A domain-label-guided translation model for molecular optimization.

Molecular optimization, which aims to improve molecular properties by modifying complex molecular structures, is a crucial and challenging task in drug discovery. In recent years, translation models provide a promising way to transform low-property molecules to high-property molecules, which enables molecular optimization to achieve remarkable progress. However, most existing models require matched molecular pairs, which are prone to be limited by the datasets. Although some models do not require matched molecular pairs, their performance is usually sacrificed due to the lack of useful supervising information. To address this issue, a domain-label-guided translation model is proposed in this paper, namely DLTM. In the model, the domain label information of molecules is exploited as a control condition to obtain different embedding representations, enabling the model to generate diverse molecules. Besides, the model adopts a classifier network to identify the property categories of transformed molecules, guiding the model to generate molecules with desired properties. The performance of DLTM is verified on two optimization tasks, namely the quantitative estimation of drug-likeness and penalized logP. Experimental results show that the proposed DLTM is superior to the compared baseline models.

A review on the antibiotic florfenicol: Occurrence, environmental fate, effects, and health risks.

Florfenicol, as a replacement for chloramphenicol, can tightly bind to the A site of the 23S rRNA in the 50S subunit of the 70S ribosome, thereby inhibiting protein synthesis and bacterial proliferation. Due to the widespread use in aquaculture and veterinary medicine, florfenicol has been detected in the aquatic environment worldwide. Concerns over the effects and health risks of florfenicol on target and non-target organisms have been raised in recent years. Although the ecotoxicity of florfenicol has been widely reported in different species, no attempt has been made to review the current research progress of florfenicol toxicity, hormesis, and its health risks posed to biota. In this study, a comprehensive literature review was conducted to summarize the effects of florfenicol on various organisms including bacteria, algae, invertebrates, fishes, birds, and mammals. The generation of antibiotic resistant bacteria and spread antibiotic resistant genes, closely associated with hormesis, are pressing environmental health issues stemming from overuse or misuse of antibiotics including florfenicol. Exposure to florfenicol at µg/L-mg/L induced hormetic effects in several algal species, and chromoplasts might serve as a target for florfenicol-induced effects; however, the underlying molecular mechanisms are completely lacking. Exposure to high levels (mg/L) of florfenicol modified the xenobiotic metabolism, antioxidant systems, and energy metabolism, resulting in hepatotoxicity, renal toxicity, immunotoxicity, developmental toxicity, reproductive toxicity, obesogenic effects, and hormesis in different animal species. Mitochondria and the associated energy metabolism are suggested to be the primary targets for florfenicol toxicity in animals, albeit further in-depth investigations are warranted for revealing the long-term effects (e.g., whole-life-cycle impacts, multigenerational effects) of florfenicol, especially at environmental levels, and the underlying mechanisms. This will facilitate the evaluation of potential hormetic effects and construction of adverse outcome pathways for environmental risk assessment and regulation of florfenicol.

Metabolomic Response of Thalassiosira weissflogii to Erythromycin Stress: Detoxification Systems, Steroidal Metabolites, and Energy Metabolism.

Erythromycin, a macrolide antibiotic, is a prioritized pollutant that poses a high risk to environmental health. It has been detected in different environmental matrices and can cause undesired effects in aquatic organisms, particularly freshwater algae, which are primary producers. However, the impact of erythromycin on marine algae remains largely unexplored. Erythromycin has been reported to induce hormetic effects in the marine diatom Thalassiosira weissflogii (T. weissflogii). These effects are associated with the molecular pathways and biological processes of ribosome assembly, protein translation, photosynthesis, and oxidative stress. However, the alterations in the global gene expression have yet to be validated at the metabolic level. The present study used non-targeted metabolomic analysis to reveal the altered metabolic profiles of T. weissflogii under erythromycin stress. The results showed that the increased cell density was possibly attributed to the accumulation of steroidal compounds with potential hormonic action at the metabolic level. Additionally, slight increases in the mitochondrial membrane potential (MMP) and viable cells were observed in the treatment of 0.001 mg/L of erythromycin (an environmentally realistic level). Contrarily, the 0.75 and 2.5 mg/L erythromycin treatments (corresponding to EC20 and EC50, respectively) showed decreases in the MMP, cell density, and viable algal cells, which were associated with modified metabolic pathways involving ATP-binding cassette (ABC) transporters, the metabolism of hydrocarbons and lipids, thiamine metabolism, and the metabolism of porphyrin and chlorophyll. These findings suggest that metabolomic analysis, as a complement to the measurement of apical endpoints, could provide novel insights into the molecular mechanisms of hormesis induced by antibiotic agents in algae.

Integration of Non-targeted Proteomics Mass Spectrometry with Machine Learning for Screening Cooked Beef Adulterated Samples.

The degradation of ingredients in heat-processed meat products makes their authentication challenging. In this study, protein profiles of raw beef, chicken, duck, pork, and binary simulated adulterated beef samples (chicken-beef, duck-beef, and pork-beef) and their heat-processed samples were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Heat-stable characteristic proteins were found by screening the overlapping characteristic protein ion peaks of the raw and corresponding heat-processed samples, which were discovered by partial least-squares discriminant analysis. Based on the 36 heat-stable characteristic proteins, qualitative classification for the raw and heat-processed meats was achieved by extreme gradient boosting. Moreover, quantitative analysis via partial least squares regression was applied to determine the adulteration ratio of the simulated adulterated beef samples. The validity of the approach was confirmed by a blind test with the mean accuracy of 97.4%. The limit of detection and limit of quantification of this method were determined to be 5 and 8%, respectively, showing its practical aspect for the beef authentication.