Human RFT1 deficiency leads to a disorder of N-linked glycosylation

N-linked glycosylation is an essential posttranslational modification of proteins in eukaryotes. The substrate of N-linked glycosylation, dolichol pyrophosphate (DolPP)-GlcNAc(2)Man(9)Glc(3), is assembled through a complex series of ordered reactions requiring the translocation of the intermediate DolPP-GlcNAc(2)Man(5) structure across the endoplasmic-reticulum membrane. A young patient diagnosed with a congenital disorder of glycosylation characterized by an intracellular accumulation of DolPP-GlcNAc(2)Man(5) was found to carry a homozygous point mutation in the RFT1 gene. The c.199C-->T mutation introduced the amino acid substitution p.R67C. The human RFT1 protein shares 22% identity with its yeast ortholog, which is involved in the translocation of DolPP-GlcNAc(2)Man(5) from the cytosolic into the lumenal side of the endoplasmic reticulum. Despite the low sequence similarity between the yeast and the human RFT1 proteins, we demonstrated both their functional orthology and the pathologic effect of the human p.R67C mutation by complementation assay in Deltarft1 yeast cells. The causality of the RFT1 p.R67C mutation was further established by restoration of normal glycosylation profiles in patient-derived fibroblasts after lentiviral expression of a normal RFT1 cDNA. The definition of the RFT1 defect establishes the functional conservation of the DolPP-GlcNAc(2)Man(5) translocation process in eukaryotes. RFT1 deficiency in both yeast and human cells leads to the accumulation of incomplete DolPP-GlcNAc(2)Man(5) and to a profound glycosylation disorder in humans.     

The human exosome: an autoantigenic complex of exoribonucleases in myositis and scleroderma

The anti-PM/Scl autoantibodies are known to characterize a subset of autoimmune patients with myositis, scleroderma (Scl), and the PM/Scl overlap syndrome. The major autoantigens that are recognized by anti-PM/Scl autoantibodies are designated PM/Scl-100 and PM/Scl-75. These autoantigens have been reported to associate into a large complex consisting of 11 to 16 proteins and to play a role in ribosome synthesis. Recently, it was discovered that the PM/Scl complex is the human counterpart of the yeast (Saccharomyces cerevisiae) exosome, which is an RNA-processing complex consisting of 11 3' → 5' exoribonucleases. To date, 10 human exosome components have been identified, although only some of these were studied in more detail. In this review, we discuss some recent advances in the characterization of the PM/Scl complex.     

Germination ecology of Cassava (Manihot esculenta Crantz, Euphorbiaceae) in traditional agroecosystems: Seed and seedling biology of a vegetatively propagated domesticated plant

Cassava is clonally propagated, but Amerindian farmers also use plants from volunteer seedlings to prepare stem cuttings. Although sexual reproduction plays a role in cassava’s evolution it is poorly studied. We examined one aspect of cassava reproductive ecology, seed dormancy and germination. Volunteer seedlings emerge from a soil bank of seeds produced during the previous cycle of cultivation that remain ungerminated through the fallow period, then germinate synchronously after vegetation is slashed and burned. Laboratory experiments showed that germination can be enhanced by mechanical scarification and also by dry heat treatment, suggesting that burning after field clearing could help break dormancy. Germination was also stimulated by high temperatures (35°C) that in nature indicate bare soils, and inhibited by temperatures (25°C) close to those in soil shaded by vegetation and by light. Seeds of both wild and domesticated cassava exhibit physiological dormancy, an adaptation for germination in periodically disturbed habitats. In addition to these preadaptations, preliminary results also suggest specific adaptations of domesticated cassava to the distinctive disturbance regimes of swidden agriculture.     

Serum HE4: An Independent Prognostic Factor in Non-Small Cell Lung Cancer

Human epididymis secretory protein 4 (HE4) is a secreted glycosylated protein encoded by the WAP four-disulfide core domain 2 (WFDC2) gene, located on a chromosome 20 segment that is frequently amplified in many cancers. This study aimed at determining serum HE4 prognostic value in non-small cell lung cancer (NSCLC), following the REMARK guidelines. Serum samples from 346 consecutive patients with histologically proven and previously untreated NSCLC and 41 patients with benign pulmonary disease were collected at the Montpellier-Nimes Academic Hospital. Work-up investigations performed to determine the disease characteristics and treatment algorithms were congruent with international guidelines. HE4 levels in serum were measured with an ELISA test (Fujirebio Diagnostics) that uses two monoclonal antibodies, 2H5 and 3D8, against the C-WFDC domain of HE4. The area under the ROC curve (i.e., overall ability of HE4 to discriminate between controls and patients) was 0.78 (95% confidence interval [CI], 0.738–0.821; z test P <0.0001). Serum HE4 levels were significantly higher in patients with worse performance status, advanced TNM stage and positive nodal status. In the Cox model, overall survival was shorter in patients with high pretreatment serum HE4 (above 140 pmol/L) than in patients with serum H4 level ≤ 140 pmol/L [median survival: 17.7 weeks (95% CI, 11.9 to 24.9) and 46.4 weeks (95% CI, 38.6 to 56.3), respectively; hazard ratio: 1.48 (95% CI, 1.12 to 1.95) for high HE4; adjusted P = 0.0057]. High serum HE4 level at diagnosis is an independent determinant of poor prognosis in NSCLC.     

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N²), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.