Rediscovery of Ellobium scheepmakeri (Petit De La Saussaye, 1850) (Mollusca: Gastropoda: Ellobiidae), a rare ellobiid in Bukit Belimbing mangrove forest,Peninsular Malaysia

The ellobiid Ellobium scheepmakeri (Petit de la Saussaye, 1850) is reported from the banks of the Selangor River estuary, 57 years after it was first collected in Peninsular Malaysia. It was found in abundance under logs in the dryland mangrove forest of a dominantly Nypa swamp at the upper reaches of the Kuala Selangor estuary where sediment pore water salinity was recorded at 6–7 ppt.     

Trends and challenges in phytotherapy and phytocosmetics for skin aging

Oxidative stress and inflammation mostly contribute to aging and age-related conditions including skin aging. The potential of natural products in the form of naturally-derived cosmetics, cosmeceuticals, and nutricosmetics have, however, not been fully harnessed. This review, thus, critically analyzes the potential roles of natural products in inflammation-related skin aging diseases due to the increasing consumers’ concerns and demands for efficacious, safe, natural, sustainable, and religiously permitted alternatives to synthetic products. The information and data were collated from various resources and literature databases such as PubMed, Science Direct, Wiley, Springer, Taylor and Francis, Scopus, Inflibnet, Google, and Google Scholar using relevant keywords and Medical Subject Headings (MeSH). The role of green extraction solvents as promising alternatives is also elucidated. The potential enhancements of the bioavailability, stability, solubility and controlled release profile of the bioactives using different delivery systems are also presented. The current potential global market value, motivators, drivers, trends, challenges, halal, and other regulatory certifications for cosmeceuticals and nutricosmetics are equally discussed. The adoption of the suggested extractions and delivery systems would enhance the stability, bioavailability, and target delivery of the bioactives.     

Application of String Kernels in Protein Sequence Classification

INTRODUCTION: The production of biological information has become much greater than its consumption. The key issue now is how to organise and manage the huge amount of novel information to facilitate access to this useful and important biological information. One core problem in classifying biological information is the annotation of new protein sequences with structural and functional features. METHOD: This article introduces the application of string kernels in classifying protein sequences into homogeneous families. A string kernel approach used in conjunction with support vector machines has been shown to achieve good performance in text categorisation tasks. We evaluated and analysed the performance of this approach, and we present experimental results on three selected families from the SCOP (Structural Classification of Proteins) database. We then compared the overall performance of this method with the existing protein classification methods on benchmark SCOP datasets. RESULTS: According to the F1 performance measure and the rate of false positive (RFP) measure, the string kernel method performs well in classifying protein sequences. The method outperformed all the generative-based methods and is comparable with the SVM-Fisher method. DISCUSSION: Although the string kernel approach makes no use of prior biological knowledge, it still captures sufficient biological information to enable it to outperform some of the state-of-the-art methods.     

Cloning and in silico characterization of two signal peptides from Pediococcus pentosaceus and their function for the secretion of heterologous protein in Lactococcus lactis

Fifty signal peptides of Pediococcus pentosaceus were characterized by in silico analysis and, based on the physicochemical analysis, (two potential signal peptides Spk1 and Spk3 were identified). The coding sequences of SP were amplified and fused to the gene coding for green fluorescent protein (GFP) and cloned into Lactococcus lactis pNZ8048 and pMG36e vectors, respectively. Western blot analysis indicated that the GFP proteins were secreted using both heterologous SPs. ELISA showed that the secretion efficiency of GFP using Spk1 (0.64 μg/ml) was similar to using Usp45 (0.62 μg/ml) and Spk3 (0.58 μg/ml).     

The Mechanism of HdeA Unfolding and Chaperone Activation

HdeA is a periplasmic chaperone that is rapidly activated upon shifting the pH to acidic conditions. This activation is thought to involve monomerization of HdeA. There is evidence that monomerization and partial unfolding allow the chaperone to bind to proteins denatured by low pH, thereby protecting them from aggregation. We analyzed the acid-induced unfolding of HdeA using NMR spectroscopy and fluorescence measurements, and obtained experimental evidence suggesting a complex mechanism in HdeA's acid-induced unfolding pathway, as previously postulated from molecular dynamics simulations. Counterintuitively, dissociation constant measurements show a stabilization of the HdeA dimer upon exposure to mildly acidic conditions. We provide experimental evidence that protonation of Glu37, a glutamate residue embedded in a hydrophobic pocket of HdeA, is important in controlling HdeA stabilization and thus the acid activation of this chaperone. Our data also reveal a sharp transition from folded dimer to unfolded monomer between pH 3 and pH 2, and suggest the existence of a low-populated, partially folded intermediate that could assist in chaperone activation or function. Overall, this study provides a detailed experimental investigation into the mechanism by which HdeA unfolds and activates.     

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.