The time-dependent expression of keratins 5 and 13 during the reepithelialization of human skin wounds

The time-dependent reepithelialization of 55 human surgical skin wounds with a wound age between 8h and more than 2 months was investigated by the immunohistochemical localization of cytokeratins 5 and 13. A complete, rebuilt epidermal layer over the wound area was first detectable in a 5-day-old wound, while all wounds of more than 18 days duration contained a completely reepithelialized wound area. Between 5 and 18 days the basal layer of keratinocytes showed — in contrast to normal skin — only some cells positive for cytokeratin 5. In some, but not all lesions with a wound age of 13 days or more, a basal cell layer completely staining for cytokeratin 5 was demonstrable. This staining pattern was found in all skin wounds with a wound age of more than 23 days. The immunohistochemical detection of cytokeratin 13 which can be observed regularly in non-cornifying squamous epithelia provides no information for the time-estimation of human skin wounds, since no significant temporary expression of this polypeptide seems to occur during the healing of human skin wounds

Methods for Bayesian inversion of seismic data

The purpose of Bayesian seismic inversion is to combine information derived from seismic data and prior geological knowledge to determine a posterior probability distribution over parameters describing the elastic and geological properties of the subsurface. Typically the subsurface is modelled by a cellular grid model containing thousands or millions of cells within which these parameters are to be determined. Thus such inversions are computationally expensive due to the size of the parameter space (being proportional to the number of grid cells) over which the posterior is to be determined. Therefore, in practice approximations to Bayesian seismic inversion must be considered. A particular, existing approximate workflow is described in this thesis: the so-called two-stage inversion method explicitly splits the inversion problem into elastic and geological inversion stages. These two stages sequentially estimate the elastic parameters given the seismic data, and then the geological parameters given the elastic parameter estimates, respectively. In this thesis a number of methodologies are developed which enhance the accuracy of this approximate workflow. To reduce computational cost, existing elastic inversion methods often incorporate only simplified prior information about the elastic parameters. Thus a method is introduced which transforms such results, obtained using prior information specified using only two-point geostatistics, into new estimates containing sophisticated multi-point geostatistical prior information. The method uses a so-called deep neural network, trained using only synthetic instances (or `examples') of these two estimates, to apply this transformation. The method is shown to improve the resolution and accuracy (by comparison to well measurements) of elastic parameter estimates determined for a real hydrocarbon reservoir. It has been shown previously that so-called mixture density network (MDN) inversion can be used to solve geological inversion analytically (and thus very rapidly and efficiently) but only under certain assumptions about the geological prior distribution. A so-called prior replacement operation is developed here, which can be used to relax these requirements. It permits the efficient MDN method to be incorporated into general stochastic geological inversion methods which are free from the restrictive assumptions. Such methods rely on the use of Markov-chain Monte-Carlo (MCMC) sampling, which estimate the posterior (over the geological parameters) by producing a correlated chain of samples from it. It is shown that this approach can yield biased estimates of the posterior. Thus an alternative method which obtains a set of non-correlated samples from the posterior is developed, avoiding the possibility of bias in the estimate. The new method was tested on a synthetic geological inversion problem; its results compared favourably to those of Gibbs sampling (a MCMC method) on the same problem, which exhibited very significant bias. The geological prior information used in seismic inversion can be derived from real images which bear similarity to the geology anticipated within the target region of the subsurface. Such so-called training images are not always available from which this information (in the form of geostatistics) may be extracted. In this case appropriate training images may be generated by geological experts. However, this process can be costly and difficult. Thus an elicitation method (based on a genetic algorithm) is developed here which obtains the appropriate geostatistics reliably and directly from a geological expert, without the need for training images. 12 experts were asked to use the algorithm (individually) to determine the appropriate geostatistics for a physical (target) geological image. The majority of the experts were able to obtain a set of geostatistics which were consistent with the true (measured) statistics of the target image

Lives saved by Global Fund-supported HIV/AIDS, tuberculosis and malaria programs: estimation approach and results between 2003 and end-2007

<p>Abstract</p> <p>Background</p> <p>Since 2003, the Global Fund has supported the scale-up of HIV/AIDS, tuberculosis and malaria control in low- and middle-income countries. This paper presents and discusses a methodology for estimating the lives saved through selected service deliveries reported to the Global Fund.</p> <p>Methods</p> <p>Global Fund-supported programs reported, by end-2007, 1.4 million HIV-infected persons on antiretroviral treatment (ARV), 3.3 million new smear-positive tuberculosis cases detected in DOTS (directly observed TB treatment, short course) programs, and 46 million insecticide-treated mosquito nets (ITNs) delivered. We estimated the corresponding lives saved using adaptations of existing epidemiological estimation models.</p> <p>Results</p> <p>By end-2007, an estimated 681,000 lives (95% uncertainty range 619,000-774,000) were saved and 1,097,000 (993,000-1,249,000) life-years gained by ARV. DOTS treatment would have saved 1.63 million lives (1.09 - 2.17 million) when compared against no treatment, or 408,000 lives (265,000-551,000) when compared against non-DOTS treatment. ITN distributions in countries with stable endemic <it>falciparum </it>malaria were estimated to have achieved protection from malaria for 26 million of child-years at risk cumulatively, resulting in 130,000 (27,000-232,000) under-5 deaths prevented.</p> <p>Conclusions</p> <p>These results illustrate the scale of mortality effects that supported programs may have achieved in recent years, despite margins of uncertainty and covering only selected intervention components. Evidence-based evaluation of disease impact of the programs supported by the Global Fund with international and in-country partners must be strengthened using population-level data on intervention coverage and demographic outcomes, information on quality of services, and trends in disease burdens recorded in national health information systems.</p

Early carboniferous brachiopod faunas from the Baoshan block, west Yunnan, southwest China

38 brachiopod species in 27 genera and subgenera are described from the Yudong Formation in the Shidian-Baoshan area, west Yunnan, southwest China. New taxa include two new subgenera: Unispirifer (Septimispirifer) and Brachythyrina (Longathyrina), and seven new species: Eomarginifera yunnanensis, Marginatia cylindrica, Unispirifer (Unispirifer) xiangshanensis, Unispirifer (Septimispirifer) wafangjieensis, Brachythyrina (Brachythyrina) transversa, Brachythyrina (Longathyrina) baoshanensis, and Girtyella wafangjieensis. Based on the described material and constraints from associated coral and conodont faunas, the age of the brachiopod fauna from the Yudon Formation is considered late Tournaisian (Early Carboniferous), with a possibility extending into earlyViseacutean.<br /