The use of 3d metals in de/hydrogenation catalysis has emerged as a competitive field with respect to “traditional” precious metal catalyzed transformations. The introduction of functional pincer ligands that can store protons and/or electrons as expressed by metal–ligand cooperativity and ligand redox-activity strongly stimulated this development as a conceptual starting point for rational catalyst design. This review aims at providing a comprehensive picture of the utilization of functional pincer ligands in first-row transition metal hydrogenation and dehydrogenation catalysis and related synthetic concepts relying on these such as the hydrogen borrowing methodology. Particular emphasis is put on the implementation and relevance of cooperating and redox-active pincer ligands within the mechanistic scenarios.

First-Row Transition Metal (De)Hydrogenation Catalysis Based On Functional Pincer Ligands.

The aim of this paper is 2-fold. First, we want to report the extension of our virtual multifrequency spectrometer (VMS) to anharmonic intensities for Raman optical activity (ROA) with the full inclusion of first- and second-order resonances for both frequencies and intensities in the framework of the generalized second-order vibrational perturbation theory (GVPT2) for all kinds of vibrational spectroscopies. Then, from a more general point of view, we want to present and validate the performance of VMS for the parallel analysis of different vibrational spectra for medium-sized molecules (IR, Raman, VCD, ROA) including both mechanical and electric/magnetic anharmonicity. For the well-known methyloxirane benchmark, careful selection of density functional, basis set, and resonance thresholds permitted us to reach qualitative and quantitative agreement between experimental and computed band positions and shapes. Next, the whole series of halogenated azetidinones is analyzed, showing that it is now possible t...

Anharmonic Effects on Vibrational Spectra Intensities: Infrared, Raman, Vibrational Circular Dichroism, and Raman Optical Activity.

The chemistry and biological potential of azetidin-2-ones.

Due to the widespread emergence of resistant bacterial strains, an urgent need for the development of new antibacterial agents with novel modes of action has emerged. The discovery of naturally occurring monocyclic β-lactams in the late 1970s, mainly active against aerobic Gram-negative bacteria, has introduced a new approach in the design and development of novel antibacterial β-lactam agents. The main goal was the derivatization of the azetidin-2-one core in order to improve their antibacterial potency, broaden their spectrum of activity, and enhance their β-lactamase stability. In that respect, our review covers the updates in the field of monocyclic β-lactam antibiotics during the last three decades, taking into account an extensive collection of references. An overview of the relationships between the structural features of these monocyclic β-lactams, classified according to their N-substituent, and the associated antibacterial or β-lactamase inhibitory activities is provided. The different paragraphs disclose a number of well-established classes of compounds, such as monobactams, monosulfactams, monocarbams, monophosphams, nocardicins, as well as other known representative classes. Moreover, this review draws attention to some less common but, nevertheless, possibly important types of monocyclic β-lactams and concludes by highlighting the recent developments on siderophore-conjugated classes of monocyclic β-lactams.

Antibacterial and β‐Lactamase Inhibitory Activity of Monocyclic β‐Lactams

Purine-beta-lactam chimera were prepared as a novel class of hybrid systems through N-alkylation of 6-benzylamino- or 6-benzyloxypurine with (omega-haloalkyl)-beta-lactams, followed by reductive ring opening of the beta-lactam ring by LiEt3BH to provide an entry into the class of purine-aminopropanol hybrids. Both new types of hybrid systems were assessed for their antiviral activity and cytotoxicity, resulting in the identification of eight purine-beta-lactam hybrids and two purine-aminopropanol hybrids as promising lead structures.

Design, synthesis, and antiviral evaluation of purine-β-lactam and purine-aminopropanol hybrids.

2-Azetidinone--a new profile of various pharmacological activities

2-azetidinone, a β-lactam four member heterocyclic compound involved in research aimed to evaluate new products that possess interesting biological activities. These compounds reported for their antimicrobial and antifungal activities. Successful introduction of aztreonam as a potent inhibitor of cephalosporinase and ezetimibe as a cholesterol absorption inhibitor proved potential of 2-azetidinone moiety. Subsequently 2-azetidinones were highlighted as a potent mechanism based inhibitor of several enzymes like human tryptase, chymase, thrombin, leukocyte elastase, human cytomegalovirus protease and serine protease enzyme. These derivatives also known to possess antitubercular, anti-inflammatory, antitumor, anti-HIV, antiparkinsonian, antidiabetic and vasopressin V1a antagonist activity. The present review article focuses on the pharmacological profile of 2-azetidinones with their potential activities.

2-Azetidinone — A New Profile of Various Pharmacological Activities.

A vision transformer based approach for analysis of plasmodium vivax life cycle for malaria prediction using thin blood smear microscopic images

EyeDeep-Net: a multi-class diagnosis of retinal diseases using deep neural network

Next Word Prediction involves guessing the next word which is most likely to come after the current word. The system suggests a few words. A user can choose a word according to their choice from a list of suggested word by system. It increases typing speed and reduces keystrokes of the user. It is also useful for disabled people to enter text slowly and for those who are not good with spellings. Previous studies focused on prediction of the next word in different languages. Some of them are Bangla, Assamese, Ukraine, Kurdish, English, and Hindi. According to Census 2011, 43.63% of the Indian population uses Hindi, the national language of India. In this work, deep learning techniques are proposed to predict the next word in Hindi language. The paper uses Long Short Term Memory and Bidirectional Long Short Term Memory as the base neural network architecture. The model proposed in this work outperformed the existing approaches and achieved the best accuracy among neural network based approaches on IITB English-Hindi parallel corpus.

N. P. S. Sengar

Papers

2-Azetidinone--a new profile of various pharmacological activities

2-Azetidinone — A New Profile of Various Pharmacological Activities.

A vision transformer based approach for analysis of plasmodium vivax life cycle for malaria prediction using thin blood smear microscopic images

EyeDeep-Net: a multi-class diagnosis of retinal diseases using deep neural network

Next Word Prediction Using Deep Learning