A 37,500-year pollen record from Lake Malaŵi and implications for the biogeography of afromontane forests

Abstract. Two 10-metre cores were analysed and a 37,500 year pollen stratigraphy was established for Lake Mala?i. A lowstand from 37,500 to 35,900 BP indicates extremely dry conditions. From 35,900 to 34,000 BP montane forests were widespread indicating cold, moist climate. Between 34,000 and 26,400 BP warm and dry conditions prevailed and forest area decreased. During the Last Glacial Maximum montane forest was widespread in the catchment, although woodlands apparently persisted at low altitudes: the expansion of the montane forest indicates that the aridity that affected equatorial Africa during this time period did not affect the Lake Mala?i Catchment. The cold and relatively moist conditions during the Late Pleistocene probably allowed biotic interchange between the highlands of East and West Africa via the highlands along the Zaire—Zambezi watershed and among now-isolated islands of Afromontane vegetation in the Lake Mala?i catchment. The Holocene is characterized by climate and vegetation quite similar to today, with indications of slightly wetter conditions between 6150 and 3000 bp and slightly drier conditions between 8000 and 6150 bp . The low percentages of montane forest pollen throughout the Holocene support the hypothesis that the montane grasslands of Mala?i are not recently anthropogenic.     

Discrimination and scoring using small sets of genes for two-sample microarray data

Comparison of gene expression for two groups of individuals form an important subclass of microarray experiments. We study multivariate procedures, in particular use of Hotelling's T2 for discrimination between the groups with a special emphasis on methods based on few genes only. We apply the methods to data from an experiment with a group of atopic dermatitis patients compared with a control group. We also compare our methodology to other recently proposed methods on publicly available datasets. It is found that (i) use of several genes gives a much improved discrimination of the groups as compared to one gene only, (ii) the genes that play the most important role in the multivariate analysis are not necessarily those that rank first in univariate comparisons of the groups, (iii) Linear Discriminant Analysis carried out with sets of 2-5 genes selected according to their Hotelling T2 give results comparable to state-of-the-art methods using many more genes, a feature of our method which might be crucial in clinical applications. Finding groups of genes that together give optimal multivariate discrimination (given the size of the group) can identify crucial pathways and networks of genes responsible for a disease. The computer code that we developed to make computations is available as an R package.     

A probabilistic approach to the use of pollen indicators for plant attributes and biomes: an application to European vegetation at 0 and 6 ka

Aim This paper presents a probabilistic method for the characterization of pollen taxa using attributes, and for the reconstitution of past biomes. The probabilities are calculated on the basis of European floristic and pollen databases sufficiently large and exhaustive to provide robust estimates. Location The analysis is based on data from approximately 1000 sites throughout Europe. Method We use all the pollen data from the European Pollen Database (EPD), which contains about 50 000 pollen assemblages distributed across Europe and covering the period from the Last Glacial Maximum to the present. Using existing floras, each pollen taxon has been characterized by allocating one or more modes of several attributes, chosen according to the biogeography and phenology of the taxon. With this information, conditional probabilities are defined, representing the chance of a given attribute mode occurring in a given pollen spectrum, when the taxa assemblage is known. The concept of co‐occurrence is used to provide a greater amount of information to compensate for difficulties in the identification of pollen grains, allowing a better interpretation when there is little diversity in the pollen assemblage. Results The method has been validated using a dataset of modern samples against existing methods of biome classification and remote sensing data. An application is proposed in which the new method is used to produce biomes for pollen data 6000 years ago. This confirms previous results showing an extension of the deciduous forest to the north, east and south, explained by milder winters in western and northern Europe, and cooler and wetter climate in the Mediterranean region. Conclusion The results show the new method to be efficient, reliable and flexible and to be an improvement over the previous method of biomization. They will be used to test simulations of earth system models running on periods with climate significantly different from the present day, enabling a robust test of the validity of applying these models to the future.     

Predicting the start of the birch pollen season at London, Derby and Cardiff, United Kingdom, using a multiple regression model, based on data from 1987 to 1997

Recent changes in weather in North-West Europehave been reflected in the start dates ofpollen seasons. It is therefore necessary toupdate previous models, such as the oneproduced by Jones (1995), so that the modelwill be weighted by current weather patterns. Birch pollen data, collected over a period ofeleven years (1987 to 1997 inclusive) fromthree pollen counting stations in the UK,London, Derby and Cardiff, were analysed todetermine the start dates using the Sum75method. The start dates of the birch pollenseasons of the eleven-year period were thentested for significance against ten-dayaggregated variables of temperature andrainfall for each site. The significantvariables were entered into multiple regressionmodels until the most valid equation for eachsite was found. The models were then tested onthree years not included in their data sets. The models showed mean differences betweenactual and predicted start dates, for theeleven years used, of 1.5, 3 and 5 days atDerby, Cardiff and London respectively. Forthe test years the mean difference was 1, 4.5and 7.5 days at Derby, Cardiff and Londonrespectively. The most powerful model was forDerby where the corresponding meteorologicalstation is at 0.5 km distance and the weakestwas for London where the correspondingmeteorological station is much further away at21 km distance. Weather variables from earlyFebruary to mid March were found to be the mostinfluential on the start dates of the birchpollen season at the three sites.     

Simplified population data analysis using gamma distribution for nutritional requirements and its application to the estimation of iron requirements for women of child-bearing age

BackgroundEstimation of nutritional requirements is a difficult task, especially for nutrients whose requirements have skewed distribution like iron in menstruating women.ObjectiveTo mathematically develop a simplified population data analysis using gamma distribution for the estimation of nutritional requirements, not depending on extensive numerical calculation.MethodsThe required equations for the estimation of requirements were devised and solved. Existing data of iron intakes and iron losses in literature were fitted to cumulative distribution curves including gamma distribution. The proposed method was applied to the estimation of iron requirements in women using the National Health and Nutrition Survey data from 2003 to 2007 in Japan.ResultsThe type 2 equation of nutritional state is first introduced: prevalence of inadequate nutritional state = Σ(individuals with intake/requirement <1)/(total number of individuals). The prevalence of inadequate nutritional status is determined by F-distribution with positive real number parameters, if the intake and the requirement have independent gamma distributions. The sum of basal and menstrual iron losses is well approximated by gamma distribution, if the basal and menstrual iron losses have independent gamma distributions. Using these relationships, an approximate estimate of iron requirements was determined. Iron intakes and losses were found to be well approximated by gamma distribution. The median of the coefficient of variation (CV) of basal iron loss was 34 %. A new correction method for intra-individual variation in gamma distribution under constant CV is presented also. The median of the estimated median iron requirement was 8.12 mg, 8.15 mg and 8.18 mg for women aged 18−29 years, respectively, as the exact numerical estimate, the approximate estimate using BETA.INV in Excel and the approximate estimate using F.INV in Excel. For women aged 30−49 years, it was 9.15 mg, 9.17 mg and 9.14 mg. The intake covering the needs of 97.7 % women was 14.55 mg, 14.44 mg and 14.49 mg for women aged 18−29 years, and 15.70 mg, 15.77 mg and 15.60 mg for women aged 30−49 years.ConclusionThe approximate estimates of iron requirements agreed well with the exact numerical estimate. The proposed method is useful for the estimation of iron requirements in menstruating women that usually requires extensive numerical calculations.     

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses.In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.     

A new experimental approach and signal processing scheme for the detection and quantitation of P brain neurochemicals from in vivo MRS studies using dual tuned (H/P) head coil

Brain ³¹P-neurometabolites play an important role in energy and membrane metabolism. Unambiguous identification and quantification of these neurochemicals in different brain regions would be a great aid in advancing the understanding of metabolic processes in the nervous system. Phosphomonoester (PME), consisting of phosphoethanolamine (PE) and phosphocholine (PC), is the “building block” for membranes, while phosphodiesters (PDE), consisting of glycerophosphocholine (GPC) and glycerophosphoethanolamine (GPE) metabolites are involved in the membrane breakdown process. In the clinical setting, generating well-resolved spectra for PC, PE, GPC, and GPE could be crucial phospholipids in providing information regarding membrane metabolism. We present here a new experimental approach for generating well-resolved ³¹P spectra for PC and PE as well as for GPC, GPE, and other ³¹P metabolites. Our results (based on uni-dimensional (1D) and multi-voxel ³¹P studies) indicate that an intermediate excitation pulse angle (35°) is best suited to obtain well-resolved PC/PE and GPC/GPE resonance peaks. Our novel signal processing scheme allows generating metabolite maps of different phospholipids include PC/PE and GPC/GPE using the ‘time-domain–frequency-domain’ method as referred to in the MATLAB programming language.