Identification and Prioritization of Emerging Organophosphorus Compounds Beyond Organophosphate Esters in Chinese Estuarine Waters.

Organophosphorus compounds (OPCs) pose potential hazards to human health and aquatic ecosystems. However, limited knowledge of emerging OPCs beyond organophosphate esters (OPEs) hinders a thorough understanding of the environmental occurrence and exposure risks. Through target, suspect, and nontarget screening analysis, 64 OPCs were successfully identified in Chinese estuarine waters, including 24 known OPEs and 40 emerging analogues (i.

Unveiling emerging polycyclic aromatic compounds in the urban atmospheric particulate matter.

Despite the ubiquity and complexity of atmospheric polycyclic aromatic compounds (PACs), many of these compounds are largely unknown and lack sufficient toxicity data for comprehensive risk assessments. In this study, nontarget screening assisted by in-house and self-developed spectra databases was, therefore, employed to identify PACs in atmospheric particulate matter collected from multiple outdoor settings. Additionally, absorption, distribution, metabolism, excretion, and toxicity properties were evaluated to indicate PAC's overall abilities to cause adverse outcomes and incorporated into a novel health risk assessment model to assess their inhalation risks.

Identifying Organic Chemicals with Acetylcholinesterase Inhibition in Nationwide Estuarine Waters by Machine Learning-Assisted Mass Spectrometric Screening.

Neurotoxicity is frequently observed in the global aquatic environment, threatening aquatic ecosystems and human health. However, a very limited proportion of neurotoxic effects (∼1%) has been explained by known chemicals of concern. Here, we integrated machine learning, nontargeted analysis, and in vitro biotesting to identify neurotoxic drivers of acetylcholinesterase (AChE) inhibition in estuarine waters along the coast of China.

Comprehensive Characterization of Oxidative Stress-Modulating Chemicals Using GPT-Based Text Mining.

The screening of hazardous environmental pollutants is hindered by the limited availability of toxicological databases. Large language model (LLM)-based text mining holds the potential to automatically extract complex toxicological information from the literature. Due to its relevance to diseases and the challenge of comprehensive characterization, oxidative stress serves as a suitable case for research by texting mining.

Utilizing artificial intelligence for precision exploration of N protein targeting phenanthridine sars-cov-2 inhibitors: A novel approach.

The persistent mutation of the novel coronavirus presents a continual threat of infections and associated illnesses. While considerable research efforts have concentrated on the functional proteins of SARS-CoV-2 in the development of anti-COVID-19 therapeutics, the structural proteins, particularly the N protein, have received comparatively less attention. This study focuses on the N protein, a critical structural component of the virus, and employs advanced deep learning models, including EMPIRE and DeepFrag, to optimize the structures of phenanthridine-based compounds.

Probing nitro(so) and chloro byproducts and their precursors in natural organic matter during UV/NHCl treatment by FT-ICR MS with machine learning insights.

The UV/monochloramine (UV/NHCl) process, while efficiently eliminating micropollutants, produces toxic byproducts. This study utilized Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to investigate molecular-level changes in natural organic matter (NOM) and to disclose formation pathways of nitro(so) and chloro byproducts in the UV/NHCl process. The UV/NHCl process significantly increased the saturation and oxidation levels and altered the elemental composition of NOM.

Occurrence and Distribution of Antibacterial Quaternary Ammonium Compounds in Chinese Estuaries Revealed by Machine Learning-Assisted Mass Spectrometric Analysis.

Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now emerging as another significant driver of AMR. However, assessing the AMR risks of QACs in complex environmental matrices remains challenging due to the ambiguity in their chemical structures and antibacterial activity.

Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.

Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) in conjunction with machine learning, we comprehensively investigated the reactivity and transformation of NOM, and the formation of organosulfates during the UV/peroxydisulfate (PDS) process. After 60 min UV/PDS treatment, the CHO formula number and dissolved organic carbon concentration significantly decreased by 83.

Occurrence and Ecological Risk of Alkylamine Triazines in Chinese Estuarine Sediments: An Emerging Class of Persistent, Mobile, and Toxic Substances.

Identifying persistent, mobile, and toxic (PMT) substances from synthetic chemicals is critical for chemical management and ecological risk assessment. Inspired by the triazine analogues (e.g.

Immunomodulatory Prodrug Micelles Imitate Mild Heat Effects to Reshape Tumor Microenvironment for Enhanced Cancer Immunotherapy.

Physical stimulation with mild heat possesses the notable ability to induce immunomodulation within the tumor microenvironment (TME). It transforms the immunosuppressive TME into an immune-active state, making tumors more receptive to immune checkpoint inhibitor (ICI) therapy. Transient receptor potential vanilloid 1 (TRPV1), which can be activated by mild heat, holds the potential to induce these alterations in the TME.

Abundant nitrogenous secondary organic aerosol formation accelerated by cloud processing.

Nitrogenous organic (CHON), crucial for secondary organic aerosol (SOA), forms through poorly studied mechanisms in clouds. Our study explores CHON transformation during cloud processes (CPs). These processes play a vital role in enhancing the variety of CHONs, leading to the formation of CHONs with oxygen atom counts ranging from 1 to 10 and double bond equivalent (DBE) values spanning from 2 to 10.

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds.

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%.

Suspect screening and effect evaluation for small-molecule agonists of the antioxidant response element pathway in fine particulate matter.

Oxidative stress is an important mechanism by which fine particulate matter (PM) generates toxicity. However, few inducers have been identified, and the combined effects of the contributing chemicals have rarely been examined. In this study, the occurrence of small-molecule agonists of the antioxidant response element (ARE) pathway was explored in 59 PM samples from urban Beijing over a one-year period via target and suspect screening analysis.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective.

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made.

Nanocontroller-mediated dissolving hydrogel that can sustainably release cold-mimetic menthol to induce adipocyte browning for treating obesity and its related metabolic disorders.

Obesity leads to the development of many metabolic diseases, causing severe health problems. Menthol can induce adipocyte browning and thus has been used to combat obesity. To deliver menthol with a sustained effect, an injectable hydrogel that comprises carboxymethyl chitosan and aldehyde-functionalized alginate that are crosslinked through dynamic Schiff-base linkages is developed to load menthol-cyclodextrin inclusion complexes (IC).

Prognostic factors of survival in patients with non-small cell lung cancer: a competing risk model using the SEER database.

Background: To explore the prognostic factors of survival in non-small cell lung cancer (NSCLC) patients using the competing risk analysis.

Methods: This was a retrospective cohort study. NSCLC patients with complete data were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015.

Epidemic characteristics of infection: a retrospective analysis of a single center in Suzhou from 2014 to 2020.

Background: ) is a common pathogen of respiratory tract infections, but there is still a lack of detailed investigation on the large sample of infection in the all age population. And patients with severe pneumonia (SMPP) still have a certain risk of death. How to identify the clinical characteristics and population of patients with SMPP as soon as possible is still an urgent problem in clinical practice.

Occurrence and Temporal Trends of Benzotriazole UV Stabilizers in Mollusks (2010-2018) from the Chinese Bohai Sea Revealed by Target, Suspect, and Nontarget Screening Analysis.

Benzotriazole UV stabilizers (BZT-UVs), including 2-(3,5-di--amyl-2-hydroxyphenyl)benzotriazole (UV-328) that is currently under consideration for listing under the Stockholm Convention, are applied in many commodities and industrial products. However, limited information is available on the interannual variation of their environmental occurrence. In this study, an all-in-one strategy combining target, suspect, and nontarget screening analysis was established to comprehensively explore the temporal trends of BZT-UVs in mollusks collected from the Chinese Bohai Sea between 2010 and 2018.

Occurrence and Ecological Impact of Chemical Mixtures in a Semiclosed Sea by Suspect Screening Analysis.

Stress from mixtures of synthetic chemicals is among the key issues that have significant adverse impacts on the marine ecosystems. A robust screening workflow integrating toxicological-based ranking schemes is still deficient for comprehensive investigation on the main constituents in chemical mixtures that contribute to the ecological risks. In this study, the presence and compositions of a collection of priority pollutants were monitored by suspect screening analysis of seawater and estuarine water samples from the semiclosed Bohai Sea.