Site-Selective Modification of Peptides and Proteins via Organocatalyzed Henry Reaction

In this research, peptides and protein containing serine on the N-terminus underwent site-selective modification following organocatalyzed bioconjugation that offered an additional functional group. It was shown that transforming the N-terminus serine to an aldehyde allowed site-specific bioconjugation to occur by utilizing the well-known Henry reaction. This method also grants a safer pathway for bioconjugation utilizing “green-chemistry” and biocompatible conditions. Amino acids and amino acid derived organocatalysts were utilized in the Henry reaction resulting in yields of up to 86 % conversion. Promising preliminary results were achieved in this research using peptides and myoglobin as the bioconjugation targets. Further investigation to be performed includes the analysis of the final product, as well as, applying this methodology to a number of other proteins

Site-Selective Modification of Peptides and Proteins via Organocatalyzed Henry Reaction

In this research, peptides and protein containing serine on the N-terminus underwent site-selective modification following organocatalyzed bioconjugation that offered an additional functional group. It was shown that transforming the N-terminus serine to an aldehyde allowed site-specific bioconjugation to occur by utilizing the well-known Henry reaction. This method also grants a safer pathway for bioconjugation utilizing “green-chemistry” and biocompatible conditions. Amino acids and amino acid derived organocatalysts were utilized in the Henry reaction resulting in yields of up to 86 % conversion. Promising preliminary results were achieved in this research using peptides and myoglobin as the bioconjugation targets. Further investigation to be performed includes the analysis of the final product, as well as, applying this methodology to a number of other proteins

Optimal Feature Subset Selection Based on Combining Document Frequency and Term Frequency for Text Classification

Feature selection plays a vital role to reduce the high dimension of the feature space in the text document classification problem. The dimension reduction of feature space reduces the computation cost and improves the text classification system accuracy. Hence, the identification of a proper subset of the significant features of the text corpus is needed to classify the data in less computational time with higher accuracy. In this proposed research, a novel feature selection method which combines the document frequency and the term frequency (FS-DFTF) is used to measure the significance of a term. The optimal feature subset which is selected by our proposed work is evaluated using Naive Bayes and Support Vector Machine classifier with various popular benchmark text corpus datasets. The experimental outcome confirms that the proposed method has a better classification accuracy when compared with other feature selection techniques

A Study on Kalanjagapadai

The disease Psoriasis was comparatively studied with the disease Kalanjaga padai. In considering the following three important facts that, Psoriasis has been linked to an increased risk of stroke and atrial fibrillation (ole Ahuhoff et al., 2011), its important complication in many patients is psoriatic arthritis (Gelfand IM et al., 2005) and Long term toxicities are observed with all currently available system treatments (European Medicine agency Journal), it is a need to evaluate the safe and effective drug for the treatment of psoriasis. For this a clinical trial with internal medicine Neeradi muthu vallathy melugu and external medicine kalapai kilangu velipoochu in meeting the disease psoriasis was conducted. For this 40 cases were selected. The pre clinical studies of the trial drug were found to be encouraging. Out of 40 cases 30 were treated in OPD and remaining 10 in IPD of Govt. Siddha Medical College & Hospital Palayamkottai. Some of the complementary therapies were followed along the course of the treatment. Complete proforma was maintained for each and every patient. Daily progress was observed to note the clinical efficacy of the drug. The results obtained were found to be auspicious. Pre clinical pharmacological analysis of the trial drug had 1. Significant anti histamine action. 2. Significant acute anti inflammatory actions. 3. Moderate chronic anti-inflammatory actions. 4. Significant analgesic action No adverse reactions like nausea, vomiting, diarrhoea, abdominal discomfort, drowsiness were reported during the study period. Hence the trial drug was found to be safe and effective. CONCLUSION: In this clinical study “Neeradi muthu vallathy melugu” and “kalapai kilangu velipuchu” were taken as Internal & External drug respectively for treating the disease Kalanjaga padai. The Overall results of efficacy of the trial drugs along with complementary therapies by reducing the clinical signs and symptoms like Itching, Scaling and erythema in this Clinical study were found to be Good in 67.5% cases, Moderate in 25% cases and Mild in 7.5%. The costs of the trial medicines are relatively economical. The raw drugs are easily available and the preparation is also convenient. No adverse effects and side effects were found clinically for the trial drugs. So the study proved conclusively that the clinical effects of the trial drugs were found to be good in treating the disease Psoriasis

A collage of results on the divisibility and indivisibility of class numbers of quadratic fields

The investigation of the ideal class group $Cl_K$ of an algebraic number field $K$ is one of the key subjects of inquiry in algebraic number theory since it encodes a lot of arithmetic information about K. There is a considerable amount of research on many topics linked to quadratic field class groups notably intriguing aspect is the divisibility of the class numbers. This article discusses a few recent results on the divisibility of class numbers and the Izuka conjecture. We also discuss the quantitative aspect of the Izuka conjecture.Comment: Comments are welcome.11 page

ParaQG: A System for Generating Questions and Answers from Paragraphs

Generating syntactically and semantically valid and relevant questions from paragraphs is useful with many applications. Manual generation is a labour-intensive task, as it requires the reading, parsing and understanding of long passages of text. A number of question generation models based on sequence-to-sequence techniques have recently been proposed. Most of them generate questions from sentences only, and none of them is publicly available as an easy-to-use service. In this paper, we demonstrate ParaQG, a Web-based system for generating questions from sentences and paragraphs. ParaQG incorporates a number of novel functionalities to make the question generation process user-friendly. It provides an interactive interface for a user to select answers with visual insights on generation of questions. It also employs various faceted views to group similar questions as well as filtering techniques to eliminate unanswerable questionsComment: EMNLP 201

Surface Defect incorporated Diamond Machining of Silicon

This paper reports the performance enhancement benefits in diamond turning of the silicon wafer by incorporation of the Surface Defect Machining (SDM) method. The hybrid micromachining methods usually require additional hardware to leverage the added advantage of hybrid technologies such as laser heating, cryogenic cooling, electric pulse or ultrasonic elliptical vibration. The SDM method tested in this paper does not require any such additional baggage and is easy to implement in a sequential micro-machining mode. This paper made use of Raman spectroscopy data, average surface roughness data and imaging data of the cutting chips of silicon for drawing a comparison between conventional Single Point Diamond Turning (SPDT) and SDM while incorporating surface defects in the (i) circumferential and (ii) radial directions. Complimentary 3D Finite Element Analysis (FEA) was performed to analyse the cutting forces and the evolution of residual stress on the machined wafer. It was found that the surface defects generated in the circumferential direction with an interspacing of 1 mm revealed the lowest average surface roughness (Ra) of 3.2 nm as opposed to 8 nm Ra obtained through conventional SPDT using the same cutting parameters. The observation of the Raman spectroscopy performed on the cutting chips showed remnants of phase transformation during the micromachining process in all cases. FEA was used to extract quantifiable information about the residual stress as well as the sub-surface integrity and it was discovered that the grooves made in the circumferential direction gave the best machining performance. The information being reported here is expected to provide an avalanche of opportunities in the SPDT area for low-cost machining solution for a range of other nominal hard, brittle materials such as SiC, ZnSe and GaAs as well as hard steels

Surface defects incorporated diamond machining of silicon

Abstract This paper reports the performance enhancement benefits in diamond turning of the silicon wafer by incorporation of the surface defect machining (SDM) method. The hybrid micromachining methods usually require additional hardware to leverage the added advantage of hybrid technologies such as laser heating, cryogenic cooling, electric pulse or ultrasonic elliptical vibration. The SDM method tested in this paper does not require any such additional baggage and is easy to implement in a sequential micro-machining mode. This paper made use of Raman spectroscopy data, average surface roughness data and imaging data of the cutting chips of silicon for drawing a comparison between conventional single-point diamond turning (SPDT) and SDM while incorporating surface defects in the (i) circumferential and (ii) radial directions. Complementary 3D finite element analysis (FEA) was performed to analyse the cutting forces and the evolution of residual stress on the machined wafer. It was found that the surface defects generated in the circumferential direction with an interspacing of 1 mm revealed the lowest average surface roughness (Ra) of 3.2 nm as opposed to 8 nm Ra obtained through conventional SPDT using the same cutting parameters. The observation of the Raman spectroscopy performed on the cutting chips showed remnants of phase transformation during the micromachining process in all cases. FEA was used to extract quantifiable information about the residual stress as well as the sub-surface integrity and it was discovered that the grooves made in the circumferential direction gave the best machining performance. The information being reported here is expected to provide an avalanche of opportunities in the SPDT area for low-cost machining solution for a range of other nominal hard, brittle materials such as SiC, ZnSe and GaAs as well as hard steels.</jats:p

Generation of SARS-CoV-2 escape mutations by monoclonal antibody therapy

COVID-19 patients at risk of severe disease may be treated with neutralising monoclonal antibodies (mAbs). To minimise virus escape from neutralisation these are administered as combinations e.g. casirivimab+imdevimab or, for antibodies targeting relatively conserved regions, individually e.g. sotrovimab. Unprecedented genomic surveillance of SARS-CoV-2 in the UK has enabled a genome-first approach to detect emerging drug resistance in Delta and Omicron cases treated with casirivimab+imdevimab and sotrovimab respectively. Mutations occur within the antibody epitopes and for casirivimab+imdevimab multiple mutations are present on contiguous raw reads, simultaneously affecting both components. Using surface plasmon resonance and pseudoviral neutralisation assays we demonstrate these mutations reduce or completely abrogate antibody affinity and neutralising activity, suggesting they are driven by immune evasion. In addition, we show that some mutations also reduce the neutralising activity of vaccine-induced serum