Gametophyte life-history dominance of Chondrus crispus (Gigartinaceae, Rhodophyta) along the Atlantic coast of Nova Scotia, Canada

Mclachlan, Jack L.,Blanchard, Wade,Field, Christopher,Lewis, Nancy I. The Korean Society of Phycology 2011 ALGAE Vol.26 No.1

Similar to other species of Gigartinaceae Chondrus crispus has an alternation of perennial, isomorphic gametophytic and sporophytic generations. As these two generations co-exist independently within populations and obtain their resources in a similar manner, intraspecific competition is expected. In populations within the southern Gulf of St. Lawrence, fronds of both generations of C. crispus occur in similar numbers. This equivalency can be related to substratum instability, where the population is dynamic with a high turn-over rate of genets. These observations support a stochastic hypothesis to account for distribution of gametophytes and sporophytes in this area. Along the Atlantic coast of Nova Scotia, where the substratum is stable, gametophytes are overwhelmingly predominant. Gametophytic predominance is greatest in the lower littoral zone where C. crispus is abundant and space is limited. Under the fucoid canopy where "free-space" exists, the gametophyte to sporophyte ratio is lower. Gametophytic and sporophytic fronds are distributed equally among different size-classes and size-distribution is not considered a competitive factor. Previous studies have shown that sporophytic fronds of C. crispus are more susceptible to infections by endophytic algae and other pathogens, and are more heavily grazed by herbivores than are gametophytic fronds. Thus, mechanistic factors are strongly implied in the selection of gametophytes in the Atlantic population.

The angiotensin-converting enzyme 2 (ACE2) receptor in the prevention and treatment of COVID-19 are distinctly different paradigms

McLachlan Craig Steven 대한고혈압학회 2020 Clinical Hypertension Vol.26 No.4

There is current debate concerning the use of angiotensin-converting enzyme (ACE) inhibitors or angiotensin II type 1 receptor blockers (ARBs), for hypertension management, during COVID-19 infection. Specifically, the suggestion has been made that ACE inhibitors or ARBs could theoretically contribute to infection via increasing ACE2 receptor expression and hence increase viral load. The ACE2 receptor is responsible for binding the SAR-CoV2 viral spike and causing COVID-19 infection. What makes the argument somewhat obtuse for ACE inhibitors or ARBs is that ACE2 receptor expression can be increased by compounds that activate or increase the expression of SIRT1. Henceforth common dietary interventions, vitamins and nutrients may directly or indirectly influence the cellular expression of the ACE2 receptor. There are many common compounds that can increase the expression of the ACE2 receptor including Vitamin C, Metformin, Resveratrol, Vitamin B3 and Vitamin D. It is important to acknowledge that down-regulation or blocking the cellular ACE2 receptor will likely be pro-inflammatory and may contribute to end organ pathology and mortality in COVID-19. In conclusion from the perspective of the ACE2 receptor, COVID-19 prevention and treatment are distinctly different. This letter reflects on this current debate and suggests angiotensin-converting enzyme inhibitors and ARBs are likely beneficial during COVID-19 infection for hypertensive and normotensive patients.

Gametophyte life-history dominance of Chondrus crispus (Gigartinaceae, Rhodophyta) along the Atlantic coast of Nova Scotia, Canada

Jack L. McLachlan,Wade Blanchard,Christopher Field,Nancy I. Lewis 한국조류학회I 2011 ALGAE Vol.26 No.1

Similar to other species of Gigartinaceae Chondrus crispus has an alternation of perennial, isomorphic gametophytic and sporophytic generations. As these two generations co-exist independently within populations and obtain their resources in a similar manner, intraspecific competition is expected. In populations within the southern Gulf of St. Lawrence, fronds of both generations of C. crispus occur in similar numbers. This equivalency can be related to substratum instability, where the population is dynamic with a high turn-over rate of genets. These observations support a stochastic hypothesis to account for distribution of gametophytes and sporophytes in this area. Along the Atlantic coast of Nova Scotia, where the substratum is stable, gametophytes are overwhelmingly predominant. Gametophytic predominance is greatest in the lower littoral zone where C. crispus is abundant and space is limited. Under the fucoid canopy where “free-space” exists, the gametophyte to sporophyte ratio is lower. Gametophytic and sporophytic fronds are distributed equally among different size-classes and size-distribution is not considered a competitive factor. Previous studies have shown that sporophytic fronds of C. crispus are more susceptible to infections by endophytic algae and other pathogens,and are more heavily grazed by herbivores than are gametophytic fronds. Thus, mechanistic factors are strongly implied in the selection of gametophytes in the Atlantic population.

Mixtures of common t-factor analyzers for clustering high-dimensional microarray data

Baek, J.,McLachlan, G. J. Oxford University Press 2011 Bioinformatics Vol.27 No.9

Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data

Jangsun Baek,McLachlan, Geoffrey J,Flack, Lloyd K IEEE 2010 IEEE transactions on pattern analysis and machine Vol.32 No.7

<P>Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data, where the number of observations n is not very large relative to their dimension p. In practice, there is often the need to further reduce the number of parameters in the specification of the component-covariance matrices. To this end, we propose the use of common component-factor loadings, which considerably reduces further the number of parameters. Moreover, it allows the data to be displayed in low--dimensional plots.</P>

A spatial heterogeneity mixed model with skew-elliptical distributions

Farzammehr, Mohadeseh Alsadat,McLachlan, Geoffrey J. The Korean Statistical Society 2022 Communications for statistical applications and me Vol.29 No.3

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model

Baek, Jangsun,Son, Young Sook,McLachlan, Geoffrey J. Oxford University Press 2007 Bioinformatics Vol.23 No.4

<P><B>Motivation:</B> We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate <I>t</I> distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this <I>t</I> distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between <I>R</I> and <I>G</I> foreground intensities. This gamma-<I>t</I> mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership.</P><P>The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or <I>t</I> distributions; (4) the use of the bivariate <I>t</I> distribution for the foreground intensity provides a model that is less sensitive to extreme observations; (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts.</P><P><B>Results:</B> We apply our method for gridding, segmentation and estimation to cDNA microarray real images and artificial data. Our method provides better segmentation results in spot shapes as well as intensity estimation than Spot and spotSegmentation R language softwares. It detected blank spots as well as bright artifact for the real data, and estimated spot intensities with high-accuracy for the synthetic data.</P><P><B>Availability:</B> The algorithms were implemented in Matlab. The Matlab codes implementing both the gridding and segmentation/estimation are available upon request.</P><P><B>Contact:</B> jbaek@chonnam.ac.kr</P><P><B>Supplementary information:</B> Supplementary material is available at <I>Bioinformatics</I> online.</P>

Order selection with confidence for finite mixture models

Nguyen Hien D.,Fryer Daniel,McLachlan Geoffrey J. 한국통계학회 2023 Journal of the Korean Statistical Society Vol.52 No.1

The determination of the number of mixture components (the order) of a finite mixture model has been an enduring problem in statistical inference. We prove that the closed testing principle leads to a sequential testing procedure (STP) that allows for confidence statements to be made regarding the order of a finite mixture model. We construct finite sample tests, via data splitting and data swapping, for use in the STP, and we prove that such tests are consistent against fixed alternatives. Simulation studies and real data examples are used to demonstrate the performance of the finite sample tests-based STP, yielding practical recommendations of their use as confidence estimators in combination with point estimates such as the Akaike information or Bayesian information criteria. In addition, we demonstrate that a modification of the STP yields a method that consistently selects the order of a finite mixture model, in the asymptotic sense. Our STP is not only applicable for order selection of finite mixture models, but is also useful for making confidence statements regarding any sequence of nested models.

Relationship Between ACE Insertion/Deletion Genotype, Telomere Length and Diabetes Mellitus Type Ii

( Yu Ling Zhou ),( Ya Xin Lu ),( Herbert Jelinek ),( Hassan Assareh ),( Craig S Mclachlan ),( Brett D Hambly ) 대한내과학회 2014 대한내과학회 추계학술대회 Vol.2014 No.1

Background: Telomere length has been used as a surrogate biomarker for biological aging. Chronic diseases, i.e. Type 2 Diabetes mellitus (DMT2), resulting in infl ammation have been reported to shorten telomere length. The deletion allele of the angiotensin- converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism has been associated with infl ammation and susceptibility and severity of DMT2. We aimed to examine the interactions of ACE I/D genotype and DMT2 on telomere length. Methods: A total of 195 healthy controls and 80 patients with DMT2 were recruited from the Charles Sturt University Diabetes Screening Research Initiative in Australia. We measured leukocyte telomere length (LTL) by monochrome multiplex quantitative PCR and genotyped ACE I/D polymorphism by PCR and electrophoresis. Multivariate linear regression was used to determine the relationship between telomere length and ACE I/D genotype, covariates controlled for diabetic status. Results: Total population data demonstrated ACE DD or ID genotype carriers have longer mean LTL (1.091 and 1.095, respectively) than II genotype carriers (1.063, P=0.036). When stratifi ed on the basis of diabetes or no diabetes, a signifi cant increase in LTL was maintained in control subjects, but not in the DMT2 subjects. In control subjects, mean relative LTL for DD plus ID carriers is 1.090 and II carriers is 1.043 (P=0.009). In DMT2 patients, the mean relative LTL of samples carrying at least one D allele is 1.089 and II genotype carriers is 1.083 (P=0.868). In control but not DMT2 patients, female gender is associated with longer relative LTL (1.103, P=0.010). Conclusions: The II genotype is associated with shorter telomere length in a control population, but this association is lost in DMT2 patients. These findings support a hypothesis that ACE DD or ID genotype increases telomere length but that diabetes mellitus status alters this effect.

p-Doping of organic hole transport layers in p-i-n perovskite solar cells: correlating open-circuit voltage and photoluminescence quenching

Du, Tian,Xu, Weidong,Daboczi, Matyas,Kim, Jinhyun,Xu, Shengda,Lin, Chieh-Ting,Kang, Hongkyu,Lee, Kwanghee,Heeney, Martin J.,Kim, Ji-Seon,Durrant, James R.,McLachlan, Martyn A. The Royal Society of Chemistry 2019 Journal of Materials Chemistry A Vol.7 No.32

<P>Doping is a widely implemented strategy for enhancing the inherent electronic properties of charge transport layers in photovoltaic (PV) devices. Here, in direct contrast to existing understanding, we find that a reduction in p-doping of the organic hole transport layer (HTL) leads to substantial improvements in PV performance in planar p-i-n perovskite solar cells (PSCs), driven by improvements in open circuit voltage (<I>V</I>OC). Employing a range of transient and steady state characterisation tools, we find that the improvements of <I>V</I>OC correlate with reduced surface recombination losses in less p-doped HTLs. A simple device model including screening of bulk electric fields in the perovskite layer is used to explain this observation. In particular, photoluminescence (PL) emission of complete solar cells shows that efficient performance is correlated to a high PL intensity at open circuit and a low PL intensity at short circuit. We conclude that desirable transport layers for p-i-n PSCs should be charge selective contacts with low doping densities.</P>