Environmental Science & Technology Letters

Sequencing-based wastewater surveillance is emerging as an important tool in pathogen-agnostic threat detection, potentially enabling early identification before capture through clinical surveillance systems. However, virus sequences of human pathogens are typically low in abundance in wastewater while much of the data is unclassifiable at the read level. This presents a challenge because genomes may not assemble well for novel pathogens of interest, but read-based methods cannot currently separate novel from previously seen unclassified sequences. Using ultra-deep untargeted sequencing of the wastewater RNA virome performed by the CASPER consortium (321 samples), we constructed a wastewater virus genome database (WVDB) with the goal of expanding the set of available high-quality non-redundant reference genomes. The first version of this database contains 21,015 near-complete viral genomes, of which the majority are ssRNA bacteriophage (79%). We additionally recovered genomes for putative plant and vertebrate-infecting viruses, human enteric viruses, and viruses whose host could not be predicted. Fewer than 4000 genomes had matches in previously published virus genome databases, and WVDB captured around one fifth of the reads that could not be classified by Kraken2. Further expansion of WVDB will provide a comprehensive resource of RNA virus genomes for characterization of viral diversity and dynamics in wastewater across space and time.

BackgroundBenzene, toluene, ethylbenzene, and xylene (BTEX) are volatile aromatic hydrocarbons that are widespread environmental pollutants arising from petroleum processing, fuel combustion, and other industrial activities. Persistent BTEX contamination poses substantial risks to human health and ecosystems, underscoring the need for effective long term remediation strategies. Microbial bioremediation is a promising and sustainable approach for BTEX removal, but development of these approaches requires accurate detection of the genes and pathways responsible for substrate specific degradation. Although profile hidden Markov model (HMM) databases are widely used for functional annotation, existing annotation resources lack the substrate-specific resolution needed to distinguish between closely-related BTEX-degrading enzymes with different catalytic specificities. ResultsWe developed BTEXgenie as a sensitive annotation tool that uses custom HMMs built from alignments of experimentally validated BTEX degradation proteins to identify genes involved in the initial steps of aerobic and anaerobic BTEX degradation. BTEXgenie improved detection of anaerobic BTEX degradation genes that were absent from KOfam annotations. In benchmarking against the KEGG KOfam HMM database, BTEXgenie achieved 17.73%higher overall sensitivity while maintaining comparable specificity at 97.02%across genes involved in BTEX degradation pathways. When applied to environmental metagenomes, BTEXgenie recovered pathway patterns consistent with reported site characteristics and known degradation potential. In addition to gene annotation, BTEXgenie supports downstream interpretation through KEGG pathway-based visualization of detected functions and Circos-based visualization of genomic hit distributions. ConclusionsBTEXgenie is a substrate-specific annotation tool built from custom HMMs for detecting genes involved in BTEX degradation. By integrating gene annotation with pathway and genome-level visualizations, BTEXgenie facilitates characterization of microbial BTEX degradation potential in environmental and comparative genomic studies.

Wastewater genomic surveillance provides an opportunity to detect human and animal influenza A virus (IAV). We aimed to implement an IAV genomic surveillance framework agnostic to subtype, which enables recovery of IAV from multiple hosts and estimation of proportions across subtypes. We conducted IAV genomic surveillance in wastewater during the 2024-2025 flu season at multiple sites in California and compared these data with available human clinical IAV sequences and test positivity. We applied a custom whole-genome, multi-host IAV probe enrichment panel and adapted our custom expectation-maximization (EM) algorithm to deconvolute IAV mixtures in wastewater and infer subtype relative abundances. Absolute IAV concentrations were quantified using RT-PCR-based assays. H5N1 wastewater and clinical sequences were further characterized by constructing a whole-genome maximum-likelihood phylogenetic tree. Finally, we performed variant analysis to examine amino acid substitutions detected in wastewater. Our IAV probe enrichment method and EM algorithm successfully enriched all eight segments of three circulating IAV subtypes and accurately estimated subclade relative abundances for mixed IAV samples. Seasonal human H1N1pdm09 and H3N2 were detected throughout the study period from both wastewater and clinical sequencing data, with H1N1 subclades 6B.1A.5a.2a.1 and 6B.1A.5a.2a co-circulating, and H3N2 dominated by subclade 3C.2a1b.2a.2a.3a.1. Wastewater surveillance consistently detected H5N1 clade 2.3.4.4b across three monitored wastewater sites, while clinical H5N1 detections, from anywhere in CA, were sporadic and rare. Whole-genome phylogenetic analysis revealed that wastewater H5N1 sequences clustered with reference sequences associated with dairy cow and avian infections, while all human clinical H5N1 sequences clustered exclusively with reference sequences associated with dairy cow infections. Amino acid substitutions were identified across viral segments, and no mutations associated with mammalian adaptation were observed from wastewater samples.

Respiratory Syncytial Virus (RSV) is responsible for a substantial health burden worldwide, particularly among children and older adults. In 2023, novel immunoprophylactic interventions for RSV were approved, underscoring the need to monitor circulating RSV lineages and detect mutations that could compromise intervention effectiveness. Here, we implemented wastewater-based genomic RSV surveillance by integrating digital PCR and amplicon-based sequencing within Switzerland's national wastewater monitoring program. We tracked RSV subtypes and individual mutations across the 2024-2025 peak season in six Swiss cities. RSV-A and RSV-B co-circulated nationwide, and both exhibited similar epidemiological dynamics estimated from their subtype-specific effective reproduction numbers. No previously reported F protein mutations relevant to prophylaxis efficacy were identified. Genetic diversity analysis of wastewater-derived sequences reflected patterns previously reported in clinical data, with higher diversity in RSV-A than RSV-B and greater variability in the G compared to the F gene. These findings demonstrate the potential of wastewater-based RSV surveillance for monitoring RSV dynamics and diversity and establish a national baseline for RSV evolution during the first season following vaccine implementation in Switzerland.

Omics technologies are increasingly integrated into next-generation risk assessment, yet quantitative toxicogenomics outcomes remain highly dependent on analytical choices, motivating a systematic evaluation of how bioinformatics workflows influence hazard characterization and transcriptomic Points of Departure (tPOD). Here, we applied five independent transcriptomics pipelines to a shared dataset of RPTEC-TERT1 kidney cells exposed to cisplatin across multiple concentrations and timepoints, comparing effects of pre-processing, benchmark concentration modeling, and pathway-based interpretation strategies. Across workflows, substantial variability was observed in gene-level benchmark concentrations (BMCs), primarily driven by differences in normalization, filtering, and especially the modeling software used. Despite this variability, convergence increased at later timepoints as transcriptional responses strengthened, with 24 h consistently identified as the most sensitive timepoint at the gene level. Aggregation of gene-level BMCs into pathway-based metrics reduced variability but did not eliminate it, with pathway definition emerging as a major determinant of sensitivity estimates. Notably, distinct pathway resources showed minimal gene overlap, and smaller, biologically coherent gene sets (e.g., co-expression modules and biomarker panels) produced lower and less dispersed BMCs compared with broader pathway annotations. Furthermore, direct modeling of pathway activity scores yielded systematically different sensitivity estimates relative to median-based aggregation, with method-dependent conservativeness influenced by pathway coverage and response strength. Overall, our findings demonstrate that both analytical workflow design and pathway selection critically shape toxicogenomic-derived potency estimates, highlighting the need for harmonized, transparent methodologies to enable robust application of transcriptomics in chemical safety assessment and regulatory decision-making.

Enteroviruses (EVs) are ubiquitous contaminants of surface waters, where they can remain infectious for long periods of time. Most methods used for EV monitoring are unable to distinguish between infectious and non-infectious particles or between EV types. Because different types exhibit both distinct environmental persistence and health implications, there is a need for type-resolved infectivity measurements. Here we developed Integrated Cell Culture-Nanopore Sequencing (ICC-NanoporeSeq), a method combining short-term cell culture amplification with Nanopore sequencing of the VP1 gene. The ICC approach was adapted from a previously described ICC-RTqPCR protocol, while the NanoporeSeq workflow was derived from a clinical EV typing protocol and optimized for environmentally circulating EV types. Using samples containing known concentrations of ten EV types, the NanoporeSeq method accurately and reproducibly recovered the original proportions of all EV types after correction of biases. Furthermore, type-specific calibration curves generated with ICC-NanoporeSeq enabled quantification of the infectious concentrations of six EV types, allowing a simultaneous and type-resolved assessment of infectivity in mixed samples. Overall, ICC-NanoporeSeq provides a scalable approach for the parallel analysis of multiple EV types. Compared with the predecessor ICC-RTqPCR method, it eliminates the need for multiple type-specific PCR primers and can therefore be readily expanded to include additional EV types. IMPORTANCECurrent methods used to detect EVs in environmental samples generally measure viral genome copies without determining whether viruses remain infectious, limiting their use in public health risk assessment or water quality monitoring. At the same time, available infectivity assays are often labor-intensive and cannot distinguish between different EV types. Here, we developed ICC-NanoporeSeq, a method combining cell culture and Nanopore sequencing to simultaneously quantify the infectious concentrations of multiple EV types in samples containing mixed EV populations. The method provides an efficient and scalable approach for studying EVs in complex environmental matrices. ICC-NanoporeSeq has potential applications in wastewater-based epidemiology, environmental surveillance, and disinfection studies, where understanding the persistence of different EV types simultaneously is crucial.

Nano- and microplastics (NMPs), by-products of the fragmentation and degradation of plastic products, are ubiquitous environmental contaminants, yet their burden in pediatric immune tissues and functional consequences for developing immunity remain unknown. Here we report the first comprehensive characterization of NMPs in surgically excised pediatric tonsils (n = 30) using pyrolysis gas chromatography- mass spectrometry (Py-GC/MS), Nile Red fluorescence microscopy, and optical photothermal infrared (O-PTIR) spectroscopy. NMPs were detected in all specimens, with polystyrene, polyethylene, polyethylene terephthalate, and acrylonitrile butadiene styrene present in >90% of samples. To bridge clinical exposure data with mechanistic insight, we formulated a cryo-milled multi-polymer mixture reflecting the patient-derived polymer profile and challenged human lymphoid aggregate culture (HLAC) tonsil organoids at environmentally relevant concentrations. Multiplexed cytokine profiling of culture supernatants revealed a robust early inflammatory response at day 3, with significant upregulation of IL-6 (p = 0.011) and MIP-1{beta}/CCL4 (p = 0.011), followed by convergence toward control levels by day 14. Functional cytokine modules spanning immune, metabolic, structural, and growth factor pathways showed coordinated deviation from controls at day 3 post-exposure with subsequent normalization. Fluorescence-guided depth profiling demonstrated time-dependent penetration of 100 nm particles into organoid aggregates (70% tissue depth at day 3 versus 95% at day 14), and transmission electron microscopy revealed intracellular polyethylene within lymphocyte lysosomes. These findings establish pediatric tonsils as a sentinel tissue for NMP bioaccumulation and demonstrate that environmentally relevant polymer mixtures elicit transient but significant immunomodulatory responses in human lymphoid tissue, with implications for mucosal and systemic immune health in children. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/728317v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@19395f4org.highwire.dtl.DTLVardef@5a0380org.highwire.dtl.DTLVardef@19c0741org.highwire.dtl.DTLVardef@a052c5_HPS_FORMAT_FIGEXP M_FIG Structure: Translational pipeline from clinical tissue characterization to patient-informed preclinical modeling of nano-microplastic (NMP) exposure in pediatric lymphoid tissue. Pediatric tonsil tissue collected from clinically indicated tonsillectomies underwent tissue digestion for NMP characterization to identify NMP type and size distributions. In parallel, tonsil tissue was used to generate human lymphoid aggregate culture (HLAC) organoids that recapitulate the cellular complexity of the native tissue. These patient-derived organoids were then exposed to environmentally relevant compositions and concentrations of NMPs over time-course experiments, with longitudinal assessment of immunomodulatory responses including cytokine profiling and functional readouts. This bedside-to-bench approach establishes a physiologically relevant human system for investigating NMP-immune interactions, bridging clinical tissue analysis with mechanistic preclinical modeling to inform understanding of pediatric environmental exposures and their potential health impacts. C_FIG

Background: Climate mitigation policies can lower air pollutant concentrations and deliver substantial health co-benefits. The French Ecological Transition Agency (ADEME) proposed four contrasting Transitions 2050 net-zero scenarios. We quantified mortality, morbidity, and health-economic co-benefits from projected PM2.5 and NO2 reductions across all four scenarios in continental France. Methods: Emission projections were input to the CHIMERE chemistry-transport model to estimate PM2.5 and NO2 concentrations for 2030 and 2050. Health impacts were assessed using disease-specific cessation-lag assumptions relative to 2019, covering premature mortality, morbidity, DALYs, and economic benefits across nine outcomes (hypertension, lung cancer, ischaemic heart disease, stroke, COPD, type-2 diabetes, acute lower respiratory infections, and asthma in children and adults). Findings: Population exposure is projected to decline by about 40% for PM2.5 and 70% for NO2 by 2050, with health gains remaining substantial and broadly equivalent across all four scenarios and modest differences between sufficiency-oriented and technology-driven pathways. Under delayed-impact assumptions, avoided premature deaths ranged from 21,300 to 22,100 for PM2.5 and 24,500 to 26,200 for NO2. Morbidity and disability-adjusted life year (DALY) reductions, as well as economic savings, spanned similarly; total avoided morbidity cases were 84,000-88,000, direct medical cost reductions were e1.0-1.1 billion/year, and intangible cost savings of e41-43 billion and e36-39 billion, respectively. Interpretation: Health co-benefits are substantial, consistent across contrasting scenarios, and increase markedly from 2030 to 2050. Explicitly incorporating these co-benefits into climate policy appraisals may strengthen the case for ambitious mitigation and improve decision-maker acceptability.

Mass gatherings pose significant public health risks by facilitating the spread of infectious diseases. While wastewater-based surveillance (WBS) has been widely used to monitor pathogens in high-income settings, its use as a practical, multi-pathogen surveillance tool during mass gatherings in low- and middle-income countries remains limited. This study aimed to assess the operational feasibility, epidemiological significance, and public health utility of multi-pathogen WBS during the African Nations Championship (CHAN) football tournament in Uganda. Wastewater surveillance was conducted at Mandela National Stadium during eight match days in August 2025. Moore swabs were deployed at 38 manholes receiving wastewater from different toilet facilities across the stadium to capture representative wastewater samples. Samples were processed using Nanotrap(R) microbiome virus particles to concentrate pathogens, followed by nucleic acid extraction. Samples were analyzed for multiple enteric and respiratory pathogens, including Mpox, using quantitative PCR (qPCR). Descriptive analyses were performed to characterize pathogen detection patterns, positivity rates, and temporal distribution across surveillance sites. A total of 304 wastewater samples were collected and analyzed, of which 259 (85.2%) tested positive for at least one pathogen. Multiple pathogens were consistently detected across sampling days, with enteric pathogens predominating, particularly Shigella spp. (53.6%), Rotavirus A (35.9%) and Enterovirus (32.2%). The mpox virus was also detected in a notable proportion of samples (28.6%) across several sampling days. Respiratory pathogens, including SARS-CoV-2 (11.8%) and Influenza B (8.2%), were identified intermittently at lower frequencies. Pathogen diversity varied over time, with up to eight pathogens detected on a single day, and co-detection of multiple pathogens observed in the majority of positive samples. Cq value distributions further demonstrated variability in detected signal patterns across pathogens. Surveillance findings informed real-time public health interventions, including sanitation reinforcement, intensified hygiene promotion, environmental disinfection, and targeted risk communication, strengthened syndromic surveillance with on-site triage, and targeted environmental health assessments of food handling and wastewater infrastructure. These findings demonstrate the operational feasibility and public health utility of integrating multi-pathogen wastewater-based surveillance into mass-gathering preparedness and response frameworks in low-resource settings. By capturing diverse pathogen signals and informing targeted interventions during the CHAN football tournament, WBS can provide actionable population-level insights that can support outbreak preparedness and response. Scaling WBS within national preparedness systems could strengthen epidemic intelligence, enhance early warning capacity, and support data-driven public health decision-making during future mass gatherings and emerging infectious disease threats.

Respiratory syncytial virus (RSV) transmission via the aerosol route remains poorly understood, particularly with respect to how evolving virus-laden particles (bioaerosols) microenvironments influence viral survival. Bioaerosol particles contain complex mixtures of organic and inorganic components, and their physicochemical properties change dynamically during evaporation as water is lost upon emission from respiratory activities. These changes directly affect the local environment surrounding embedded virus during both the evaporation stage and the subsequent equilibrium state. However, how these microenvironmental conditions under different relative humidity (RH) levels regulate RSV survival remains unclear. In this study, we quantified RSV survival during the evaporation and early equilibrium stages using a flow-tube system with controlled residence times. Bioaerosols were generated from virus medium alone or supplemented with bovine serum albumin (BSA) or mucin and evaluated under low (35%) and intermediate (61%) RH conditions. Viral infectivity was normalized to RNA copy number to account for particle and sampling losses. At 35% RH, RSV infectivity decreased by one to three orders of magnitude, depending on the solution composition. In contrast, survival was significantly higher at intermediate RH, particularly for virus medium and BSA-supplemented aerosols. Scanning electron microscopy revealed that low RH conditions promote efflorescence, whereas intermediate RH results in viscous or semi-solid particles with higher water content. These observations suggest that efflorescence is associated with enhanced RSV inactivation, while viscous or semi-solid phases tend to preserve RSV in the aerosol state for respirable particles. Overall, RSV infectivity depends strongly on particle chemical composition, phase state (effloresced versus semi-solid), and relative humidity. These results highlight the importance of characterizing particle phase behavior and chemical composition during early aerosol processes to improve mechanistic understanding of viral survival relevant to short-range transmission.

Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.

This study aimed to clarify aerosol exposure risks throughout the workflow of a Biosafety Level 2 (BSL-2) polymerase chain reaction (PCR) laboratory, validate the suitability of the {Phi}X174 bacteriophage as an indicator virus, and provide evidence for biosafety control measures. The {Phi}X174 bacteriophage was used to simulate viral samples, and a concentration-bacteriophage plaque standard curve was constructed (R2=0.998). Five operational steps in a simulated PCR laboratory were quantitatively monitored for aerosol concentration using double-layer agar plates, with blank controls used to eliminate interference. Statistical analysis was employed to identify risk differences. Sample homogenization ((5.67 {+/-} 1.23) x 104 plaque-forming units (PFU)/m3) and nucleic acid extraction ((3.45 {+/-} 0.89) x 104 PFU/m3) were identified as high-/very high-risk steps. The viral load in the samples was strongly positively correlated with the aerosol concentration (r = 0.926, P <0.001), with aerosol levels linearly decreasing with increasing distance in high-risk steps. The {Phi}X174 bacteriophage demonstrated high detection sensitivity (101 PFU/ml) and demonstrated safety compatibility with BSL-2 laboratories. Aerosol risks in PCR laboratories exhibit step-specific differentiation, and {Phi}X174 serves as an ideal indicator virus. Proposed strategies such as equipment upgrades and personal protective equipment (PPE) grading can reduce exposure risks.

Until now, there has been no animal-free alternative method for predicting chronic inflammation and delivering the associated dose responses, the timing of onset, and the duration of inflammation, as required by regulatory agencies. We present the results of pre-validation of an in-vitro-learned digital twin (InFiniteLungDT) capable of predicting chronic neutrophilic lung inflammation for regulatory use. The method is based on measuring the dynamics of early biological effects in vitro induced by respirable materials or their mixtures, without the need to know their intrinsic properties. We constructed the digital twin(s) for each of the material, for which we have in vivo exposure data. The instillation data set, comprising 49 different nanomaterials, was used as the primary anchor to calibrate the model. Inhalation data set, comprising 7 different nanomaterials, compliant with OECD TG 412, was used to show the general applicability of the method across species and for different exposure scenaria. In total, about 3094 single mouse exposures and 364 rat exposures (and approx. 775/225 non-exposed mouse/rat controls) were used to predict concentration-dependent time-evolved neutrophil influx into the lung. The accuracy (predictive capacity) of LOAEL determination is 93% for instillation and 84% for inhalation exposure. Taking into account the time-to-deliver-result being less than 1 week, this proves that the effect of inhaled material from acute to chronic conditions can be assessed orders of magnitude faster and cheaper than in a reference animal study.

Volatile organic compounds (VOCs) demonstrate promise as non-invasive diagnostic tools. However, lack of mechanistically linked VOCs with biomarker discovery platforms limit delivery to the clinic. In this cohort-based study, we observed significant alterations of chloride-containing volatile fluxes, inclusive of methyl chloride (MeCl), in the breath of cancer patients that are consistent with our newly described metabolic model, derived through in vitro cellular assays and in vivo mice models. The diagnostic accuracy of this cohort study (60 patients) is equivalent to mammogram approaches. This newly identified and novel metabolism along with associated diagnostic biomarkers were initially identified through headspace studies of breast cancer cell lines which were deprived of serum, glucose or oxygen, similar to cellular conditions in tumors. In these cellular assays MeCl was consistently informative of cellular stress. Under resource limited conditions cellular production of MeCl was significantly reduced, and in several cases, cellular metabolism shifted to consumption. We present a new "push-pull" model in which cellular production of MeCl is linked to cellular methylation potential and methyl-transferase activity while consumption of MeCl is associated with methionine generation. Neither consumption nor production metabolisms have been described or quantified in humans or human tissues previously. The cellular headspace-derived model was tested using xenograft tumour bearing mice, which demonstrated reduced MeCl production, consistent with this model This work therefore presents a potentially powerful breath biomarker for cancer that translates from cellular and mice models through to human subjects. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/726956v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@98154org.highwire.dtl.DTLVardef@9c23aorg.highwire.dtl.DTLVardef@ae96e3org.highwire.dtl.DTLVardef@342a0d_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI(Poly)chloromethane compounds, including methyl chloride and chloroform, are indicative of cancer status in breath sampled from breast cancer clinic patients C_LIO_LIGlucose, serum and oxygen starvation induce significant changes in cellular metabolic fluxes C_LIO_LIReduced methyl chloride production is indicative of cellular stress in vitro C_LIO_LIMethyl chloride production is linked to cellular methylation activity C_LIO_LIMethyl chloride consumption is linked to methionine synthesis, cellular enrichment in chloride concentration, and enhanced chloroform fluxes C_LIO_LIMethyl chloride fluxes in in vitro cell cultures under pathophysiologically relevant conditions translate to the breath of tumour bearing mice C_LI

To explore the safety of combined use of lidocaine/prilocaine aerosol and condoms of different materials, this study conducted compatibility tests between them. By observing changes in various physical properties of condom materials after exposure to the aerosol, the compatibility of different polymer materials with the aerosol was analyzed.The results showed that within 15 minutes of exposure to the aerosol, there was no significant difference in all physical properties of natural rubber latex condoms compared with the blank control group (P>0.05), indicating they can be used together. In contrast, obvious changes in physical properties of polyurethane condoms occurred within 5 minutes of exposure (P<0.05), and their performances failed to meet industrial application standards, so combined use is strictly prohibited.This study clarifies the compatibility differences between two mainstream condom materials and lidocaine/prilocaine aerosol, providing experimental evidence and theoretical references for rational matching in clinical and daily use as well as avoiding potential safety risks.

Laboratory research generates substantial plastic waste and associated greenhouse gas emissions, yet researchers often lack practical tools for quantifying the environmental impact of routine protocols or identifying realistic opportunities for reduction. Here, we present an open-source calculator for estimating plastic use and carbon dioxide equivalent emissions from laboratory protocols, using item weight, plastic composition, and estimated cradle-to-grave carbon footprint factors. We apply the tool to a standard cell culture workflow to demonstrate how evidence-based protocol adjustments can reduce plastic consumption and emissions without affecting experimental design or efficiency. The calculator is designed to be transparent, adaptable, and extendable, allowing researchers to add new consumables and tailor analyses to their own laboratory practices. This work provides a quantitative framework for translating sustainability principles into measurable, protocol-level changes and supports more environmentally responsible decision-making in biomedical research.

Airborne transmission of respiratory pathogens depends on their ability to remain viable in drying respiratory droplets, yet the physicochemical drivers of bacterial inactivation during droplet evaporation remain poorly quantified. This study combines controlled droplet experiments with physicochemical modeling to investigate how osmotic pressure dynamics influence bacterial survival. Using Escherichia coli and Staphylococcus epidermidis as Gram-negative and Gram-positive surrogates, respectively, we measured viability loss in artificial saliva droplets dried at multiple relative humidities and reconstructed the time-resolved osmotic pressure using the Respiratory Aerosol Model (ResAM). Both organisms remained stable while droplets were liquid but lost viability following efflorescence, when rapid solute concentration changes produced sharp osmotic pressure increases. The extent of inactivation scales log-linearly with the rate of osmotic pressure change around efflorescence: E. coli decays faster than S. epidermidis, and relationships derived in artificial saliva predict survival in independent phosphate-buffered saline experiments. A more rapid drop in humidity led to more severe osmotic shocks and greater inactivation. These results identify the rate of osmotic pressure change during efflorescence as a quantitative, medium-independent predictor of bacterial survival in drying respiratory droplets. ImportanceAirborne infection risk depends on how long microorganisms remain viable in respiratory particles after exhalation, yet the physical mechanisms controlling bacterial survival during droplet drying are not well defined. Evaporation of respiratory droplets concentrates salts and can impose sudden and extreme osmotic stress on microbes, but this process has been difficult to quantify because osmotic pressure cannot be measured directly inside microscopic droplets. Integration of droplet experiments with a physicochemical aerosol model shows that bacterial inactivation is governed primarily by the rate of osmotic pressure increase during droplet efflorescence rather than by static values of humidity or solute concentration alone. This mechanism explains why rapid drying may produce strong inactivation.

Introduction Air pollution is the largest environmental risk to human health. Children are disproportionately affected by air pollution and their exposure is amplified during physical activity. Observed concentrations of nitrogen dioxide in 1 in 4 London school playground exceeds the European limit, but the health impacts of air pollution exposure in London school playgrounds remain unexplored. Our study aims to assess and compare the acute changes in lung function and airway inflammation of primary school-aged children exercising in school playgrounds. Methods and analysis 330 children aged 8 to 11 years from ten London schools will be recruited to complete 90 minutes of physical activity and 90 minutes of rest in their school playground in a randomised crossover design. Pre-, post-, and 24-hour post-exposure oscillometry measurements will be performed with airway resistance at 5 Hz (R5) the primary physiological outcome. Nasal lavage samples will be collected pre-exposure and 24-hour post-exposure for analysis of inflammatory, oxidative, and vascular biomarkers, with IL-6 as the primary biological outcome. Mixed-effects regression models will examine associations between estimated pollutant exposures, exercise and physiological responses.

Background Foodborne diseases cause substantial global morbidity and mortality, yet remain largely unattended. To support countries to address this public health concern, the World Health Assembly Resolution 73.5 called for strengthening global food safety efforts and led to the development of the WHO Global Strategy for Food Safety 2022-2030, adopted at the 75th WHA (2022). To this end, the World Health Organization (WHO) reconvened the Foodborne Disease Burden Epidemiology Reference Group (FERG) to advise and support the work to generate updated global, regional, and national estimates of the foodborne disease burden for the reference period 2000-2021. Methods We developed an incidence-based framework expanding coverage to 42 foodborne hazards. Standardized systematic reviews, Global Health Estimates and Global Burden of Disease envelopes, and United Nations population data informed the evidence base. Missing epidemiological data were imputed using Bayesian hierarchical meta-regression models. Disease models mapped acute and chronic health outcomes, applying updated disability weights, life tables, and probabilistic Monte Carlo calculations to estimate incidence, mortality, Years Lived with Disability, Years of Life Lost and Disability-Adjusted Life Years for all 194 WHO Member States. Transparency and analysis reproducibility were ensured through availed open-source R packages and standardized workflows. Results The computational framework provides annual, country-level estimates with improved internal consistency and an expanded hazard scope compared with the WHO 2015 edition. Advances include refined modelling, enhanced uncertainty propagation, and broader inclusion of microbial, parasitic, and chemical hazards. Persistent data gaps---especially in high-burden regions---were filled through extensive imputation. Conclusions The computational framework for the WHO 2026 edition delivers the most comprehensive and transparent assessment of the global burden of foodborne diseases to date. Despite remaining limitations, it enables routine monitoring, supports evaluation of global food safety efforts, and highlights priorities for strengthening national data systems.

BackgroundCloud water harbors diverse microbial communities despite its extreme oligotrophic conditions. However, the ecological and evolutionary dynamics of viruses in these transient atmospheric habitats remain poorly understood. Clouds have traditionally been regarded primarily as passive carriers of microorganisms rather than as active ecological environments supporting microbial interactions. In this study, cloud water was sampled at Mount Verde, Cape Verde Islands (744 m a.s.l.). We performed metagenomic analyses of iron-flocculated cloud water alongside genome analyses of a bacterial isolate and metagenome-assembled genomes using established bioinformatic approaches. Viral diversity, virus-host interactions, metabolic functions, genetic adaptations, and viral population dynamics across cloud events were investigated. In addition, UV-B resistance experiments were conducted for a novel cloud-water isolate. ResultsWe isolated 24 cloud water bacteria, including four novel species lineages, and recovered 62 high-quality metagenome-assembled genomes, including 10 novel species lineages. We identified 458 viral operational taxonomic units and 237 virus-host linkages across diverse prokaryotic hosts, revealing active viral predation across diverse bacterial taxa. In addition, CRISPR spacer matches from isolates of novel bacterial lineages such as Deinococcus nubigenus MPC36 were found. Viruses carried genes involved in host adaptation to environmental stressors, including cold-shock response, UV radiation resistance, and osmotic stress. In addition, viral populations exhibited SNP-level microdiversity and shifts in single-nucleotide variant composition across temporally proximate cloud events, indicating rapid population turnover. Experimental characterization of the cloud isolate Curtobacterium nubigenum MPC39 further revealed pronounced resistance to UV-B radiation and the presence of an inducible prophage, Curtobacterium phage vB_CnuS_Cirrus1 assigned to the new viral family Nebulaviridae, which could be validated in transmission electron microscopy. Reconstructed genomes from cloud-associated bacteria encoded carbon monoxide dehydrogenase genes and UV resistance genes, suggesting trace gas metabolism and enhanced UV protection as survival strategies in oligotrophic cloud droplets. In silico replication rates estimated using iRep were consistent with active bacterial replication at the time of sampling. ConclusionsTogether, these findings demonstrate that clouds are not merely passive carriers of microorganisms, but dynamic atmospheric ecosystems in which virus-host interactions shape microbial diversity and contribute to microbial turnover, atmospheric dispersal, and cloud-water biogeochemistry.