Exposure Distribution Research Articles

UV-C Disinfection and Impact on the Quality of Black, White, Green, and Pink Peppercorns Using a Scalable Reactor

Abstract The spice industry faces significant challenges in ensuring the safety and quality of its products, mainly since they are commonly consumed raw. Whilst effective in inactivating pathogens, thermal treatments often degrade the sensory quality of spices, making them unfeasible. This study explores the potential of short wavelength ultraviolet (UV) disinfection as a non-thermal alternative, focusing on its disinfection efficacy and impact on the quality of black, white, green, and pink peppercorns from various geographical sources. A substantial reduction in Escherichia coli was demonstrated using an industrially scalable rotary reactor, with the highest reductions observed in green and black peppercorns. The use of the reactor proved to be more effective than a static treatment, highlighting the importance of uniform distribution of the UV light exposure. The results demonstrated that the antioxidant activity, total phenolic content, and piperine content remained unaltered following UV-C treatment in most of the samples. This finding indicates that the sensory characteristics of the peppers were not significantly altered, whilst food safety was enhanced. Nevertheless, additional research on sensory analysis is necessary to understand the impact on sensory perception and the potential of LED-based UV lamps as an effective and efficient method for ensuring food safety in the spice industry.

Spatially Mapping Banks' Commercial & Industrial Loan Exposures: Including an Application to Climate-Related Risks

The correlation of the spatial distribution of banking exposures with changes in spatial patterns of economic activity (e.g., internal migration, changes in agglomeration patterns, climate change, etc.) may have financial stability implications. We therefore study the spatial distribution of large U.S. banks' commercial and industrial (C&I) lending portfolios. We construct a novel dataset that augments FR Y-14Q regulatory data with borrower microdata for a more granular understanding of where banks' exposures are located by looking beyond headquarters to the location of facilities. We find that banks are exposed to almost all U.S. counties, with clustered exposure in certain geographies. We then use our dataset for a climate-related application by analyzing what fraction of C&I loans have been extended to firms that operate in areas vulnerable to physical risks, identifying, for example, counties where both (i) banks are highly exposed via their lending portfolios, and (ii) physical risks have historically resulted in large losses. Results of this kind can help inform risk management and be used to improve resilience to future stresses.

Spatially Mapping Banks' Commercial & Industrial Loan Exposures: Including an Application to Climate-Related Risks

The correlation of the spatial distribution of banking exposures with changes in spatial patterns of economic activity (e.g., internal migration, changes in agglomeration patterns, climate change, etc.) may have financial stability implications. We therefore study the spatial distribution of large U.S. banks' commercial and industrial (C&I) lending portfolios. We construct a novel dataset that augments FR Y-14Q regulatory data with borrower microdata for a more granular understanding of where banks' exposures are located by looking beyond headquarters to the location of facilities. We find that banks are exposed to almost all U.S. counties, with clustered exposure in certain geographies. We then use our dataset for a climate-related application by analyzing what fraction of C&I loans have been extended to firms that operate in areas vulnerable to physical risks, identifying, for example, counties where both (i) banks are highly exposed via their lending portfolios, and (ii) physical risks have historically resulted in large losses. Results of this kind can help inform risk management and be used to improve resilience to future stresses.

Socioeconomic inequality in exposure to second-hand smoke among middle-aged adults of the RaNCD cohort study: a decomposition analysis

BackgroundSecondhand smoke (SHS) can cause various health problems among different age groups worldwide. Socioeconomic factors may influence the distribution of SHS exposure among population subgroups. We aimed to estimate socioeconomic inequality in SHS exposure and identify its contributing factors among a sample of Iranian adults.MethodsThis cross-sectional investigation utilized baseline data from the Ravansar Non-Communicable Disease cohort study. The study population comprised 7991 middle-aged adults aged between 35 and 65 years. To determine socioeconomic status (SES) principal component analysis (PCA) was used. The Wagstaff normalized concentration index (Cn) was utilized to measure the extent of socioeconomic inequality in SHS. Furthermore, decomposition analysis was performed to identify the factors contributing to the observed inequality in SHS exposure.ResultsThe prevalence of SHS exposure among men, women, and the total population was 38.23%, 47.29%, and 43.89%, respectively. The concentration index (Cn) value for SHS exposure was − 0.121 (95% confidence interval [CI]: -0.146, -0.096) in the study participants. Among men and women, the values were − 0.080 (95% CI: -0.122, -0.037) and − 0.095 (95% CI: -0.112, -0.063), respectively, indicating a higher concentration of SHS among individuals with low SES. Female sex (35.17%), socioeconomic status (31.83%), being married (-26.36%), and rural residency (22.44%) were identified as the primary factors contributing to the observed inequality in SHS exposure.ConclusionThe research findings revealed a pro-rich inequality in SHS, with a significant concentration among low-SES individuals. In terms of the main contributors to socioeconomic inequality in SHS exposure, policy interventions need to pay attention to females, individuals with low SES, and married individuals to address inequality in SHS exposure.

Exploring Opioid Use Disorder Outcomes by Quantitative Urinalysis: Post Hoc Analysis of a Phase 3 Randomized Clinical Trial.

Opioid use disorder (OUD) is a global concern. Urine drug screening uses opioid immunoassays to monitor OUD treatment response but is limited to yes/no results. Analytical cutoff variation complicates interstudy comparisons. This study investigated whether quantitative urinalysis can provide additional clinically meaningful treatment efficacy information and assessed the impact of different cutoffs on treatment differences. Quantitative urine drug test data were analyzed from a randomized, active-controlled, parallel-group, double-blind, 31-week phase 3 trial (N = 428; December 29, 2015, to October 19, 2016) assessing CAM2038 subcutaneous (SC) buprenorphine (BPN) extended-release injections compared to daily sublingual (SL) BPN/naloxone (BPN/NX) tablets, and equivalent placebos, in OUD treatment (NCT02651584). Urine samples were analyzed by gas or liquid chromatography with mass spectrometry. The European Medicines Agency (EMA)-directed primary endpoint, based on opioid detection above the lower limit of quantification (LLOQ), was explored using different cutoffs. Using the LLOQ, the mean percentage of opioid-negative samples was 35.1% and 28.4% for CAM2038 and SL BPN/NX, respectively (mean difference [95% confidence interval], 6.7% [-0.1% to 13.6%]). Using standard cutoffs (1 ng/mg creatinine [fentanyl/norfentanyl], 300 ng/mg creatinine [other opioids]), results were 41.2% and 32.2% (9.0% [1.8%-16.1%]). Increasing cutoffs led to greater differences favoring CAM2038. Significant differences in mean concentrations over time and cumulative distribution of exposure to different opioids also favored CAM2038. The difference in fentanyl exposure between treatments was nonsignificant. Quantitative urinalysis provides insights into opioid use beyond assessment of abstinence. Study outcomes are impacted by analytical thresholds, which should be carefully considered when designing, interpreting, and comparing clinical trial results.

Assessment of external occupational exposure of radiation workers in Jiangsu Province, 2019-2022.

This article analyzes the external occupational radiation exposure distribution and trends among radiation workers in Jiangsu Province. The results show that the total annual collective effective dose for radiation workers in Jiangsu Province from 2019 to 2022 was 24.82 person·Sv, with an average annual effective dose of 0.34mSv over the 4-y period. The average annual effective dose exhibited an initial increase followed by a subsequent decrease, with statistically significant differences (P<.001) between different years. In the medical uses, nuclear medicine and interventional radiology had higher average annual effective doses compared to other categories, at 0.42 and 0.38mSv, respectively (P<.05). In industrial applications, accelerator operation and industrial testing workers had higher average annual effective doses compared to others, at 0.32 and 0.31mSv, respectively (P<.001). Among different levels of medical institutions, secondary hospitals had the highest average annual effective dose (0.38mSv, P<.001). Overall, the average annual effective dose for radiation workers in Jiangsu Province remained relatively low from 2019 to 2022, meeting national standards. However, special attention should still be given to radiation workers in nuclear medicine, interventional radiology, industrial testing, and accelerator operation.

Individual patterns of anadromy determine the cost of salmon lice exposure in brown trout

AbstractFacultative anadromous salmonids may alter migratory behavior to mitigate against detrimental infections of aquaculture‐derived salmon lice (Lepeophtheirus salmonis); however, this likely incurs negative growth and fitness consequences. This flexibility in migratory behavior also creates analytical challenges in estimating lice infestation levels and the consequences of exposure. We utilized simulated individual migration trajectories of facultatively anadromous brown trout (Salmo trutta) (N = 8049), generated from spatial‐temporal fjord‐use models fitted to empirical tracking data (N = 517). These trajectories were superimposed with open‐access spatial‐temporal modeled lice densities. Individual accumulated lice exposure and infestation were simulated over a 6‐month period for smolts and annually for veteran migrant life‐stages. The degree of lice‐induced mortality was estimated according to year (2013–2015), population (N = 5), and life‐stage of brown trout, within a semi‐enclosed fjord system (Sognefjorden, Norway). A gradient of lice was spatially distributed throughout the fjord. Highest densities were modeled in the outer‐fjord at a closer vicinity to aquaculture facilities. Accordingly, estimates of accumulated lice infestation were higher for individuals that underwent long‐distance migrations, residing for longer in the outer‐fjord, with limited differences observed between years. As most brown trout remained in the inner‐fjord, an area protected from aquaculture, individual accumulated levels of lice exposure and infestation were low, resulting in infestation estimates largely below critical‐mortality thresholds. The fraction of total mortality attributed to lice during sea‐sojourn was greater for long‐distance migrants (smolts: 25.3%; veteran migrants: 14.8%) versus those remaining within the inner‐fjord (smolts: 14.7%; veteran migrants: 1.7%). This resulted in an unequal contribution of lice to total mortality among populations (range: 3.3%–34.3%). Despite an equal distribution of lice exposure for all populations within the fjord, diverse mortality consequences among populations were estimated, largely resulting from individual selection of migration trajectory. Therefore, generic models of lice effects on facultative anadromous salmonids should be used with caution. Instead, the application of simulated migration trajectories to incorporate flexible behavior at the individual level is suggested. The findings indicate that Sognefjorden brown trout may have reduced their seaward migration extent to avoid direct mortality from salmon lice. This emphasizes the importance of monitoring and management actions to preserve selection for anadromy.

Summertime compound heat extremes change and population heat exposure distribution in China

Amid the cumulative effects of rapid urbanization and climate warming, urban residents face serious health threats posed by heat extremes. Long-term monitoring of extreme high temperatures in cities can provide a foundational framework for mitigating the urban heat environment and enhancing the livability of residents. Utilizing long-term MODIS land surface temperature (LST) data, this study examined the fluctuations of extreme high temperatures, as well as the distribution of urban populations exposed to heat extremes and the associated health risks for urban residents across 289 prefecture-level and above cities in China from 2002 to 2020, considering natural, population and economic regional scales. The results indicated that: (1) Variations in extreme high temperatures. Extreme LST thresholds exhibited an upward trend, with the nighttime growth rate being 0.24°C/decade higher than the day. Regions characterized by higher extreme LST thresholds during the day were concentrated in Northwest and North China, while nighttime were primarily found in South Central and East China. Furthermore, regions showing higher extreme LST thresholds during the day and night were situated in well-developed cities. (2) Changes in cities exposed to heat extremes. Over the past 19 years, the majority of cities have been exposed to compound extreme high temperatures, and the number of such cities increased from 230 to 256. Notably, nearly 42% of cities have been exposed to extreme high temperatures for 15 consecutive years or longer, particularly concentrated in East China and South Central China. Developed cities were more likely to endure persistent heat extremes, especially those with a population of over 5 million and a per capita GDP of over 20,000, which have almost continuously experienced heat extreme exposure for the past 19 years. (3) Urban populations exposed to compound heat extremes. The urban population heat exposure across the country was on the rise, with the fastest growth rate of 2.91 million people per year in the nighttime, and a greater escalation in East and South Central China. Moreover, cities with lower levels of population and economic development represented the primary areas for growth0, while cities with moderate development levels showcased the slowest growth rate. (4) Health risks for urban residents. The number of urban residents dying from cardiovascular and respiratory diseases increased by 522,500, with the elderly and males accounting for a greater proportion of the increase by 234,200 and 149,800, respectively. Additionally, there existed a significant positive correlation between the deaths and heat extremes during the day and night.

Pharmacokinetics of Tarlatamab, a Delta-Like Ligand-3 (DLL3) Targeted Half-Life Extended Bispecific T-Cell Engager (BiTE®) Immunotherapy in Adult Patients with Previously Treated Small-Cell Lung Cancer: Results from DeLLphi-300, a Phase I Multiple-Dose-Escalation Study.

Tarlatamab binds to delta-like ligand 3 on cancer cells and cluster of differentiation-3 on T cells, leading to T-cell-mediated tumor lysis, and has demonstrated a promising safety and efficacy profile in patients with previously treated small-cell lung cancer (SCLC). Here, we present pharmacokinetic results from DeLLphi-300 (NCT03319940), an ongoing international, open-label, first-in-human study in previously treated adult patients with SCLC. Multiple escalating doses of tarlatamab were administered every 2 weeks (Q2W; 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30, and 100 mg) in a 28-day cycle. To reduce the risk of cytokine-release syndrome, starting at the 3 mg dose level, a step dose regimen was employed consisting of a 1 mg infusion on cycle 1 day 1 (C1D1), followed by the target dose on C1D8, C1D15, and Q2W thereafter. All doses were infused over 1 h. Other tarlatamab dosing regimens were also explored, either for patient convenience (every 3 weeks) or to mitigate cytokine-release syndrome (extended intravenous infusion over a period of 3 days). Intensive pharmacokinetic samples were collected during cycles 1 and 2, and additional samples for pharmacokinetic and immunogenicity measurement were collected at regular intervals in later cycles. Pharmacokinetic data were analyzed using noncompartmental analysis, and antidrug antibody (ADA) incidence, including any effect on tarlatamab pharmacokinetic parameters, was summarized. Pharmacokinetic data were available from 203 patients. The median age was 62 years (range 32-80), and 55.7% (n = 113) of patients were male, 78.3% (n = 159) were white, and 8.3% (n = 17) were of Japanese descent. Following intravenous infusion, serum tarlatamab concentrations declined with time in a biphasic manner. Serum exposures increased in an approximately dose-proportional manner across the evaluated target dose range with a mean (standard deviation) estimated terminal phase elimination half-life of 5.8 (1.6) days, and steady state achieved by approximately C2D15. Of the 183 evaluable patients, 12 (6.6%) developed treatment-emergent ADAs; the distribution of dose-normalized serum concentrations were similar between patients who were ADA positive and ADA negative. In addition, the distribution of exposures was comparable in Japanese and non-Japanese patients. In patients with previously treated SCLC, tarlatamab demonstrated dose-proportional pharmacokinetic and extended half-life characteristics that support a Q2W dosing interval. Neither Japanese race nor ADA had a clinically relevant impact on exposures.

An exploration of exposure to river flood risk in Spain using the National Floodplain Mapping System

In Spain, human exposure to flooding continues to increase driven by changes in land use and population growth in urban and coastal areas. This study explores the geography of flood exposure in Spain in relation to human population, economic activities and points of special significance. The analysis is based on public flood hazard and risk mapping generated by water management administrators at the river basin district level. The data are published and accessible through the Spanish National Floodplain Mapping System (NFMS). The results show for first time, the spatial distribution of human population exposure, which amounts to at least 3,263,000 inhabitants nationwide (6.9% of the total Spanish population), the potential economic loss, totalling at least 122,132 million euros across Spain, and points of special significance classified into eleven different categories that have been analysed for all Spanish river basin districts. The results also indicate a higher exposure concentration along the Mediterranean coast.

Analyzing missingness patterns in real-world data using the SMDI toolkit: application to a linked EHR-claims pharmacoepidemiology study

BackgroundMissing data in confounding variables present a frequent challenge in generating evidence using real-world data, including electronic health records (EHR). Our objective was to apply a recently published toolkit for characterizing missing data patterns and based on the toolkit results about likely missingness mechanisms, illustrate the decision-making process for analyses in an empirical case example.MethodsWe utilized the Structural Missing Data Investigations (SMDI) toolkit to characterize missing data patterns in the context of a pharmacoepidemiology study comparing cardiovascular outcomes of initiating sodium-glucose-cotransporter-2 inhibitors (SGLT2i) and dipeptidyl peptidase‐4 inhibitors (DPP‐4i) among older adults. The study used a linked EHR-Medicare claims dataset from Duke Health patients (2015–2017), focusing on partially observed confounders from EHR data (HbA1c lab and body mass index [BMI] values). Our analysis incorporated SMDI's descriptive functions and diagnostic tests to explore missingness patterns and determine missingness mitigation approaches. We used findings from these investigations to inform estimation of adjusted hazard ratios comparing the two classes of medications.ResultsHigh levels of missingness were noted for important confounding variables including HbA1c (63.6%) and BMI (16.5%). Diagnostic tests resulted in output that described: 1) the distributions of patient characteristics, exposure, and outcome between patients with or without an observed value of the partially observed covariate, 2) the ability to predict missingness based on observed covariates, and 3) estimate if the missingness of a partially observed covariate is differential with respect to the outcome. There was evidence that missingness could be sufficiently described using observed data, which allowed multiple imputation by chained equations using random forests to address missing confounder data in estimating treatment effects. Multiple imputation resulted in improved alignment of effect estimates with previous studies.ConclusionsWe were able to demonstrate the practical application of the SMDI toolkit in a real-world setting. Application of the SMDI toolkit and the resulting insights of potential missingness patterns can inform the choice of appropriate analytic methods and increase transparency of research methods in handling missing data. This type of approach can inform analytic decision making and may increase our ability to generate evidence from real-world data.

Machine Learning‐Driven Spatiotemporal Analysis of Ozone Exposure and Health Risks in China

AbstractAccurate and fine‐scaled prediction of ozone concentrations across space and time, as well as the assessment of associated human risks, is crucial for protecting public health and promoting environmental conservation. This paper introduces NetGBM, an innovative machine‐learning model designed to comprehensively model ozone levels across China's diverse topography and analyze the spatiotemporal distribution of ozone and exposure. Our model focuses on daily, weekly, and monthly predictions, achieving commendable coefficients of 0.83, 0.77, and 0.79, respectively. By constructing a gridded map of ozone and incorporating both land use and meteorological features into each grid, we achieved ozone prediction at a high spatiotemporal resolution, outperforming previous research in terms of performance and scale, particularly in regions with limited monitoring stations. The results can be further improved when applied to regional research using meteorological and ozone data from regional stations. Additionally, our research revealed that temperature is the most significant factor affecting ozone concentrations across China. In health risk assessment, we retrieved a high‐resolution spatial distribution of ozone‐attributed mortality for 5‐COD and daily ozone inhalation distributions during our study period. We concluded that ozone‐attributed mortality is predominantly caused by stroke and IHD, accounting for more than 70% of the total deaths in 2021, with the highest mortality rates in developed urban areas such as the NCP and the YRD. Our experiment demonstrated the potential of NetGBM in robustly modeling ozone across China with high spatiotemporal resolution and its applicability in measuring associated health risks.

A multi-pathogen behavioral exposure model for young children playing in public spaces in developing communities.

Diarrheal disease is the second leading cause of death among children under five in developing communities, despite active interventions to improve access to water, sanitation, and hygiene resources. Even interventions with high fidelity and compliance saw minimal improvements in health outcomes, necessitating a need for looking beyond traditionally targeted exposure pathways. This study focuses on the pathogen exposure a young child may receive while playing in the public spaces of informal settlements, where animal feces, human feces, and garbage are frequently observed. The study utilized 79 soil samples previously collected across ten cluster sites in Corail, Haiti and processed using DelAgua cultural assays and quantitative Polymerase Chain Reaction methods. Molecular assays screened for Aeromonas, Vibrio cholera, and several pathogenic Escherichia coli species. Behavioral observations of young children (<5 years old) were also conducted in overlapping areas with the environmental sampling to quantify frequency of risky and mitigating behaviors. Environmental and behavioral data were combined to obtain the posterior distribution of children's pathogen exposure from playing in a public space for one hour. The model estimated that children have a likelihood of approximately 70% of being exposed to a pathogen during one hour of play and a greater than 30% chance of being exposed to multiple pathogens in the same period. While children and toddlers practice fewer risky behaviors compared to infants, they were shown to have higher likelihood of exposure and slightly higher pathogen dose per exposure. As anticipated, a high correlation between genes from the same E. coli species was observed in the model output. These findings demonstrate the need to consider public spaces as an important exposure pathway for young children for both future research and interventions.

12513 Prenatal Traffic Exposures Are Associated With Earlier Age At Menarche

Abstract Disclosure: E.L. Silva: None. Z. Wang: None. S. Rifas-Shiman: None. A. Fleisch: None. H. Gibson: None. D. Gold: None. J. Chavarro: None. M. Hivert: None. E. Oken: None. B. Coull: None. J.E. Hart: None. T. James-Todd: None. S. Mahalingaiah: None. Background: The trend towards younger age at menarche over several decades has raised concern as earlier menarche is associated with various adverse health outcomes throughout adulthood including higher risk of early menopause, reproductive cancers, and metabolic disease. Some have suggested environmental exposures early in life may contribute to the temporal trend. Here we aimed to determine the extent to which prenatal residential measures of fine particulate matter (PM2.5), black carbon (BC), and other markers for traffic-related air pollution are associated with earlier age at menarche. Study Methods: Our study population included all female offspring in Project Viva, a pre-birth prospective cohort, with available age at menarche data. We used daily spatiotemporal models to estimate prenatal residential PM2.5 and BC exposures overall and by trimester. Residential proximity to major roadway and traffic density within a 100m buffer were measured at birth. Age at menarche was assessed via questionnaires during pre-teen and teen years. We used Cox proportional hazards modeling, adjusted for sociodemographic variables and census tract median household income, to estimate hazard ratios (HRs) for the association between air pollutants and age at menarche (months), where HR&amp;gt;1 indicates earlier onset of age at menarche associated with increased exposure to air pollutants. We weighted observations by the inverse probability of having available outcome data among all female offspring to account for cohort attrition. Results: The study included 638 females born between 2000 and 2003. Mean (standard deviation (SD)) age at menarche was 12.7 (1.4) years. Mean (SD) prenatal PM2.5 and BC exposures were 11.3 (1.5) g/m3 and 0.72 (0.21) g/m3, respectively. Only 7% of the cohort lived within 100m of a major roadway at birth. Prenatal PM2.5 exposure was not associated with age at menarche and the exposure distribution was mostly below US standards at the time (range: 6.8-15.8 g/m3, interquartile range (IQR): 2.0-3.0 g/m3). Higher overall prenatal and 3rd trimester BC were associated with earlier age at menarche [e.g., HR: 1.26 (95% CI, 1.04, 1.54) per IQR increment in 3rd trimester BC]. Living within 100m of a major roadway (versus 200m) [HR = 1.42 (95% CI, 1.08, 1.86)] and living in areas in the 2nd or 3rd (versus 1st) tertile of traffic density [2nd tertile: HR = 1.37 (95% CI, 1.07, 1.76); 3rd tertile: HR = 1.30 (95% CI, 1.02, 1.66)] at birth were also associated with earlier age at menarche. Conclusions: Higher prenatal exposure to BC, closer residential proximity to road major roadways, and higher traffic density were all associated with earlier age at menarche. The 3rd prenatal trimester and the window around birth may be especially important for traffic-related endocrine-disrupting and pro-inflammatory exposures with potential to accelerate puberty timing among females. Presentation: 6/1/2024

The Distribution of Carceral Harm: County-Level Jail Incarceration and Mortality by Race, Sex, and Age

Jail incarceration remains an overlooked yet crucial component of the U.S. carceral system. Although a growing literature has examined the mortality costs associated with residing in areas with high levels of incarceration, far less is known about how local jails shape this burden at the intersection of race, sex, and age. In this study, I examine the relationship between county-level jail incarceration and age-specific mortality for non-Hispanic Black and White men and women, uniquely leveraging race-specific jail rates to account for the unequal racial distribution of jail exposures. This study finds evidence of positive associations between mortality and jail incarceration: this association peaks in late adulthood (ages 50–64), when increases in jail rates are associated with roughly 3% increases in mortality across all race–sex groups. However, patterns vary at the intersection of race, sex, and age. In particular, I find more marked and consistent penalties among women than among men. Additionally, a distinctly divergent age pattern emerges among Black men, who face insignificant but negative associations at younger ages but steep penalties at older ages—significantly larger among those aged 65 or older relative to their White male and Black female counterparts. Evidence further suggests that the use of race-neutral incarceration measures in prior work may mask the degree of harm associated with carceral contexts, because the jail rate for the total population underestimates the association between jail rates and mortality across nearly all race–age–sex combinations. These findings highlight the need for future ecological research to differentiate between jail and prison incarceration, consider the demographic distribution of incarceration's harms, and incorporate racialized measures of exposure so that we may better capture the magnitude of harm associated with America's carceral state.

The processing mechanism of vinegar-processed Curcumae Rhizome enhances anti hepatic fibrotic effects through regulation of PI3K/Akt/mTOR signaling pathway

BackgroundHepatic fibrosis, a chronic pathological condition resulting from various forms of persistent liver injury, in the later stage, it can evolve into cirrhosis and even liver cancer. Curcumae Rhizoma (CR), traditionally recognized for its properties in line qi break blood, eliminate accumulation and relieve pain. According to traditional Chinese medicine (TCM) principles, vinegar-processing enhances CR's ability to enter the liver meridian and act on the blood level, potentially augmenting its therapeutic effects on hepatic diseases. Therefore, vinegar-processed Curcumae Rhizoma (VCR) is frequently employed in treating liver fibrosis and related hepatic conditions. However, the underlying mechanisms of vinegar processing in enhancing its therapeutic efficacy remain unclear. MethodsThe anti-liver fibrosis effects of CR and VCR were verified at individual and cellular levels. Subsequently, HPLC-Q-TOFMS and pharmacokinetic analysis were utilized to elucidate the potential bioactive substances underlying the enhanced anti-fibrotic efficacy of VCR. Building upon these findings, network pharmacology and metabolomics were integrated to screen for key effect components and regulatory pathways. Finally, the mechanisms of action were further analyzed and validated at the tissue and cellular levels through Western blotting (WB) and molecular docking studies. ResultsBoth CR and VCR exhibited therapeutic effects against hepatic fibrosis, with VCR demonstrating enhanced efficacy after vinegar processing. 6 sesquiterpenes including furanodiene and curdione, showed significant alterations in plasma exposure and hepatic distribution post-processing. VCR significantly improved pathological liver conditions, lipid accumulation, and fibrosis severity. Additionally, VCR markedly reduced the expression of α-SMA in the liver and attenuated the elevations in liver function markers such as ALT and AST. Combined network pharmacology, metabolomics, and hepatic tissue WB analysis revealed that the reduced phosphorylation of the PI3K/Akt/mTOR pathway is a critical mechanism in VCR's anti-fibrotic effects. Experiments on LX-2 cells demonstrated that four sesquiterpenes, including furanodiene and curdione, effectively inhibited the proliferation of activated hepatic stellate cells (HSCs). Furanodiene, in particular, promoted apoptosis in activated HSCs by reducing phosphorylation levels of the PI3K/Akt/mTOR pathway proteins, increasing BAX expression, and activating downstream caspase-3 to achieve the effect of anti-liver fibrosis. ConclusionVinegar-processing significantly increases the plasma exposure and hepatic distribution of components such as furanodiene in VCR, enhancing anti-fibrotic efficacy by downregulating the phosphorylation levels of the PI3K/Akt/mTOR pathway and promoting HSC apoptosis. This study provides a comprehensive explanation of the vinegar-processing mechanism and its role in enhancing the anti-fibrotic effects of VCR, offering insights for its clinical application in liver fibrosis treatment and reference for the mechanistic study of other vinegar-processed herbal medicines.

Brain Exposure to the Macrocyclic ALK Inhibitor Zotizalkib is Restricted by ABCB1, and Its Plasma Disposition is Affected by Mouse Carboxylesterase 1c.

Zotizalkib (TPX-0131), a fourth-generation macrocyclic anaplastic lymphoma kinase (ALK) inhibitor, is designed to overcome resistance due to secondary ALK mutations in non-small cell lung cancer (NSCLC). We here evaluated the pharmacokinetic roles of the ABCB1 (P-gp/MDR1) and ABCG2 (BCRP) efflux transporters, OATP1 influx transporters and the metabolizing enzymes CES1 and CYP3A in plasma and tissue disposition of zotizalkib after oral administration in relevant mouse models. Zotizalkib was efficiently transported by hABCB1 in vitro. In vivo, a significant ∼9-fold higher brain-to-plasma ratio was observed in Abcb1a/b-/- and Abcb1a/b;Abcg2-/- compared to wild-type mice. No change in brain disposition was observed in Abcg2-/- mice, suggesting that mAbcb1a/b markedly restricts the brain accumulation of zotizalkib. ABCB1-mediated efflux of zotizalkib was completely inhibited by elacridar, a dual ABCB1/ABCG2 inhibitor, increasing brain exposure without any signs of acute CNS-related toxicities. In Oatp1a/b-/- mice, no marked changes in plasma exposure or tissue-to-plasma ratios were observed, indicating that zotizalkib is not a substantial in vivo substrate for mOatp1a/b. Zotizalkib may further be metabolized by CYP3A4 but only noticeably at low plasma concentrations. In Ces1-/- mice, a 2.5-fold lower plasma exposure was seen compared to wild-type, without alterations in tissue distribution. This suggests increased plasma retention of zotizalkib by binding to the abundant mouse plasma Ces1c. Notably, the hepatic expression of human CES1 did not affect zotizalkib plasma exposure or tissue distribution. The obtained pharmacokinetic insights may be useful for the further development and optimization of therapeutic efficacy and safety of zotizalkib and related compact macrocyclic ALK inhibitors.

A probabilistic hazard assessment for cyanobacterial toxins accounting for regional geography and water body trophic status

Under climate change scenarios freshwater eutrophication is expected to increase, and with it the occurrence of cyanobacterial toxin-producing harmful algal blooms. In the current study, microcystin toxin occurrence data from literature sources and a long-term provincial monitoring program were used to conduct a probabilistic hazard assessment for Alberta, Canada. The large temporal and spatial range of data makes Alberta a model system for identifying regional geography and water body trophic status factors driving toxin concentrations. Environmental exposure distributions of microcystin concentrations were plotted and used to identify the likelihood of a given sample exceeding water guideline values as a function of regional geography, total phosphorus and chlorophyll-a concentration. This process identified regions with intensive cultivation and those most prone to water deficits associated with climate change to be most associated with exceedances of regulatory guideline values. Elevated phosphorus and chlorophyll-a concentrations were also drivers of toxin occurrence. This assessment can be used to identify water bodies of greatest risk to human and animal populations from cyanotoxins and thereby inform regulators as to most effective monitoring strategies.

Integrated Geospatial and Geostatistical Multi-Criteria Evaluation of Urban Groundwater Quality Using Water Quality Indices

Groundwater contamination poses a severe public health risk in Lahore, Pakistan’s second-largest city, where over-exploited aquifers are the primary municipal and domestic water supply source. This study presents the first comprehensive district-wide assessment of groundwater quality across Lahore using an innovative integrated approach combining geographic information systems (GIS), multi-criteria decision analysis (MCDA), and water quality indexing techniques. The core objectives were to map the spatial distributions of critical pollutants like arsenic, model their impacts on overall potability, and evaluate targeted remediation scenarios. The analytic hierarchy process (AHP) methodology was applied to derive weights for the relative importance of diverse water quality parameters based on expert judgments. Arsenic received the highest priority weight (0.28), followed by total dissolved solids (0.22) and hardness (0.15), reflecting their significance as health hazards. Weighted overlay analysis in GIS delineated localized quality hotspots, unveiling severely degraded areas with very poor index values (&gt;150) in urban industrial zones like Lahore Cantt, Model Town, and parts of Lahore City. This corroborates reports of unregulated industrial effluent discharges contributing to aquifer pollution. Prospective improvement scenarios projected that reducing heavy metals like arsenic by 30% could enhance quality indices by up to 20.71% in critically degraded localities like Shalimar. Simulating advanced multi-barrier water treatment processes showcased an over 95% potential reduction in arsenic levels, indicating the requirement for deploying advanced oxidation and filtration infrastructure aligned with local contaminant profiles. The integrated decision support tool enables the visualization of complex contamination patterns, evaluation of remediation options, and prioritizing risk-mitigation investments based on the spatial distribution of hazard exposures. This framework equips urban planners and utilities with critical insights for developing targeted groundwater quality restoration policies through strategic interventions encompassing treatment facilities, drainage infrastructure improvements, and pollutant discharge regulations. Its replicability across other regions allows for tackling widespread groundwater contamination challenges through robust data synthesis and quantitative scenario modeling capabilities.

Identifying groups at-risk to extreme heat: Intersections of age, race/ethnicity, and socioeconomic status

Anthropogenic climate change has resulted in a significant rise in extreme heat events, exerting considerable but unequal impacts on morbidity and mortality. Numerous studies have identified inequities in heat exposure across different groups, but social identities have often been viewed in isolation from each other. Children (5 and under) and older adults (65 and older) also face elevated risks of heat-related health impacts. We employ an intersectional cross-classificatory approach to analyze the distribution of heat exposure between sociodemographic categories split into age groups in the contiguous US. We utilize high-resolution daily air temperature data to establish three census tract-level heat metrics (i.e., average summer temperature, heat waves, and heat island days). We pair those metrics with American Community Survey estimates on racial/ethnic, socioeconomic, and disability status by age to calculate population weighted mean exposures and absolute disparity metrics. Our findings indicate few substantive differences between age groups overall, but more substantial differences between sociodemographic categories within age groups, with children and older adults from socially marginalized backgrounds facing greater exposure than adults from similar backgrounds. When looking at sociodemographic differences by age, people of color of any age and older adults without health insurance emerge as the most exposed groups. This study identifies groups who are most exposed to extreme heat. Policy and program interventions aimed at reducing the impacts of heat should take these disparities in exposure into account to achieve health equity objectives.