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Nevin Manimala Statistics

An equation of state unifies diversity, productivity, abundance and biomass

Commun Biol. 2022 Aug 25;5(1):874. doi: 10.1038/s42003-022-03817-8.

ABSTRACT

To advance understanding of biodiversity and ecosystem function, ecologists seek widely applicable relationships among species diversity and other ecosystem characteristics such as species productivity, biomass, and abundance. These metrics vary widely across ecosystems and no relationship among any combination of them that is valid across habitats, taxa, and spatial scales, has heretofore been found. Here we derive such a relationship, an equation of state, among species richness, energy flow, biomass, and abundance by combining results from the Maximum Entropy Theory of Ecology and the Metabolic Theory of Ecology. It accurately captures the relationship among these state variables in 42 data sets, including vegetation and arthropod communities, that span a wide variety of spatial scales and habitats. The success of our ecological equation of state opens opportunities for estimating difficult-to-measure state variables from measurements of others, adds support for two current theories in ecology, and is a step toward unification in ecology.

PMID:36008589 | DOI:10.1038/s42003-022-03817-8

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Nevin Manimala Statistics

Spatial-temporal pattern evolution and influencing factors of coupled coordination between carbon emission and economic development along the Pearl River Basin in China

Environ Sci Pollut Res Int. 2022 Aug 26. doi: 10.1007/s11356-022-22685-7. Online ahead of print.

ABSTRACT

The Pearl River Basin (PRB) is a significant area for economic development (ED) and ecological protection in China. Studying the relationship between carbon emission (CE) and ED is crucial for China and the world to cope with climate change and achieve CO2 reduction. For 48 cities in the PRB, we used the coupling coordination model and geographically weighted regression model to analyze the coupling coordination degree (CCD) between CE and ED and investigate the main influencing factors. The results suggested that (1) the CCD presents spatial heterogeneity, with the Pearl River Delta having the highest value and the middle reaches having the lowest value; (2) the coupling coordination type between CE and ED changes from incoordination to coordination in general; and (3) the resident income and population size have a positive influence on the CCD of the cities in the lower reaches, while the secondary industry scale has a beneficial impact on the upstream. Finally, we put forward corresponding policy suggestions to achieve sustainable development in terms of reducing economic inequities, enhancing public expenditure and innovation capability, and streamlining the industrial structure.

PMID:36008585 | DOI:10.1007/s11356-022-22685-7

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Nevin Manimala Statistics

Are there joint effects of different air pollutants and meteorological factors on mental disorders? A machine learning approach

Environ Sci Pollut Res Int. 2022 Aug 26. doi: 10.1007/s11356-022-22662-0. Online ahead of print.

ABSTRACT

Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM2.5, PM10, O3, SO2, and NO2), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients’ average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m3 increase in O3, PM2.5 and PM10 exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O3 and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O3 and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.

PMID:36008583 | DOI:10.1007/s11356-022-22662-0

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Nevin Manimala Statistics

Greenhouse gas emissions from global production and use of nitrogen synthetic fertilisers in agriculture

Sci Rep. 2022 Aug 25;12(1):14490. doi: 10.1038/s41598-022-18773-w.

ABSTRACT

The global agri-food system relies on synthetic nitrogen (N) fertilisation to increase crop yields, yet the use of synthetic N fertiliser is unsustainable. In this study we estimate global greenhouse (GHG) emissions due to synthetic N fertiliser manufacture, transportation, and field use in agricultural systems. By developing the largest field-level dataset available on N2O soil emissions we estimate national, regional and global N2O direct emission factors (EFs), while we retrieve from the literature the EFs for indirect N2O soil emissions, and for N fertiliser manufacturing and transportation. We find that the synthetic N fertiliser supply chain was responsible for estimated emissions of 1.13 GtCO2e in 2018, representing 10.6% of agricultural emissions and 2.1% of global GHG emissions. Synthetic N fertiliser production accounted for 38.8% of total synthetic N fertiliser-associated emissions, while field emissions accounted for 58.6% and transportation accounted for the remaining 2.6%. The top four emitters together, China, India, USA and EU28 accounted for 62% of the total. Historical trends reveal the great disparity in total and per capita N use in regional food production. Reducing overall production and use of synthetic N fertilisers offers large mitigation potential and in many cases realisable potential to reduce emissions.

PMID:36008570 | DOI:10.1038/s41598-022-18773-w

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Nevin Manimala Statistics

Coarse-Graining of Imaginary Time Feynman Path Integrals: Inclusion of Intramolecular Interactions and Bottom-up Force-Matching

J Phys Chem A. 2022 Aug 25. doi: 10.1021/acs.jpca.2c04349. Online ahead of print.

ABSTRACT

Feynman’s imaginary time path integral formalism of quantum statistical mechanics and the corresponding quantum-classical isomorphism provide a tangible way of incorporating nuclear quantum effect (NQE) in the simulation of condensed matter systems using well-developed classical simulation techniques. Our previous work has presented the many-body coarse-graining of path integral (CG-PI) theory that builds an isomorphism between the quantum partition function of N distinguishable particles and the classical partition function of 2N pseudoparticles. In this present work, we develop a generalized version of the many-body CG-PI theory that incorporates many-body interactions in the force field. Based on the new derivation, we provide a numerical CG-PI (n-CG-PI) modeling strategy parametrized from the underlying path integral molecular dynamics (PIMD) trajectories using force matching and Boltzmann inversion. The n-CG-PI models for two liquid systems are shown to capture well both the intramolecular and intermolecular structural correlations of the reference PIMD simulations. The generalized derivation of the many-body CG-PI theory and the n-CG-PI model presented in this work extend the scope of the CG-PI formalism by generalizing the previously limited theory to incorporate force fields of realistic molecular systems.

PMID:36007243 | DOI:10.1021/acs.jpca.2c04349

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Nevin Manimala Statistics

Risk Factors for Legal Blindness in 77 Japanese Patients with Endogenous Endophthalmitis: A Multicenter Cohort Study from J-CREST

Ocul Immunol Inflamm. 2022 Aug 25:1-8. doi: 10.1080/09273948.2022.2112237. Online ahead of print.

ABSTRACT

PURPOSE: We investigated potential predictive factors for visual prognosis in Japanese patients with endogenous endophthalmitis.

DESIGN: Retrospective observational multicenter cohort study.

METHODS: We examined the characteristics of 77 Japanese patients with endogenous endophthalmitis and performed statistical analyses of these real-world data. The primary endpoint was the identification of factors associated with visual prognosis. We examined differences between patients in the better vision and legal blindness groups at 12 weeks after treatment initiation.

RESULTS: The five risk factors for visual impairment at 12 weeks after treatment initiation were presence of pressure injuries, severe clinical symptoms (presence of eye pain and ciliary injection), pathogen identification, and poor best-corrected visual acuity at baseline. Staphylococcus aureus and fungus were associated with a better visual impairment outcome.

CONCLUSIONS: Endogenous endophthalmitis remains a severe ocular infection; however, it can be managed with rapid treatments, as well as other advances in medical knowledge and technology.

PMID:36007241 | DOI:10.1080/09273948.2022.2112237

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Nevin Manimala Statistics

Principal microbial groups: compositional alternative to phylogenetic grouping of microbiome data

Brief Bioinform. 2022 Aug 26:bbac328. doi: 10.1093/bib/bbac328. Online ahead of print.

ABSTRACT

Statistical and machine learning techniques based on relative abundances have been used to predict health conditions and to identify microbial biomarkers. However, high dimensionality, sparsity and the compositional nature of microbiome data represent statistical challenges. On the other hand, the taxon grouping allows summarizing microbiome abundance with a coarser resolution in a lower dimension, but it presents new challenges when correlating taxa with a disease. In this work, we present a novel approach that groups Operational Taxonomical Units (OTUs) based only on relative abundances as an alternative to taxon grouping. The proposed procedure acknowledges the compositional data making use of principal balances. The identified groups are called Principal Microbial Groups (PMGs). The procedure reduces the need for user-defined aggregation of $textrm{OTU}$s and offers the possibility of working with coarse group of $textrm{OTU}$s, which are not present in a phylogenetic tree. PMGs can be used for two different goals: (1) as a dimensionality reduction method for compositional data, (2) as an aggregation procedure that provides an alternative to taxon grouping for construction of microbial balances afterward used for disease prediction. We illustrate the procedure with a cirrhosis study data. PMGs provide a coherent data analysis for the search of biomarkers in human microbiota. The source code and demo data for PMGs are available at: https://github.com/asliboyraz/PMGs.

PMID:36007229 | DOI:10.1093/bib/bbac328

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Nevin Manimala Statistics

Clinical Outcomes of Operating an Acute Palliative Care Unit at a Comprehensive Cancer Center

JCO Oncol Pract. 2022 Aug 25:OP2200163. doi: 10.1200/OP.22.00163. Online ahead of print.

ABSTRACT

PURPOSE: Acute palliative care units (APCUs) are inpatient services in tertiary hospitals that provide intensive symptom management and assist in hospital discharge for transitions to hospice care. We aimed to analyze the clinical outcomes of operating an APCU at a comprehensive cancer center.

PATIENTS AND METHODS: We retrospectively reviewed the medical records of 1,440 consecutive patients admitted to the APCU and analyzed demographic and clinical information, discharge outcomes, symptom assessments using the Edmonton Symptom Assessment System, spiritual distress, and financial distress.

RESULTS: The median age of patients was 67.0 (range, 23-97) years, and 41% were female. The most common primary cancer types were lung (21.9%), hepatopancreatobiliary (14.1%), and colorectal cancers (12.9%). The median length of stay was 8.0 days (range, 1-60 days), and 31.0% of patients died in the APCU. Death in the APCU showed a significant decrease over time, and overall inpatient death in oncology wards did not increase after APCU opening. In total, 44.7% of patients were discharged to government-certified hospice centers. The proportion of patients discharged to certified hospice centers increased from 32.2% in 2015 to 62.4% in 2018. Among 715 patients with a follow-up evaluation 1 week after admission, Edmonton Symptom Assessment System symptom scores, spiritual distress, and financial distress showed statistically significant improvements compared with the baseline symptom scores (P < .001). This improvement was limited to patients who did not die in the APCU.

CONCLUSION: Patients with advanced cancer admitted to the APCU may experience significant improvements in distressing symptoms. The majority of patients requiring transition to hospice were successfully transferred to certified hospice centers. The percentage discharged alive improved over time.

PMID:36007209 | DOI:10.1200/OP.22.00163

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Nevin Manimala Statistics

Partisan Polarization of Childhood Vaccination Policies, 1995‒2020

Am J Public Health. 2022 Aug 25:e1-e9. doi: 10.2105/AJPH.2022.306964. Online ahead of print.

ABSTRACT

Objectives. To examine trends in partisan polarization of childhood vaccine bills and the impact of polarization on bill passage in the United States. Methods. We performed content analysis on 1497 US state bills (1995-2020) and obtained voting returns for 228 legislative votes (2011‒2020). We performed descriptive and statistical analyses using 2 measures of polarization. Results. Vote polarization rose more rapidly for immunization than abortion or veterans’ affairs bills. Bills in 2019-2020 were more than 7 times more likely to be polarized than in 1995-1996 (odds ratio [OR] = 7.04; 95% confidence interval [CI] = 3.54, 13.99). Bills related to public health emergencies were more polarized (OR = 1.76; 95% CI = 1.13, 2.75). Sponsor polarization was associated with 34% lower odds of passage (OR = 0.66; 95% CI = 0.42, 1.03). Conclusions. State lawmakers were more divided on vaccine policy, but partisan bills were less likely to pass. Bill characteristics associated with lower polarization could signal opportunities for future bipartisanship. Public Health Implications. Increasing partisan polarization could alter state-level vaccine policies in ways that jeopardize childhood immunization rates or weaken responsiveness during public health emergencies. Authorities should look for areas of bipartisan agreement on how to maintain vaccination rates. (Am J Public Health. Published online ahead of print August 25, 2022:e1-e9. https://doi.org/10.2105/AJPH.2022.306964).

PMID:36007205 | DOI:10.2105/AJPH.2022.306964

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Nevin Manimala Statistics

End-of-Semester Report-Out: A Curriculum Evaluation Strategy

Nurs Educ Perspect. 2022 Aug 23. doi: 10.1097/01.NEP.0000000000001025. Online ahead of print.

ABSTRACT

An end-of-semester course -reporting strategy serves as one component of an overall curriculum evaluation plan. A framework specifying reporting criteria is used to guide the process. Report elements include integration of concepts in clinical, descriptions of active classroom learning strategies, testing data on concept performance, and exam statistics. Grade distribution and standardized testing scores are also reported. The report-out strategy has helped identify curricular strengths and weaknesses, encouraged instructional collaboration among faculty, informed decision-making, and contributed significantly to a successful curriculum transformation. The strategy has supported improved program outcomes in standardized testing scores and licensure pass rates.

PMID:36007099 | DOI:10.1097/01.NEP.0000000000001025