Evolutionary genomics and HIV restriction factors.

PURPOSE OF REVIEW: To provide updated insights into innate antiviral immunity and highlight prototypical evolutionary features of well characterized HIV restriction factors. RECENT FINDINGS: Recently, a new HIV restriction factor, Myxovirus resistance 2, has been discovered and the region/residue responsible for its activity identified using an evolutionary approach. Furthermore, IFI16, an innate immunity protein known to sense several viruses, has been shown to contribute to the defense to HIV-1 by causing cell death upon sensing HIV-1 DNA. SUMMARY: Restriction factors against HIV show characteristic signatures of positive selection. Different patterns of accelerated sequence evolution can distinguish antiviral strategies--offense or defence--as well as the level of specificity of the antiviral properties. Sequence analysis of primate orthologs of restriction factors serves to localize functional domains and sites responsible for antiviral action. We use recent discoveries to illustrate how evolutionary genomic analyses help identify new antiviral genes and their mechanisms of action.

Current status of biotechnology in China

There has been increasing interest over past decade in exploring the possibility of using new biotechinology to produce new products and to improve the old productive process. The researches and applications of genetic engineering, cell fusion, mutagenesis, cell and enzyme immobilization in enzyme, antibiotic, vitamine, steroid, amino acid, organic acid, solvent, food and brewage industries is reviewed.

The current molecular phylogeny of Eutherian mammals challenges previous interpretations of placental evolution.

Based on histology, the placentae of eutherians are currently grouped in epitheliochorial, endotheliochorial and haemochorial placentae. In a haeckelian sense, the epitheliochorial contact with marked histiotrophic feeding by uterine milk is generally considered as primitive, especially since similar contacts exist in Marsupials. In contrast, the more intimate endotheliochorial and haemochorial contact, facilitating haemotrophic nutrition, is interpreted as a derived state. A cladistic analysis based on the phylogenetic relationships established by molecular analyses reveals that the basic clades are all characterized by an endotheliochorial or haemochorial placenta, and that the epitheliochorial placenta evolved at least three times in a convergent manner. This evolution may be explained by the fact that the epitheliochorial placenta in eutherians is more efficient in nutritional transfer (flow rate by exchange surface). Moreover, this arrangement may confer an advantage to the mother who can probably reduce the degree of manipulation by a genetically imprinted embryo.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI.

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

On the current existence of a coccidial line of development in the malaria parasites: a theory

Most opinion favors the origin of the malaria parasites from a coccidial ancestor. It is assumed that whatever the process through which the coccidia differentiated into a Plasmodium this phenomenon very probably occured millions of year ago, and during that differentiation process the original coccidia vanished. Therefore it has never repeated. At the light of some experiments the existence, at the present time, of a coccidial cycle of development in the malaria parasites, is proposed. The conection routes and mechanisms through which the malaria parasite changes to a coccidial life, and the routes in reverse are exposed. Transmission of the malaria-coccidial forms is suggested.

Current Molecular Imaging of Spinal Tumors in Clinical Practice.

Energy metabolism measurements in spinal cord tumors, as well as in osseous spinal tumors/metastasis in vivo, are rarely performed only with molecular imaging (MI) by positron emission tomography (PET). This imaging modality developed from a small number of basic clinical science investigations followed by subsequent work that influenced and enhanced the research of others. Apart from precise anatomical localization by coregistration of morphological imaging and quantification, the most intriguing advantage of this imaging is the opportunity to investigate the time course (dynamics) of disease-specific molecular events in the intact organism. Most importantly, MI represents one of the key technologies in translational molecular neuroscience research, helping to develop experimental protocols that may later be applied to human patients. PET may help monitor a patient at the vertebral level after surgery and during adjuvant treatment for recurrent or progressive disease. Common clinical indications for MI of primary or secondary CNS spinal tumors are: (i) tumor diagnosis, (ii) identification of the metabolically active tumor compartments (differentiation of viable tumor tissue from necrosis) and (iii) prediction of treatment response by measurement of tumor perfusion or ischemia. While spinal PET has been used under specific circumstances, a question remains as to whether the magnitude of biochemical alterations observed by MI in CNS tumors in general (specifically spinal tumors) can reveal any prognostic value with respect to survival. MI may be able to better identify early disease and to differentiate benign from malignant lesions than more traditional methods. Moreover, an adequate identification of treatment effectiveness may influence patient management. MI probes could be developed to image the function of targets without disturbing them or as treatment to modify the target's function. MI therefore closes the gap between in vitro and in vivo integrative biology of disease. At the spinal level, MI may help to detect progression or recurrence of metastatic disease after surgical treatment. In cases of nonsurgical treatments such as chemo-, hormone- or radiotherapy, it may better assess biological efficiency than conventional imaging modalities coupled with blood tumor markers. In fact, PET provides a unique possibility to correlate topography and specific metabolic activity, but it requires additional clinical and experimental experience and research to find new indications for primary or secondary spinal tumors.

Defining the site of light perception and initiation of phototropism in Arabidopsis.

Phototropism is an adaptive response allowing plants to optimize photosynthetic light capture. This is achieved by asymmetric growth between the shaded and lit sides of the stimulated organ. In grass seedlings, the site of phototropin-mediated light perception is distinct from the site of bending; however, in dicotyledonous plants (e.g., Arabidopsis), spatial aspects of perception remain debatable. We use morphological studies and genetics to show that phototropism can occur in the absence of the root, lower hypocotyl, hypocotyl apex, and cotyledons. Tissue-specific expression of the phototropin1 (phot1) photoreceptor demonstrates that light sensing occurs in the upper hypocotyl and that expression of phot1 in the hypocotyl elongation zone is sufficient to enable a normal phototropic response. Moreover, we show that efficient phototropism occurs when phot1 is expressed from endodermal, cortical, or epidermal cells and that its local activation rapidly leads to a global response throughout the seedling. We propose that spatial aspects in the steps leading from light perception to growth reorientation during phototropism differ between grasses and dicots. These results are important to properly interpret genetic experiments and establish a model connecting light perception to the growth response, including cellular and morphological aspects.

Current concepts of snail control

Schistosomiasis control was impossible without effective tools. Synthetic molluscicides developed in the 1950s spearheaded community level control. Snail eradication proved impossible but repeated mollusciciding to manage natural snail populations could eliminate transmission. Escalating costs, logistical complexity, its labour-intensive nature and possible environmental effects caused some concern. The arrival of safe, effective, single-dose drugs in the 1970s offered an apparently better alternative but experience revealed the need for repeated treatments to minimise reinfection in programmes relying on drugs alone. Combining treatment with mollusciciding was more successful, but broke down if mollusciciding was withdrawn to save money. The provision of sanitation and safe water to prevent transmission is too expensive in poor rural areas where schistosomiasis is endemic; rendering ineffective public health education linked to primary health care. In the tropics, moreover, children (the key group in maintaining transmission) will always play in water. Large scale destruction of natural snail habitats remains impossibly expensive (although proper design could render many new man-made habitats unsuitable for snails). Neither biological control agents nor plant molluscicides have proved satisfactory alternatives to synthetic molluscicides. Biologists can develop effective strategies for using synthetic molluscicides in different epidemiological situations if only, like drugs, their price can be reduced.

Current advances on the study of snail-snail interactions, with special emphasis on competition process

Field work research on population dynamic of snails from the regions of Belo Horizonte and Lagoa Santa give much information about interactions among two or more species of mollusks: Pomacea haustrum, Biomphalaria glabrata, B. tenagophila, B. straminea and Melanoides tuberculata. Data ranging from two years to several decades ago suggest that the Pampulha reservoir is like a cemetery of B. glabrata and B. straminea, species that coexist for more than 14 years in a small part of a stream, whereas only B. glabrata lives in all the streams of the basin. In the last ten to twenty years B. tenagophila has coexisted with P. haustrum and M. tuberculata in the Serra Verde ponds and in the Pampulha dam. However these species have not settled in any of the brooks, except temporarily. The data suggest that the kind of biotope and the habitat conditions are decisive factors for the permanence of each species in its preferencial biotope. B. glabrata, natural from streams and riverheads, quickly disappears from the reservoirs and ponds where it coexists with other species for a short time, independently of the competitive process. Competition needs to be better studied, since in Central America and Caribean islands this kind of study has favored the biological control of planorbid species.

Innate receptors for adaptive immunity.

Pattern recognition receptors (PRRs) are commonly known as sensor proteins crucial for the early detection of microbial or host-derived stress signals by innate immune cells. Interestingly, some PRRs are also expressed and functional in cells of the adaptive immune system. These receptors provide lymphocytes with innate sensing abilities; for example, B cells express Toll-like receptors, which are important for the humoral response. Strikingly, certain other NOD-like receptors are not only highly expressed in adaptive immune cells, but also exert functions related specifically to adaptive immune system pathways, such as regulating antigen presentation. In this review, we will focus particularly on the current understanding of PRR functions intrinsic to B and T lymphocytes; a developing aspect of PRR biology.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.