAS) top hits along with estimates of the number of yet-to-be-discovered causal SNPs. We show how the effect sizes of the top hits and estimates of the number of yet-to-be-discovered causal SNPs can be used to choose between the Laplace and Normal priors, to estimate the prior parameters and to quantify the uncertainty in this estimation. The methodology can readily be applied to other priors. We show that the top hits available from breast cancer GWAS provide overwhelming support for the Laplace over the Normal prior, which has important consequences for variant prioritisation. This work in this paper enables practitioners to derive more objective priors than are currently being used and could lead to prioritisation of different variants.
    Matched MeSH terms: Bayes Theorem
  5. Lim ZX, Hitch AT, Lee BPY, Low DHW, Neves ES, Borthwick SA, et al.
    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
  6. Dunn M, Kruspe N, Burenhult N
    Hum Biol, 2013 Feb-Jun;85(1-3):383-400.
    PMID: 24297234
    The Aslian language family, located in the Malay Peninsula and southern Thai Isthmus, consists of four distinct branches comprising some 18 languages. These languages predate the now dominant Malay and Thai. The speakers of Aslian languages exhibit some of the highest degree of phylogenetic and societal diversity present in Mainland Southeast Asia today, among them a foraging tradition particularly associated with locally ancient, Pleistocene genetic lineages. Little advance has been made in our understanding of the linguistic prehistory of this region or how such complexity arose. In this article we present a Bayesian phylogeographic analysis of a large sample of Aslian languages. An explicit geographic model of diffusion is combined with a cognate birth-word death model of lexical evolution to infer the location of the major events of Aslian cladogenesis. The resultant phylogenetic trees are calibrated against dates in the historical and archaeological record to infer a detailed picture of Aslian language history, addressing a number of outstanding questions, including (1) whether the root ancestor of Aslian was spoken in the Malay Peninsula, or whether the family had already divided before entry, and (2) the dynamics of the movement of Aslian languages across the peninsula, with a particular focus on its spread to the indigenous foragers.
    Matched MeSH terms: Bayes Theorem
  7. 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
  8. Phung CC, Heng PS, Liew TS
    PeerJ, 2017;5:e3981.
    PMID: 29104827 DOI: 10.7717/peerj.3981
    Leptopoma is a species rich genus with approximately 100 species documented. Species-level identification in this group has been based on shell morphology and colouration, as well as some anatomical features based on small sample sizes. However, the implications of the inter- and intra-species variations in shell form to the taxonomy of Leptopoma species and the congruency of its current shell based taxonomy with its molecular phylogeny are still unclear. There are four Leptopoma species found in Sabah, Borneo, and their taxonomy status remains uncertain due to substantial variation in shell forms. This study focuses on the phylogenetic relationships and geographical variation in shell form of three Leptopoma species from Sabah. The phylogenetic relationship of these species was first estimated by performing Maximum Likelihood and Bayesian analysis based on mitochondrial genes (16S rDNA and COI) and nuclear gene (ITS-1). Then, a total of six quantitative shell characters (i.e., shell height, shell width, aperture height, aperture width, shell spire height, and ratio of shell height to width) and three qualitative shell characters (i.e., shell colour patterns, spiral ridges, and dark apertural band) of the specimens were mapped across the phylogenetic tree and tested for phylogenetic signals. Data on shell characters of Leptopoma sericatum and Leptopoma pellucidum from two different locations (i.e., Balambangan Island and Kinabatangan) where both species occurred sympatrically were then obtained to examine the geographical variations in shell form. The molecular phylogenetic analyses suggested that each of the three Leptopoma species was monophyletic and indicated congruence with only one of the shell characters (i.e., shell spiral ridges) in the current morphological-based classification. Although the geographical variation analyses suggested some of the shell characters indicating inter-species differences between the two Leptopoma species, these also pointed to intra-species differences between populations from different locations. This study on Leptopoma species is based on small sample size and the findings appear only applicable to Leptopoma species in Sabah. Nevertheless, we anticipate this study to be a starting point for more detailed investigations to include the other still little-known (ca. 100) Leptopoma species and highlights a need to assess variations in shell characters before they could be used in species classification.
    Matched MeSH terms: Bayes Theorem
  9. Al-Fakih AM, Algamal ZY, Lee MH, Aziz M
    SAR QSAR Environ Res, 2018 May;29(5):339-353.
    PMID: 29493376 DOI: 10.1080/1062936X.2018.1439531
    A penalized quantitative structure-property relationship (QSPR) model with adaptive bridge penalty for predicting the melting points of 92 energetic carbocyclic nitroaromatic compounds is proposed. To ensure the consistency of the descriptor selection of the proposed penalized adaptive bridge (PBridge), we proposed a ridge estimator ([Formula: see text]) as an initial weight in the adaptive bridge penalty. The Bayesian information criterion was applied to ensure the accurate selection of the tuning parameter ([Formula: see text]). The PBridge based model was internally and externally validated based on [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], the Y-randomization test, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and the applicability domain. The validation results indicate that the model is robust and not due to chance correlation. The descriptor selection and prediction performance of PBridge for the training dataset outperforms the other methods used. PBridge shows the highest [Formula: see text] of 0.959, [Formula: see text] of 0.953, [Formula: see text] of 0.949 and [Formula: see text] of 0.959, and the lowest [Formula: see text] and [Formula: see text]. For the test dataset, PBridge shows a higher [Formula: see text] of 0.945 and [Formula: see text] of 0.948, and a lower [Formula: see text] and [Formula: see text], indicating its better prediction performance. The results clearly reveal that the proposed PBridge is useful for constructing reliable and robust QSPRs for predicting melting points prior to synthesizing new organic compounds.
    Matched MeSH terms: Bayes Theorem
  10. Khoo HL, Ahmed M
    Accid Anal Prev, 2018 Apr;113:106-116.
    PMID: 29407657 DOI: 10.1016/j.aap.2018.01.025
    This study had developed a passenger safety perception model specifically for buses taking into consideration the various factors, namely driver characteristics, environmental conditions, and bus characteristics using Bayesian Network. The behaviour of bus driver is observed through the bus motion profile, measured in longitudinal, lateral, and vertical accelerations. The road geometry is recorded using GPS and is computed with the aid of the Google map while the perceived bus safety is rated by the passengers in the bus in real time. A total of 13 variables were derived and used in the model development. The developed Bayesian Network model shows that the type of bus and the experience of the driver on the investigated route could have an influence on passenger's perception of their safety on buses. Road geometry is an indirect influencing factor through the driver's behavior. The findings of this model are useful for the authorities to structure an effective strategy to improve the level of perceived bus safety. A high level of bus safety will definitely boost passenger usage confidence which will subsequently increase ridership.
    Matched MeSH terms: Bayes Theorem
  11. Soo TCC, Bhassu S
    PLoS One, 2023;18(1):e0280250.
    PMID: 36634148 DOI: 10.1371/journal.pone.0280250
    In recent years, shrimp aquaculture industry had grown significantly to become the major source of global shrimp production. Despite that, shrimp aquaculture production was impeded by various shrimp diseases over the past decades. Interestingly, different shrimp species demonstrated variable levels of immune strength and survival (immune-survival) ability towards different diseases, especially the much stronger immune-survival ability shown by the ancient shrimp species, Macrobrachium rosenbergii compared to other shrimp species. In this study, two important shrimp species, M. rosenbergii and Penaeus monodon (disease tolerant strain) (uninfected control and VpAHPND-infected) were compared to uncover the potential underlying genetic factors. The shrimp species were sampled, followed by RNA extraction and cDNA conversion. Five important immune-survival genes (C-type Lectin, HMGB, STAT, ALF3, and ATPase 8/6) were selected for PCR, sequencing, and subsequent genetics analysis. The overall genetic analyses conducted, including Analysis of Molecular Variance (AMOVA) and population differentiation, showed significant genetic differentiation (p<0.05) between different genes of M. rosenbergii and P. monodon. There was greater genetic divergence identified between HMGB subgroups of P. monodon (uninfected control and VpAHPND-infected) compared to other genes. Besides that, based on neutrality tests conducted, purifying selection was determined to be the main evolutionary driving force of M. rosenbergii and P. monodon with stronger purifying selection exhibited in M. rosenbergii genes. Potential balancing selection was identified for VpAHPND-infected HMGB subgroup whereas directional selection was detected for HMGB (both species) and ATPase 8/6 (only P. monodon) genes. The divergence times between M. rosenbergii and P. monodon genes were estimated through Bayesian molecular clock analysis, which were 438.6 mya (C-type Lectin), 1885.4 mya (HMGB), 432.6 mya (STAT), 448.1 mya (ALF3), and 426.4 mya (ATPase 8/6) respectively. In conclusion, important selection forces and evolutionary divergence information of immune-survival genes between M. rosenbergii and P. monodon were successfully identified.
    Matched MeSH terms: Bayes Theorem
  12. Haque F, Reaz MBI, Chowdhury MEH, Ezeddin M, Kiranyaz S, Alhatou M, et al.
    Sensors (Basel), 2022 May 05;22(9).
    PMID: 35591196 DOI: 10.3390/s22093507
    Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is one of the pervasive types of complications that arise due to DN. In the literature, for the last 50 years, researchers have been trying to observe the biomechanical changes due to DN and DFU by studying muscle electromyography (EMG) and ground reaction forces (GRF). However, the literature is contradictory. In such a scenario, we propose using Machine learning techniques to identify DN and DFU patients by using EMG and GRF data. We collected a dataset from the literature which involves three patient groups: Control (n = 6), DN (n = 6), and previous history of DFU (n = 9) and collected three lower limb muscles EMG (tibialis anterior (TA), vastus lateralis (VL), gastrocnemius lateralis (GL)), and three GRF components (GRFx, GRFy, and GRFz). Raw EMG and GRF signals were preprocessed, and different feature extraction techniques were applied to extract the best features from the signals. The extracted feature list was ranked using four different feature ranking techniques, and highly correlated features were removed. In this study, we considered different combinations of muscles and GRF components to find the best performing feature list for the identification of DN and DFU. We trained eight different conventional ML models: Discriminant analysis classifier (DAC), Ensemble classification model (ECM), Kernel classification model (KCM), k-nearest neighbor model (KNN), Linear classification model (LCM), Naive Bayes classifier (NBC), Support vector machine classifier (SVM), and Binary decision classification tree (BDC), to find the best-performing algorithm and optimized that model. We trained the optimized the ML algorithm for different combinations of muscles and GRF component features, and the performance matrix was evaluated. Our study found the KNN algorithm performed well in identifying DN and DFU, and we optimized it before training. We found the best accuracy of 96.18% for EMG analysis using the top 22 features from the chi-square feature ranking technique for features from GL and VL muscles combined. In the GRF analysis, the model showed 98.68% accuracy using the top 7 features from the Feature selection using neighborhood component analysis for the feature combinations from the GRFx-GRFz signal. In conclusion, our study has shown a potential solution for ML application in DN and DFU patient identification using EMG and GRF parameters. With careful signal preprocessing with strategic feature extraction from the biomechanical parameters, optimization of the ML model can provide a potential solution in the diagnosis and stratification of DN and DFU patients from the EMG and GRF signals.
    Matched MeSH terms: Bayes Theorem
  13. 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
  14. T Thurai Rathnam J, Grigg MJ, Dini S, William T, Sakam SS, Cooper DJ, et al.
    Malar J, 2023 Feb 14;22(1):54.
    PMID: 36782162 DOI: 10.1186/s12936-023-04483-9
    BACKGROUND: The incidence of zoonotic Plasmodium knowlesi infections in humans is rising in Southeast Asia, leading to clinical studies to monitor the efficacy of anti-malarial treatments for knowlesi malaria. One of the key outcomes of anti-malarial drug efficacy is parasite clearance. For Plasmodium falciparum, parasite clearance is typically estimated using a two-stage method, that involves estimating parasite clearance for individual patients followed by pooling of individual estimates to derive population estimates. An alternative approach is Bayesian hierarchical modelling which simultaneously analyses all parasite-time patient profiles to determine parasite clearance. This study compared these methods for estimating parasite clearance in P. knowlesi treatment efficacy studies, with typically fewer parasite measurements per patient due to high susceptibility to anti-malarials.

    METHODS: Using parasite clearance data from 714 patients with knowlesi malaria and enrolled in three trials, the Worldwide Antimalarial Resistance Network (WWARN) Parasite Clearance Estimator (PCE) standard two-stage approach and Bayesian hierarchical modelling were compared. Both methods estimate the parasite clearance rate from a model that incorporates a lag phase, slope, and tail phase for the parasitaemia profiles.

    RESULTS: The standard two-stage approach successfully estimated the parasite clearance rate for 678 patients, with 36 (5%) patients excluded due to an insufficient number of available parasitaemia measurements. The Bayesian hierarchical estimation method was applied to the parasitaemia data of all 714 patients. Overall, the Bayesian method estimated a faster population mean parasite clearance (0.36/h, 95% credible interval [0.18, 0.65]) compared to the standard two-stage method (0.26/h, 95% confidence interval [0.11, 0.46]), with better model fits (compared visually). Artemisinin-based combination therapy (ACT) is more effective in treating P. knowlesi than chloroquine, as confirmed by both methods, with a mean estimated parasite clearance half-life of 2.5 and 3.6 h, respectively using the standard two-stage method, and 1.8 and 2.9 h using the Bayesian method.

    CONCLUSION: For clinical studies of P. knowlesi with frequent parasite measurements, the standard two-stage approach (WWARN's PCE) is recommended as this method is straightforward to implement. For studies with fewer parasite measurements per patient, the Bayesian approach should be considered. Regardless of method used, ACT is more efficacious than chloroquine, confirming the findings of the original trials.

    Matched MeSH terms: Bayes Theorem
  15. Mohamad MS, Abdul Maulud KN, Faes C
    Int J Health Geogr, 2023 Jun 21;22(1):14.
    PMID: 37344913 DOI: 10.1186/s12942-023-00336-5
    BACKGROUND: National prevalence could mask subnational heterogeneity in disease occurrence, and disease mapping is an important tool to illustrate the spatial pattern of disease. However, there is limited information on techniques for the specification of conditional autoregressive models in disease mapping involving disconnected regions. This study explores available techniques for producing district-level prevalence estimates for disconnected regions, using as an example childhood overweight in Malaysia, which consists of the Peninsular and Borneo regions separated by the South China Sea. We used data from Malaysia National Health and Morbidity Survey conducted in 2015. We adopted Bayesian hierarchical modelling using the integrated nested Laplace approximation (INLA) program in R-software to model the spatial distribution of overweight among 6301 children aged 5-17 years across 144 districts located in two disconnected regions. We illustrate different types of spatial models for prevalence mapping across disconnected regions, taking into account the survey design and adjusting for district-level demographic and socioeconomic covariates.

    RESULTS: The spatial model with split random effects and a common intercept has the lowest Deviance and Watanabe Information Criteria. There was evidence of a spatial pattern in the prevalence of childhood overweight across districts. An increasing trend in smoothed prevalence of overweight was observed when moving from the east to the west of the Peninsular and Borneo regions. The proportion of Bumiputera ethnicity in the district had a significant negative association with childhood overweight: the higher the proportion of Bumiputera ethnicity in the district, the lower the prevalence of childhood overweight.

    CONCLUSION: This study illustrates different available techniques for mapping prevalence across districts in disconnected regions using survey data. These techniques can be utilized to produce reliable subnational estimates for any areas that comprise of disconnected regions. Through the example, we learned that the best-fit model was the one that considered the separate variations of the individual regions. We discovered that the occurrence of childhood overweight in Malaysia followed a spatial pattern with an east-west gradient trend, and we identified districts with high prevalence of overweight. This information could help policy makers in making informed decisions for targeted public health interventions in high-risk areas.

    Matched MeSH terms: Bayes Theorem
  16. Abuelmaali SA, Mashlawi AM, Ishak IH, Wajidi MFF, Jaal Z, Avicor SW, et al.
    Sci Rep, 2024 Feb 05;14(1):2978.
    PMID: 38316804 DOI: 10.1038/s41598-024-52591-6
    Although knowledge of the composition and genetic diversity of disease vectors is important for their management, this is limiting in many instances. In this study, the population structure and phylogenetic relationship of the two Aedes aegypti subspecies namely Aedes aegypti aegypti (Aaa) and Aedes aegypti formosus (Aaf) in eight geographical areas in Sudan were analyzed using seven microsatellite markers. Hardy-Weinberg Equilibrium (HWE) for the two subspecies revealed that Aaa deviated from HWE among the seven microsatellite loci, while Aaf exhibited departure in five loci and no departure in two loci (A10 and M201). The Factorial Correspondence Analysis (FCA) plots revealed that the Aaa populations from Port Sudan, Tokar, and Kassala clustered together (which is consistent with the unrooted phylogenetic tree), Aaf from Fasher and Nyala populations clustered together, and Gezira, Kadugli, and Junaynah populations also clustered together. The Bayesian cluster analysis structured the populations into two groups suggesting two genetically distinct groups (subspecies). Isolation by distance test revealed a moderate to strong significant correlation between geographical distance and genetic variations (p = 0.003, r = 0.391). The migration network created using divMigrate demonstrated that migration and gene exchange between subspecies populations appear to occur based on their geographical proximity. The genetic structure of the Ae. aegypti subspecies population and the gene flow among them, which may be interpreted as the mosquito vector's capacity for dispersal, were revealed in this study. These findings will help in the improvement of dengue epidemiology research including information on the identity of the target vector/subspecies and the arboviruses vector surveillance program.
    Matched MeSH terms: Bayes Theorem
  17. Heuts S, de Heer P, Gabrio A, Bels JLM, Lee ZY, Stoppe C, et al.
    Clin Nutr ESPEN, 2024 Feb;59:162-170.
    PMID: 38220371 DOI: 10.1016/j.clnesp.2023.10.040
    BACKGROUND: The PRECISe trial is a pragmatic, multicenter randomized controlled trial that evaluates the effect of high versus standard enteral protein provision on functional recovery in adult, mechanically ventilated critically ill patients. The current protocol presents the rationale and analysis plan for an evaluation of the primary and secondary outcomes under the Bayesian framework, with an emphasis on clinically important effect sizes.

    METHODS: This protocol was drafted in agreement with the ROBUST-statement, and is submitted for publication before database lock and primary data analysis. The primary outcome is health-related quality of life as measured by the EQ-5D-5L health utility score and is longitudinally assessed. Secondary outcomes comprise the 6-min walking test and handgrip strength over the entire follow-up period (longitudinal analyses), and 60-day mortality, duration of mechanical ventilation, and EQ-5D-5L health utility scores at 30, 90 and 180 days (cross-sectional). All analyses will primarily be performed under weakly informative priors. When available, informative priors elicited from contemporary literature will also be incorporated under alternative scenarios. In all other cases, objectively formulated skeptical and enthusiastic priors will be defined to assess the robustness of our results. Relevant identified subgroups were: patients with acute kidney injury, severe multi-organ failure and patients with or without sepsis. Results will be presented as absolute risk differences, mean differences, and odds ratios, with accompanying 95% credible intervals. Posterior probabilities will be estimated for clinically important benefit and harm.

    DISCUSSION: The proposed secondary, pre-planned Bayesian analysis of the PRECISe trial will provide additional information on the effects of high protein on functional and clinical outcomes in critically ill patients, such as probabilistic interpretation, probabilities of clinically important effect sizes, and the integration of prior evidence. As such, it will complement the interpretation of the primary outcome as well as several secondary and subgroup analyses.

    Matched MeSH terms: Bayes Theorem
  18. GBD 2021 Diabetes Collaborators
    Lancet, 2023 Jul 15;402(10397):203-234.
    PMID: 37356446 DOI: 10.1016/S0140-6736(23)01301-6
    BACKGROUND: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050.

    METHODS: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively.

    FINDINGS: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.

    INTERPRETATION: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.

    FUNDING: Bill & Melinda Gates Foundation.

    Matched MeSH terms: Bayes Theorem
  19. Chan KO, Grismer LL
    BMC Evol. Biol., 2019 04 25;19(1):95.
    PMID: 31023232 DOI: 10.1186/s12862-019-1422-3
    BACKGROUND: Recent studies have demonstrated that Bayesian species delimitation based on the multispecies coalescent model can produce inaccurate results by misinterpreting population splits as species divergences. An approach based on the genealogical divergence index (gdi) was shown to be a viable alternative, especially for delimiting allopatric populations where gene flow is low. We implemented these analyses to assess species boundaries in Southeast Asian toads, a group that is understudied and characterized by numerous unresolved species complexes.

    RESULTS: Multilocus phylogenetic analyses showed that deep evolutionary relationships including the genera Sigalegalephrynus, Ghatophryne, Parapelophryne, Leptophryne, Pseudobufo, Rentapia, and Phrynoides remain unresolved. Comparison of genetic divergences revealed that intraspecific divergences among allopatric populations of Pelophyrne signata (Borneo vs. Peninsular Malaysia), Ingerophrynus parvus (Peninsular Malaysia vs. Myanmar), and Leptophryne borbonica (Peninsular Malaysia, Java, Borneo, and Sumatra) are consistent with interspecific divergences of other Southeast Asian bufonid taxa. Conversely, interspecific divergences between Pelophryne guentheri/P. api, Ansonia latiffi/A. leptopus, and I. gollum/I. divergens were low (

    Matched MeSH terms: Bayes Theorem
  20. 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
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