A preferred conformation in the vasoactive intestinal peptide (VIP). Molecular architecture of gastrointestinal hormones

The ORD spectrum of the vasoactive intestinal peptide (VIP) in water indicates a preferred conformation with low helix content. Addition of organic solvents, especially of trifluoroethanol, results, even at low solvent concentration, in spectra with pronounced helical character. The readiness of shorter chains, with C-terminal sequences of VIP, to take up helical conformation under the effect of organic solvents parallels their biological activity. This suggests that an “active architecture” may be required for the interaction between hormone and receptor.     

The major flavonoids of the seed of Tephrosia apollinea

A total of six complex 7-oxygenated-8-prenylflavones have been isolated from the seeds of Tephrosia apollinea and identified as the diastereoisomers (?)-semiglabrin and (?)-pseudosemiglabrin, (+)-glabratephrin, (+)-glabratephrinol, appollinine (7-methoxy-8-[3″-(2″,5″-dihydro-5″,5″-dimethyl-2″-oxofuryl)]-flavone and lanceolatin-A. The use of ¹³C NMR in the structure elucidation of flavones of this type is discussed. The potential chemotaxonomic value of Tephrosia flavones of the type isolated from T. apollinea is explored.     

Biochemical Characterization of Novel Phenylalanine Ammonia-Lyase from Spirulina CPCC-695

The Protein Journal - Phenylalanine ammonia lyase (PAL) catalyzes the deamination of phenylalanine to cinnamic acid and ammonia. It plays a crucial role in the formation of secondary metabolites...     

In vitro propagation of the medicinal plant Ziziphora tenuior L. and evaluation of its antioxidant activity

Ziziphora tenuior L. (Lamiaceae) is an aromatic herb used for its medicinal values against fungi, bacteria. Micropropagation can be used for large-scale multiplication of essential oil producing plants thus avoiding an overexploitation of natural resources. This work aims to develop a reliable protocol for the in vitro propagation of Z. tenuior, and to compare the antioxidant activity between in vitro propagated and wild plants.The explants were sterilized and cultured on MS medium containing different concentrations of growth regulators naphthalene acetic acid (NAA) or indole-3-butyric acid (IBA) with 0.5 mg/L of kinetin (Kin) callus formation was 70.2% after 45 days of incubation in dark on medium supplemented with 1.5 mg/L of NAA. After one month of callus culture on medium supplemented with 2 mg/L BA the shoot number was 5.12 and for the multiplication stage. The shoot number was 4.21 and length was 6.17 cm on medium supplemented with 1 mg/L Kin + 0.1 mg/L NAA.DPPH• reagent was used to test the antioxidant activity. The aqueous and methanol extracts of in vitro plants which were treated with 1.5 and 1 mg/L of kin plus 0.1 mg/L of NAA showed a strong DPPH• scavenging activity where IC₅₀ was 0.307 and 0.369 mg/ml, respectively, while the IC₅₀ of aqueous and methanol extracts of wild plants was 0.516 and 9.229 mg/ml, respectively. Our results suggested that plant growth regulators and in vitro culture conditions increased the antioxidant activity.     

Fast activated charcoal prepurification of Fusarium solani β-glucosidase for an efficient oleuropein bioconversion

Fungal β-glucosidases were extensively studied regarding their various potential biotechnology applications. Here, we report the selection of Fusarium solani strain producing high yield of β-glucosidase activity. The effect of some factors on β-glucosidase production was studied including: Initial pH, medium composition, concentration of carbon and nitrogen sources, and particle size of raw substrates. The optimal enzyme production was obtained with 4?units of pH. The highest β-glucosidase activity was produced on 4% wheat bran (WB) as raw carbon sources, reaching 5?U/mL. A positive correlation between WB particle size and the β-glucosidase production level was settled. The last one was enhanced to 13.60?U/mL in the presence of 0.5% (w/v) of ammonium sulfate. Interestingly, the activated charcoal was used as an inexpensive reagent enabling a rapid and efficient purification prior step that improved the enzyme-specific activity. Eventually, F. solani β-glucosidase acts efficiently during the bioconversion process of oleuropein. Indeed, 82.5% of oleuropein was deglycosylated after 1?hr at 40°C. Altogether, our data showed that the β-glucosidase of F. solani has a potential application to convert oleuropein to ameliorate food quality.     

Structurally designed novel furogamma lactams as inhibitors for bacterial propagations

Some novel furogamma lactams have been synthesised by one step condensation of arylaminomalonates with substituted furyl acryloyl chlorides. The annulation of substituted monocyclic gammalactams followed by cyclization produced novel tricyclic furogamma lactams. Some of these furogammalactams are found to exhibit Gram-positive and Gram-negative antibacterial activity at very high concentrations.     

Adaptive learning style prediction in e-learning environment using levy flight distribution based CNN model

A learning style that focuses on individual learning is one of the most important aspects of any learning environment. Each learner has a unique manner of understanding, retaining, processing, and interpreting new information based on their learning styles. The ability of an e-learning system to automatically determine a student's learning style has become more essential. For learning events, the evolution of e-learning platforms provides students with higher opportunities online. In this paper, we proposed a Convolutional Neural Network-based Levy Flight Distribution (CNN-LFD) algorithm for learning style prediction. An adaptive e-learning system is divided into two sections: automatic learning style prediction and classification based on the number of learning styles included. Initially, the student logs in with their user ID, and the data is saved in the database. The features such as questionnaire score, login credentials (session ID, learner ID, and course ID), and login time (location, session ID) are extracted along with the sequence of the user's learning behavior. After that, the CNN-LFD algorithm predicts the learning styles of the learners namely Active/reflective, Sensing/intuitive, visual/verbal, sequential/global based on the extracted features. The dataset information are gathered from a Massive Open Online Course (MOOC), and the proposed model is built in JAVA software. The experimental results demonstrate higher classification accuracy during learning style prediction. The proposed CNN-LFD algorithm accomplishes 97.09% accuracy, 94.76% specificity, 92.12% sensitivity, and 97.56%, precision values than other methods.