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The delivery of significant concentrations of biologically active free curcuminoids (curcumin, demethoxycurcumin and bisdemethoxycurcumin) at the target tissues has always been regarded as a major limitation for the efficacy of curcumin. Herein we report the blood–brain-barrier permeability, tissue distribution and enhanced bioavailability of free curcuminoids following the oral administration of a food grade curcumin formulation in comparison with the standardized native curcumin, for the first time. UPLC-ESI-MS/MS analyses of post-administration tissue samples of Wistar rats (200 mg/kg body weight) demonstrated significant (p

Computational methods have been established as cornerstones in optical imaging and holography in recent years. Every year, the dependence of optical imaging and holography on computational methods is increasing significantly to the extent that optical methods and components are being completely and efficiently replaced with computational methods at low cost. This roadmap reviews the current scenario in four major areas namely incoherent digital holography, quantitative phase imaging, imaging through scattering layers, and super-resolution imaging. In addition to registering the perspectives of the modern-day architects of the above research areas, the roadmap also reports some of the latest studies on the topic. Computational codes and pseudocodes are presented for computational methods in a plug-and-play fashion for readers to not only read and understand but also practice the latest algorithms with their data. We believe that this roadmap will be a valuable tool for analyzing the current trends in computational methods to predict and prepare the future of computational methods in optical imaging and holography. [ABSTRACT FROM AUTHOR]

The given text provides information on various developments in the pharmaceutical industry in India. The Indian Government has implemented new rules to fast-track the launch of breakthrough drugs, while the US House of Representatives has passed a bill to improve access to orphan drugs. Indian companies are also succeeding in patent litigations against global pharmaceutical giants, indicating a more balanced approach to patent rights and patient access to healthcare. The text also mentions the High Court of Madras directing an enquiry about a banned anti-diabetic drug and highlights the potential for discovering new drugs from herbal resources. Additionally, it briefly mentions Dr. Gopakumar G. Nair, the editor of Indian Drugs, without providing specific information about the content of the publication. [Extracted from the article]

This article explores the United Nations' Sustainable Development Goals (SDGs) and their relevance to the pharmaceutical and healthcare industry. It emphasizes the importance of addressing market needs and gaps to increase the commercialization of innovations. The article also highlights the connection between intellectual property (IP) and the SDGs, encouraging Indian universities and research institutions to undertake projects related to the 17 listed SDGs. It further discusses the potential for discovering new drugs from herbal resources and the significance of research on biomolecules. The text briefly introduces Gopakumar Nair, who has established his own boutique IP firm and holds positions in various educational institutions. Readers are provided with contact information to provide feedback on the editorial. [Extracted from the article]

The electronic structure of the 5-dehydro-meta-xylylene (DMX) triradical and its two-nitrogen and two-phosphorus derivatives are analyzed. The analysis is conducted using state-averaged complete active space self-consistent-field (CASSCF) followed by second-order multistate multiconfiguration perturbation theories MS-CASPT2 and MR-QDPT in conjunction with large ANO-L and the 6-311G(d,p) basis.

The past few years have witnessed machine learning techniques take the limelight in multiple research domains. One such domain that has reaped the benefits of machine learning is computer-aided drug discovery, where the search space for candidate drug molecules is decreased using methods such as virtual screening. Current state-of-the-art sequential neural network models have shown promising results and we would like to replicate similar results with virtual screening using the encoded molecular information known as simplified molecular-input line-entry system (SMILES). Our work includes the use of attention-based sequential models — the long short-term memory with attention and an optimized version of the transformer network specifically designed to deal with SMILES (ChemBERTa). We also propose the "Overall Screening Efficacy", an averaging metric that aggregates and encapsulates the model performance over multiple datasets. We found an overall improvement of about 2 7 % over the benchmark model, which relied on parallelized random forests. Our work consists of training two sequence models over the SMILES dataset - the LSTM with Attention model and a pre-trained ChemBERTa model to help optimize and accelerate the virtual screening pipeline. We propose the use of a new metric - "Overall Screening Efficacy", which takes the weighted average of F1-scores over multiple datasets and favours the ones that are more imbalanced. Comparative analysis showed that our models improved by up to 27% over the benchmark model, which used parallelized Random Forests on a GPU environment. [ABSTRACT FROM AUTHOR]

The article focuses on the need for greater involvement of the Indian research community in policy-making related to research and innovation, particularly concerning regulatory aspects that affect researchers' work. It highlights ongoing developments in intellectual property rights (IPR) regime reviews and amendments, emphasizing the importance of providing feedback to ensure a conducive environment for research.

The article discusses the crucial connection between regulatory policies and research and innovation in the pharmaceutical industry. It highlights the historical significance of natural product research in India, emphasizing the need for renewed interest and participation in herbal and natural product research, especially in light of regulatory challenges imposed by the Biodiversity Act.

The angular distribution of O 1s photoelectrons emitted from uniaxially oriented methanol is studied experimentally and theoretically. We employed circularly polarized photons of an energy of hν = 550 eV for our investigations. We measured the three-dimensional photoelectron angular distributions of methanol, with the CH3–OH axis oriented in the polarization plane, by means of cold target recoil ion momentum spectroscopy. The experimental results are interpreted by single active electron calculations performed with the single center method. A comparative theoretical study of the respective molecular-frame angular distributions of O 1s photoelectrons of CO, performed for the same photoelectron kinetic energy and for a set of different internuclear distances, allows for disentangling the role of internuclear distance and the hydrogen atoms of methanol as compared to carbon monoxide. [ABSTRACT FROM AUTHOR]

Cell survival requires the presence of essential proteins. Detection of essential proteins is relevant not only because of the critical biological functions they perform but also the role played by them as a drug target against pathogens. Several computational techniques are in place to identify essential proteins based on protein–protein interaction (PPI) network. Essential protein detection using only physical interaction data of proteins is challenging due to its inherent uncertainty. Hence, in this work, we propose a multiplex network-based framework that incorporates multiple protein interaction data from their physical, coexpression and phylogenetic profiles. An extended version termed as multiplex eigenvector centrality (MEC) is used to identify essential proteins from this network. The methodology integrates the score obtained from the multiplex analysis with subcellular localization and Gene Ontology information and is implemented using Saccharomyces cerevisiae datasets. The proposed method outperformed many recent essential protein prediction techniques in the literature. [ABSTRACT FROM AUTHOR]

Quantum chemical calculations were applied to investigate the electronic structure of mono-, di-, and trilithiated digermanium (Ge2Lin) and their cations (n=0–3). Computations using a multiconfigurational quasidegenerate perturbation approach based on complete active space self-consistent-field wave functions, and density functional theory reveal that Ge2Li has a 2B1 ground state with a doublet-quartet energy gap of 33 kcal/mol. Ge2Li2 has a singlet ground state with a 3Au-1A1 gap of 29 kcal/mol, and Ge2Li3 a doublet ground state with a 4B2-2A2 separation of 22 kcal/mol. The cation Ge2Li+ has a 3B1 ground state, being 13 kcal/mol below the open-shell 1B1 state. The computed electron affinities for diatomic germanium are EA(1)=1.9 eV, EA(2)=-2.5 eV, and EA(3)=-6.0 eV, for Ge2-, Ge22-, and Ge23-, respectively, indicating that only the monoanion is stable with respect to electron detachment, in such a way that Ge2Li is composed by Ge2-·Li+ ions. An “atoms-in-molecules” analysis shows the absence of a ring critical point in Ge2Li. An electron localization function analysis on Ge2Li supports the view that the Ge–Li bond is predominantly ionic; however, a small covalent character could be anticipated from the analysis of the Laplacian at the Ge–Li bond critical point. The ionic picture of the Ge–Li bond is further supported by a natural-bond-order analysis and the Laplacian of the electron density. The calculated Li affinity value for Ge2 is 2.08 eV, while the Li+ cation affinity value for Ge2- is 5.7 eV. The larger Li+ cation affinity value of Ge2- suggests a Ge2-Li+ interaction and thus supports the ionic nature of Ge–Li bond. In GeLi4 and Ge2Li, the presence of trisynaptic basins indicates a three-center bond connecting the germanium and lithium atoms. [ABSTRACT FROM AUTHOR]

Quantum chemical calculations are used for examining the structure and properties of small neutral and cationic Cr[Ge.sub.n.sup.0,+) (n = 1-5) clusters. Electron localization function (ELF) analyses have shown that the chemical bonding in chromium-doped germanium clusters have differed from that of their pure or Li-doped counterparts and have allowed the origin of the inherent high-spin ground state to be described.

The electronic structure calculations are used to show that the borane molecule (B[H.sub.3]) act as an efficient bifunctional acid-base catalyst in the [H.sub.2] elimination reactions of X[H.sub.n]Y[H.sub.n] systems (X, Y=C, B, N). It is found that the B[H.sub.3] acts as a bifunctional catalyst facilitating H-transfer leading to [H.sub.2] bond formation.

Background and study aims Advanced endoscopic resection techniques carry a risk of delayed bleeding (DB). A novel fully synthetic self-assembling peptide (SAP) has shown promising results in mitigating this risk. In this meta-analysis, we evaluated all available data and analyzed the effectiveness of SAP in reducing DB after advanced endoscopic resection of gastrointestinal luminal lesions.

The article presents the discussion on pharmaceutical research laboratory in India having a distinguished track record in drug discovery research. Topics include team being granted many US and Indian patents, including those licensed to Industry for commercialization as described above; and Radha Rangarajan is also deeply involved in translational research and product development in the public health arena for the last two decade.