Category: Statistics

Environ Health Perspect. 2023 Dec;131(12):127005. doi: 10.1289/EHP12906. Epub 2023 Dec 4.

ABSTRACT

BACKGROUND: Long-term noise exposure is associated with cardiovascular disease (CVD), including acute cardiovascular events such as myocardial infarction and stroke. However, longitudinal cohort studies in the U.S. of long-term noise and CVD are almost exclusively from Europe and few modeled nighttime noise, when an individual is likely at home or asleep, separately from daytime noise. We aimed to examine the prospective association of outdoor long-term nighttime and daytime noise from anthropogenic sources with incident CVD using a U.S.-based, nationwide cohort of women.

METHODS: We linked $L_{50}$ nighttime and $L_{50}$ daytime anthropogenic modeled noise estimates from a U.S. National Parks Service model ($L_{50}$: sound pressure levels exceeded 50 percent of the time) to geocoded residential addresses of 114,116 participants in the Nurses’ Health Study. We used time-varying Cox proportional hazards models to estimate risk of incident CVD, coronary heart disease (CHD), and stroke associated with long-term average (14-y measurement period) noise exposure, adjusted for potential individual- and area-level confounders and CVD risk factors (1988-2018; biennial residential address updates; monthly CVD updates). We assessed effect modification by population density, region, air pollution, vegetation cover, and neighborhood socioeconomic status, and explored mediation by self-reported average nightly sleep duration.

RESULTS: Over 2,548,927 person-years, there were 10,331 incident CVD events. In fully adjusted models, the hazard ratios for each interquartile range increase in $L_{50}$ nighttime noise (3.67 dBA) and $L_{50}$ daytime noise (4.35 dBA), respectively, were 1.04 (95% CI: 1.02, 1.06) and 1.04 (95% CI: 1.02, 1.07). Associations for total energy-equivalent noise level ($L_{\text{eq}}$) measures were stronger than for the anthropogenic statistical $L_{50}$ noise measures. Similar associations were observed for CHD and stroke. Interaction analyses suggested that associations of $L_{50}$ nighttime and $L_{50}$ daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep ($<5$ h/night) mediated associations of $L_{50}$ nighttime noise and CVD.

DISCUSSION: Outdoor $L_{50}$ anthropogenic nighttime and daytime noise at the residential address was associated with a small increase in CVD risk in a cohort of adult female nurses. https://doi.org/10.1289/EHP12906.

PMID:38048103 | DOI:10.1289/EHP12906

Environ Health Perspect. 2023 Dec;131(12):127004. doi: 10.1289/EHP11921. Epub 2023 Dec 4.

ABSTRACT

BACKGROUND: The rapid evolution of electronic cigarette (e-cigarette) products warrants surveillance of the differences in exposure across device types-modifiable devices (MODs), cartridge (“pod”)-containing devices (PODs), disposable PODs (d-PODs)-and flavors of the products available on the market.

OBJECTIVE: This study aimed to measure and compare metal aerosol concentrations by device type and common flavors.

METHODS: We collected aerosol from 104 MODs, 67 PODs (four brands: JUUL, Bo, Suorin, PHIX), and 23 d-PODs (three brands: ZPOD, Bidi, Stig) via droplet deposition in a series of conical pipette tips. Metals and metalloids [aluminum (Al), arsenic (As), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), and zinc (Zn)] were measured using inductively coupled plasma mass spectrometry (ICP-MS), results were log-transformed for statistical analysis, and concentrations are reported in aerosol units (${\mathrm{mg}/m}^3$).

RESULTS: Of the 12 elements analyzed, concentrations were statistically significantly higher in MOD devices, except for Co and Ni, which were higher in PODs and d-PODs. Of the POD brands analyzed, PHIX had the highest median concentrations among four metals (Al, Ni, Pb, and Sn) compared to the rest of the POD brands. According to POD flavor, seven metals were three to seven orders of magnitude higher in tobacco-flavored aerosol compared to those in mint and mango flavors. Among the d-POD brands, concentrations of four metals (Al, Cu, Ni, and Pb) were higher in the ZPOD brand than in Bidi Stick and Stig devices. According to d-POD flavor, only Cr concentrations were found to be statistically significantly higher in mint than tobacco-flavored d-PODs.

DISCUSSION: We observed wide variability in aerosol metal concentrations within and between the different e-cigarette device types, brands, and flavors. Overall, MOD devices generated aerosols with higher metal concentrations than PODs and d-PODs, and tobacco-flavored aerosols contained the highest metal concentrations. Continued research is needed to evaluate additional factors (i.e., nicotine type) that contribute to metal exposure from new and emerging e-cigarette devices in order to inform policy. https://doi.org/10.1289/EHP11921.

PMID:38048100 | DOI:10.1289/EHP11921

Brief Bioinform. 2023 Nov 22;25(1):bbad423. doi: 10.1093/bib/bbad423.

ABSTRACT

Identifying task-relevant structures is important for molecular property prediction. In a graph neural network (GNN), graph pooling can group nodes and hierarchically represent the molecular graph. However, previous pooling methods either drop out node information or lose the connection of the original graph; therefore, it is difficult to identify continuous subtructures. Importantly, they lacked interpretability on molecular graphs. To this end, we proposed a novel Molecular Edge Shrinkage Pooling (MESPool) method, which is based on edges (or chemical bonds). MESPool preserves crucial edges and shrinks others inside the functional groups and is able to search for key structures without breaking the original connection. We compared MESPool with various well-known pooling methods on different benchmarks and showed that MESPool outperforms the previous methods. Furthermore, we explained the rationality of MESPool on some datasets, including a COVID-19 drug dataset.

PMID:38048081 | DOI:10.1093/bib/bbad423

Indian J Pediatr. 2023 Dec 4. doi: 10.1007/s12098-023-04915-z. Online ahead of print.

ABSTRACT

OBJECTIVES: To develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes.

METHODS: Six hundred thirty-nine cases of type III BA were retrospectively collected from the Children’s Hospital of Fudan University from Jan 1^st, 2017 to Dec 1^st, 2019 as a training dataset, and a survival-based forward clustering method, which can also be used to predict the subtype of a new patient was developed to identify BA subtypes.

RESULTS: A total of 2 clusters were identified (cluster 1 = 324 and cluster 2 = 315), where cluster 2 had a lower 2 y native liver survival post-Kasai rate. The infant patients in cluster 2 have higher weight, liver, and spleen volume, wider portal vein width, and older operative age; worse coagulation and liver function results; higher grade of liver fibrosis and detection rate of hepatic portal fibrous mass, and higher recent infection detection rate of herpes simplex virus type I. With the proposed prognostic classification system, the authors predicted the subtypes of the 187 cases of type III BA in a testing dataset collected from the whole year of 2020. The p-value computed from the log-rank testing for the Kaplan-Meier survival curves of the predicted two testing groups was 0.0113.

CONCLUSIONS: This classification system would be a convenient tool to choose appropriate treatment and accelerate the choice-making between clinicians and infant patients.

PMID:38047995 | DOI:10.1007/s12098-023-04915-z

Curr Allergy Asthma Rep. 2023 Dec 4. doi: 10.1007/s11882-023-01110-0. Online ahead of print.

ABSTRACT

PURPOSE OF REVIEW: With increasing industrialization, exposure to ambient and wildfire air pollution is projected to increase, necessitating further research to elucidate the complex relationship between exposure and sinonasal disease. This review aims to summarize the role of ambient and wildfire air pollution in chronic rhinosinusitis (CRS) and olfactory dysfunction and provide a perspective on gaps in the literature.

RECENT FINDINGS: Based on an emerging body of evidence, exposure to ambient air pollutants is correlated with the development of chronic rhinosinusitis in healthy individuals and increased symptom severity in CRS patients. Studies have also found a robust relationship between long-term exposure to ambient air pollutants and olfactory dysfunction. Ambient air pollution exposure is increasingly recognized to impact the development and sequelae of sinonasal pathophysiology. Given the rising number of wildfire events and worsening impacts of climate change, further study of the impact of wildfire-related air pollution is a crucial emerging field.

PMID:38047993 | DOI:10.1007/s11882-023-01110-0

Support Care Cancer. 2023 Dec 4;32(1):2. doi: 10.1007/s00520-023-08177-5.

ABSTRACT

PURPOSE: To evaluate the discrepancy and correlation between sleep-wake measures (i.e., time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE%)) reported on sleep diary and measured by actigraphy among cancer survivors with insomnia symptoms; and examine the influences of sociodemographic and clinical variables on these measurement differences.

METHODS: A heterogenous sample of cancer survivors with insomnia symptoms (n = 120; M age = 63.7 ± 10.1; female = 58.3%) was included. Seven consecutive days of sleep diary and actigraphic data were obtained along with information on demographic, sleep, and mental health symptoms. Bland-Altman plot, Pearson correlation coefficient, concordance correlation coefficient, and mixed linear model approach were used to conduct the analysis.

RESULTS: Self-reported TIB, SOL, and WASO were longer than measured by actigraphy (TIB: 8.6 min. (95% CI, 3.7, 13.5; p < .001); SOL: 14.8 min. (95% CI, 9.4, 20.2; p < .0001); and WASO: 20.7 min. (95% CI, 9.4, 20.2; p < .0001), respectively); and self-reported TST and SE% were shorter than measured by actigraphy (TST: 6.8 min. (95% CI, -18.7, 5.13); and SE%: 0.7% (95%CI, -3.0, 2.0), respectively), but were not statistically significant. Sex, higher insomnia severity, and poor sleep quality were associated with discrepancy between several sleep-wake measures.

CONCLUSION: Subjective and objective sleep-wake measures may present discrepant finding among cancer survivors with symptoms of insomnia. Future research is needed to validate appropriate sleep-wake assessment, and better understand factors that influence the discrepancy that exists between measures among this population.

CLINICAL TRIAL REGISTRATION: Clinical trials identifier: NCT03810365. Date of registration: January 14, 2019.

PMID:38047967 | DOI:10.1007/s00520-023-08177-5

Eur J Pediatr. 2023 Dec 4. doi: 10.1007/s00431-023-05346-w. Online ahead of print.

NO ABSTRACT

PMID:38047960 | DOI:10.1007/s00431-023-05346-w

Parasitol Res. 2023 Dec 4;123(1):2. doi: 10.1007/s00436-023-08024-w.

ABSTRACT

Trypanosoma evansi infects domestic animals, causing a debilitating and occasionally fatal disease. The disease leads to significant economic losses to farmers and poses a substantial impediment to the growth of livestock production in developing nations, including India. Considering the challenges associated with managing this infection, there is an urgent need to enhance our understanding of the molecular and genetic diversity of T. evansi. Therefore, this study was planned to analyze the genetic diversity of T. evansi using available internal transcribed spacer-1 (ITS-1) gene sequences from India and compare them with sequences from around the globe. Blood samples used in this study were collected from naturally infected animals including dogs, cattle, and buffaloes in the Indian state of Madhya Pradesh. Using the ITS-1 gene, we amplified a 540 base pairs (bp) segment using polymerase chain reaction (PCR), sequenced it, and identified intra-specific variations. Phylogenetic analysis of 90 sequences, including 27 from India, revealed three distinct clusters with high bootstrap support values. A haplotype network analysis identified 34 haplotypes, with H7 being the most prevalent, indicating a complex evolutionary history involving multiple countries. The genetic analysis of the Indian population revealed distinct characteristics. Despite low nucleotide diversity, there was high haplotype diversity in comparison to other populations. Tajima’s D, Fu and Li’s D, and Fu and Li’s F exhibited non-significant negative values, indicating potential stability. Additionally, the slightly positive values in Fu’s Fs, Raggedness (r), and Ramos-Onsins and Rozas (R2) statistics suggested a lack of recent significant selective pressures or population expansions. Furthermore, the presence of genetic differentiation and gene flow among T. evansi populations highlighted ongoing evolutionary processes. These findings collectively depicted a complex genetic landscape, suggesting both stability and ongoing evolutionary dynamics within the Indian population of T. evansi. The findings of this study are important for understanding the evolutionary history and population dynamics of T. evansi, and they may help us develop effective control strategies.

PMID:38047956 | DOI:10.1007/s00436-023-08024-w

Cancer Sci. 2023 Dec 4. doi: 10.1111/cas.16021. Online ahead of print.

ABSTRACT

Due to the scarcity of large-sized prospective databases, the Japanese Joint Committee for Lung Cancer Registry conducted a nationwide prospective registry for newly diagnosed and untreated pleural mesothelioma. All new cases diagnosed pathologically as any subtype of pleural mesothelioma in Japan during the period between April 1, 2017, to March 31, 2019, were included before treatment. Data on survival were collected in April 2021. The eligible 346 patients (285 men [82.3%]; 61 women [17.7%]; median age, 71.0 years [range, 44-88]) were included for analysis. Among these patients, 138 (39.9%) underwent surgery, 164 (47.4%) underwent non-surgical therapy, and the remaining 44 (12.7%) underwent best supportive care. The median overall survival for all 346 patients was 19.0 months. Survival rates at 1, 2, and 3 years for all patients were, 62.8%, 42.3%, and 26.5%, respectively. Median overall survival was significantly different among patients undergoing surgery, non-surgical treatment, and best supportive care (32.2 months vs. 14.0 months vs. 3.8 months, p < 0.001). The median overall survival of patients undergoing pleurectomy/decortication and extrapleural pneumonectomy was 41.8 months and 25.0 months, respectively. Macroscopic complete resection resulted in longer overall survival than R2 resection and partial pleurectomy/exploratory thoracotomy (41.8 months vs. 32.2 months vs. 16.8 months, p < 0.001). Tumor shape, maximum tumor thickness, and sum of three level thickness were significant prognostic factors. The data in the prospective database would serve as a valuable reference for clinical practice and further studies for pleural mesothelioma.

PMID:38047872 | DOI:10.1111/cas.16021

Chimia (Aarau). 2023 Feb 22;77(1-2):7-16. doi: 10.2533/chimia.2023.7.

ABSTRACT

Accelerating R&D is essential to address some of the challenges humanity is currently facing, such as achieving the global sustainability goals. Today’s Edisonian approach of trial-and-error still prevalent in R&D labs takes up to two decades of fundamental and applied research for new materials to reach the market. Turning around this situation calls for strategies to upgrade R&D and expedite innovation. By conducting smart experiment planning that is data-driven and guided by AI/ML, researchers can more efficiently search through the complex – often constrained – space of possible experiments and find or hit the global optima much faster than with the current approaches. Moreover, with digitized data management, researchers will be able to maximize the utility of their data in the short and long terms with the aid of statistics, ML and visualization tools. In what follows, we describe a framework and lay out the key technologies to accelerate R&D and optimize experiment planning.

PMID:38047848 | DOI:10.2533/chimia.2023.7