Toxicity Identification Research Articles

Sediment TIE Validation Study Using South Korean Domestic Species Glyptotendipes tokunagai to Evaluate Contamination with Two Heavy Metals and Ammonia

Toxicity identification evaluation (TIE) is used to support sustainable soil management. However, TIE studies for sediment contamination have been limited and no previous study has validated its applicability to a species native to South Korea, to the best of our knowledge. Therefore, this study aims to validate the applicability of domestic species inhabiting East Asia to a TIE framework. We selected Glyptotendipes tokunagai, a common benthic invertebrate in urban areas. Contaminated sediment samples were generated using cadmium, copper, and ammonia, which are the major pollutants in sediment. Three different adsorbents were chosen as pollutant removal agents to validate the applicability of TIE using G. tokunagai. In the results, G. tokunagai exhibited a mortality rate that was dependent on the concentration of each pollutant. The mortality rate dramatically decreased after adding the chosen adsorbents to the contaminated sediments. Additionally, the observed reduction in toxicant concentrations suggests that these additives are efficient for toxicant removal. In contrast, WCA10L showed a mortality higher than 20% and seems not to be a proper additive for a toxicity assay. Through this study, G. tokunagai was demonstrated to be sufficiently sensitive to sediment contaminated with different pollutants and showed reproducible measurements, making it a suitable test organism for the TIE framework. Moreover, suitable adsorbents were suggested by measuring efficiency and toxicity after the toxicant removal procedure.

Integrated Chemical and Ecotoxicological Assessment of Metal Contamination in the Andong Watershed: Identifying Key Toxicants and Ecological Risks

This study employed an integrated field monitoring approach, combining chemical analysis and ecotoxicity testing of multiple environmental matrices—water, sediment, and sediment elutriates—to comprehensively assess the environmental health of the Andong watershed, located near a Zn smelter and mining area. The primary objectives were to evaluate the extent of metal contamination, identify key toxicants contributing to ecological degradation, and trace the sources of these pollutants. Our findings revealed severe metal contamination and significant ecotoxicological effects both in proximity to and downstream from industrial sites. Specifically, Cd, Zn, and Pb were strongly linked to the smelter, while Hg, Ni, Cu, and As were predominantly associated with mining activities in the tributaries. To further assess toxicity of field-collected sediment and their elutriates, a logistic regression analysis was employed to estimate benchmark values for distinguishing between toxic and non-toxic samples, using the sum of toxic units for sediment elutriates and the mean probable effect level (PEL) quotient for sediment toxicity. These models demonstrated greater predictive accuracy than conventional benchmarks for determining toxicity thresholds. Our results highlight that integrating chemical and ecotoxicological monitoring with site-specific concentration–response relationships enhances the precision of ecological risk assessments, facilitating more accurate identification of key toxicants driving mixture toxicity in complex, pollution-impacted aquatic ecosystems.

Revolutionizing Patient Safety: Machine Learning and AI for the Early Detection of Adverse Drug Reactions and Drug-Induced Toxicity

Adverse drug reactions and drug-induced toxicity provide significant issues in drug research, jeopardizing patient safety and driving up healthcare costs. Toxicity has a greater potential impact than infectious diseases since it is less visible. Early diagnosis of these difficulties is critical to determining a drug's safety and viability profile. The combination of machine learning and artificial intelligence has marked a watershed moment in the identification of early adverse drug reactions and toxicity. These computational approaches enable rapid, extensive, and precise prediction of likely adverse drug reactions and toxicity even before practical drug manufacture, preclinical testing, and clinical trials. This paradigm change strives to create more efficient and safe drugs, lowering the likelihood of drug withdrawal. This comprehensive review investigates the critical role of machine learning and artificial intelligence in quickly detecting adverse drug reactions and toxicity, including approaches from data mining to deep learning. It lists essential databases, modelling techniques, and software that may be used to model and predict a wide range of toxicities and adverse drug reactions. This review provides a comprehensive overview, outlining recent developments and projecting future opportunities in machine learning and artificial intelligence-driven rapid identification of adverse drug reactions and drug-induced toxicity. It highlights the capabilities of these technologies and their enormous potential to improve patient safety and revolutionize medication discovery.

Advancing the Effect-Directed Identification in Combined Pollution: Using Pathways to Link Effects and Toxicants.

The difficulty in associating diverse pollutants with mixture effects has led to significant challenges in identifying toxicants in combined pollution. In this study, pathways were used to link effects and toxicants. By pathways evaluated by the concentration-dependent transcriptome, individual effects were extended to molecular mechanisms encompassing 135 pathways corresponding to 6 biological processes. Accordingly, mechanism-based identification of toxicants was achieved by constructing a pathway toxicant database containing 2413 chemical-pathway interactions and identifying pathway active fragments of 72 pathways. The developed method was applied to two different wastewaters, industrial wastewater OB and municipal wastewater HL. Although lethality and teratogenesis were both observed at the individual level, different molecular mechanisms were revealed by pathways, with cardiotoxicity- and genotoxicity-related pathways significantly enriched in OB, and neurotoxicity- and environmental information processing-related pathways significantly enriched in HL. Further suspect and nontargeted screening generated 59 and 86 causative toxicants in OB and HL, respectively, among which 29 toxicants were confirmed, that interacted with over 90% of enriched pathways and contributed over 50% of individual effects. After upgrading treatments based on causative toxicants, consistent removal of toxicants, pathway effects, and individual effects were observed. Mediation by pathways enables mechanism-based identification, supporting the assessment and management of combined pollution.

Active symptom monitoring for premenopausal women with breast cancer initiating adjuvant endocrine therapy: Protocol for the SWOG S2010 randomized controlled efficacy trial

BackgroundPremenopausal women with early stage, high risk hormone receptor positive breast cancer are at risk of early discontinuation of adjuvant endocrine therapy (ET), primarily because of toxicity, which can increase the risk of disease recurrence and death. We hypothesize that identification of bothersome symptoms between clinic visits, and automated notification of clinicians about symptoms, will result in improved persistence with ET. MethodsPre- and perimenopausal women planning to receive adjuvant treatment with tamoxifen or an aromatase inhibitor plus ovarian function suppression or ablation for treatment of breast cancer are eligible. A total of 540 participants will be enrolled and randomized 1:1 to patient education with or without Active Symptom Monitoring (ASM). The ASM intervention includes 6 symptom questions (hot flashes, sadness, anxiety, insomnia, vaginal dryness, joint pain) that will be completed via text, email, or telephone weekly for 24 weeks, then every 4 weeks for 48 weeks. All participants will complete a battery of questionnaires every 12 weeks to examine symptoms, beliefs about medicine, self-efficacy, and ET adherence. Optional blood draws will be collected at baseline and after 12, 48, and 72 weeks of therapy to examine estradiol and ET concentrations. The primary endpoint is time to nonpersistence with initially prescribed ET within the first 72 weeks, evaluated using Kaplan-Meier plots and multivariable Cox regression. ConclusionWe expect early identification and management of ET-related toxicities to improve persistence with breast cancer therapy, breast cancer outcomes, and quality of life for premenopausal women at high risk of breast cancer recurrence.Clinicaltrials.govNCT05568472

The Challenges of Treating Lead Toxicity During the COVID-19 Pandemic.

Despite decades of environmental reform, legacy lead is a persistent health hazard within communities. Secondary prevention with screening for childhood lead exposure typically occurs at the 12-month and 24-month well visits, and early identification of toxicity is of vital importance to reduce morbidity and mortality. Over the past few years, there have been multiple challenges impacting the management of lead toxicity, including the coronavirus disease 2019 pandemic, a national shortage of the chelation agent CaNa2EDTA, and housing-related concerns that may result in re-exposure of lead before lead abatement. This report identifies the importance of lead screening and limitations that a pandemic has placed on health care while emphasizing access to care and community resources needs to be a priority.

Artificial intelligence as a tool in drug discovery and development.

The rapidly advancing field of artificial intelligence (AI) has garnered substantial attention for its potential application in drug discovery and development. This opinion review critically examined the feasibility and prospects of integrating AI as a transformative tool in the pharmaceutical industry. AI, encompassing machine learning algorithms, deep learning, and data analytics, offers unprecedented opportunities to streamline and enhance various stages of drug development. This opinion review delved into the current landscape of AI-driven approaches, discussing their utilization in target identification, lead optimization, and predictive modeling of pharmacokinetics and toxicity. We aimed to scrutinize the integration of large-scale omics data, electronic health records, and chemical informatics, highlighting the power of AI in uncovering novel therapeutic targets and accelerating drug repurposing strategies. Despite the considerable potential of AI, the review also addressed inherent challenges, including data privacy concerns, interpretability of AI models, and the need for robust validation in real-world clinical settings. Additionally, we explored ethical considerations surrounding AI-driven decision-making in drug development. This opinion review provided a nuanced perspective on the transformative role of AI in drug discovery by discussing the existing literature and emerging trends, presenting critical insights and addressing potential hurdles. In conclusion, this study aimed to stimulate discourse within the scientific community and guide future endeavors to harness the full potential of AI in drug development.

Ecotoxicological assessment of sanitary sewer overflows and rainfall dynamics offers insights into conditions for potential adverse ecological outcomes

Sewer overflows are an environmental concern due to their potential to introduce contaminants that can adversely affect downstream aquatic ecosystems. As these overflows can occur during rainfall events, the influence of rainwater ingress from inflow and infiltration on raw untreated wastewater (influent) within the sewer is a critical factor influencing the dilution and toxicity of the contaminants. The Vineyard sewer carrier in the greater city of Sydney, Australia, was selected for an ecotoxicological investigation of a sanitary (separate from stormwater) sewerage system and a wet-weather overflow (WWO). Three influent samples were collected representing dry-weather (DW), intermediate wet-weather (IWW) and wet-weather (WW). In addition, a receiving water sample was also collected downstream in Vineyard Creek (WW-DS) coinciding with a WWO.We employed direct toxicity assessment (DTA) and toxicity identification evaluation (TIE) approaches to gain comprehensive insights into the nature and magnitude of the impact on influent from rainwater ingress into the sewer. Three standard ecotoxicological model species, a microalga, Chlorella vulgaris, the water flea, Ceriodaphnia dubia and the midge larva, Chironomus tepperi were used for both acute and chronic tests. The study revealed variable toxicity responses, with the sample of influent collected in wet-weather displaying lower toxicity compared to the dry-weather sample of influent. Ammonia, and metals, were identified in dry weather as contributors to the observed toxicity, however, this risk was alleviated through rainwater ingress in wet-weather with further dilution within the receiving water. Based on toxicity data, dilutions of influent to minimise effects on C. vulgaris and C. dubia ranged from 1 in 12 in DW to 1 in 2.8 in WW, and further diminished in the receiving water to 1 in 1.8. The successful application of ecotoxicological approaches enabled the assessment of cumulative effects of contaminants in influent, offering valuable insights into the sanitary sewer system under rainwater ingress.

Use of Radiation Therapy in the Management of Vulvar Cancers—Identification and Management of Acute and Late Toxicities

Radiation therapy plays a critical role in the management of locally advanced vulvar cancers but can lead to a unique spectrum of side effects, with >25% of patients experiencing high-grade toxicities. The treatment phase requires meticulous perineal skincare and may require pharmacologic management of dysuria and cystitis, diarrhea, nausea, and dermatitis/mucositis. The addition of chemotherapy warrants close laboratory monitoring for hematologic and metabolic derangements.

Phase I Study of Simlukafusp Alfa (FAP-IL2v) with or without Atezolizumab in Japanese Patients with Advanced Solid Tumors.

The aim of the study was to evaluate the safety/tolerability and pharmacokinetics of simlukafusp alfa (FAP-IL2v), an immunocytokine containing an anti-fibroblast activation protein-α (FAP) antibody and an IL2 variant, administered alone or with the PDL1 inhibitor atezolizumab, in Japanese patients with advanced solid tumors. In this phase 1, open-label, dose-escalation study, patients received i.v. FAP-IL2v at 10 or 15/20 mg alone or 10 mg when combined with i.v. atezolizumab. The primary objectives were identification of dose-limiting toxicities (DLT), recommended dose, and maximum tolerated dose, and evaluation of the safety/tolerability and pharmacokinetics of FAP-IL2v alone and combined with atezolizumab. All 11 patients experienced adverse events (AE) during FAP-IL2v treatment. Although most AEs were of mild severity, four treatment-related AEs led to study treatment discontinuation in two patients: one with infusion-related reaction, hypotension, and capillary leak syndrome, and the other with increased aspartate aminotransferase. No AE-related deaths occurred. One DLT (grade 3 hypotension) occurred in a patient receiving FAP-IL2v 15/20 mg alone. The recommended dose and maximum tolerated dose could not be determined. The pharmacokinetics of FAP-IL2v remained similar with or without atezolizumab. The study was terminated early as FAP-IL2v development was discontinued because of portfolio prioritization (not for efficacy/safety reasons). This study describes the safety/tolerability of FAP-IL2v 10 mg alone and in combination with atezolizumab in Japanese patients with advanced solid tumors; one DLT (hypotension) occurred with FAP-IL2v 15/20 mg. However, dose escalation of FAP-IL2v was not conducted because of early study termination. This phase I study assessed the safety/tolerability and PK of simlukafusp alfa alone or combined with atezolizumab in Japanese patients with advanced solid tumors. No notable differences in PK were noted with the combination versus simlukafusp alfa alone; however, high-dose simlukafusp alfa treatment was associated with recombinant IL2-related toxicity, despite the drug's FAP targeting and IL2Rβγ-biased IL2 variant design.

Strongly acidic lead contaminated soil solidification/stabilization using metakaolin-modified fly ash phosphoric-based geopolymer

The existing binders are difficult to be compatible with the acidic environment of acidic heavy metal contaminated soil, it is hard to repair acidic heavy metal contaminated soil. In this study, a modified acid phosphorus-based geopolymer (MAPG) binder suitable for the solidification/stabilization (S/S) treatment of acidic heavy metal Pb2+ contaminated soil was fabricated using aluminum dihydrogen phosphate (ADP) as activator, fly ash and metakaolin (MK) as raw materials. The influences of liquid–solid ratio (L/S), MK content, ADP concentration, curing age and leaching environment on the compressive strength, toxic leaching, resistivity, pH and EC of MAPG stabilized acidic Pb2+ contaminated soil were studied. Meantime, the X-ray diffraction, scanning electron microscopy, fourier transform infrared spectroscopy, and mercury intrusion (MIP) experiments were used to study the chemical properties and microscopic performance of MAPG treated acidic Pb2+ contaminated soil. The results showed that the MAPG binder prepared from MK had an excellent S/S effect on the acidic Pb2+ contaminated soil, and the MAPG binders had good compatibility with the acidic environment. The compressive strength of each group of MAPG stabilized soil could meet the strength standard (>350 kPa) for solid waste landfill and Pb2+ leaching concentration is < 5 mg/L for toxicity identification criteria after 7 days of curing. With an increase in curing age, the strength of stabilized acidic contaminated soil decreased slightly, but the strength still met the requirements of landfill strength standard after 28 days of curing. In three different leaching environments, the Pb2+ leaching decreased with an increase in curing age. Microscopic analysis showed that the main crystalline compounds in stabilized contaminated soil were potassium feldspar, Berlinite and lead phosphate compounds, and their contents were related to L/S, MK content, ADP concentration, and curing time. Potassium feldspar, berlinite, and lead phosphate compounds could not only fill pores, but also had physisorption, encapsulation and chemical precipitation effects on Pb2+. The study could provide an economical, environmental friendly and efficient binder for the remediation of acidic Pb2+ contaminated soil, but the further investigation into the long-term effectiveness of the MAPG binder or its applicability to other types of contaminated soil is also needed.

AI-driven Discovery of Morphomolecular Signatures in Toxicology.

Early identification of drug toxicity is essential yet challenging in drug development. At the preclinical stage, toxicity is assessed with histopathological examination of tissue sections from animal models to detect morphological lesions. To complement this analysis, toxicogenomics is increasingly employed to understand the mechanism of action of the compound and ultimately identify lesion-specific safety biomarkers for which in vitro assays can be designed. However, existing works that aim to identify morphological correlates of expression changes rely on qualitative or semi-quantitative morphological characterization and remain limited in scale or morphological diversity. Artificial intelligence (AI) offers a promising approach for quantitatively modeling this relationship at an unprecedented scale. Here, we introduce GEESE, an AI model designed to impute morphomolecular signatures in toxicology data. Our model was trained to predict 1,536 gene targets on a cohort of 8,231 hematoxylin and eosin-stained liver sections from Rattus norvegicus across 127 preclinical toxicity studies. The model, evaluated on 2,002 tissue sections from 29 held-out studies, can yield pseudo-spatially resolved gene expression maps, which we correlate with six key drug-induced liver injuries (DILI). From the resulting 25 million lesion-expression pairs, we established quantitative relations between up and downregulated genes and lesions. Validation of these signatures against toxicogenomic databases, pathway enrichment analyses, and human hepatocyte cell lines asserted their relevance. Overall, our study introduces new methods for characterizing toxicity at an unprecedented scale and granularity, paving the way for AI-driven discovery of toxicity biomarkers.

3MTox: A motif-level graph-based multi-view chemical language model for toxicity identification with deep interpretation

Toxicity identification plays a key role in maintaining human health, as it can alert humans to the potential hazards caused by long-term exposure to a wide variety of chemical compounds. Experimental methods for determining toxicity are time-consuming, and costly, while computational methods offer an alternative for the early identification of toxicity. For example, some classical ML and DL methods, which demonstrate excellent performance in toxicity prediction. However, these methods also have some defects, such as over-reliance on artificial features and easy overfitting, etc. Proposing novel models with superior prediction performance is still an urgent task. In this study, we propose a motifs-level graph-based multi-view pretraining language model, called 3MTox, for toxicity identification. The 3MTox model uses Bidirectional Encoder Representations from Transformers (BERT) as the backbone framework, and a motif graph as input. The results of extensive experiments showed that our 3MTox model achieved state-of-the-art performance on toxicity benchmark datasets and outperformed the baseline models considered. In addition, the interpretability of the model ensures that the it can quickly and accurately identify toxicity sites in a given molecule, thereby contributing to the determination of the status of toxicity and associated analyses. We think that the 3MTox model is among the most promising tools that are currently available for toxicity identification.

Leaching behavior and kinetics of beryllium in beryllium-containing sludge (BCS)

Beryllium-containing sludge (BCS) is a byproduct of the physicochemical treatment of beryllium smelting wastewater. The pollutant element beryllium within BCS is highly unstable and extremely toxic, characterized by its small ionic radius and low charge density, resulting in a high risk of leaching and migration. This study is the first to investigate the leaching behavior, influencing mechanisms, and kinetic processes of beryllium in BCS under various environmental conditions. The results indicate that, under national standard conditions, beryllium exhibits a rapid leaching phase within the first 5 h, which then stabilizes after 10 h, with the total leached content significantly exceeding the leaching toxicity identification standards. Under mildly acidic (pH ≤ 5) or highly alkaline (pH = 14) conditions, beryllium demonstrates pronounced leaching and migration behaviors. Notably, in acidic conditions, the leaching rate exceeds 80% within 5 h. Combining the treatment process of beryllium-containing wastewater with analytical methods such as SEM, XPS, ToF-SIMS, and FTIR, it is revealed that due to the heterogeneous nature of BCS, the particle aggregates dissociate over time under acidic conditions. The particle surfaces become increasingly rough, leading to dissolution and the emergence of more reactive sites, resulting in a high proportion of beryllium leaching. Under these conditions, the gradual reaction of Be(OH)2 in BCS to form soluble Be2+ and its hydrolytic complexes is identified as the primary mechanism for extensive beryllium migration. The process encounters minimal diffusion resistance and is classified as reaction-controlled. In acidic conditions with pH = 4, the leaching rate of beryllium significantly increases with rising temperature. The leaching kinetics equation is [(1−x)−0.44]=e(18.26−53050RT)·t, with an apparent activation energy of 53.05 kJ mol−1.

Characterizing immune checkpoint inhibitor-related cutaneous adverse reactions: A comprehensive analysis of FDA adverse event reporting system (FAERS) database

BackgroundThe increasing adoption of immune checkpoint inhibitors (ICIs) in clinical settings highlights their efficacy in treating diverse conditions, while also emphasizing the potential for common cutaneous adverse reactions to arise. The aim of this study is to investigate a multitude of impacting factors and determinants among patients presenting with ICI-associated cutaneous adverse reactions. MethodsWe conducted a comprehensive analysis of ICI-associated cutaneous adverse reactions using data from the FAERS. Our study spans from January 1, 2015, to March 31, 2023, focusing on ICIs, including anti-PD-1, anti-PD-L1, and anti-CTLA-4 agents. FindingsAmong the 334,293 reported irAR, 17,431 were identified as cutaneous adverse reactions (ARs). Predominant cutaneous ARs included rash (21.01 %), pruritus (11.22 %), and pemphigoid (3.90 %). Stevens-Johnson syndrome emerged as the most reported severe cutaneous adverse reaction (SCAR) (2.08 %). Anti-CTLA-4 agents exhibited higher cutaneous toxicity compared to anti-PD-1 and anti-PD-L1 agents. Anti-PD-1 agents demonstrated an elevated mortality rate. The combined use of ICIs with chemotherapy amplified the risk of SCAR and mortality. Targeted therapy was a risk factor for cutaneous ARs but was associated with reduced mortality. The median onset day for cutaneous toxicity was 21 days, while for SCAR, it was 23 days. Weight and age were identified as predictors of SCAR, cutaneous toxicity, and mortality. Skin cancer increased skin toxicity, while lung cancer heightened SCAR formation. The number of administered ICIs positively correlated with SCAR, skin toxicity, and mortality. InterpretationThis study highlights the significance of early identification and effective management of cutaneous toxicities, along with personalized follow-up care, as essential strategies for minimizing risks and preventing treatment disruptions.

Toxicity Evaluation of Water and Pore Water from a Pilot-Scale Pit Lake in the Alberta Oil Sands Region to Daphnia Species.

Significant amounts of tailings and oil sands process-affected water (OSPW) are generated by bitumen extraction in the Alberta Oil Sands region. These by-products are potentially toxic to aquatic organisms and require remediation. The study site was Lake Miwasin, a pilot-scale pit lake integrated into broader reclamation efforts. It consists of treated tailings overlaid with blended OSPW and freshwater, exhibiting meromictic conditions and harboring aquatic communities. This study assessed the potential toxicity of Lake Miwasin surface water (LMW) and pore water (LMP) using saline-acclimated Cladocera, including lab strains of Daphnia magna and Daphnia pulex and native Daphnia species collected in brackish Humboldt Lake (HL) and Lake Miwasin (LM). The pore water evaluation was used to represent a worst-case water quality scenario during pond stratification. Additionally, the inclusion of native organisms incorporated site-specific adaptations and regional sensitivity into the toxicity evaluation. Our results showed that LMW did not display acute or chronic toxicity to lab species and native Daphnia sp. (HL). Conversely, LMP was acutely toxic to both lab species and native D. pulex (LM). In chronic tests (12days exposure), LMP negatively affected reproduction in D. pulex (lab), with reductions in the number of offspring. Limited ability to acclimated organisms to the high salinity levels of LMP resulted in a shortened exposure duration for the chronic toxicity test. In addition to salinity being identified as a stressor in LMP, toxicity identification evaluation (TIE) phase I findings demonstrated that the observed toxicity for D. magna (lab) and D. pulex (LM, native) might be attributed to ammonia and metals in LMP. Further investigations are required to confirm the contributions of these stressors to LMP toxicity.

Rapid identification of reproductive toxicants among environmental chemicals using an in vivo evaluation of gametogenesis in budding yeast Saccharomyces cerevisiae

Infertility affects ∼12 % of couples, with environmental chemical exposure as a potential contributor. Of the chemicals that are actively manufactured, very few are assessed for reproductive health effects. Rodents are commonly used to evaluate reproductive effects, which is both costly and time consuming. Thus, there is a pressing need for rapid methods to test a broader range of chemicals. Here, we developed a strategy to evaluate large numbers of chemicals for reproductive toxicity via a yeast, S. cerevisiae high-throughput assay to assess gametogenesis as a potential new approach method (NAM). By simultaneously assessing chemicals for growth effects, we can distinguish if a chemical affects gametogenesis only, proliferative growth only or both. We identified a well-known mammalian reproductive toxicant, bisphenol A (BPA) and ranked 19 BPA analogs for reproductive harm. By testing mixtures of BPA and its analogs, we found that BPE and 17 β-estradiol each together with BPA showed synergistic effects that worsened reproductive outcome. We examined an additional 179 environmental chemicals including phthalates, pesticides, quaternary ammonium compounds and per- and polyfluoroalkyl substances and found 57 with reproductive effects. Many of the chemicals were found to be strong reproductive toxicants that have yet to be tested in mammals. Chemicals having affect before meiosis I division vs. meiosis II division were identified for 16 gametogenesis-specific chemicals. Finally, we demonstrate that in general yeast reproductive toxicity correlates well with published reproductive toxicity in mammals illustrating the promise of this NAM to quickly assess chemicals to prioritize the evaluation for human reproductive harm.

Interventions of the nurse navigator in the identification and management of toxicities after the start of treatment in patients with cancer using antineoplastic therapy.

12139 Background: Monitoring symptoms during chemotherapy is crucial as patients experience adverse effects, requiring therapeutic modifications, supportive care, and education. Patient navigation provides individualized assistance, overcoming barriers to healthcare access for patients, families, and caregivers. A previous study (Tabriz et al. JAMA Netw Open 2023) has shown that 52% of emergency room (ER) visits can be preventable. Thus, this study sought to determine effect of a nurse navigation program on reducing the rate of ER visit. Methods: This retrospective study was conducted from June to December 2023 in two cancer centers within the Oncoclinicas Network, located in the Southeast and Northwest regions of Brazil. Eligible patients were diagnosed with breast, lung, and gastrointestinal cancer, and were undergoing treatment with chemotherapy and/or immunotherapy. These patients were monitored by nurse navigators at post-therapy. Interventions were categorized as home management (care provided at patient’s home), outpatient (referral to the treatment clinic), and hospital (referral to emergency care). All toxicities were graded according to the Common Terminology Criteria for Adverse Events 5.0. Results: A total of 531 patients were included in the analysis, with the majority aged over 61 years old (44.4%), diagnosed breast (%) or colon (%) cancers. Throughout the six month study period, 3,201 toxicities were identified, with the majority graded between 1 and 2 (95.9%). This resulted in 91.9% of patients being managed at home or referred to the outpatient care. The cumulative proportion of patients having their symptoms managed at home or outpatient care is significantly higher than historical controls (P=0.001). Conclusions: Our findings highlight the effectiveness of a nurse navigation program in managing toxicities and symptoms, preventing ER visit. These findings underscore the importance of this program in optimizing patient care and reducing the burden on healthcare facilities. Further research and implementation of such programs may contribute to improved outcomes and patient satisfaction in oncological care.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review.

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Teasing out the Effects of Natural Stressors at Chemically Contaminated Sites.

Aquatic ecosystems are often impacted by a multitude of stressors, many of which are introduced by a combination of anthropogenic activities such as agricultural development, urbanization, damming, and industrial discharge. Determining the primary stressors responsible for ecological impairments at a site can be complex and challenging; however, it is crucial for making informed management decisions. Improper diagnosis of an impaired system can lead to misguided attempts at remediation, which can be both time consuming and costly. We focused on the development, implementation, and evaluation of methodologies that, in combination, allowed us to identify the primary stressors. These included a four-phase, weight-of-evidence (WOE) assessment including in situ Toxicity Identification and Evaluation (iTIE) testing, physicochemical and macrobenthos characterization, reciprocal sediment transplants, and laboratory and in situ toxicity testing. The contaminants of concern (COCs) at the site were elevated levels of ammonia, chloride, pH, and total dissolved solids in groundwater upwellings into a high-quality waterway. Reciprocal transplants of site sediments and nearby reference sediments and traditional benthic sampling showed impaired benthic indices and multiple stations around a contaminated industrial settling basin. Impaired stations had elevated COCs in groundwaters but exhibited a steep vertical concentration gradient, with concentrations decreasing near the sediment-surface water interface. We describe Phase 4 of the study, which focused on teasing out the role of dissolved oxygen sags in benthic macroinvertebrate responses. Extensive submerged and emergent macrophytes, algae, and cyanobacteria co-occurred at the impaired sites and increased throughout the summer. Laboratory testing suggested that ammonia and pH were possibly toxic at the sites, based on groundwater concentrations. The in situ toxicity testing, however, showed toxicity occurring even at stations with low levels of COCs concurrently with large diurnal fluxes in dissolved oxygen (DO). A final phase using a type of iTIE approach utilized limnocorrals with and without aeration and with in situ toxicity measures using Hyalella azteca. The Phase 4 assessment revealed that low DO levels were primarily responsible for impaired benthic communities, and COC upwellings were diluted at the sediment-water interface to nontoxic levels. These findings will allow for improved management decisions for more efficient and effective restoration activities. Environ Toxicol Chem 2024;43:1524-1536. © 2024 SETAC.