Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to ...rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein-ligand-based pharmacophore models ('toxicophores') for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes.
Natural products play a significant role in drug discovery and development. Many topological pharmacophore patterns are common between natural products and commercial drugs. A better understanding of ...the specific physicochemical and structural features of natural products is important for corresponding drug development. Several encyclopedias of natural compounds have been composed, but the information remains scattered or not freely available. The first version of the Supernatural database containing ∼ 50,000 compounds was published in 2006 to face these challenges. Here we present a new, updated and expanded version of natural product database, Super Natural II (http://bioinformatics.charite.de/supernatural), comprising ∼ 326,000 molecules. It provides all corresponding 2D structures, the most important structural and physicochemical properties, the predicted toxicity class for ∼ 170,000 compounds and the vendor information for the vast majority of compounds. The new version allows a template-based search for similar compounds as well as a search for compound names, vendors, specific physical properties or any substructures. Super Natural II also provides information about the pathways associated with synthesis and degradation of the natural products, as well as their mechanism of action with respect to structurally similar drugs and their target proteins.
The real-world evidence data from multiple sources which includes information on patient health status and medical behavior in routine clinical setup can give deeper insights into drugs 'safety and ...efficacy. The RWE-based analysis in this study revealed a statistically significant link between biologics usage and hepatotoxicity in patients. To the best of our knowledge, this study is the first to conduct a large-scale multi-cohort analysis on the hepatotoxic profiles of biologics. Biologics are among the most prescribed medicines for several chronic inflammatory diseases. These agents target critical pathogenic pathways, but they may also have serious side effects. It is important to analyze whether biologics agents are an added concern or therapeutic opportunity. Real-world evidence (RWE) data were extracted for patients using biologics to monitor the safety and effectiveness of the biologics. All six biologics included in this analysis-are mostly highly prescribed biologics. The aim of the study was to assess the hepatotoxic profiles of subjects using different biologics. We evaluated the safety of current treatment regimens for patients in a large real-world cohort from multiple health care centers. Total number of eligible patients retrieved from the database is 38,112,285. Of these 38 million patients, 2.3 million take biologics. The primary objective was to assess the potential adverse hepatotoxic effects of the six biologics; adalimumab, trastuzumab, prevnar13, pegfilgrastim, interferon-beta1a and insulin glargine across different indications like diabetes mellitus, encounter for immunization, malignant neoplasm of breast, multiple sclerosis, malignant neoplasm of kidney, aplastic anaemias, radiation sickness, Crohn's disease, psoriasis, rheumatoid arthritis, spondylopathies. Data from patients using the six most-used biologics-adalimumab, trastuzumab, prevnar13, pegfilgrastim, interferon-beta1a and insulin glargine were retrieved from a global research network covering 250 million patients' data from 19 countries, and assigned to the cohorts 1 and 2, respectively. The cohorts were propensity score matched for age and sex. After defining the primary outcome as "hepatotoxicity" (endpoint defined as ICD-10 code: K71 (hepatotoxic liver disease), a Kaplan-Meier survival analysis was performed, and risk ratios (RR), odds ratios (OR), and hazard ratios (HR) were determined. A total number of 2,312,655 subjects were eligible who take biologics, and after matching total cohorts accounted for 2,303,445. We have considered the clinical data as a 1:1 matched-study design, using propensity score-matched sub-cohorts to better control for confounding associations that might stem from different distributions of age and gender between the whole dataset and the subset of patients. We discovered evidence supporting the hepatotoxic-causing effect of biologic drugs: (i) all biologics considered together had an OR of 1.9 (95% CI, 1.67-2.35), with (ii) Adalimumab 1.9 (95% CI, 1.72-2.20), Trastuzumab 1.7 (95% CI, 1.2-2.3), Prevnar13 2.3 (95% CI, 2.16-2.60), Pegfilgrastim 2.3 (95% CI, 2.0-2.50), Interferon-Beta1a 1.7 (95% CI, 1.18-2.51), and Insulin glargine 1.9 (95% CI, 1.8-1.99). Our findings indicate that clinicians should consider evaluating hepatic profiles of patients undergoing treatment with biologic drugs and counsel them regarding the risk of developing hepatic injury. Strengths of the study includes a large sample size and robust statistical techniques. Limitations of this study include lack of detailed information regarding clinical severity. Major biologics are associated with hepatotoxicity. We discovered evidence supporting the hepatotoxicity-causing effects of biologics: all biologics considered together had an OR of 1.9 (95% CI, 1.67-2.35).
Increase in the number of new chemicals synthesized in past decades has resulted in constant growth in the development and application of computational models for prediction of activity as well as ...safety profiles of the chemicals. Most of the time, such computational models and its application must deal with imbalanced chemical data. It is indeed a challenge to construct a classifier using imbalanced data set. In this study, we analyzed and validated the importance of different sampling methods over non-sampling method, to achieve a well-balanced sensitivity and specificity of a machine learning model trained on imbalanced chemical data. Additionally, this study has achieved an accuracy of 93.00%, an AUC of 0.94, F1 measure of 0.90, sensitivity of 96.00% and specificity of 91.00% using SMOTE sampling and Random Forest classifier for the prediction of Drug Induced Liver Injury (DILI). Our results suggest that, irrespective of data set used, sampling methods can have major influence on reducing the gap between sensitivity and specificity of a model. This study demonstrates the efficacy of different sampling methods for class imbalanced problem using binary chemical data sets.
Airway smooth muscle (ASM) is known for its role in asthma exacerbations characterized by acute bronchoconstriction and remodeling. The molecular mechanisms underlying multiple gene interactions ...regulating gene expression in asthma remain elusive. Herein, we explored the regulatory relationship between ASM genes to uncover the putative mechanism underlying asthma in humans. To this end, the gene expression from human ASM was measured with RNA-Seq in non-asthmatic and asthmatic groups. The gene network for the asthmatic and non-asthmatic group was constructed by prioritizing differentially expressed genes (DEGs) (121) and transcription factors (TFs) (116). Furthermore, we identified differentially connected or co-expressed genes in each group. The asthmatic group showed a loss of gene connectivity due to the rewiring of major regulators. Notably, TFs such as ZNF792, SMAD1, and SMAD7 were differentially correlated in the asthmatic ASM. Additionally, the DEGs, TFs, and differentially connected genes over-represented in the pathways involved with herpes simplex virus infection, Hippo and TGF-β signaling, adherens junctions, gap junctions, and ferroptosis. The rewiring of major regulators unveiled in this study likely modulates the expression of gene-targets as an adaptive response to asthma. These multiple gene interactions pointed out novel targets and pathways for asthma exacerbations.
We have investigated photo-response as well as resistive switching behaviour in hybrid zinc oxide (ZnO)/reduced graphene oxide (rGO) bilayer thin film, equipped through sol–gel process on an ITO ...coated glass substrate under the dark and variation of light illumination. This ZnO/rGO photodetector reveals a stout photocurrent dependency on the colour of the lights illuminating (white and red laser light), where the magnitude of photocurrent has been found to increase exponentially with the increase in energy of photons of the incident light. In the same device, we have observed resistive switching behaviour and polarity effect of SET/RESET bias similar to that exhibited by the non-volatile memory device (NVRAM). The
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is approximately 60 at bias voltage 2 V. We have explained this feature in light of filament formation and biasing effect on it. Photo annealing has been done to reduce GO to rGO for fabricating this device on ITO-coated glass substrate. Our study on electrical characterization of the ITO/ZnO/rGO/Au device explores the coexistence of photo-response and memresistive characteristics, which could be potential for developing multifunctional photodetector with memory effect.
Diseases related to the central nervous system (CNS) are major health concerns and have serious social and economic impacts. Developing new drugs for CNS-related disorders presents a major challenge ...as it actively involves delivering drugs into the CNS. Therefore, it is imperative to develop in silico methodologies to reliably identify potential lead compounds that can penetrate the blood-brain barrier (BBB) and help to thoroughly understand the role of different physicochemical properties fundamental to the BBB permeation of molecules. In this study, we have analysed the chemical space of the CNS drugs and compared it to the non-CNS-approved drugs. Additionally, we have collected a feature selection dataset from Muehlbacher et al. (J Comput Aided Mol Des 25(12):1095-1106, 2011. 10.1007/s10822-011-9478-1) and an in-house dataset. This information was utilised to design a molecular fingerprint that was used to train machine learning (ML) models. The best-performing models reported in this study achieved accuracies of 0.997 and 0.98, sensitivities of 1.0 and 0.992, specificities of 0.971 and 0.962, MCCs of 0.984 and 0.958, and ROC-AUCs of 0.997 and 0.999 on an imbalanced and a balanced dataset, respectively. They demonstrated overall good accuracies and sensitivities in the blind validation dataset. The reported models can be applied for fast and early screening drug-like molecules with BBB potential. Furthermore, the bbbPythoN package can be used by the research community to both produce the BBB-specific molecular fingerprints and employ the models mentioned earlier for BBB-permeability prediction.
Mineral dust is known to affect many aspects of the climate of the north Indian Ocean (IO). However, what controls its interannual variability over this region is largely unknown. The authors study ...the mechanism controlling the interannual variability of dust aerosols in the principal dust belts bordering the northwest IO. It is shown that annual dust activity to the north of the Persian Gulf has an inverse relation with preceding precipitation during October–December and soil moisture during current dust season (April–August). These are in turn remotely controlled by El Niño–Southern Oscillation (ENSO) through the modification of the intensity of convection over the Indo-Pacific warm pool region, which affects moisture flux to the dust sources. While La Niña leads to a negative precipitation anomaly and more dust generation during the following summer, El Niño is responsible for the opposite. During the summer following La Niña, the air–sea interaction leads to a lowering of geopotential height over the Indo-Iranian region, resulting in an increased gradient between the Indo-Iranian region and the surrounding regions. This intensifies the dust-transporting northwesterly and northeasterly winds over the Arabian Peninsula. The dust transport by the intensified low-level southwesterlies and upper-level westerlies is the main factor responsible for enhanced dust over the open northwest IO during the years following La Niña. The Indian Ocean dipole potentially impacts the variability of dust over the northwest IO by modifying the moisture associated with El Niño.
Cellular senescence-the irreversible cell cycle arrest driven by a variety of mechanisms and, more specifically, the senescence-associated secretory phenotype (SASP)-is an important area of research ...in the context of different age-related diseases, such as cardiovascular disease and cancer. SASP factors play both beneficial and detrimental roles in age-related disease progression depending on the source of the SASPs, the target cells, and the microenvironment. The impact of senescence and the SASP on different cell types, the immune system, and the vascular system has been widely discussed. However, the impact of replicative or stress-induced senescence on lymphatic biology and pathological lymphangiogenesis remains underexplored. The lymphatic system plays a crucial role in the maintenance of body fluid homeostasis and immune surveillance. The perturbation of lymphatic function can hamper normal physiological function. Natural aging or stress-induced premature aging influences the lymphatic vessel structure and function, which significantly affect the role of lymphatics in tumor dissemination and metastasis. In this review, we focus on the role of senescence on lymphatic pathobiology, its impact on cancer, and potential therapeutic interventions to manipulate the aged or senescent lymphatic system for disease management.
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