International Life Sciences Institute

Advances in QSAR are led by two core paradigms, 1) descriptor engineering, where complex fixedlength vectors of compounds are generated and conventional ML methods are applied to those representations and 2) raw chemical inputs (e.g., SMILES, 2D-graph) being provided to deep learning neural network models, which construct their own internal representations of molecules and learn iteratively over them.Here we present the Tsetlin Machine (TM) -which combines the accuracy and easy-use of existing rule-based QSAR ML methods (e.g., RF and XGBoost), the iterative learning aspect of NN algorithms and its intrinsic interpretability.The TM uses teams of finite-state automata which capture frequent patterns as propositional logic (clauses) via reinforcement learning.The benchmarking pipeline presented here demonstrates that TM-QSAR coupled with ECFP4 descriptors frequently performs better than existing rule-based QSAR methods for ROC-AUC, PRC-AUC and PPV, with a high capacity for inter-scaffold generalisation.However, due to the binary nature of TM-QSAR, performance it is currently limited when descretised continuous descriptors are used.TM-QSAR demonstrated particularly impressive classification scores for MOR (ROC-AUC = 0.87, PRC-AUC = 0.77) and CYPA4 (ROC-AUC = 0.92, PRC-AUC = 0.63), when compared to RF and XGBoost.Using TM in combination with substructural fingerprinting descriptors allows for an interpretability suite which can be extracted directly from clauses.Here we detail molecule property maps (TM-MPM) to view atom-wise TM-QSAR bioactivity contributions for single molecules and closed-form WAC scores (Weights Activations Clauses) for descriptor-wise contributions to regions of predicted chemical space.These methods show strong alignment of TM-QSAR interpretations to known ligandprotein interactions of the MOR target and gives non-linear, conditional interpretations for greater predicted bioactivity.Given this combination of accuracy, computational efficiency and interpretability, we provide a basis for TM-QSAR to be explored as a standard methodology in virtual screening toolkits.

Plasmodium falciparum dihydrofolate reductase (PfDHFR) is an essential enzyme in the development of parasitic DNA and its inhibition often leads to the impediment of parasite growth. Several studies have also shown that a genetic mutation in this enzyme can cause reduced receptor responsiveness and efficacy of antimalarial drugs. Therefore, this study aimed to examine 100 compounds derived from Indonesian medicinal plants as potential antimalarial candidates using a structure-based virtual screening approach. The PASS online was used to screen 100 compounds, and those with Pa values higher than 0.3 were docked with the wild-type (PDB code:1j3i) and quadrupole mutant PfDHFR (PDB code:1j3k). The stability of the chemical complex was then examined using molecular dynamics simulations, followed by an assessment of the pharmacokinetic profile and drug-likeness parameters. The top 5 compounds were then identified with binding energies ranging from -9.7 to -10.0 kcal/mol for the wild-type PfDHFR-TS and from -9.2 to -10.0 kcal/mol for the quadrupole mutant PfDHFR. The results showed that compound C90 exhibited the most stable and impressive score in its pharmacokinetic and drug-likeness assessment.

近年来,对益生元和益生菌作用机制的科学认识有了很大的发展。虽然保健功效往往来自菌株及其产品的特异性,但一些益生元和益生 菌的保健作用可能是由它们的互作机制驱动的,并且可能是可遗传的。在多学科研究环境中使用新兴的生理学和分析工具将有助于进一步 阐明其作用机制。通过这种方式,将有可能提高对人们对益生元、益生菌和合生元保健作用的理解。本简版专论的编写基于最新的科学证据,是一本有价值的参考书, 旨在向广大读者介绍肠道微生物群以及益生元和益生菌的健康概念。

Health-care expenses have been projected to increase from 17.7% of the U.S. gross domestic product (GDP) in 2014 to 19.6% in 2024. The unsustainable increase in health-care costs has contributed toward support for value-based health care (VBHC) reform. Contemporary VBHC reform programs relevant to orthopaedic surgery include the voluntary Bundled Payments for Care Improvement initiatives (BPCI and BPCI-Advanced) and the Comprehensive Care for Joint Replacement (CJR) program, a mandatory bundled payment program.The purported benefits of transitioning from volume-based reimbursement to value-based reimbursement include moving from a fragmented provider-centered care model to a patient-centered model, with greater care coordination and alignment among providers focused on improving value. VBHC models allow innovative strategies to proactively invest resources to promote value (e.g., the use of nurse navigators) while eliminating unnecessary resources that do not promote value. However, major concerns regarding VBHC include the absence of medical and socioeconomic risk stratification as well as decreased access for higher-risk patients.This article identifies the benefits and potential unintended consequences of VBHC reform, with a focus on joint arthroplasty. We also discuss some potential strategies to promote innovation and improve value without compromising access for vulnerable patients.

Introduction: The Cabo Verde Telemedicine program (CVTP) was established by the International Virtual e-Hospital Foundation using the Initiate-Build-Operate-Transfer strategy to improve access to specialty care for the population in the archipelago of Cabo Verde in 2012. Since its inception, the CVTP has proven a great success story of telemedicine in Africa. Our first report on the initial results of a nationwide CVTP was published in 2014. The aim of this article is to analyze the follow-up data and analyze the activity of CVTP. Methods: All telemedicine consultations of the CVTP from 2014 to 2018 were analyzed. Patient demographics, clinical discipline, and transfer status were analyzed. Categorical variables were compared with a chi-squared test. Results: There were 2,442 telemedicine consultations in 24 clinical programs performed during the study period. The most common clinical disciplines with >100 consultations were neurology, cardiology, orthopedic surgery, general surgery, endocrinology, otolaryngology, urology, and dermatology. Overall, the transfer rate was 34.3%. Conclusion: The nationwide CVTP continues to increase access to specialized care, prevent unnecessary and costly transfers, and has become a great success story of telemedicine in Africa. Moreover, this program should serve as a model for establishing island-nations telemedicine programs worldwide.

Ethanol and nicotine are two common substances that are often linked to complications in alcoholic smokers. The high number of the co-consumptions in alcoholic smokers suggested a possible interaction between ethanol and nicotine in the central nervous system and a potential similar mechanism of action. Both ethanol and nicotine are shown to bind with neuronal nicotinic acetylcholine receptors (nAChRs), a ligand gated cation channel specifically targeted by the endogenous acetylcholine. Ethanol has a much less specific binding capability to modulate the receptors, however, emerging reports indicates that ethanol can interact with nAChRs both directly and indirectly. This study focuses on the analysis of ethanol binding sites with nAChRs using molecular docking techniques obtained from the Protein Data Bank. The obtained data showed a possible binding site for ethanol in nAChRs, however, upon validation, result is not substantial. Nevertheless, the obtained data should be useful for future reference for the basis of ethanol interactions with the human nAChRs proteins.

A Scientific Integrity Consortium developed a set of recommended principles and best practices that can be used broadly across scientific disciplines as a mechanism for consensus on scientific integrity standards and to better equip scientists to operate in a rapidly changing research environment. The two principles that represent the umbrella under which scientific processes should operate are as follows: (1) Foster a culture of integrity in the scientific process. (2) Evidence-based policy interests may have legitimate roles to play in influencing aspects of the research process, but those roles should not interfere with scientific integrity. The nine best practices for instilling scientific integrity in the implementation of these two overarching principles are (1) Require universal training in robust scientific methods, in the use of appropriate experimental design and statistics, and in responsible research practices for scientists at all levels, with the training content regularly updated and presented by qualified scientists. (2) Strengthen scientific integrity oversight and processes throughout the research continuum with a focus on training in ethics and conduct. (3) Encourage reproducibility of research through transparency. (4) Strive to establish open science as the standard operating procedure throughout the scientific enterprise. (5) Develop and implement educational tools to teach communication skills that uphold scientific integrity. (6) Strive to identify ways to further strengthen the peer review process. (7) Encourage scientific journals to publish unanticipated findings that meet standards of quality and scientific integrity. (8) Seek harmonization and implementation among journals of rapid, consistent, and transparent processes for correction and/or retraction of published papers. (9) Design rigorous and comprehensive evaluation criteria that recognize and reward the highest standards of integrity in scientific research.

Interpretation of positive genotoxicity findings using the current in vitro testing battery is a major challenge to industry and regulatory agencies. These tests, especially mammalian cell assays, have high sensitivity but suffer from low specificity, leading to high rates of irrelevant positive findings (i.e., positive results in vitro that are not relevant to human cancer hazard). We developed an in vitro transcriptomic biomarker-based approach that provides biological relevance to positive genotoxicity assay data, particularly for in vitro chromosome damage assays, and propose its application for assessing the relevance of the in vitro positive results to carcinogenic hazard. The transcriptomic biomarker TGx-DDI (previously known as TGx-28.65) readily distinguishes DNA damage-inducing (DDI) agents from non-DDI agents. In this study, we demonstrated the ability of the biomarker to classify 45 test agents across a broad set of chemical classes as DDI or non-DDI. Furthermore, we assessed the biomarker's utility in derisking known irrelevant positive agents and evaluated its performance across analytical platforms. We correctly classified 90% (9 of 10) of chemicals with irrelevant positive findings in in vitro chromosome damage assays as negative. We developed a standardized experimental and analytical protocol for our transcriptomics biomarker, as well as an enhanced application of TGx-DDI for high-throughput cell-based genotoxicity testing using nCounter technology. This biomarker can be integrated in genetic hazard assessment as a follow-up to positive chromosome damage findings. In addition, we propose how it might be used in chemical screening and assessment. This approach offers an opportunity to significantly improve risk assessment and reduce cost.