Diagnosing dementia: do we get it right?

To find out whether the diagnosis of dementia agreed with findings at necropsy a detailed assessment of 27 elderly patients (mean age 82 (range 70-94] presenting with dementia was conducted at a combined department of geriatric medicine and psychiatry for the elderly. On the basis of the results the cause of the dementia was diagnosed clinically. Neuropathological examinations were performed after death. The clinical diagnosis made during life was not supported by the findings at necropsy in 11 cases. Alzheimer''s disease was overdiagnosed in life (13 cases, of which only six were confirmed at necropsy). Although the clinical investigation was limited by availability of resources, neither cranial computed tomography nor the Hachinski score helped to distinguish between multi-infarct dementia and Alzheimer''s disease in this age group. This study confirms the value of neuropathological studies in the precise diagnosis of dementia.     

Biodeterioration of Mayan buildings at uxmal and tulum,Mexico

Uxmal and Tulum are two important Mayan sites in the Yucatan peninsula. The buildings are mainly composed of limestone and grey/black discoloration is seen on exposed walls and copious greenish biofilms on inner walls. The principal microorganisms detected on interior walls at both Uxmal and Tulum were cyanobacteria; heterotrophic bacteria and filamentous fungi were also present. A dark‐pigmented mitosporic fungus and Bacillus cereus, both isolated from Uxmal, were shown to be acidogenic in laboratory cultures. Cyanobacteria belonging to rock‐degrading genera Synechocystis and Gloeocapsa were identified at both sites. Surface analysis previously showed that calcium ions were present in the biofilms on buildings at Uxmal and Tulum, suggesting the deposition of biosolubilized stone. Apart from their potential to degrade the substrate, the coccoid cyanobacteria supply organic nutrients for bacteria and fungi, which can produce organic acids, further increasing stone degradation.     

Partner-specific prediction of RNA-binding residues in proteins: A critical assessment

RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are “specific”, that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are “non-RNA specific.” Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both.     

Predicting binding sites of hydrolase-inhibitor complexes by combining several methods

Background

Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results

In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.

Conclusions

We developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.     

Downregulation of RKIP is associated with poor outcome and malignant progression in gliomas

Malignant gliomas are highly infiltrative and invasive tumors, which precludes the few treatment options available. Therefore, there is an urgent need to elucidate the molecular mechanisms underlying gliomas aggressive phenotype and poor prognosis. The Raf Kinase Inhibitory protein (RKIP), besides regulating important intracellular signaling cascades, was described to be associated with progression, metastasis and prognosis in several human neoplasms. Its role in the prognosis and tumourigenesis of gliomas remains unclear. In the present study, we found that RKIP protein is absent in a low frequency (10%, 20/193) of glioma tumors. Nevertheless, the absence of RKIP expression was an independent prognostic marker in glioma. Additionally, by in vitro downregulation of RKIP, we found that RKIP inhibition induces a higher viability and migration of the cells, having no effect on cellular proliferation and angiogenesis, as assessed by in vivo CAM assay. In conclusion, this is the largest series studied so far evaluating the expression levels of this important cancer suppressor protein in glioma tumors. Our results suggest that in a subset of tumors, the absence of RKIP associates with highly malignant behavior and poor survival of patients, which may be a useful biomarker for tailored treatment of glioma patients.     

Establishing human lacrimal gland cultures with secretory function

Purpose

Dry eye syndrome is a multifactorial chronic disabling disease mainly caused by the functional disruptions in the lacrimal gland. The treatment involves palliation like ocular surface lubrication and rehydration. Cell therapy involving replacement of the gland is a promising alternative for providing long-term relief to patients. This study aimed to establish functionally competent lacrimal gland cultures in–vitro and explore the presence of stem cells in the native gland and the established in-vitro cultures.

Methods

Fresh human lacrimal gland from patients undergoing exenteration was harvested for cultures after IRB approval. The freshly isolated cells were evaluated by flow cytometry for expression of stem cell markers ABCG2, high ALDH1 levels and c-kit. Cultures were established on Matrigel, collagen and HAM and the cultured cells evaluated for the presence of stem cell markers and differentiating markers of epithelial (E-cadherin, EpCAM), mesenchymal (Vimentin, CD90) and myofibroblastic (α-SMA, S-100) origin by flow cytometry and immunocytochemistry. The conditioned media was tested for secretory proteins (scIgA, lactoferrin, lysozyme) post carbachol (100 µM) stimulation by ELISA.

Results

Native human lacrimal gland expressed ABCG2 (mean±SEM: 3.1±0.61%), high ALDH1 (3.8±1.26%) and c-kit (6.7±2.0%). Lacrimal gland cultures formed a monolayer, in order of preference on Matrigel, collagen and HAM within 15–20 days, containing a heterogeneous population of stem-like and differentiated cells. The epithelial cells formed ‘spherules’ with duct like connections, suggestive of ductal origin. The levels of scIgA (47.43 to 61.56 ng/ml), lysozyme (24.36 to 144.74 ng/ml) and lactoferrin (32.45 to 40.31 ng/ml) in the conditioned media were significantly higher than the negative controls (p<0.05 for all comparisons).

Conclusion

The study reports the novel finding of establishing functionally competent human lacrimal gland cultures in-vitro. It also provides preliminary data on the presence of stem cells and duct-like cells in the fresh and in-vitro cultured human lacrimal gland. These significant findings could pave way for cell therapy in future.     

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art

Background

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data.

Results

Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16?S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA).

Conclusions

The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.     

Terrigenous sediment-dominated reef platform infilling: an unexpected precursor to reef island formation and a test of the reef platform size–island age model in the Pacific

Low-lying coral reef islands are considered highly vulnerable to climate change, necessitating an improved understanding of when and why they form, and how the timing of formation varies within and among regions. Several testable models have been proposed that explain inter-regional variability as a function of sea-level history and, more recently, a reef platform size model has been proposed from the Maldives (central Indian Ocean) to explain intra-regional (intra-atoll) variability. Here we present chronostratigraphic data from Pipon Island, northern Great Barrier Reef (GBR), enabling us to test the applicability of existing regional island evolution models, and the platform size control hypothesis in a Pacific context. We show that reef platform infilling occurred rapidly (~4–5 mm yr⁻¹) under a “bucket-fill” type scenario. Unusually, this infilling was dominated by terrigenous sedimentation, with platform filling and subsequent reef flat formation complete by ~5000 calibrated years BP (cal BP). Reef flat exposure as sea levels slowly fell post highstand facilitated a shift towards intertidal and subaerial-dominated sedimentation. Our data suggest, however, a lag of ~1500 yr before island initiation (at ~3200 cal BP), i.e. later than that reported from smaller and more evolutionarily mature reef platforms in the region. Our data thus support: (1) the hypothesis that platform size acts to influence the timing of platform filling and subsequent island development at intra-regional scales; and (2) the hypothesis that the low wooded islands of the northern GBR conform to a model of island formation above an elevated reef flat under falling sea levels.

     

Genetic Admixture in the Culturally Unique Peranakan Chinese Population in Southeast Asia

The Peranakan Chinese are culturally unique descendants of immigrants from China who settled in the Malay Archipelago ∼300–500 years ago. Today, among large communities in Southeast Asia, the Peranakans have preserved Chinese traditions with strong influence from the local indigenous Malays. Yet, whether or to what extent genetic admixture co-occurred with the cultural mixture has been a topic of ongoing debate. We performed whole-genome sequencing (WGS) on 177 Singapore (SG) Peranakans and analyzed the data jointly with WGS data of Asian and European populations. We estimated that Peranakan Chinese inherited ∼5.62% (95% confidence interval [CI]: 4.76–6.49%) Malay ancestry, much higher than that in SG Chinese (1.08%, 0.65–1.51%), southern Chinese (0.86%, 0.50–1.23%), and northern Chinese (0.25%, 0.18–0.32%). A sex-biased admixture history, in which the Malay ancestry was contributed primarily by females, was supported by X chromosomal variants, and mitochondrial (MT) and Y haplogroups. Finally, we identified an ancient admixture event shared by Peranakan Chinese and SG Chinese ∼1,612 (95% CI: 1,345–1,923) years ago, coinciding with the settlement history of Han Chinese in southern China, apart from the recent admixture event with Malays unique to Peranakan Chinese ∼190 (159–213) years ago. These findings greatly advance our understanding of the dispersal history of Chinese and their interaction with indigenous populations in Southeast Asia.